Three-Dimensional Echocardiography-Derived Myocardial Mechanistic Insights into Obstructive Hypertrophic Cardiomyopathy with Moderate Septal Hypertrophy

Three-Dimensional Echocardiography-Derived Myocardial Mechanistic Insights into Obstructive Hypertrophic Cardiomyopathy with Moderate Septal Hypertrophy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Three-Dimensional Echocardiography-Derived Myocardial Mechanistic Insights into Obstructive Hypertrophic Cardiomyopathy with Moderate Septal Hypertrophy Yuwei Bao, Wei Zhou, Jie Tian, Jeffrey B. Geske, Si Fang, Shiliang Liu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8315722/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Mar, 2026 Read the published version in BMC Medical Imaging → Version 1 posted 12 You are reading this latest preprint version Abstract Background The mechanisms of left ventricular outflow tract obstruction (LVOTO) in hypertrophic cardiomyopathy (HCM) with moderate septal hypertrophy (≤ 18 mm) remain uncertain with therapeutic implications. This study investigated the role of three-dimensional echocardiography (3DE)-derived myocardial mechanics in LVOTO. Methods We retrospectively analyzed 216 HCM patients with moderate septal hypertrophy, stratified into nonobstructive (n = 38), provokable LVOTO (n = 63), and resting LVOTO (n = 115). Transthoracic echocardiography assessed LV geometry, LVOT diameter, anterior mitral leaflet length, and papillary muscle abnormalities (via a composite SubMV score). 3DE-derived strain parameters, including global longitudinal (GLS), circumferential, radial, area (GAS) strain, twist, and torsion, were quantified. Determinants of LVOTO were evaluated using multivariate regression, restricted cubic splines (RCS), and receiver operating characteristic (ROC) analysis. Results Both LVOTO subgroups showed significantly augmented strain mechanics versus nonobstructive patients, greatest in resting LVOTO (p < 0.05); twist and torsion were the strongest discriminators (p < 0.001). Multivariate regression showed that, beyond LVOT diameter and SubMV score, torsion (B = 9.47), twist (B = 1.92), and GAS (B = 1.29) independently predicted provoked LVOT gradients (all p < 0.05); RCS demonstrated nonlinear twist/torsion–LVOTO relationships, with obstruction risk rising sharply above twist = 15° and torsion = 3°/cm, especially under provocation. Torsion discriminated provokable LVOTO achieving 81% specificity (cutoff 2.4°/cm, AUC = 0.72), outperforming all structural parameters. Integrating 3DE-derived mechanics with structural metrics improved diagnostic accuracy, especially in provokable LVOTO (AUC 0.84 vs. 0.76, DeLong p = 0.003). Conclusions In moderate-hypertrophy HCM, 3DE-derived strain mechanics, especially twist and torsion, independently determine LVOTO beyond structural narrowing, particularly under provocation, strengthening mechanistic insight and clinical applicability. hypertrophic cardiomyopathy left ventricular outflow tract obstruction three-dimensional speckle tracking strain myocardial mechanics hypertrophy Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Hypertrophic cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy with prevalence of 1:200–1:500[ 1 ]. HCM is characterized by left ventricular (LV) hypertrophy without a secondary cause, with patients demonstrating a heterogeneous clinical course. Up to 70% of patients develop LV outflow tract obstruction (LVOTO), either at rest or with provocation, a dynamic phenomenon strongly associated with adverse outcomes including progressive heart failure, ventricular arrhythmias, and sudden cardiac death [ 1 – 3 ]. While septal hypertrophy remains the primary anatomical determinant of LVOTO, a notable proportion of patients with only moderate septal thickening (≤ 18 mm) paradoxically exhibit significant LVOT pressure gradients[ 4 , 5 ]. Even moderate septal thickening can be associated with extreme LVOTO[ 6 ]. This observation suggests that factors beyond myocardial morphology contribute to the development and severity of obstruction. Notably, Parag et al. highlighted the contribution of mitral valve (MV) and subvalvular anomalies to LVOTO development in this subgroup through integrated cardiac magnetic resonance (CMR) and echocardiographic analyses[ 5 ]. These insights have led to some advocating for concomitant MV interventions alongside septal myectomy in selected patients[ 5 , 7 ]. Conversely, findings from a large cohort study from the Mayo Clinic challenged this approach, demonstrating that MV abnormalities are frequently present in obstructive HCM but can often be adequately addressed by extended septal myectomy alone, without requiring direct MV intervention[ 8 ]. However, a potential limitation in patients with moderate septal hypertrophy is the insufficient septal thickness for effective resection and obstruction relief. These divergent perspectives underscore the need for a more nuanced understanding of LVOTO pathophysiology beyond traditional structural assessments in this moderate hypertrophic cohort. Currently, the emergence of novel pharmacotherapies like mavacamten, a cardiac myosin inhibitor that alleviates LVOTO via contractility modulation, highlights the pivotal role of myocardial mechanics in the genesis of obstruction[ 9 , 10 ]. Imaging studies using CMR feature tracking have shown that elevated global radial strain (GRS) predicts the presence of LVOTO independent of anatomic severity[ 11 ], and increased global circumferential strain (GCS) is significantly correlated with obstruction, irrespective of wall thickness(WT) or myocardial fibrosis[ 12 ]. Furthermore, two-dimensional echocardiography (2DE) speckle-tracking has demonstrated that peak LV twist correlates to obstruction, reinforcing the concept of hyperdynamic myocardial deformation as a functional contributor to obstruction[ 13 ]. Despite growing evidence supporting the biomechanical underpinnings of LVOTO, strain signatures specific to HCM patients with moderate hypertrophy remain poorly defined. We hypothesize that hypercontractile myocardial mechanics may serve as key functional drivers of obstruction in these subtypes. Three-dimensional echocardiography (3DE) with high temporal resolution has evolved into a robust, noninvasive imaging technique capable of providing comprehensive, multidirectional, and angle-independent quantification of myocardial deformation[ 14 , 15 ]. 3DE was employed herein to identify previously unrecognized biomechanical determinants of LVOTO beyond standard 2DE structural imaging. Methods Study Design and Population In this retrospective study, 1,236 consecutive HCM patients (defined according to the 2024 ESC criteria) were screened at Tongji Hospital between July 2023 and January 2025. All patients prospectively underwent standard 2DE, 3DE and contrast Echocardiography. Contrast echo and/or CMR, was used to identify moderate septal hypertrophy (maximum WT ≤ 18 mm)[ 16 ], yielding 298 eligible cases. After applying exclusion criteria: (1) prior septal reduction, valvular surgery, or major cardiovascular intervention; (2) significant intrinsic valvular disease except SAM-related MR; (3) congenital heart disease; (4) inadequate 3DE image quality; and (5) apical HCM or mid-ventricular obstruction, the final cohort comprised 216 patients: 38 nonobstructive, 115 resting LVOTO (≥ 30 mmHg), and 63 provokable LVOTO (provoked ≥ 30 mmHg with resting < 30 mmHg). The patient selection process is shown in Fig. 1 . The study was approved by the Ethics Committee of Tongji Medical College (approval number: 2022-S013-(1–4). The procedures used in this study adhere to the tenets of the Declaration of Helsinki. Clinical Data Collection and Imaging Acquisition Clinical data was extracted from electronic medical records. Echocardiographic studies were conducted by experienced sonographers (W. Z. and J. T.) using a standardized protocol and a commercial ultrasound system (Vivid E95, GE Healthcare, Horten, Norway). For 2DE, standard parasternal long-axis, apical four-chamber, and apical two-chamber views were acquired with individualized optimization to maximize frame rate and ensure clear LV endocardial definition. Patients with resting LVOT gradients < 50 mmHg underwent provocation maneuvers (e.g., Valsalva); if these failed to induce LVOTO, exercise echocardiography was performed using the modified Bruce treadmill protocol[ 17 ]. For 3DE, full-volume LV datasets were acquired from the apical window using a matrix-array transducer with multi-beat ECG-gated acquisition during end-expiratory breath-hold, maintaining ≥ 40 volumes/s to ensure adequate temporal resolution. A 12-slice display was used to verify complete LV coverage before strain analysis. Image Processing and Analysis All datasets were exported to a dedicated workstation (EchoPAC, Vision 204, GE Medical System) for offline analysis. 2DE structural measurements, including maximal WT, early diastolic transmitral flow velocity (E), early diastolic mitral annular velocity (e′), LVOT diameter (LVOTD), and anterior mitral leaflet (AML) length. LVOTD was measured in mid-systole 0.5–1 cm below the aortic annulus, and AML length in end-diastole, both in the parasternal long-axis view using the inner edge-to-inner edge method[ 18 ]. Septal morphology was determined from the long axis view[ 19 ]. SAM and MR grades were evaluated according to the 2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of HCM[ 1 ]. LAVi was derived by the biplane method at end-systole and indexed to BSA. A semi-quantitative scoring system was applied to evaluate subvalvular anomalies, with one point assigned for the presence of each of the following features (maximum score: 4): (1) accessory papillary muscle (additional or abnormally positioned papillary muscle structures) or anomalous muscular bundles (aberrant myocardial structures extending from the LV apex to the basal septum or anterior wall)[ 18 , 20 , 21 ], (2) anterior displacement or bifurcation of the papillary muscles, (3) papillary muscle hypertrophy (an end-diastolic diameter > 9 mm on imaging), and (4) direct insertion of papillary muscle into the MV. These characteristics were defined based on prior literature descriptions[ 20 – 22 ] and expert consensus. Representative features and scoring criteria are illustrated in Fig S1 . Scoring was performed independently by two experienced sonographers with 6 and 13 years of experience, respectively. Discrepancies were resolved by consensus. When available, CMR images were reviewed for reference, and late gadolinium enhancement (LGE) percentage of myocardium was analyzed when applicable. Three-dimensional speckle-tracking echocardiography (3D-STE) analysis was performed using 4D AutoLVQ software (GE Healthcare) following standardized protocols[ 23 ] with analysis workflow showcase in Fig S2 . LV end-diastolic volume (EDV), end-systolic volume (ESV), and ejection fraction (EF) were calculated, followed by dynamic LV modeling and volume–time curve generation. For strain analysis, automated endocardial tracking was performed across the cardiac cycle using a 16-segment LV model. Global longitudinal (GLS), GCS, GRS, and area strain (GAS) were computed as weighted averages of segmental values. LV twist (°) was defined as apical − basal rotation, and torsion (°/cm) as twist normalized to LV long-axis length. All 3D-STE analyses were performed by a 6-year-experienced echocardiographer (Y.W.B.). Inter-study reproducibility was tested in 20 randomly selected patients, reanalyzed one week apart. Statistical Analysis Continuous variables were expressed as mean ± SD and categorical variables as counts (%). Between-group comparisons used one-way ANOVA or Kruskal–Wallis tests for continuous variables, and chi-square or Fisher’s exact tests for categorical variables. Variables with p < 0.05 in univariate analyses entered multivariate linear regression models, adjusted for confounders (e.g., age, BSA) to identify independent LVOTO predictors. Regression coefficients (B) with 95% CIs were reported. Restricted cubic spline (RCS) models assessed nonlinear associations between 3DE-derived mechanics (twist, torsion) and LVOT gradients, with Wald tests evaluating overall and nonlinear effects. Receiver operating characteristic (ROC) analysis determined discriminative performance of significant strain parameters, with AUCs compared by the DeLong test to evaluate the incremental value of 3DE mechanics. Reproducibility was tested using intraclass correlation coefficients (ICC) and Bland–Altman analysis. Analyses were performed with SPSS 23.0 (IBM, Chicago, IL) and MedCalc 20.0.22 (MedCalc, Ostend, Belgium). A two-sided p < 0.05 was considered significant. Results Baseline Characteristics and Echocardiographic Parameters The baseline clinical characteristics of 216 HCM patients stratified by LVOTO status (nonobstructive, resting, and provokable) summarizes in Table 1 . Systolic blood pressure was highest in the nonobstructive group (p < 0.05). Paroxysmal supraventricular tachycardia and dyspnea were most frequent in the resting LVOTO group (p < 0.05). NT-proBNP levels were elevated in both nonobstructive and resting LVOTO groups compared to the provokable group. Table 1 Population Clinical Characteristics HCM with moderate hypertrophy P All(n = 216) No LVOTO (n = 38) Provokable LVOTO(n = 63) Resting LVOTO (n = 115) ANOVA Male, n/% 130/60.2% 29 (76.32%)# 40 (63.49%) 61 (53.04%) 0.032 Age, year 56(45,64) 52 (38,61) 57 (46,63) 56 (45.5,65) 0.241 BSA, m 2 /kg 1.75 ± 0.2 1.73 ± 0.24 1.75 ± 0.2 1.75 ± 0.18 0.847 Resting LVOT gradient, mmHg 38 (11,98) 6 (4,9)#* 14 (9,19)# 86 (59,125)* < 0.001 Provoked LVOT gradient, mmHg 91 (57,131) 18 (8,24)#* 70 (57,99)# 120 (92,146)* < 0.001 SBP, mmHg 128 (115,142) 137 (111,148) 132 (120,146)# 125 (113,137)* 0.027 DBP, mmHg 77 ± 11 78 ± 13 79 ± 12# 74 ± 10* 0.034 Heart rate, bpm 61 (56,69) 66 (61,73) 60 (54,68) 61 (58,69) 0.419 NYHA class 3 (2,3) 3 (1,3) 2 (2,3) 3 (2,3) 0.302 NT-proBNP, pg/ml 260 (115,583) 444 (149.5,875)* 206 (96.3,299.2)# 455 (194.3,893.7)* 0.020 cTnI, ng/ml 11(7.4,18) 23.5 (4.4,41.8) 6.8 (4.2,15) 7 (4,15.8) 0.087 Comorbidity Hypertension 75 (34.72%) 11 (28.95%) 22 (34.92%) 42 (36.52%) 0.696 Diabetes 27 (12.5%) 3 (7.89%) 8 (12.7%) 16 (13.91%) 0.622 CAD 67 (31.02%) 7 (18.42%) 20 (31.75%) 40 (34.78%) 0.166 PSVT 29 (13.43%) 1 (2.63%)# 6 (9.52%) 22 (19.13%) 0.02 Chest pain 71 (32.87%) 11 (28.95%) 19 (30.16%) 41 (35.65%) 0.645 Dyspnea 102 (47.22%) 11 (28.95%)# 26 (41.27%) 65 (56.52%) 0.007 Syncope 28 (12.96%) 5 (13.16%) 7 (11.11%) 16 (13.91%) 0.867 Palpitation 66 (30.56%) 9 (23.68%) 17 (26.98%) 40 (34.78%) 0.334 Medication β-blocker 85 (39.35%) 7 (18.42%)#* 26 (41.27%) 52 (45.22%) 0.013 Calcium channel antagonists 23 (10.65%) 0 (0%)* 12 (19.05%) 11 (9.57%) 0.009 Footnote : #indicates vs resting LVOTO; *indicates vs provokable LVOTO. Data are presented as mean ± standard deviation or median (interquartile range) for continuous variables and number (percentage) for categorical variables. Comparisons among groups were performed using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables, and the chi-square test for categorical variables. Adjusted p-values were calculated using the Bonferroni correction for multiple comparisons. BSA: body surface area; LVOT: left ventricular outflow tract; SBP: systolic blood pressure; DBP: diastolic blood pressure; NYHA: New York Heart Association; CAD: coronary artery disease; PSVT: paroxysmal supraventricular tachycardia. Among conventional parameters, maximal WT was slightly greater in the resting LVOTO group compared to the provokable group (16 mm vs. 15 mm, p<0.05). Overall LVEF was preserved (66%), with the highest value in the resting LVOTO subgroup (71.2%), paralleling the trend in 2DE-derived GLS. Diastolic dysfunction was most pronounced in the resting LVOTO group with the highest E/e′ ratio and greatest LAVI (both p < 0.05). The severity of SAM and MR followed the pattern of obstruction, greatest in the resting LVOTO group, followed by the provokable group, and then the nonobstructive cohort. Morphologically, a sigmoid septum predominated in the resting LVOTO group (63.4%), while a reverse curve was more common in the nonobstructive group (52.6%). Detailed comparations are supplemented in Table 2 . Table 2 Conventional LV Structural Measurements of HCM subgroups Footnote : #indicates vs resting LVOTO, * indicates vs provoked LVOTO. Data are presented as mean ± standard deviation or median (interquartile range) for continuous variables and number (percentage) for categorical variables. Comparisons among groups were performed using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables, and the chi-square test for categorical variables. Adjusted p-values were calculated using the Bonferroni correction for multiple comparisons. WT: wall thickness, LVEDVi: left ventricular end diastolic volume index, LVESVi: left ventricular end systolic volume index, LVEF: left ventricular ejection fraction, LAVI: left atrial volume index, SAM: systolic anterior motion, GLS: global longitudinal strain, MR: mitral regurgitation, CMR: cardiac magnetic resonance, LGE: late gadolinium enhancement. HCM with Moderate Hypertrophy p-value All (n = 216) Nonobstructive (n = 38) Provokable LVOTO(n = 63) Resting LVOTO (n = 115) ANOVA Maximal WT, mm 16 (15,17) 16 (15,17) 15 (14,16) 16 (15,17)* 0.009 LVEDVi, ml/m 2 49.7 (42.8,56.1) 51.9 (41.7,59.4) 54.2 (45.8,59.9) 58.5 (48.94,64.0) 0.030 LVESVi, ml/m 2 18.72 (16.1,20.5) 18.2 (14.7,22.9)#* 15.91 (12.35,20.05) 15.12 (12.8,18.82) 0.000 LVEF, % 66 (60,64) 63.0 (57.8,62.5)# 66.4 (63.1,73.9)# 71.2(65.01,77.3)* < 0.001 LAVi, ml/m 2 38 (30,45.92) 35 (26,41.75)# 34.7 (28,39)# 42 (34.2,50.95)* < 0.001 E/e’ 13 (10,16) 10.8 (8,12.75)# 12 (8.22,15)# 15 (12,18)* < 0.001 SAM 2 (0,3) 0 (0,1)# 1 (0,2)# 3 (2,4)* < 0.001 2D GLS, % -15.99 ± 3.12 -13.95 ± 3.54#* -16.16 ± 2.75# -16.56 ± 2.91 < 0.001 MR grade 2 (1,3) 1 (1,1)# 1 (1,2)# 3 (2,4)* < 0.001 Septal morphology Sigmoid 137(63.4%) 8(21.1%)#* 46(73.0%)# 83(62.6%)* < 0.001 Reverse curve 48(22.2%) 20(52.6%)#* 9(14.3%)# 19(14.8%)* < 0.001 Others CMR-derived LGE 31(14.4%) 150(69.4%) 10(26.3%)# 19(50%) 8(12.7%) 38(60.3%) 13(4.3%) 93(80.9%) < 0.001 <5% 126(84%) 9/19(47.4%)#* 31/38(81.6%) 86/93(92.5%) < 0.001 5–15% 19(12.7%) 8/19(42.1%)#* 4/38(10.5%)# 7/93(0.8%)* 15% 5(3.3%) 2/19(10.5%)#* 3/38(7.9%) 0 < 0.001 SubMV Score 1(0,1) 1 (0,1)# 1 (0,1)# 1 (1,2)* < 0.001 Accessory papillary muscle 40 (18.52%) 6 (15.79%) 10 (15.87%) 24 (20.87%) 0.234 Anterior displacement of papillary muscles 77 (35.65%) 11 (28.95%) 14 (22.22%)# 52 (45.22%)* 0.006 Papillary muscle hypertrophy 12 (5.56%) 2 (5.26%) 3 (4.76%) 7 (6.09%) 0.931 Papillary muscle multifurcation 25 (11.63%) 3 (7.89%) 1 (1.61%)# 21 (18.26%)* 0.003 Insertion of papillary muscle into the MV 6(2.8%) 0(0) 1(1.6%) 5(4.3%) 0.291 Of the 216 patients, 150 (69.4%) underwent CMR with LGE evaluation. Among these, 19 (12.7%) were in the nonobstructive group, 38 (25.3%) in the provokable LVOTO group, and 93 (62.0%) in the resting LVOTO group. The extent of LGE was significantly lower in both the resting (p = 0.001) and provokable (p = 0.018) LVOTO groups compared to the nonobstructive group. SubMV scores were highest in the resting LVOTO group (p < 0.001), driven mainly by anterior papillary muscle displacement and bifurcation (p < 0.001). 3DE Metrics Comparison As summarized in Table 3 , patients with resting LVOTO showed the greatest augmentation in multidirectional mechanics, including GCS, GAS, GRS, twist, and torsion, followed by the provokable LVOTO group and then the nonobstructive group. Differences between either LVOTO subgroup and the nonobstructive group were statistically significant (all p 0.05). Representative 3DE strain maps for each subgroup are shown in Fig. 2 , visually illustrating these intergroup differences. Notably, twist and torsion demonstrated the highest difference across subgroups (both p < 0.001). Supplementarily, strain parameters of the nonobstructive group exhibited the highest degree of similarity to those of 32 healthy control subjects, with comparison data provided in Table S1 . Table 3 Comparison of 3DE LV Strain Components of HCM Subgroups HCM with Moderate Hypertrophy P values of LVOTO vs nonobstructive P values of two LVOTO groups All (n = 216) Nonobstructive (n = 38) Provokable LVOTO(n = 63) Resting LVOTO(n = 115) Provokable LVOTO Resting LVOTO GLS, -% 14.39(11.98,16.7) 12.5 (10,13.25) 15 (13,17) 15 (12,17) 0.003* 0.002* > 0.999 GCS, -% 18.6(16.1,21,1) 17 (14,18.25) 18 (15.25,21) 19 (17,21) 0.023* 0.002* 0.213 GAS, -% 28.8(24.6,32.3) 25 (22,29) 29 (25,32.8) 30 (26,32) 0.020* 0.001* > 0.999 GRS, % 46.6(37.2,53.5) 36.5 (32,46.5) 48 (38,54) 48 (40,54.5) 0.012* 0.001* > 0.999 Peak twist, ° 12.4(6.6,17.3) 6.25 (3.1,10.4) 13.2 (7.05,17.4) 13.7 (8.35,19.35) 0.004* < 0.001* 0.397 Peak torsion, °/cm 2.50 ± 1.24 1.55 (0.88,2.22) 2.45 (1.5,3.08) 2.7 (2.05,3.6) 0.031* < 0.001* 0.092 Footnote : *indicates statistic difference is significant (p<0.05). Data are presented as mean ± standard deviation or median (interquartile range) for continuous variables and number (percentage) for categorical variables. Comparisons among groups were performed using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables, and the chi-square test for categorical variables. GLS: global longitudinal strain, GCS: global circumferential strain, GAS: global area strain, GRS: global radial strain. Associations and Diagnostic Performance Multivariate models adjusted for age, sex, and BSA identified LVOTD and SubMV score as consistent structural predictors of both resting and provoked LVOT gradients. Due to collinearity, ESVi was used to represent LV size, and twist and torsion were analyzed separately. Maximal WT independently predicted resting but not provoked gradients. Importantly, twist, torsion, and GAS remained independent mechanical predictors of both resting and provoked LVOT gradients (all p < 0.05 in models within torsion). Detailed results are presented in Table 4 . Table 4 Univariate and Multivariate Linear Regression Analysis of the Resting and Provoked Gradients of Left Ventricular Outflow Tract Provokable LVOT Gradient Resting LVOT Gradient Univariate Multivariable (Model 1) Multivariable (Model 2) Univariate Multivariable (Model 1) Multivariable (Model 2) B P B (95% CI) P B (95% CI) P B P B (95% CI) P B (95% CI) P Sex -14.94 0.05 -21.11 0.003 Age 0.66 0.01 0.64 0.009 Maximal WT, mm 4.36 0.048 3.33(-0.90,7.55) 0.125 3.44(-0.96,7.83) 0.124 4.323 0.039 4.10(0.12,8.09) 0.044* 3.93(0.15,7.70) 0.043* LVOTD, mm -5.55 0.000 -4.95(-7.20,-2.70) 0.000* -3.70(-6.3,-1.07) 0.006* -6.561 0.000 -4.89(-7.28,-2.49) 0.000* -5.02(-7.05,-2.99) 0.000* 3DE EDVi, ml/m2 0.816 0.007 - - 0.628 0.029 - - 3DE ESVi, ml/m2 -1.54 0.011 -1.37 0.017 AML length, mm 1.563 0.062 1.235 0.122 SubMV score 17.762 0.000 11.56(3.0,20.11) 0.009* 13.04(4.3,21.75) 0.004* 17.148 0.000 10.79(2.81,18.78) 0.008* 11.08(3.45,18.71) 0.005* GLS, -% 2.334 0.037 1.512 0.158 GCS, -% 2.27 0.013 2.87 0.001 GAS, -% 1.898 0.004 1.29(0.35,2.39) 0.035* 2.86(-0.38,6.11) 0.084 2.0 0.001 1.21(-0.83,3.25) 0.241 1.24(0.15,2.33) 0.027* GRS, % 0.426 0.127 0.385 0.149 Twist, ° 1.997 0.000 1.92(1.02,2.82) 0.000* - 1.644 0.001 1.35(0.48,2.23) 0.003* - Torsion, °/cm 13.386 0.000 - 9.47(3.63,15.31) 0.002* 14.416 0.000 - 10.64(5.55,15.73) 0.000* Footnote : Univariate variables with p-values less than 0.05 were included in the multivariate model in a stepwise manner. Model 1 of Multivariable analysis indicates enrolling LV twist, while Model 2 indicates torsion was enrolled for model construction. LVOTO: left ventricular outflow tract obstruction; LVEDVi: left ventricular end diastolic volume index, LVESVi: left ventricular end systolic volume index, LVEF: left ventricular ejection fraction, 3DE: three-dimensional echocardiography, AML: anterior mitral leaflet; GLS: global longitudinal strain, GCS: global circumferential strain, GAS: global area strain, GRS: global radial strain. Further RCS analyses demonstrated load-dependent and nonlinear associations between LV twist/torsion and the risk of LVOTO, with evident threshold effects as indicated in Fig. 3 . For twist, in the resting state, the association was modest and near linear, with odds ratios (ORs) gradually increasing from 1.0 to ~ 2.0 as twist rose to 15°, followed by a plateau at higher values (> 15°). Under provocation, the association became more prominent and nonlinear, with ORs rising sharply from 1.0 to ~ 4.0 across 5–15°, then reaching a plateau at > 15°. For torsion, the nonlinear relationship was more pronounced. At rest, ORs increased steeply from 1.0 to ~ 3.0 within the 1–3°/cm range, with a plateau thereafter (> 3°/cm). In the provoked state, the association was markedly nonlinear, with ORs rising rapidly and peaking near 6.0, indicating a substantial risk of obstruction under hemodynamic stress. ROC analysis (Table 5 ) demonstrated LV torsion as the strongest determinant of provokable LVOTO, achieving 81% specificity at a threshold of 2.4°/cm (AUC = 0.72, p < 0.001), outperforming all structural metrics, with twist as the next best performer. For resting LVOTO, LVOTD yielded the highest AUC, while twist at a value of 8.0° offered superior sensitivity of 78% (p = 0.005). Integrating 3DE-derived mechanics with structural metrics significantly improved diagnostic performance. For provokable LVOTO, the AUC improved from 0.75 to 0.84 (Delong p = 0.003), with specificity rising from 63% to 78%. Similarly, for resting LVOTO, the AUC increased from 0.76 to 0.82 (Delong p = 0.013), with sensitivity improving from 68% to 86%. These gains are visualized in Fig. 4 . Table 5 ROC Results of Variables for Identifying Resting and Provokable LVOTO Variates Provokable LVOTO Resting LVOTO AUC (95% CI) P Thresholds (Sen/ Spe) AUC (95% CI) P Thresholds (Sen/ Spe) LVOTD, mm 0.71(0.62,0.79) <0.001 16.5(55%,72%) 0.68(0.60,0.75) <0.001 16.5(65%,64%) SubMV Score 0.60(0.50,0.70) 0.059 0.5(70%,44%) 0.67(0.60,0.72) <0.001 1.5(36%,90%) GAS, -% 0.68(0.58,0.78) <0.001 25.5(75%,58%) 0.60(0.52,0.68) 0.011 27.5(67%,54%) Twist, ° 0.72(0.62,0.81) <0.001 10.9(61%,78%) 0.62(0.54,0.69) 0.005 8.0(78%,44%) Torsion, °/cm 0.72(0.62,0.82) <0.001 2.4(60%,81%) 0.66(0.59,0.74) <0.001 2.7(57%,71%) Combined metrics Structural metrics 0.75(0.68,0.83) <0.001 0.80(77%,63%) 0.76(0.70,0.82) <0.001 0.56(68%,73%) 3DE mechanics 0.75(0.66,0.85) <0.001 0.83(68%,75%) 0.67(0.57,0.76) <0.001 0.43(78%,50%) Structure + 3DE 0.84(0.76,0.91) <0.001 0.83(78%,78%) 0.82(0.76,0.87) <0.001 0.41(86%,63%) Footnote : LVOTO, left ventricular outflow tract obstruction; AUC: area under the curve; Sen, sensitivity; Spe, specificity; CI, confidence intervals; LVOTD, left ventricular outflow tract diameter; SubMV score, sub mitral valve anomaly score; GAS, global area strain. Bland-Altman plots (Fig S3 ) and ICCs confirmed good to excellent reproducibility of 3DE strain measurements, with ICCs ranging from 0.887 to 0.984 ( Table S2 ). Discussion To our knowledge, this is the first study to characterize 3DE-derived myocardial mechanics in relation to LVOTO specifically in HCM patients with moderate septal hypertrophy (WT ≤ 18 mm). Three key insights emerged : (1) Both resting and provokable LVOTO groups showed significantly greater 3DE-derived strain than the nonobstructive group (all p < 0.05), with twist and torsion the most discriminative parameters (both p < 0.001). (2) Multivariable regression identified twist, torsion, and GAS as predictors of provoked LVOT gradients independent of structural factors. Nonlinear associations were evident, with obstruction risk sharply rising above twist = 15° and torsion = 3°/cm, particularly under provocation. (3) Twist and torsion outperformed structural parameters in detecting provokable LVOTO, and twist was most sensitive for resting LVOTO. Integrating 3DE-derived mechanics with structural indices improved diagnostic performance. This study extends previous understanding by showing that, in HCM with moderate LV hypertrophy, LVOTO results from hypertrophy, MV abnormalities, and notably, exaggerated myocardial mechanics. Among structural parameters, LVOTD emerged as the strongest independent predictor, outperforming maximal WT. This highlights that systolic LVOT narrowing, not septal hypertrophy alone, is the dominant driver of obstruction pathogenesis. To better quantify subvalvular apparatus contributions, we developed a composite SubMV score capturing diverse mitral subvalvular abnormalities. This score showed a strong and independent association with elevated LVOT gradients, extending previous findings[ 2 , 20 – 22 ] and reinforcing the concept that the MV apparatus is not merely a bystander but rather an active contributor to LVOTO pathophysiology[ 1 , 5 , 18 ]. Among its sub-components, apical displacement and bifid morphology of the papillary muscles were the most frequently observed anomalies although relatively lower prevalence in our cohort compared to earlier reports[ 20 , 24 ] likely reflects the exclusion of apical- and mid-ventricular obstructive HCM, in which these anomalies are more prevalent[ 25 , 26 ]. These papillary anomalies aggravate flow obstruction by magnifying valvular motion during systole, a mechanism well-established in previous literature[ 8 , 27 ]. Importantly, our findings highlight the independent, mechanistical role of myocardial hypercontractility in LVOTO development, as assessed by 3DE. Unlike prior studies associating impaired GLS with myocardial injury without accounting for hypertrophy severity[ 15 , 28 ], this study focused on patients with moderate septal hypertrophy, where GLS was only mildly reduced (-14.4%) despite preserved ejection fraction (67%), underscoring its value as an early marker of subclinical dysfunction[ 29 ]. Importantly, both resting and provokable obstruction groups exhibited markedly enhanced myocardial mechanics compared with nonobstructive patients, hint hypercontractility as a contributor of outflow tract obstruction. These exaggerated patterns persisted after structural adjustment and were most pronounced in provokable obstruction, even twist and torsion outperformed anatomy. Collectively, these results support the paradigm that contractile mechanics are core contributors, not mere epiphenomena, in developing LVOTO among moderate HCMs. Our results align with those of Lo et al.[ 13 ], who also highlighted the role of rotational mechanics in obstructive HCM using 2DE. Increased LV twist and torsion reflects enhanced shear deformation between the apex and base[ 14 ]. RCS analysis provides mechanistic insight that excessive LV torsion contributes directly to LVOTO. Physiologically, twist and torsion enhance ejection efficiency but once exceeding a critical threshold (~ 15°/~3°/cm), they may induce abnormal wall stress, distort the LVOT geometry, and increase obstruction risk. Concurrently, elevated GAS indicates reinforced centripetal contraction, further amplifying intraventricular pressure gradients. These exaggerated mechanical responses act synergistically to drive LVOTO, a pattern most pronounced under provoked conditions when hemodynamic demand intensifies. The improved diagnostic performance of models incorporating 3DE-derived strain indices further supports this mechanistic interpretation. Morphologically, most LVOTO patients showed a sigmoid septal shape with basal bulging and minimal fibrosis, consistent with preserved contractility that accelerates LVOT flow and sustains the hypercontractility–obstruction cycle. Conversely, nonobstructive patients more often exhibited a reverse-curved phenotype with diffuse fibrosis and impaired mechanics. Additionally, part of nonobstructive patients exhibited higher BNP levels than obstructive groups in our continuous cohort, consistent with advanced remodeling in prior reports[ 12 , 15 , 30 ]. These hint that absence of obstruction also does not guarantee clinical improvement in this cohort, as end-stage patients may develop systolic dysfunction (“burn out”) or pseudo-normalized nonobstructive state with impaired contractile reserve. Given the dynamic nature of LVOTO, continued and longitudinal evaluation may be warranted in suspected and fore-documented cases[ 31 ]. While selection bias may exist, since early-stage, moderately hypertrophic, nonobstructive patients often remain undiagnosed because of asymptomatic, this has little impact on interpretation of clinical referred patients. By capturing true volumetric motion, 3DE eliminates geometric assumptions and avoids the out-of-plane speckle-tracking loss inherent to 2D imaging [ 15 ], enabling more reliable quantification of multidirectional deformation and rotational mechanics. These advantages are essential for accurately quantifying the highly heterogeneous myocardial morphology in HCM. Prior comparative studies have demonstrated strong concordance between 3DE strain, 2D strain, and CMR-derived deformation metrics, with 3DE offering the shortest analysis time[ 32 ] and good reproducibility demonstrated in our study. Moreover, its broad clinical availability makes 3DE well suited for large real-world HCM cohorts, where CMR access often varies. Collectively, these attributes support the robustness, scalability, and translational relevance of our 3DE-based findings. With the advent of cardiac myosin inhibitors that specifically target hypercontractility, these findings may help identify patients most likely to benefit as well as those at risk of contractile reserve exhaustion[ 33 , 34 ]. Accordingly, routine integration of 3DE analysis holds promise for refined patient selection, risk stratification, and longitudinal follow-up. Limitations This study has several limitations. First, its single-center and design may limit generalizability. Although 3DE datasets were acquired prospectively, analyses were retrospective. Only patients with moderate hypertrophy were included, excluding those with severe or apical/mid-ventricular obstruction. Second, genetic heterogeneity across HCM subtypes was not considered, which may influence myocardial mechanics and LVOTO susceptibility. Our subvalvular score assessed key mitral anomalies but did not fully evaluate chordal elongation, posterior leaflet length, or annular displacement. Moreover, only 150 of 216 patients underwent CMR, limiting fibrosis assessment. Despite high reproducibility, 3DE remains image-dependent; ~10% of patients were excluded for poor quality, highlighting limitations in routine practice. Prospective multicenter studies are warranted to validate these findings and clarify the prognostic role of myocardial mechanics in LVOTO progression. Conclusions In HCM with moderate septal hypertrophy, 3D-derived hypercontractility, particularly exaggerated LV twist and torsion, emerged as independent biomechanical determinants of obstruction beyond conventional anatomic factors. The demonstrated nonlinear and threshold-dependent associations between twist/torsion and LVOTO refine mechanistic understanding and challenge anatomy-centric paradigms, underscoring the clinical value of integrating myocardial mechanics into risk stratification and individualized management for this heterogeneous population. Abbreviations AUC area under the curve AML anterior mitral leaflet 2/3DE 2/3-dimensional echocardiography CMR cardiac magnetic resonance EDV end-diastolic volume EF ejection fraction ESC European Society of Cardiology ESV end-systolic volume GAS global area strain GCS global circumferential strain GLS global longitudinal strain GRS global radial strain HCM hypertrophic cardiomyopathy ICC intraclass correlation coefficients LGE late gadolinium enhancement LV left ventricular LVOTO left ventricular outflow tract obstruction MR mitral valve regurgitation MV mitral valve OR odds ratio ROC receiver operating characteristic RCS restricted cubic splines SAM systolic anterior motion WT wall thickness Declarations Ethics approval and consent to participate ： This study was approved by the Ethics Committee of Tongji Medical College (Approval No.: 2022-S013-(1-4)) and complied with the latest Declaration of Helsinki (2013, Fortaleza, Brazil). Informed consent was obtained from all individual participants included in the study. Consent for publication ： Not applicable. Availability of data and materials: Datasets and study materials (e.g., echocardiographic protocols, analysis templates) from this study are available from the corresponding author upon reasonable request. Data are securely stored at Tongji hospital in line with relevant regulations. Competing interests: The authors declare that they have no competing interests. Funding : This work was supported by National Natural Science Foundation of China (82472010 and 82272109), Cardiovascular Ultrasound Innovation Team of Yunnan Province (202305AS350021). Authors' contributions: All authors made substantial contributions to this work. Yuwei Bao, Wei Zhou, and Jie Tian were primarily responsible for study conception, study design, and the acquisition and analysis of three-dimensional echocardiographic data. Jeffrey B. Geske, Si Fang, Shiliang Liu, Liming Xia, and Youbin Deng contributed to the interpretation of clinical findings and provided critical intellectual input during data analysis and manuscript revision. The first draft of the manuscript was prepared by Yuwei Bao, and all authors contributed to subsequent critical revisions for important intellectual content. Yani Liu, as the corresponding author, supervised the overall project, provided methodological oversight, and ensured the integrity of the analyses and the manuscript. All authors read and approved the final version of the manuscript and agree to be accountable for all aspects of the work. Acknowledgements: None. References Ommen SR, Ho CY, Asif IM, Balaji S, Burke MA, Day SM, et al. 2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of Hypertrophic Cardiomyopathy: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. 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Additional Declarations No competing interests reported. Supplementary Files TableS1.docx TableS2.docx FigS1.jpg FigS2.jpg FigS3.jpg Cite Share Download PDF Status: Published Journal Publication published 07 Mar, 2026 Read the published version in BMC Medical Imaging → Version 1 posted Editorial decision: Revision requested 28 Jan, 2026 Reviews received at journal 25 Jan, 2026 Reviews received at journal 19 Jan, 2026 Reviews received at journal 16 Jan, 2026 Reviewers agreed at journal 13 Jan, 2026 Reviewers agreed at journal 13 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviewers invited by journal 07 Jan, 2026 Editor invited by journal 18 Dec, 2025 Editor assigned by journal 15 Dec, 2025 Submission checks completed at journal 12 Dec, 2025 First submitted to journal 12 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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07:46:06","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":22029,"visible":true,"origin":"","legend":"","description":"","filename":"Table4.docx","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/47a222cbc0d393d7ee163d7c.docx"},{"id":100036586,"identity":"6a42787b-0acc-4c92-b9a6-1cb4ceb54b2b","added_by":"auto","created_at":"2026-01-12 10:25:07","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19148,"visible":true,"origin":"","legend":"","description":"","filename":"Table5.docx","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/a5985e0226d36eeb4b873eed.docx"},{"id":100036584,"identity":"2ee34ca2-4d93-4fbb-a102-8793617c4ec7","added_by":"auto","created_at":"2026-01-12 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10:25:08","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":742367,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/24b421cf73e4c7be587d2c5f.png"},{"id":100036619,"identity":"097573ae-ed35-40d2-953e-e5280f224c1a","added_by":"auto","created_at":"2026-01-12 10:25:08","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84084,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/46be26ee3c67461f9c68a6e2.png"},{"id":100036625,"identity":"9dddf39d-2c20-4ecf-9eb2-de26ac853a7e","added_by":"auto","created_at":"2026-01-12 10:25:09","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":147264,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/bfe67998f7b9f4002fae5da6.png"},{"id":100036559,"identity":"5e06029f-598c-4438-b070-24be48205bb3","added_by":"auto","created_at":"2026-01-12 10:25:07","extension":"xml","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":185117,"visible":true,"origin":"","legend":"","description":"","filename":"6ec556b1e9294e8c82fe359f1fb79d491structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/388d97d822ea30f63b75a46f.xml"},{"id":100363271,"identity":"4ea6d919-dc7e-4eff-951e-5b22ed4af471","added_by":"auto","created_at":"2026-01-16 07:49:15","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":201388,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/b0ae09bafd51b0a0663436c8.html"},{"id":100036536,"identity":"5488f4b5-216c-4917-b55a-5c32dc88fc4f","added_by":"auto","created_at":"2026-01-12 10:25:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":405362,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorkflow of the study enrollment. \u003c/strong\u003eHCM: hypertrophic cardiomyopathy; LVOTO: left ventricular outflow tract obstruction; LV: left ventricle; 3DE: three-dimensional echocardiography.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/2cf66fa9480b6328028a8e58.jpg"},{"id":100363590,"identity":"7e26c5f1-0165-46d6-930e-f876f7513c1e","added_by":"auto","created_at":"2026-01-16 07:50:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1393487,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative 3DE-derived strain maps in different LVOTO states.\u003c/strong\u003e Representative three-dimensional echocardiographic (3DE) strain maps are shown for individuals with nonobstructive (top row), provokable LVOTO (middle row), and resting LVOTO (bottom row). In each case, the first column presents the three-chamber view, followed by color-coded polar maps illustrating longitudinal strain, circumferential strain, area strain, radial strain, twist, and torsion. Segmental values are displayed numerically, with corresponding global values provided in the lower left corner of each map. Resting LVOTO exhibits the most pronounced multidirectional strain augmentation compared with other subgroups.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/4cceda2659d09224574c57ea.jpg"},{"id":100036546,"identity":"41bb2017-5d13-4ddc-9b87-516dccd1f9ce","added_by":"auto","created_at":"2026-01-12 10:25:06","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":331840,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRCS curves depicting the associations between LV twist and torsion (independent variables) and the presence of LVOTO; dependent variable) under resting and provoked conditions. \u003c/strong\u003eRed lines represent odds ratios (ORs) estimated from RCS models; shaded areas indicate 95% confidence intervals. P for overall tests the significance of the entire association; P for nonlinear evaluates deviation from linearity. Top row: LV twist vs. resting LVOTO (left) and provokable LVOTO (right); Bottom row: LV torsion vs. resting LVOTO (left) and provokable LVOTO (right). Both twist and torsion demonstrated significant nonlinear associations with LVOTO. The risk of obstruction increased progressively with higher values of twist and torsion, reaching a plateau or peak beyond approximately 15° for twist and 3°/cm for torsion. This elevated risk was more pronounced under provoked conditions.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/a0b17a5d4b72024b3fa30bab.jpg"},{"id":100036589,"identity":"84ca50cc-e09c-466b-a4a3-69a1467cd380","added_by":"auto","created_at":"2026-01-12 10:25:08","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":376919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe increased value of 3DE mechanics for differentiating LVOTO indicated by ROC curves. \u003c/strong\u003eThe left panel shows the ROC curves for provokable LVOTO, while the right panel shows those for resting LVOTO. The blue curves represent the ROC when 3DE mechanics are incorporated with structural metrics, and the yellow curves represent the ROC with pure structural parameters. The area under the curve (AUC: [95CI]) values are provided in the legends for each condition. A higher AUC indicates better classified performance. LVOTO, left ventricular outflow tract obstruction; 3DE, three-dimensional echocardiography; ROC, receiver-operating characteristic; AUC, area under the curve.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/a237ad3c1a75570e45a745ef.jpg"},{"id":104250734,"identity":"7eba664d-3263-40b1-9d36-b118ae69b4c1","added_by":"auto","created_at":"2026-03-09 16:07:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4408403,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/f1e7990e-d001-4894-891e-45c9bdadb0ee.pdf"},{"id":100036531,"identity":"e9d86671-37ad-4283-9104-b9940808f481","added_by":"auto","created_at":"2026-01-12 10:25:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21365,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/d992079d1654890bb8ad2988.docx"},{"id":100036541,"identity":"920f4ab7-8efa-49fa-85d1-fca3f18680c5","added_by":"auto","created_at":"2026-01-12 10:25:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17493,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/7f7049244ef9835de4d586a3.docx"},{"id":100036538,"identity":"f6a17e1d-411f-427e-8a66-25205f5e1a64","added_by":"auto","created_at":"2026-01-12 10:25:06","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":158124,"visible":true,"origin":"","legend":"","description":"","filename":"FigS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/92b244391433b61afc49820e.jpg"},{"id":100036544,"identity":"e7124e93-2680-4646-9d68-04fbd741b856","added_by":"auto","created_at":"2026-01-12 10:25:06","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":134991,"visible":true,"origin":"","legend":"","description":"","filename":"FigS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/1c5a28a60c254106c188e765.jpg"},{"id":100363273,"identity":"c7236795-ffcf-4942-995a-cae698cceec4","added_by":"auto","created_at":"2026-01-16 07:49:15","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":672896,"visible":true,"origin":"","legend":"","description":"","filename":"FigS3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8315722/v1/09c107f8443b6f9ca2a5d863.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Three-Dimensional Echocardiography-Derived Myocardial Mechanistic Insights into Obstructive Hypertrophic Cardiomyopathy with Moderate Septal Hypertrophy","fulltext":[{"header":"Background","content":"\u003cp\u003eHypertrophic cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy with prevalence of 1:200\u0026ndash;1:500[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. HCM is characterized by left ventricular (LV) hypertrophy without a secondary cause, with patients demonstrating a heterogeneous clinical course. Up to 70% of patients develop LV outflow tract obstruction (LVOTO), either at rest or with provocation, a dynamic phenomenon strongly associated with adverse outcomes including progressive heart failure, ventricular arrhythmias, and sudden cardiac death [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. While septal hypertrophy remains the primary anatomical determinant of LVOTO, a notable proportion of patients with only moderate septal thickening (\u0026le;\u0026thinsp;18 mm) paradoxically exhibit significant LVOT pressure gradients[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Even moderate septal thickening can be associated with extreme LVOTO[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This observation suggests that factors beyond myocardial morphology contribute to the development and severity of obstruction. Notably, Parag et al. highlighted the contribution of mitral valve (MV) and subvalvular anomalies to LVOTO development in this subgroup through integrated cardiac magnetic resonance (CMR) and echocardiographic analyses[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These insights have led to some advocating for concomitant MV interventions alongside septal myectomy in selected patients[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Conversely, findings from a large cohort study from the Mayo Clinic challenged this approach, demonstrating that MV abnormalities are frequently present in obstructive HCM but can often be adequately addressed by extended septal myectomy alone, without requiring direct MV intervention[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, a potential limitation in patients with moderate septal hypertrophy is the insufficient septal thickness for effective resection and obstruction relief. These divergent perspectives underscore the need for a more nuanced understanding of LVOTO pathophysiology beyond traditional structural assessments in this moderate hypertrophic cohort.\u003c/p\u003e \u003cp\u003eCurrently, the emergence of novel pharmacotherapies like mavacamten, a cardiac myosin inhibitor that alleviates LVOTO via contractility modulation, highlights the pivotal role of myocardial mechanics in the genesis of obstruction[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Imaging studies using CMR feature tracking have shown that elevated global radial strain (GRS) predicts the presence of LVOTO independent of anatomic severity[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and increased global circumferential strain (GCS) is significantly correlated with obstruction, irrespective of wall thickness(WT) or myocardial fibrosis[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Furthermore, two-dimensional echocardiography (2DE) speckle-tracking has demonstrated that peak LV twist correlates to obstruction, reinforcing the concept of hyperdynamic myocardial deformation as a functional contributor to obstruction[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite growing evidence supporting the biomechanical underpinnings of LVOTO, strain signatures specific to HCM patients with moderate hypertrophy remain poorly defined. We hypothesize that hypercontractile myocardial mechanics may serve as key functional drivers of obstruction in these subtypes. Three-dimensional echocardiography (3DE) with high temporal resolution has evolved into a robust, noninvasive imaging technique capable of providing comprehensive, multidirectional, and angle-independent quantification of myocardial deformation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. 3DE was employed herein to identify previously unrecognized biomechanical determinants of LVOTO beyond standard 2DE structural imaging.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Population\u003c/h2\u003e \u003cp\u003eIn this retrospective study, 1,236 consecutive HCM patients (defined according to the 2024 ESC criteria) were screened at Tongji Hospital between July 2023 and January 2025. All patients prospectively underwent standard 2DE, 3DE and contrast Echocardiography. Contrast echo and/or CMR, was used to identify moderate septal hypertrophy (maximum WT\u0026thinsp;\u0026le;\u0026thinsp;18 mm)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], yielding 298 eligible cases. After applying exclusion criteria: (1) prior septal reduction, valvular surgery, or major cardiovascular intervention; (2) significant intrinsic valvular disease except SAM-related MR; (3) congenital heart disease; (4) inadequate 3DE image quality; and (5) apical HCM or mid-ventricular obstruction, the final cohort comprised 216 patients: 38 nonobstructive, 115 resting LVOTO (\u0026ge;\u0026thinsp;30 mmHg), and 63 provokable LVOTO (provoked\u0026thinsp;\u0026ge;\u0026thinsp;30 mmHg with resting\u0026thinsp;\u0026lt;\u0026thinsp;30 mmHg). The patient selection process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e The study was approved by the Ethics Committee of Tongji Medical College (approval number: 2022-S013-(1\u0026ndash;4). The procedures used in this study adhere to the tenets of the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical Data Collection and Imaging Acquisition\u003c/h3\u003e\n\u003cp\u003eClinical data was extracted from electronic medical records. Echocardiographic studies were conducted by experienced sonographers (W. Z. and J. T.) using a standardized protocol and a commercial ultrasound system (Vivid E95, GE Healthcare, Horten, Norway).\u003c/p\u003e \u003cp\u003eFor 2DE, standard parasternal long-axis, apical four-chamber, and apical two-chamber views were acquired with individualized optimization to maximize frame rate and ensure clear LV endocardial definition. Patients with resting LVOT gradients\u0026thinsp;\u0026lt;\u0026thinsp;50 mmHg underwent provocation maneuvers (e.g., Valsalva); if these failed to induce LVOTO, exercise echocardiography was performed using the modified Bruce treadmill protocol[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. For 3DE, full-volume LV datasets were acquired from the apical window using a matrix-array transducer with multi-beat ECG-gated acquisition during end-expiratory breath-hold, maintaining\u0026thinsp;\u0026ge;\u0026thinsp;40 volumes/s to ensure adequate temporal resolution. A 12-slice display was used to verify complete LV coverage before strain analysis.\u003c/p\u003e\n\u003ch3\u003eImage Processing and Analysis\u003c/h3\u003e\n\u003cp\u003eAll datasets were exported to a dedicated workstation (EchoPAC, Vision 204, GE Medical System) for offline analysis.\u003c/p\u003e \u003cp\u003e2DE structural measurements, including maximal WT, early diastolic transmitral flow velocity (E), early diastolic mitral annular velocity (e\u0026prime;), LVOT diameter (LVOTD), and anterior mitral leaflet (AML) length. LVOTD was measured in mid-systole 0.5\u0026ndash;1 cm below the aortic annulus, and AML length in end-diastole, both in the parasternal long-axis view using the inner edge-to-inner edge method[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Septal morphology was determined from the long axis view[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. SAM and MR grades were evaluated according to the 2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of HCM[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. LAVi was derived by the biplane method at end-systole and indexed to BSA.\u003c/p\u003e \u003cp\u003eA semi-quantitative scoring system was applied to evaluate subvalvular anomalies, with one point assigned for the presence of each of the following features (maximum score: 4): (1) accessory papillary muscle (additional or abnormally positioned papillary muscle structures) or anomalous muscular bundles (aberrant myocardial structures extending from the LV apex to the basal septum or anterior wall)[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], (2) anterior displacement or bifurcation of the papillary muscles, (3) papillary muscle hypertrophy (an end-diastolic diameter\u0026thinsp;\u0026gt;\u0026thinsp;9 mm on imaging), and (4) direct insertion of papillary muscle into the MV. These characteristics were defined based on prior literature descriptions[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and expert consensus. Representative features and scoring criteria are illustrated in \u003cb\u003eFig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/b\u003e Scoring was performed independently by two experienced sonographers with 6 and 13 years of experience, respectively. Discrepancies were resolved by consensus. When available, CMR images were reviewed for reference, and late gadolinium enhancement (LGE) percentage of myocardium was analyzed when applicable.\u003c/p\u003e \u003cp\u003eThree-dimensional speckle-tracking echocardiography (3D-STE) analysis was performed using 4D AutoLVQ software (GE Healthcare) following standardized protocols[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] with analysis workflow showcase in \u003cb\u003eFig \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e. LV end-diastolic volume (EDV), end-systolic volume (ESV), and ejection fraction (EF) were calculated, followed by dynamic LV modeling and volume\u0026ndash;time curve generation. For strain analysis, automated endocardial tracking was performed across the cardiac cycle using a 16-segment LV model. Global longitudinal (GLS), GCS, GRS, and area strain (GAS) were computed as weighted averages of segmental values. LV twist (\u0026deg;) was defined as apical\u0026thinsp;\u0026minus;\u0026thinsp;basal rotation, and torsion (\u0026deg;/cm) as twist normalized to LV long-axis length. All 3D-STE analyses were performed by a 6-year-experienced echocardiographer (Y.W.B.). Inter-study reproducibility was tested in 20 randomly selected patients, reanalyzed one week apart.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and categorical variables as counts (%). Between-group comparisons used one-way ANOVA or Kruskal\u0026ndash;Wallis tests for continuous variables, and chi-square or Fisher\u0026rsquo;s exact tests for categorical variables. Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analyses entered multivariate linear regression models, adjusted for confounders (e.g., age, BSA) to identify independent LVOTO predictors. Regression coefficients (B) with 95% CIs were reported. Restricted cubic spline (RCS) models assessed nonlinear associations between 3DE-derived mechanics (twist, torsion) and LVOT gradients, with Wald tests evaluating overall and nonlinear effects. Receiver operating characteristic (ROC) analysis determined discriminative performance of significant strain parameters, with AUCs compared by the DeLong test to evaluate the incremental value of 3DE mechanics. Reproducibility was tested using intraclass correlation coefficients (ICC) and Bland\u0026ndash;Altman analysis. Analyses were performed with SPSS 23.0 (IBM, Chicago, IL) and MedCalc 20.0.22 (MedCalc, Ostend, Belgium). A two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics and Echocardiographic Parameters\u003c/h2\u003e \u003cp\u003eThe baseline clinical characteristics of 216 HCM patients stratified by LVOTO status (nonobstructive, resting, and provokable) summarizes in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Systolic blood pressure was highest in the nonobstructive group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Paroxysmal supraventricular tachycardia and dyspnea were most frequent in the resting LVOTO group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). NT-proBNP levels were elevated in both nonobstructive and resting LVOTO groups compared to the provokable group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePopulation Clinical Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eHCM with moderate hypertrophy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll(n\u0026thinsp;=\u0026thinsp;216)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo LVOTO\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProvokable LVOTO(n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResting LVOTO\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale, n/%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130/60.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (76.32%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (63.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61 (53.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56(45,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (38,61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (46,63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (45.5,65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBSA, m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/kg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResting LVOT gradient, mmHg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (11,98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (4,9)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9,19)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86 (59,125)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProvoked LVOT gradient, mmHg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (57,131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (8,24)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 (57,99)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120 (92,146)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP, mmHg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (115,142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137 (111,148)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132 (120,146)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125 (113,137)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDBP, mmHg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u0026thinsp;\u0026plusmn;\u0026thinsp;12#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74\u0026thinsp;\u0026plusmn;\u0026thinsp;10*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeart rate, bpm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (56,69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (61,73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (54,68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61 (58,69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNYHA class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNT-proBNP, pg/ml\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e260 (115,583)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e444 (149.5,875)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e206 (96.3,299.2)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e455 (194.3,893.7)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ecTnI, ng/ml\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(7.4,18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.5 (4.4,41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8 (4.2,15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (4,15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (34.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (28.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (34.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (36.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.696\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (7.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (13.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (31.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (18.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (31.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (34.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSVT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (13.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.63%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (9.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (19.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (32.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (28.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (30.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41 (35.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (47.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (28.95%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (41.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65 (56.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyncope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (12.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (13.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (11.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (13.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.867\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalpitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (30.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (23.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (26.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (34.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.334\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (39.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (18.42%)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (41.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (45.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium channel antagonists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (10.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (19.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (9.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eFootnote\u003c/b\u003e: #indicates vs resting LVOTO; *indicates vs provokable LVOTO. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range) for continuous variables and number (percentage) for categorical variables. Comparisons among groups were performed using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables, and the chi-square test for categorical variables. Adjusted p-values were calculated using the Bonferroni correction for multiple comparisons. BSA: body surface area; LVOT: left ventricular outflow tract; SBP: systolic blood pressure; DBP: diastolic blood pressure; NYHA: New York Heart Association; CAD: coronary artery disease; PSVT: paroxysmal supraventricular tachycardia.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong conventional parameters, maximal WT was slightly greater in the resting LVOTO group compared to the provokable group (16 mm vs. 15 mm, p\u0026lt;0.05). Overall LVEF was preserved (66%), with the highest value in the resting LVOTO subgroup (71.2%), paralleling the trend in 2DE-derived GLS. Diastolic dysfunction was most pronounced in the resting LVOTO group with the highest E/e\u0026prime; ratio and greatest LAVI (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The severity of SAM and MR followed the pattern of obstruction, greatest in the resting LVOTO group, followed by the provokable group, and then the nonobstructive cohort. Morphologically, a sigmoid septum predominated in the resting LVOTO group (63.4%), while a reverse curve was more common in the nonobstructive group (52.6%). Detailed comparations are supplemented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eConventional LV Structural Measurements of HCM subgroups Footnote\u003c/b\u003e: #indicates vs resting LVOTO, * indicates vs provoked LVOTO. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range) for continuous variables and number (percentage) for categorical variables. Comparisons among groups were performed using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables, and the chi-square test for categorical variables. Adjusted p-values were calculated using the Bonferroni correction for multiple comparisons. WT: wall thickness, LVEDVi: left ventricular end diastolic volume index, LVESVi: left ventricular end systolic volume index, LVEF: left ventricular ejection fraction, LAVI: left atrial volume index, SAM: systolic anterior motion, GLS: global longitudinal strain, MR: mitral regurgitation, CMR: cardiac magnetic resonance, LGE: late gadolinium enhancement.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eHCM with Moderate Hypertrophy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;216)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNonobstructive\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProvokable LVOTO(n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResting LVOTO\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaximal WT, mm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (15,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (15,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (14,16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (15,17)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVEDVi, ml/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.7 (42.8,56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.9 (41.7,59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.2 (45.8,59.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.5 (48.94,64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVESVi, ml/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.72 (16.1,20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.2 (14.7,22.9)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.91 (12.35,20.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.12 (12.8,18.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVEF, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (60,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.0 (57.8,62.5)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.4 (63.1,73.9)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.2(65.01,77.3)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLAVi, ml/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (30,45.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (26,41.75)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.7 (28,39)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (34.2,50.95)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eE/e\u0026rsquo;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (10,16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.8 (8,12.75)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (8.22,15)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (12,18)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSAM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0,1)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0,2)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2,4)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D GLS, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-15.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-13.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-16.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-16.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMR grade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1,1)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1,2)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2,4)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeptal morphology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSigmoid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137(63.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(21.1%)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46(73.0%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83(62.6%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReverse curve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(52.6%)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(14.3%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19(14.8%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003cp\u003e\u003cb\u003eCMR-derived LGE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(14.4%)\u003c/p\u003e \u003cp\u003e150(69.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(26.3%)#\u003c/p\u003e \u003cp\u003e19(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(12.7%)\u003c/p\u003e \u003cp\u003e38(60.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(4.3%)\u003c/p\u003e \u003cp\u003e93(80.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126(84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/19(47.4%)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31/38(81.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86/93(92.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/19(42.1%)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4/38(10.5%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7/93(0.8%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2/19(10.5%)#*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3/38(7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubMV Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0,1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0,1)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0,1)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1,2)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAccessory papillary muscle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (18.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (15.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (15.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (20.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnterior displacement of papillary muscles\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (35.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (28.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (22.22%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (45.22%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePapillary muscle hypertrophy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (5.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (5.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (4.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (6.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePapillary muscle multifurcation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (11.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (7.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.61%)#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (18.26%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsertion of papillary muscle into the MV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOf the 216 patients, 150 (69.4%) underwent CMR with LGE evaluation. Among these, 19 (12.7%) were in the nonobstructive group, 38 (25.3%) in the provokable LVOTO group, and 93 (62.0%) in the resting LVOTO group. The extent of LGE was significantly lower in both the resting (p\u0026thinsp;=\u0026thinsp;0.001) and provokable (p\u0026thinsp;=\u0026thinsp;0.018) LVOTO groups compared to the nonobstructive group. SubMV scores were highest in the resting LVOTO group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), driven mainly by anterior papillary muscle displacement and bifurcation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cb\u003e3DE Metrics Comparison\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, patients with resting LVOTO showed the greatest augmentation in multidirectional mechanics, including GCS, GAS, GRS, twist, and torsion, followed by the provokable LVOTO group and then the nonobstructive group. Differences between either LVOTO subgroup and the nonobstructive group were statistically significant (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas no significant differences were observed between the two LVOTO subgroups (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Representative 3DE strain maps for each subgroup are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, visually illustrating these intergroup differences. Notably, twist and torsion demonstrated the highest difference across subgroups (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Supplementarily, strain parameters of the nonobstructive group exhibited the highest degree of similarity to those of 32 healthy control subjects, with comparison data provided in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of 3DE LV Strain Components of HCM Subgroups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHCM with Moderate Hypertrophy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eP values of LVOTO vs nonobstructive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP values of two LVOTO groups\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;216)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNonobstructive\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProvokable LVOTO(n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResting LVOTO(n\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eProvokable LVOTO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eResting LVOTO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGLS, -%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.39(11.98,16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5 (10,13.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (13,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (12,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGCS, -%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.6(16.1,21,1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (14,18.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (15.25,21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (17,21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGAS, -%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.8(24.6,32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (22,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (25,32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (26,32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.020*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGRS, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.6(37.2,53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.5 (32,46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (38,54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (40,54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeak twist, \u0026deg;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.4(6.6,17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.25 (3.1,10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2 (7.05,17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.7 (8.35,19.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeak torsion, \u0026deg;/cm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.55 (0.88,2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.45 (1.5,3.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7 (2.05,3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.031*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cb\u003eFootnote\u003c/b\u003e: *indicates statistic difference is significant (p\u0026lt;0.05). Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range) for continuous variables and number (percentage) for categorical variables. Comparisons among groups were performed using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables, and the chi-square test for categorical variables. GLS: global longitudinal strain, GCS: global circumferential strain, GAS: global area strain, GRS: global radial strain.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociations and Diagnostic Performance\u003c/h3\u003e\n\u003cp\u003eMultivariate models adjusted for age, sex, and BSA identified LVOTD and SubMV score as consistent structural predictors of both resting and provoked LVOT gradients. Due to collinearity, ESVi was used to represent LV size, and twist and torsion were analyzed separately. Maximal WT independently predicted resting but not provoked gradients. Importantly, twist, torsion, and GAS remained independent mechanical predictors of both resting and provoked LVOT gradients (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in models within torsion). Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and Multivariate Linear Regression Analysis of the Resting and Provoked Gradients of Left Ventricular Outflow Tract\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eProvokable LVOT Gradient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c14\" namest=\"c10\"\u003e \u003cp\u003eResting LVOT Gradient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMultivariable (Model 1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMultivariable (Model 2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eMultivariable (Model 1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eMultivariable (Model 2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-14.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-21.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaximal WT, mm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.33(-0.90,7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.44(-0.96,7.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.10(0.12,8.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.044*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.93(0.15,7.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.043*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVOTD, mm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.95(-7.20,-2.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.70(-6.3,-1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-6.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-4.89(-7.28,-2.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-5.02(-7.05,-2.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3DE EDVi, ml/m2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3DE ESVi, ml/m2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAML length, mm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubMV score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.56(3.0,20.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.009*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.04(4.3,21.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e17.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e10.79(2.81,18.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e11.08(3.45,18.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGLS, -%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGCS, -%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGAS, -%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29(0.35,2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.035*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.86(-0.38,6.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.21(-0.83,3.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.24(0.15,2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.027*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGRS, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTwist, \u0026deg;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.92(1.02,2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.35(0.48,2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTorsion, \u0026deg;/cm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.47(3.63,15.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e14.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e10.64(5.55,15.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"16\"\u003e\u003cb\u003eFootnote\u003c/b\u003e: Univariate variables with p-values less than 0.05 were included in the multivariate model in a stepwise manner. Model 1 of Multivariable analysis indicates enrolling LV twist, while Model 2 indicates torsion was enrolled for model construction. LVOTO: left ventricular outflow tract obstruction; LVEDVi: left ventricular end diastolic volume index, LVESVi: left ventricular end systolic volume index, LVEF: left ventricular ejection fraction, 3DE: three-dimensional echocardiography, AML: anterior mitral leaflet; GLS: global longitudinal strain, GCS: global circumferential strain, GAS: global area strain, GRS: global radial strain.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurther RCS analyses demonstrated load-dependent and nonlinear associations between LV twist/torsion and the risk of LVOTO, with evident threshold effects as indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For twist, in the resting state, the association was modest and near linear, with odds ratios (ORs) gradually increasing from 1.0 to ~\u0026thinsp;2.0 as twist rose to 15\u0026deg;, followed by a plateau at higher values (\u0026gt;\u0026thinsp;15\u0026deg;). Under provocation, the association became more prominent and nonlinear, with ORs rising sharply from 1.0 to ~\u0026thinsp;4.0 across 5\u0026ndash;15\u0026deg;, then reaching a plateau at \u0026gt;\u0026thinsp;15\u0026deg;. For torsion, the nonlinear relationship was more pronounced. At rest, ORs increased steeply from 1.0 to ~\u0026thinsp;3.0 within the 1\u0026ndash;3\u0026deg;/cm range, with a plateau thereafter (\u0026gt;\u0026thinsp;3\u0026deg;/cm). In the provoked state, the association was markedly nonlinear, with ORs rising rapidly and peaking near 6.0, indicating a substantial risk of obstruction under hemodynamic stress.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eROC analysis (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) demonstrated LV torsion as the strongest determinant of provokable LVOTO, achieving 81% specificity at a threshold of 2.4\u0026deg;/cm (AUC\u0026thinsp;=\u0026thinsp;0.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), outperforming all structural metrics, with twist as the next best performer. For resting LVOTO, LVOTD yielded the highest AUC, while twist at a value of 8.0\u0026deg; offered superior sensitivity of 78% (p\u0026thinsp;=\u0026thinsp;0.005). Integrating 3DE-derived mechanics with structural metrics significantly improved diagnostic performance. For provokable LVOTO, the AUC improved from 0.75 to 0.84 (Delong p\u0026thinsp;=\u0026thinsp;0.003), with specificity rising from 63% to 78%. Similarly, for resting LVOTO, the AUC increased from 0.76 to 0.82 (Delong p\u0026thinsp;=\u0026thinsp;0.013), with sensitivity improving from 68% to 86%. These gains are visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC Results of Variables for Identifying Resting and Provokable LVOTO\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariates\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eProvokable LVOTO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eResting LVOTO\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThresholds\u003c/p\u003e \u003cp\u003e(Sen/ Spe)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eThresholds\u003c/p\u003e \u003cp\u003e(Sen/ Spe)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVOTD, mm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.71(0.62,0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.5(55%,72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68(0.60,0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.5(65%,64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubMV Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60(0.50,0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5(70%,44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67(0.60,0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.5(36%,90%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAS, -%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.68(0.58,0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.5(75%,58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.60(0.52,0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.5(67%,54%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwist, \u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72(0.62,0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.9(61%,78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62(0.54,0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.0(78%,44%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTorsion, \u0026deg;/cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72(0.62,0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4(60%,81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66(0.59,0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.7(57%,71%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCombined metrics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructural metrics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75(0.68,0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80(77%,63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76(0.70,0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.56(68%,73%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3DE mechanics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75(0.66,0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83(68%,75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67(0.57,0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.43(78%,50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructure\u0026thinsp;+\u0026thinsp;3DE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84(0.76,0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83(78%,78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82(0.76,0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.41(86%,63%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eFootnote\u003c/b\u003e: LVOTO, left ventricular outflow tract obstruction; AUC: area under the curve; Sen, sensitivity; Spe, specificity; CI, confidence intervals; LVOTD, left ventricular outflow tract diameter; SubMV score, sub mitral valve anomaly score; GAS, global area strain.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBland-Altman plots \u003cb\u003e(Fig \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e) and ICCs confirmed good to excellent reproducibility of 3DE strain measurements, with ICCs ranging from 0.887 to 0.984 (\u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first study to characterize 3DE-derived myocardial mechanics in relation to LVOTO specifically in HCM patients with moderate septal hypertrophy (WT\u0026thinsp;\u0026le;\u0026thinsp;18 mm). \u003cem\u003eThree\u003c/em\u003e \u003cb\u003ekey insights\u003c/b\u003e \u003cem\u003eemerged\u003c/em\u003e: \u003cb\u003e(1)\u003c/b\u003e \u003cem\u003eBoth resting and provokable LVOTO groups showed significantly greater 3DE-derived strain than the nonobstructive group (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with twist and torsion the most discriminative parameters (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/em\u003e \u003cb\u003e(2)\u003c/b\u003e \u003cem\u003eMultivariable regression identified twist, torsion, and GAS as predictors of provoked LVOT gradients independent of structural factors. Nonlinear associations were evident, with obstruction risk sharply rising above twist\u0026thinsp;=\u0026thinsp;15\u0026deg; and torsion\u0026thinsp;=\u0026thinsp;3\u0026deg;/cm, particularly under provocation.\u003c/em\u003e \u003cb\u003e(3)\u003c/b\u003e \u003cem\u003eTwist and torsion outperformed structural parameters in detecting provokable LVOTO, and twist was most sensitive for resting LVOTO. Integrating 3DE-derived mechanics with structural indices improved diagnostic performance.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eThis study extends previous understanding by showing that, in HCM with moderate LV hypertrophy, LVOTO results from hypertrophy, MV abnormalities, and notably, exaggerated myocardial mechanics.\u003c/em\u003e Among structural parameters, LVOTD emerged as the strongest independent predictor, outperforming maximal WT. This highlights that systolic LVOT narrowing, not septal hypertrophy alone, is the dominant driver of obstruction pathogenesis. To better quantify subvalvular apparatus contributions, we developed a composite SubMV score capturing diverse mitral subvalvular abnormalities. This score showed a strong and independent association with elevated LVOT gradients, extending previous findings[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and reinforcing the concept that the MV apparatus is not merely a bystander but rather an active contributor to LVOTO pathophysiology[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Among its sub-components, apical displacement and bifid morphology of the papillary muscles were the most frequently observed anomalies although relatively lower prevalence in our cohort compared to earlier reports[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] likely reflects the exclusion of apical- and mid-ventricular obstructive HCM, in which these anomalies are more prevalent[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These papillary anomalies aggravate flow obstruction by magnifying valvular motion during systole, a mechanism well-established in previous literature[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eImportantly, our findings highlight the independent, mechanistical role of myocardial hypercontractility in LVOTO development, as assessed by 3DE.\u003c/em\u003e Unlike prior studies associating impaired GLS with myocardial injury without accounting for hypertrophy severity[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], this study focused on patients with moderate septal hypertrophy, where GLS was only mildly reduced (-14.4%) despite preserved ejection fraction (67%), underscoring its value as an early marker of subclinical dysfunction[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Importantly, both resting and provokable obstruction groups exhibited markedly enhanced myocardial mechanics compared with nonobstructive patients, hint hypercontractility as a contributor of outflow tract obstruction. These exaggerated patterns persisted after structural adjustment and were most pronounced in provokable obstruction, even twist and torsion outperformed anatomy. Collectively, these results support the paradigm that contractile mechanics are core contributors, not mere epiphenomena, in developing LVOTO among moderate HCMs. Our results align with those of Lo et al.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], who also highlighted the role of rotational mechanics in obstructive HCM using 2DE. Increased LV twist and torsion reflects enhanced shear deformation between the apex and base[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. RCS analysis provides mechanistic insight that excessive LV torsion contributes directly to LVOTO. Physiologically, twist and torsion enhance ejection efficiency but once exceeding a critical threshold (~\u0026thinsp;15\u0026deg;/~3\u0026deg;/cm), they may induce abnormal wall stress, distort the LVOT geometry, and increase obstruction risk. Concurrently, elevated GAS indicates reinforced centripetal contraction, further amplifying intraventricular pressure gradients. These exaggerated mechanical responses act synergistically to drive LVOTO, a pattern most pronounced under provoked conditions when hemodynamic demand intensifies. The improved diagnostic performance of models incorporating 3DE-derived strain indices further supports this mechanistic interpretation.\u003c/p\u003e \u003cp\u003eMorphologically, most LVOTO patients showed a sigmoid septal shape with basal bulging and minimal fibrosis, consistent with preserved contractility that accelerates LVOT flow and sustains the hypercontractility\u0026ndash;obstruction cycle. Conversely, nonobstructive patients more often exhibited a reverse-curved phenotype with diffuse fibrosis and impaired mechanics. Additionally, part of nonobstructive patients exhibited higher BNP levels than obstructive groups in our continuous cohort, consistent with advanced remodeling in prior reports[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These hint that absence of obstruction also does not guarantee clinical improvement in this cohort, as end-stage patients may develop systolic dysfunction (\u0026ldquo;burn out\u0026rdquo;) or pseudo-normalized nonobstructive state with impaired contractile reserve. Given the dynamic nature of LVOTO, continued and longitudinal evaluation may be warranted in suspected and fore-documented cases[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. While selection bias may exist, since early-stage, moderately hypertrophic, nonobstructive patients often remain undiagnosed because of asymptomatic, this has little impact on interpretation of clinical referred patients.\u003c/p\u003e \u003cp\u003eBy capturing true volumetric motion, 3DE eliminates geometric assumptions and avoids the out-of-plane speckle-tracking loss inherent to 2D imaging [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], enabling more reliable quantification of multidirectional deformation and rotational mechanics. These advantages are essential for accurately quantifying the highly heterogeneous myocardial morphology in HCM. Prior comparative studies have demonstrated strong concordance between 3DE strain, 2D strain, and CMR-derived deformation metrics, with 3DE offering the shortest analysis time[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and good reproducibility demonstrated in our study. Moreover, its broad clinical availability makes 3DE well suited for large real-world HCM cohorts, where CMR access often varies. Collectively, these attributes support the robustness, scalability, and translational relevance of our 3DE-based findings. With the advent of cardiac myosin inhibitors that specifically target hypercontractility, these findings may help identify patients most likely to benefit as well as those at risk of contractile reserve exhaustion[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Accordingly, routine integration of 3DE analysis holds promise for refined patient selection, risk stratification, and longitudinal follow-up.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, its single-center and design may limit generalizability. Although 3DE datasets were acquired prospectively, analyses were retrospective. Only patients with moderate hypertrophy were included, excluding those with severe or apical/mid-ventricular obstruction. Second, genetic heterogeneity across HCM subtypes was not considered, which may influence myocardial mechanics and LVOTO susceptibility. Our subvalvular score assessed key mitral anomalies but did not fully evaluate chordal elongation, posterior leaflet length, or annular displacement. Moreover, only 150 of 216 patients underwent CMR, limiting fibrosis assessment. Despite high reproducibility, 3DE remains image-dependent; ~10% of patients were excluded for poor quality, highlighting limitations in routine practice. Prospective multicenter studies are warranted to validate these findings and clarify the prognostic role of myocardial mechanics in LVOTO progression.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn HCM with moderate septal hypertrophy, 3D-derived hypercontractility, particularly exaggerated LV twist and torsion, emerged as independent biomechanical determinants of obstruction beyond conventional anatomic factors. The demonstrated nonlinear and threshold-dependent associations between twist/torsion and LVOTO refine mechanistic understanding and challenge anatomy-centric paradigms, underscoring the clinical value of integrating myocardial mechanics into risk stratification and individualized management for this heterogeneous population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAUC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003earea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAML\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanterior mitral leaflet\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003e2/3DE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e2/3-dimensional echocardiography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCMR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecardiac magnetic resonance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEDV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eend-diastolic volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eESC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Society of Cardiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eESV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eend-systolic volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGAS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglobal area strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGCS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglobal circumferential strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGLS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglobal longitudinal strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGRS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglobal radial strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHCM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehypertrophic cardiomyopathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eICC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintraclass correlation coefficients\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLGE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elate gadolinium enhancement\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eleft ventricular\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLVOTO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eleft ventricular outflow tract obstruction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emitral valve regurgitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emitral valve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eROC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRCS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erestricted cubic splines\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSAM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esystolic anterior motion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWT\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewall thickness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eThis study was approved by the Ethics Committee of Tongji Medical College (Approval No.: 2022-S013-(1-4)) and complied with the latest Declaration of Helsinki (2013, Fortaleza, Brazil).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e Datasets and study materials (e.g., echocardiographic protocols, analysis templates) from this study are available from the corresponding author upon reasonable request. Data are securely stored at Tongji hospital in line with relevant regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This work was supported by National Natural Science Foundation of China (82472010 and 82272109), Cardiovascular Ultrasound Innovation Team of Yunnan Province (202305AS350021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e All authors made substantial contributions to this work. Yuwei Bao, Wei Zhou, and Jie Tian were primarily responsible for study conception, study design, and the acquisition and analysis of three-dimensional echocardiographic data. Jeffrey B. Geske, Si Fang, Shiliang Liu, Liming Xia, and Youbin Deng contributed to the interpretation of clinical findings and provided critical intellectual input during data analysis and manuscript revision. The first draft of the manuscript was prepared by Yuwei Bao, and all authors contributed to subsequent critical revisions for important intellectual content. Yani Liu, as the corresponding author, supervised the overall project, provided methodological oversight, and ensured the integrity of the analyses and the manuscript. All authors read and approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements: None.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOmmen SR, Ho CY, Asif IM, Balaji S, Burke MA, Day SM, et al. 2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of Hypertrophic Cardiomyopathy: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. Circulation. 2024;149. https://doi.org/10.1161/CIR.0000000000001250.\u003c/li\u003e\n\u003cli\u003eVeselka J, Anavekar NS, Charron P. Hypertrophic obstructive cardiomyopathy. The Lancet. 2017;389:1253\u0026ndash;67. https://doi.org/10.1016/S0140-6736(16)31321-6.\u003c/li\u003e\n\u003cli\u003eGandhi R, Ooi EL, Mugwagwa A, Botrous C, Raman B. A Review of Multimodality Imaging in Hypertrophic Cardiomyopathy: Diagnosis, Risk Stratification, and Therapeutic Guidance. Radiology: Cardiothoracic Imaging. 2025;7:e240555. https://doi.org/10.1148/ryct.240555.\u003c/li\u003e\n\u003cli\u003eNeubauer S, Kolm P, Ho CY, Kwong RY, Desai MY, Dolman SF, et al. Distinct Subgroups in Hypertrophic Cardiomyopathy in the NHLBI HCM Registry. Journal of the American College of Cardiology. 2019;74:2333\u0026ndash;45. https://doi.org/10.1016/j.jacc.2019.08.1057.\u003c/li\u003e\n\u003cli\u003ePatel P, Dhillon A, Popovic ZB, Smedira NG, Rizzo J, Thamilarasan M, et al. Left Ventricular Outflow Tract Obstruction in Hypertrophic Cardiomyopathy Patients Without Severe Septal Hypertrophy: Implications of Mitral Valve and Papillary Muscle Abnormalities Assessed Using Cardiac Magnetic Resonance and Echocardiography. Circ: Cardiovascular Imaging. 2015;8. https://doi.org/10.1161/CIRCIMAGING.115.003132.\u003c/li\u003e\n\u003cli\u003eGeske JB, Stephens EH, Dearani JA. Hypertrophic cardiomyopathy with extreme outflow tract obstruction. European Heart Journal. 2022;43:4518\u0026ndash;4518. https://doi.org/10.1093/eurheartj/ehac439.\u003c/li\u003e\n\u003cli\u003eGersh BJ, Maron BJ, Bonow RO, Dearani JA, Fifer MA, Link MS, et al. 2011 ACCF/AHA guideline for the diagnosis and treatment of hypertrophic cardiomyopathy: executive summary: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2011;58:2703\u0026ndash;38. https://doi.org/10.1016/j.jacc.2011.10.825.\u003c/li\u003e\n\u003cli\u003eLentz Carvalho J, Schaff HV, Nishimura RA, Ommen SR, Geske JB, Lahr BD, et al. Is anterior mitral valve leaflet length important in outcome of septal myectomy for obstructive hypertrophic cardiomyopathy? 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European Heart Journal Open. 2023;3:oead043. https://doi.org/10.1093/ehjopen/oead043.\u003c/li\u003e\n\u003cli\u003eSmiseth OA, Rider O, Cvijic M, Valkovič L, Remme EW, Voigt J-U. Myocardial Strain Imaging. JACC: Cardiovascular Imaging. 2025;18:340\u0026ndash;81. https://doi.org/10.1016/j.jcmg.2024.07.011.\u003c/li\u003e\n\u003cli\u003eSatriano A, Heydari B, Guron N, Fenwick K, Cheung M, Mikami Y, et al. 3-Dimensional regional and global strain abnormalities in hypertrophic cardiomyopathy. Int J Cardiovasc Imaging. 2019;35:1913\u0026ndash;24. https://doi.org/10.1007/s10554-019-01631-8.\u003c/li\u003e\n\u003cli\u003eLapenna E, Nisi T, Carino D, Bargagna M, Ruggeri S, Zancanaro E, et al. Hypertrophic cardiomyopathy with moderate septal thickness and mitral regurgitation: long-term surgical results. Eur J Cardiothorac Surg. 2021;60:244\u0026ndash;51. https://doi.org/10.1093/ejcts/ezab097.\u003c/li\u003e\n\u003cli\u003eNagueh SF, Phelan D, Abraham T, Armour A, Desai MY, Dragulescu A, et al. Recommendations for Multimodality Cardiovascular Imaging of Patients with Hypertrophic Cardiomyopathy: An Update from the American Society of Echocardiography, in Collaboration with the American Society of Nuclear Cardiology, the Society for Cardiovascular Magnetic Resonance, and the Society of Cardiovascular Computed Tomography. J Am Soc Echocardiogr. 2022;35:533\u0026ndash;69. https://doi.org/10.1016/j.echo.2022.03.012.\u003c/li\u003e\n\u003cli\u003eAuthors/Task Force members, Elliott PM, Anastasakis A, Borger MA, Borggrefe M, Cecchi F, et al. 2014 ESC Guidelines on diagnosis and management of hypertrophic cardiomyopathy: the Task Force for the Diagnosis and Management of Hypertrophic Cardiomyopathy of the European Society of Cardiology (ESC). Eur Heart J. 2014;35:2733\u0026ndash;79. https://doi.org/10.1093/eurheartj/ehu284.\u003c/li\u003e\n\u003cli\u003eBinder J, Ommen SR, Gersh BJ, Van Driest SL, Tajik AJ, Nishimura RA, et al. Echocardiography-Guided Genetic Testing in Hypertrophic Cardiomyopathy: Septal Morphological Features Predict the Presence of Myofilament Mutations. Mayo Clinic Proceedings. 2006;81:459\u0026ndash;67. https://doi.org/10.4065/81.4.459.\u003c/li\u003e\n\u003cli\u003eKwon DH, Setser RM, Thamilarasan M, Popovic ZV, Smedira NG, Schoenhagen P, et al. Abnormal papillary muscle morphology is independently associated with increased left ventricular outflow tract obstruction in hypertrophic cardiomyopathy. Heart. 2007;94:1295\u0026ndash;301. https://doi.org/10.1136/hrt.2007.118018.\u003c/li\u003e\n\u003cli\u003eSilbiger JJ. Abnormalities of the Mitral Apparatus in Hypertrophic Cardiomyopathy: Echocardiographic, Pathophysiologic, and Surgical Insights. J Am Soc Echocardiogr. 2016;29:622\u0026ndash;39. https://doi.org/10.1016/j.echo.2016.03.003.\u003c/li\u003e\n\u003cli\u003eMalcolmson J, Shipolini A, Mohiddin S, Savvatis K. The Mitral Valve in Hypertrophic Cardiomyopathy. Current Opinion in Cardiology. 2023;38:415\u0026ndash;23. https://doi.org/10.1097/HCO.0000000000001067.\u003c/li\u003e\n\u003cli\u003eMuraru D, Badano LP, Piccoli G, Gianfagna P, Del Mestre L, Ermacora D, et al. Validation of a novel automated border-detection algorithm for rapid and accurate quantitation of left ventricular volumes based on three-dimensional echocardiography. European Heart Journal - Cardiovascular Imaging. 2010;11:359\u0026ndash;68. https://doi.org/10.1093/ejechocard/jep217.\u003c/li\u003e\n\u003cli\u003eHarrigan CJ, Appelbaum E, Maron BJ, Buros JL, Gibson CM, Lesser JR, et al. Significance of Papillary Muscle Abnormalities Identified by Cardiovascular Magnetic Resonance in Hypertrophic Cardiomyopathy. The American Journal of Cardiology. 2008;101:668\u0026ndash;73. https://doi.org/10.1016/j.amjcard.2007.10.032.\u003c/li\u003e\n\u003cli\u003eGroarke JD, Galazka PZ, Cirino AL, Lakdawala NK, Thune JJ, Bundgaard H, et al. Intrinsic mitral valve alterations in hypertrophic cardiomyopathy sarcomere mutation carriers. European Heart Journal - Cardiovascular Imaging. 2018;19:1109\u0026ndash;16. https://doi.org/10.1093/ehjci/jey095.\u003c/li\u003e\n\u003cli\u003eFilomena D, Vandenberk B, Dresselaers T, Willems R, Van Cleemput J, Olivotto I, et al. Apical papillary muscle displacement is a prevalent feature and a phenotypic precursor of apical hypertrophic cardiomyopathy. European Heart Journal - Cardiovascular Imaging. 2023;24:1009\u0026ndash;16. https://doi.org/10.1093/ehjci/jead078.\u003c/li\u003e\n\u003cli\u003eManabe S, Kasegawa H, Arai H, Takanashi S. Management of systolic anterior motion of the mitral valve: a mechanism-based approach. Gen Thorac Cardiovasc Surg. 2018;66:379\u0026ndash;89. https://doi.org/10.1007/s11748-018-0915-0.\u003c/li\u003e\n\u003cli\u003eZhao X, Tan RS, Tang HC, Leng S, Zhang J-M, Zhong L. Analysis of three-dimensional endocardial and epicardial strains from cardiac magnetic resonance in healthy subjects and patients with hypertrophic cardiomyopathy. Med Biol Eng Comput. 2018;56:159\u0026ndash;72. https://doi.org/10.1007/s11517-017-1674-2.\u003c/li\u003e\n\u003cli\u003eTower‐Rader A, Betancor J, Popovic ZB, Sato K, Thamilarasan M, Smedira NG, et al. Incremental Prognostic Utility of Left Ventricular Global Longitudinal Strain in Hypertrophic Obstructive Cardiomyopathy Patients and Preserved Left Ventricular Ejection Fraction. JAHA. 2017;6:e006514. https://doi.org/10.1161/JAHA.117.006514.\u003c/li\u003e\n\u003cli\u003eKobayashi T, Dhillon A, Popovic Z, Bhonsale A, Smedira NG, Thamilarasan M, et al. Differences in Global and Regional Left Ventricular Myocardial Mechanics in Various Morphologic Subtypes of Patients With Obstructive Hypertrophic Cardiomyopathy Referred for Ventricular Septal Myotomy/Myectomy. The American Journal of Cardiology. 2014;113:1879\u0026ndash;85. https://doi.org/10.1016/j.amjcard.2014.03.020.\u003c/li\u003e\n\u003cli\u003ePrasad M, Geske JB, Sorajja P, Ommen SR, Schaff HV, Gersh BJ, et al. Hemodynamic changes in systolic and diastolic function during isoproterenol challenge predicts symptomatic response to myectomy in hypertrophic cardiomyopathy with labile obstruction. Cathet Cardio Intervent. 2016;88:962\u0026ndash;70. https://doi.org/10.1002/ccd.26472.\u003c/li\u003e\n\u003cli\u003eObokata M, Nagata Y, Wu VC-C, Kado Y, Kurabayashi M, Otsuji Y, et al. Direct comparison of cardiac magnetic resonance feature tracking and 2D/3D echocardiography speckle tracking for evaluation of global left ventricular strain. Eur Heart J Cardiovasc Imaging. 2016;17:525\u0026ndash;32. https://doi.org/10.1093/ehjci/jev227.\u003c/li\u003e\n\u003cli\u003eAbood Z, Jan MF, Ashraf M, Hundal P, Howard L, Sanders H, et al. Real-World Assessment of Mavacamten\u0026rsquo;s Impact on Left Ventricular Systolic and Diastolic Functions in Obstructive Hypertrophic Cardiomyopathy: A 1-Year Single-Center Observational Study. Am J Cardiol. 2025;242:68\u0026ndash;74. https://doi.org/10.1016/j.amjcard.2025.01.032.\u003c/li\u003e\n\u003cli\u003eDesai MY, Okushi Y, Gaballa A, Wang Q, Geske JB, Owens AT, et al. Serial Changes in Ventricular Strain in Symptomatic Obstructive Hypertrophic Cardiomyopathy Treated With Mavacamten: Insights From the VALOR-HCM Trial. Circ Cardiovasc Imaging. 2024;17:e017185. https://doi.org/10.1161/CIRCIMAGING.124.017185.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"hypertrophic cardiomyopathy, left ventricular outflow tract obstruction, three-dimensional speckle tracking strain, myocardial mechanics, hypertrophy","lastPublishedDoi":"10.21203/rs.3.rs-8315722/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8315722/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe mechanisms of left ventricular outflow tract obstruction (LVOTO) in hypertrophic cardiomyopathy (HCM) with moderate septal hypertrophy (\u0026le;\u0026thinsp;18 mm) remain uncertain with therapeutic implications. This study investigated the role of three-dimensional echocardiography (3DE)-derived myocardial mechanics in LVOTO.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed 216 HCM patients with moderate septal hypertrophy, stratified into nonobstructive (n\u0026thinsp;=\u0026thinsp;38), provokable LVOTO (n\u0026thinsp;=\u0026thinsp;63), and resting LVOTO (n\u0026thinsp;=\u0026thinsp;115). Transthoracic echocardiography assessed LV geometry, LVOT diameter, anterior mitral leaflet length, and papillary muscle abnormalities (via a composite SubMV score). 3DE-derived strain parameters, including global longitudinal (GLS), circumferential, radial, area (GAS) strain, twist, and torsion, were quantified. Determinants of LVOTO were evaluated using multivariate regression, restricted cubic splines (RCS), and receiver operating characteristic (ROC) analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBoth LVOTO subgroups showed significantly augmented strain mechanics versus nonobstructive patients, greatest in resting LVOTO (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05); twist and torsion were the strongest discriminators (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariate regression showed that, beyond LVOT diameter and SubMV score, torsion (B\u0026thinsp;=\u0026thinsp;9.47), twist (B\u0026thinsp;=\u0026thinsp;1.92), and GAS (B\u0026thinsp;=\u0026thinsp;1.29) independently predicted provoked LVOT gradients (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05); RCS demonstrated nonlinear twist/torsion\u0026ndash;LVOTO relationships, with obstruction risk rising sharply above twist\u0026thinsp;=\u0026thinsp;15\u0026deg; and torsion\u0026thinsp;=\u0026thinsp;3\u0026deg;/cm, especially under provocation. Torsion discriminated provokable LVOTO achieving 81% specificity (cutoff 2.4\u0026deg;/cm, AUC\u0026thinsp;=\u0026thinsp;0.72), outperforming all structural parameters. Integrating 3DE-derived mechanics with structural metrics improved diagnostic accuracy, especially in provokable LVOTO (AUC 0.84 vs. 0.76, DeLong p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn moderate-hypertrophy HCM, 3DE-derived strain mechanics, especially twist and torsion, independently determine LVOTO beyond structural narrowing, particularly under provocation, strengthening mechanistic insight and clinical applicability.\u003c/p\u003e","manuscriptTitle":"Three-Dimensional Echocardiography-Derived Myocardial Mechanistic Insights into Obstructive Hypertrophic Cardiomyopathy with Moderate Septal Hypertrophy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 10:24:34","doi":"10.21203/rs.3.rs-8315722/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-28T15:03:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-25T16:46:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T20:34:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-16T10:14:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"281880887965272918276403628332239619337","date":"2026-01-13T23:53:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284150800747173246125119060764117767938","date":"2026-01-13T13:53:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240849177801795467484355594745776858938","date":"2026-01-08T18:57:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-07T18:05:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-18T15:06:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-15T16:08:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-12T12:20:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2025-12-12T12:08:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ffdcb630-6726-4c84-9db7-284535f40e41","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:03:01+00:00","versionOfRecord":{"articleIdentity":"rs-8315722","link":"https://doi.org/10.1186/s12880-026-02257-8","journal":{"identity":"bmc-medical-imaging","isVorOnly":false,"title":"BMC Medical Imaging"},"publishedOn":"2026-03-07 15:59:14","publishedOnDateReadable":"March 7th, 2026"},"versionCreatedAt":"2026-01-12 10:24:34","video":"","vorDoi":"10.1186/s12880-026-02257-8","vorDoiUrl":"https://doi.org/10.1186/s12880-026-02257-8","workflowStages":[]},"version":"v1","identity":"rs-8315722","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8315722","identity":"rs-8315722","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}