Validation of a novel three-dimensional ultrafast cardiac MRI protocol in adolescents: a non-inferiority study compared with the 2D gold standard

Validation of a novel three-dimensional ultrafast cardiac MRI protocol in adolescents: a non-inferiority study compared with the 2D gold standard | 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 Validation of a novel three-dimensional ultrafast cardiac MRI protocol in adolescents: a non-inferiority study compared with the 2D gold standard Wei Chen, Shuo Liu, Wei Li, Hui Wang, Shuang Li, Yike Zhao, Xinyan Tao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8587794/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Cardiac magnetic resonance (CMR) is the gold standard for assessing cardiac anatomy and function. However, long acquisition times and multiple breath-holds pose significant challenges in pediatric imaging. Objective To perform a non-inferiority analysis comparing a novel three-dimensional (3D) ultrafast CMR protocol against the conventional two-dimensional (2D) gold standard for evaluating cardiac function, strain, and tissue characterization in adolescents. Materials and Methods Thirty-nine adolescents (mean age 12.2 ± 2.6 years) underwent both a standard 2D protocol and a 3D ultrafast protocol at 3.0 T. The 3D protocol comprised Enhanced Sensitivity Encoding by Static Outer Volume Subtraction (ESSOS) cine and 3D Late Gadolinium Enhancement (LGE). Image quality and diagnostic confidence were compared. A pre-specified non-inferiority margin (Δ) was used to assess functional and strain parameters. Agreement was evaluated using Bland-Altman analysis and intraclass correlation coefficients (ICCs). Results The total scan time was significantly shorter for the 3D protocol compared to the 2D protocol (75.8 ± 10.0 s vs. 734.4 ± 19.6 s, P < 0.05). Image quality scores were comparable between protocols (median score 4.0, P = 0.74). The 3D protocol demonstrated statistical non-inferiority for all functional and strain metrics. Bland-Altman analysis showed minimal bias for key parameters, and the 95% confidence intervals for differences met the pre-specified non-inferiority margins.ICCs indicated good to excellent agreement for all parameters. Conclusion The novel 3D ultrafast CMR protocol is non-inferior to the conventional 2D gold standard for quantitative assessment of cardiac function and strain in adolescents. It offers comparable image quality with significantly reduced acquisition times, potentially improving clinical feasibility in pediatric populations. Cardiac magnetic resonance Adolescents 3D imaging ESSOS Non-inferiority Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Cardiovascular diseases (CVDs) in pediatric populations encompass a range of conditions, including congenital heart disease (CHD), cardiomyopathy, myocarditis, Kawasaki disease, and arrhythmia. Recent advances in diagnostic and therapeutic techniques have led to a substantial increase in the survival rates of children diagnosed with CVD [ 1 ]. Accurate characterization of cardiac anatomy, hemodynamics, function, and myocardial tissue before and after treatment is crucial for clinical decision-making and long-term follow-up [ 2 ]. Echocardiography is the primary imaging tool for evaluating CVD in children. However, it exhibits certain limitations, especially in the detailed assessment of extracardiac vascular imaging, retrosternal structures, and myocardial tissue characteristics. Moreover, its effectiveness is influenced by operator dependence and consistency [ 3 – 5 ]. Cardiac magnetic resonance (CMR) is recognized as the gold standard for quantifying ventricular morphology and functional features. Accurate assessment of morphological and functional alterations is crucial for treatment planning, determining efficacy, and monitoring follow-up [ 5 , 6 ]. Therefore, CMR has emerged as an essential diagnostic modality in the evaluation of CVD in pediatric patients. Nevertheless, one limitation of CMR examination is its prolonged scanning time and the fact that specific sequences are acquired using the breath-holding method, which is not well-suited for children across various age groups [ 1 , 5 , 7 ]. Therefore, CMR examinations characterized by rapid acquisition, free breathing, reduced breath-holding times, and shortened scanning times are urgently needed, particularly for the diagnosis of CVD in children [ 7 , 8 ]. Recently, isotropic three-dimensional (3D) cine (enhanced sensitivity encoding [SENSE]) (ESSOS) and 3D late gadolinium enhancement (LGE) sequences have been introduced, enabling the accurate assessment of the heart anatomy, function, and myocardial characteristics in a shorter time compared with conventional two-dimensional (2D) sequences [ 6 , 9 ]. However, whether this fast 3D CMR protocol is suitable for pediatric and adolescent patients remains unclear. In addition, the strain analysis ability should be compared between 3D and 2D cine sequences. Therefore, our study aimed to validate a new 3D ultrafast CMR protocol for determining cardiac anatomy, function, and LGE. Materials and Methods Subjects The study protocol complied with the Declaration of Helsinki and was approved by the local Institutional Review Board (No. KS20220585). The parents or guardians of all participants provided written informed consent. A total of 50 adolescents were screened, and 43 were finally enrolled in the program. They were able to undergo magnetic resonance examination either alone or in the presence of a guardian and could cooperate with breath-holding. Pediatric patients who required CMR examinations for clinical reasons were recruited, including those with suspected or confirmed myocarditis; those presenting with chest tightness, chest pain, or palpitations; those suspected of or diagnosed with hypertrophic cardiomyopathy; those with hypertension; those referred owing to abnormal electrocardiograms; those with CHD; and those on follow-up after cardiac surgery. The exclusion criteria were as follows: ① patients with claustrophobia; ② patients who were restless during the examination and could not complete it; ③ patients who could not tolerate the MRI scanning noise; and ④ patients with severe arrhythmia or spontaneous interruption of scanning. CMR protocols CMR examinations were conducted using a 3-T scanner (Ingenia CX, Philips Healthcare, Best, the Netherlands) equipped with a 16-element phased-array cardiac coil. Routine breath-hold 2D cine and LGE sequences were acquired. The 3D CMR protocol comprised enhanced sensitivity encoding by static outer volume subtraction (ESSOS) and isotropic 3D LGE sequences. Routine standard 2D cine scans were performed before injecting the gadolinium contrast agent. Balanced turbo field echo (TFE) steady-state free precession sequences with the following parameters were used: field of view (FOV), 270 × 270 × 96 mm; voxel size, 1.8 × 1.8 mm; repetition time (TR), 2.8 ms; echo time (TE), 1.41 ms; flip angle, 45°; SENSE 2.8, and a slice thickness of 5 mm, with no gap between the slices. ESSOS was acquired after the intravenous administration of 0.10 mmol/kg gadoteric acid contrast agent (Gadovist, Bayer AG). The parameters of the ESSOS sequence included a nonregulated 3D coronal volume with an FOV of 300 × 321 × 340 mm (FH-AP-RL). The 3D k-space was acquired via centric spiral ky-kz profile order with a voxel size of 2.60 ×2.66 ×2.74 mm (reconstructed to 1.34×1.34×1.70 mm) and 20 cardiac phases (triggered retrospectively). Nonselective radiofrequency excitation pulses were utilized to obtain a short TR (2.8 ms) with a relatively high flip angle (45°) while using full echo acquisition (TE = 1.35 ms). Briefly, the principle of ESSOS reconstruction is based on acquiring two interleaved datasets, one static and the other dynamic. The static dataset is obtained with a relatively low SENSE factor and is acquired only once during the cardiac cycle, as it does not require any temporal information. In contrast, the dynamic (cine) dataset is acquired with a higher SENSE factor for each cardiac phase. ESSOS automatically selects static regions in the image domain and subtracts them from the dynamic dataset. Subsequently, the dynamic dataset is reconstructed and added to the static region in the image domain. After static region subtraction, the dynamic regions occupy a smaller volume in the FOV, resulting in a reduced effective SENSE factor. After 10 minutes of gadoteric acid contrast agent injection, a Look-Locker scan was performed to determine the appropriate inversion time for acquiring 3D and 2D LGE images. 3D LGE imaging was conducted in the sagittal orientation using inversion recovery spoiled TFE acquisition (TR = 2.2 ms; TE = 1.08 ms; flip angle = 7°). A 3D volume of 350 × 350 × 141 mm (FH-AP-LR) was acquired, with a spatial resolution of 2.2 × 2.2 × 2.2 mm. The acquisition was triggered at end-diastole with a mean shot interval of 185 ms, and the entire acquisition was accelerated using a parallel acquisition factor of 4 (2 × 2 in the AP and LR directions), resulting in a breath-hold time of 13 s. For comparison, multiple 2D slices were acquired using an equivalent acquisition technique. The in-plane resolution of the 2D images was 1.55 × 0.55 mm, the slice thickness was 8 mm, and the images were acquired with an FOV of 380 × 380 mm and a parallel acquisition factor of 2, resulting in a 15-s breath-hold per slice. Image Analysis All CMR data were transferred to an offline workstation with the commercial post-processing software CVI42 (Circle Cardiovascular Imaging). Image quality was evaluated by two radiologists (both with over 10 years of experience) via a subjective visual assessment before image analysis. Subjective image quality was rated on a five-point Likert scale, as follows: 5 = excellent image quality, interpretable with no artifacts; 4 = good image quality, interpretable with minimal artifacts; 3 = average image quality, interpretation mildly compromised by image artifacts; 2 = below-average image quality, interpretable but moderately compromised; and 1 = poor image quality, uninterpretable images [ 6 , 10 ]. Detailed qualitative scoring (scores of 0–3) was performed according to the standardized criteria of the European Cardiovascular Magnetic Resonance Registry, considering image artifacts or impaired image quality, with lower scores indicating better image quality [ 4 , 11 , 12 ]. Interobserver and intraobserver variability were assessed in 20 randomly selected patients, with a minimum of 1 week between evaluations. In all cardiac phases, 3D cine images were reformatted by radiologists in the short-axis view using a slice thickness of 5 mm with no gap, mimicking the coverage of 2D cine images. Images were obtained from 2D and 3D cine for functional and strain analysis, whereas the presence of LGE was obtained from 2D and 3D LGE images. The left ventricular end-diastolic volume (LVEDV), right ventricular end-diastolic volume (RVEDV), left ventricular end-systolic volume (LVESV), right ventricular end-systolic volume (RVESV), left ventricular mass (LVM), left ventricular stroke volume (LVSV), and right ventricular stroke volume (RVSV) were measured. To measure strain, the endocardial and epicardial borders were traced on the entire stack of 2D and ESSOS cine short-axis and two- and four-chamber long-axis images using artificial intelligence (AI). Subsequently, these contours were tracked throughout the cardiac cycle. Manual correction was performed when the output provided by the AI was inadequate. The following myocardial strain parameters were derived: peak systolic global longitudinal strain (GLS), peak global radial strain (GRS), and peak global circumferential strain (GCS) [ 12 ]. The presence of LGE was evaluated, and diagnostic confidence was assigned a score. Where present, LGE was semiautomatically quantified using the full-width half-maximum method [ 13 ]. Statistical analysis Statistical analyses were performed using SPSS software, version 26 (IBM, Armonk, NY). Normality was assessed using the Shapiro–Wilk test. Continuous variables are presented as mean ± standard deviation (SD) for normally distributed data and as median with interquartile range (IQR) for non-normally distributed data. Categorical variables are expressed as frequencies and percentages. Continuous variables were compared between groups using paired t-tests or Wilcoxon signed-rank tests, as appropriate.The primary analysis was a non-inferiority test comparing the 3D ESSOS protocol to the 2D gold standard for cardiac function parameters, adhering to regulatory guidelines for new medical diagnostics [ 14 , 15 ]. Pre-specified non-inferiority margins (Δ) were defined based on clinical rationale and established CMR thresholds: LVEDV 15 mL, LVESV 8 mL, LVSV 10 mL, LVCO 0.8 L/min, LVM 10 g, LVEF 5%, RVEDV 15 mL, RVESV 8 mL, RVSV 10 mL, RVCO 0.8 L/min, RVEF 5%, and 3% for all strain parameters (LVGLS, LVGCS, LVGRS) [ 16 , 17 , 18 ]. Non-inferiority was established if the relevant limit of the 95% confidence interval (lower or upper bound, as appropriate) met the pre-specified margins. Specifically, considering the potential for underestimation, non-inferiority was confirmed if the lower bound of the 95% CI was greater than the negative margin (Δ)[ 14 ]. Agreement was evaluated using Bland–Altman analysis to determine mean bias and 95% limits of agreement (LoA). Inter- and intra-observer reliability were assessed using intraclass correlation coefficients (ICCs), with values > 0.75 considered good and > 0.90 excellent. A two-sided P-value < 0.05 was considered statistically significant. Results Participant characteristics The screening and enrollment process is illustrated in Fig. 1 . Of 50 screened individuals, 43 were enrolled. Two participants withdrew, and two were excluded due to suboptimal image quality, resulting in a final cohort of 39 patients (22 males, 17 females; mean age 12.2 ± 2.6 years). Clinical indications included chest symptoms (n = 10), suspected/confirmed myocarditis (n = 8), hypertrophic cardiomyopathy (n = 5), hypertension (n = 2), abnormal ECG (n = 5), congenital heart disease (n = 4), and history of cardiac surgery (n = 5). Demographic data are summarized in Table 1 . Comparison of acquisition time The 3D ultrafast CMR protocol (ESSOS + 3D LGE) required a total scanning time of 75.8 ± 10.0 s. The 3D cine sequence required repetition in only two patients. In contrast, the conventional 2D sequences required 734.4 ± 19.6 s. The 3D acquisition time was significantly shorter than that of the 2D protocol ( P < 0.05). Image quality and LGE diagnostic confidence Representative cases are shown in Fig. 2 . Subjective general image quality scores were identical between sequences (median 4.0; P = 0.74). No significant differences were found for specific artifacts (respiratory/cardiac ghosting, blurring) (all P > 0.05) (Table 2 ). Diagnostic confidence for LGE was high and comparable between techniques ( P > 0.99). Cardiac function and strain parameters The 3D ESSOS sequence demonstrated non-inferiority to the 2D sequence for all key parameters (Table 3 ). For LVEF, the mean difference was − 1.2% (95% CI: -2.69 to 0.29%); the lower bound (-2.69%) was greater than the negative margin (-5%), and the upper bound was well below the 5% margin. Similarly, volumetric parameters met non-inferiority criteria: LVEDV (mean difference 1.5 mL; upper bound 3.87 mL < Δ15 mL), LVESV (mean difference 2.0 mL; upper bound 4.17 mL < Δ8 mL), and LVM (mean difference − 1.8 g; upper bound 1.38 g < Δ10 g). Notably, for LVCO, the mean difference was − 0.15 L/min with a 95% CI of -0.45 to 0.15 L/min, falling entirely within the ± 0.8 L/min margin. Right ventricular parameters also demonstrated non-inferiority: RVEDV (mean difference − 0.5 mL) and RVSV (mean difference − 0.6 mL) had confidence intervals within margins. RVCO showed a minimal mean difference of -0.05 L/min. For myocardial strain, LVGLS showed a mean difference of 0.7%. The lower bound of the 95% CI (-2.89%) was greater than the pre-specified negative margin (-3%), thereby meeting the non-inferiority criterion.LVGCS (mean difference 0.0%) and LVGRS (mean difference 0.3%) also demonstrated good consistency. Bland–Altman analysis showed excellent agreement. The mean bias for LVEF was − 1.2% and for LVM was − 1.8 g. The mean bias for LVEDV was 1.5 mL. These minimal biases indicate no substantial systematic error between the 3D and 2D protocols. ICC analysis corroborated these findings, with absolute agreement and consistency ICC values exceeding 0.80 for most parameters (Table 4 ). Discussion This study highlights the significant clinical advantages of the 3D ultrafast CMR protocol over conventional 2D cine sequences in adolescent patients. First, the 3D protocol achieves diagnostic non-inferiority across all core cardiac functional and strain parameters, matching the reliability of the 2D gold standard that underpins clinical decision-making. Second, it preserves equivalent image quality and diagnostic confidence, ensuring no compromise in identifying clinically relevant findings such as myocardial fibrosis. Third, it delivers a dramatic reduction in scan time and simplifies the imaging workflow. These features collectively position the 3D ultrafast CMR protocol as a robust, practical alternative for routine clinical practice, addressing the challenges of patient cooperation and expanding access to high-quality cardiac imaging in pediatric populations. To our knowledge, this is the first study to rigorously validate the non-inferiority of the ESSOS-based 3D ultrafast CMR protocol against the 2D gold standard in an adolescent cohort. Unlike previous studies that reported only a lack of statistical difference, we employed a rigorous framework with predefined margins (Δ). Our results demonstrate that 3D ESSOS meets clinically acceptable equivalence standards while achieving an approximate 90% reduction in scan time, marking a paradigm shift toward a "fast, accurate, and patient-friendly" model in pediatric CMR [ 19 ]. The core strength of this study lies in establishing statistical non-inferiority. For LVEF, the upper bound of the 95% CI for the mean difference (0.29%) was far below the 5% margin—a result superior to 3D-2D differences reported in adult literature. Volumetric parameters (LVEDV, LVESV) also showed excellent performance, with variability significantly lower than that reported by Maredia et al [ 20 ] using k-t SENSE technology. Notably, our LVM measurement bias was only − 1.8 g, demonstrating higher precision than the 3 g deviation reported in deep learning-accelerated 3D CMR studies [ 21 , 22 ]; this is likely attributable to the optimized signal-to-noise ratio provided by ESSOS static outer volume subtraction. Furthermore, hemodynamic assessment proved highly reliable; LVCO and RVCO demonstrated minimal mean biases of -0.15 L/min and − 0.05 L/min, respectively, with confidence intervals falling entirely within the strict ± 0.8 L/min margin. Right ventricular assessment—historically challenging in pediatric CMR—also achieved non-inferiority, confirming the feasibility of rapid imaging for accurate biventricular quantification. Regarding myocardial strain, we are the first to demonstrate in adolescents that 3D strain analysis maintains high consistency with the gold standard (LVGLS bias of 0.7%), offering a reliable tool for detecting subclinical dysfunction. Although the confidence interval for LVGLS was slightly wider, the lower bound (-2.89%) remained within the clinically acceptable non-inferiority range (>-3%), indicating that the 3D protocol does not clinically underestimate strain values. Comprehensive agreement analysis further supported these findings. Bland–Altman plots demonstrated narrow 95% LoA for all parameters, supporting interchangeability between the 2 techniques. For LVEF, the mean bias was − 1.2% (95% LoA: -10.2% to 7.8%), notably narrower than values reported in previous pediatric CMR imaging validation studies [ 23 , 24 ]. The minimal bias and uniform distribution of differences across the measurement range confirmed the absence of systematic error proportional to disease severity, a critical consideration for monitoring progressive conditions such as cardiomyopathy. ICC analysis corroborated these results, with absolute agreement values > 0.80 for all key parameters, demonstrating excellent reliability and exceeding ICCs reported for free-breathing 3D sequences [ 26 ]. The 3D ESSOS sequence represents a transformative advancement in pediatric CMR imaging, combining ultrafast acquisition, high-resolution coverage, and comprehensive functional assessment while overcoming key limitations of conventional 2D multislice strategies. In pediatric practice, the 3D ESSOS sequence reduces breath-hold requirements, which streamlines the imaging process, enhances patient comfort, and improves compliance—key advantages for pediatric populations, who often struggle with prolonged stillness and have limited tolerance for lengthy examinations [ 28 ]. Additionally, the sequence’s nondirectional acquisition protocol eliminates the need for prescan cardiac axis alignment, a step that accounts for 28% of examination time in pediatric 2D imaging. By removing this workflow barrier, the 3D ESSOS sequence not only shortens the total scan time but also minimizes motion artifacts and errors caused by poor patient cooperation, directly addressing 2 key challenges in pediatric CMR imaging: anxiety-driven noncompliance and motion-related image degradation. These advances collectively improve imaging efficiency, enhance the patient experience, and preserve high image quality. Notably, the 3D ESSOS sequence preserves image quality comparable to that of the 2D cine sequence, with no considerable differences in left ventricular coverage, respiratory ghosts, cardiac ghosts, or image blurring. This consistency is remarkable considering its single-breath-hold acquisition and shortened scan time, highlighting that increased efficiency does not compromise diagnostic clarity [ 28 , 29 ]. Collectively, the 3D ESSOS sequence with its ultrafast single-breath-hold acquisition, isotropic resolution, comprehensive anatomical coverage, and robust functional, strain, and LGE assessment represents a uniquely valuable tool in pediatric CMR imaging. Its benefits are particularly pronounced in the diagnosis and postoperative follow-up of complex CHDs, where detailed anatomical information on the heart and great vessels is essential [ 30 ]. By overcoming the limitations of 2D imaging while maintaining or improving diagnostic performance, the 3D sequence addresses unmet needs in pediatric cardiac imaging, providing a rapid, reliable, and patient-centered solution tailored to the unique challenges of evaluating pediatric and adolescent populations. Limitations This study had several limitations. The sample size was relatively small, and the cohort included heterogeneous cardiac pathologies. Although the number of patients with LGE was small, preventing quantitative analysis of the fibrosis burden, the comparable diagnostic confidence remains a notable preliminary finding. The non-inferiority margins were predefined based on clinical rationale and literature. Various margins could yield distinct conclusions, a common consideration in non-inferiority trial design. Future studies with larger, more homogeneous patient groups are needed to further validate these results and specifically investigate the potential benefits of ESSOS imaging in complex anatomical assessments. Conclusion This study validates the novel 3D ultrafast CMR protocol as statistically non-inferior to the conventional 2D gold standard for assessing cardiac function and strain in adolescent patients. The protocol offers comparable diagnostic quality while substantially reducing scanning time, thereby enhancing patient comfort and broadening the clinical applicability of CMR in pediatric cardiology. Abbreviations 3D-three-dimensional 2D-two-dimensional CMR- cardiac magnetic resonance SENSE- sensitivity encoding ESSOS-enhanced sensitivity encoding by static outer volume subtraction EF- ejection fraction LV- left ventricular RV-right ventricular GCS- global circumferential strain GLS-global longitudinal strain GRS-global radial strain LGE- late gadolinium enhancement Declarations Competing Interests Jianxiu Lian is an employee of Philips Healthcare. The other authors have no competing interests to declare. Author Contribution L.X. and R.W. contributed to the study conception and design. Y.Z. and X.T. performed the MRI examinations and data acquisition. Material preparation and data analysis were performed by W.C., S.Liu, H.W., and S.Li. W.Li assisted with patient recruitment and clinical consultation. J.L. provided technical support for the ESSOS sequence optimization. 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Eur Heart J Imaging Methods Pract 2:e50. https://doi.org/10.1093/ehjimp/zfad054 Tables Table 1: Participant Characteristics Characteristic Value Total no. of participants 39 Male(n) 22 Female(n) 17 Mean age (y) 12.2± 2.6 Mean height (cm) 158.4±15.1 Mean weight (kg) 48.9±14.3 Table 2 Comparison of Image Quality Scores, Detailed qualitative scoring, and LGE diagnostic confidence between 2D and 3D Groups Measure Variable 2D 3D P Image quality scores General image quality 4.0(4.0,5.0) 4.0(4.0,5.0) 0.74 Detailed qualitative scoring Left ventricular coverage 0(0,0) 0(0,0) >0.99 Wraparound 0(0,0) 0(0,0) >0.99 Respiratory ghost 0(0,2) 0(0,2) 0.94 Cardiac ghost 0(0,1) 1(0,2) 0.15 Image blurring or mistriggering 1(0,2) 1(0,2) 0.16 Metallic artifacts 0(0,0) 0(0,0) 0.99 Signal loss (coil inactive) 0(0,0) 0(0,0) 0.99 Section thickness 0(0,0) 0(0,0) 0.99 Gap 0(0,0) 0(0,0) 0.99 Diagnostic confidence for LGE Diagnostic confidence 2.0(2.0,2.0) 2.0(2.0,2.0) >0.99 2D:2-dimensional,3D:3-dimensional, LGE: late gadolinium enhancement Table 3 Non-inferiority comparative analysis between the 3D group and the 2D group Variable Mean diff(3D–2D) Δ Lower limit of 95%CI Upper limit of 95%CI Non-inferiority LVEDV (mL) 1.5 15 −0.87 3.87 ✓ LVESV (mL) 2.0 8 −0.17 4.17 ✓ LVSV (mL) 2.3 10 −0.23 4.83 ✓ LVCO(L/min) −0.15 0.8 −0.45 0.15 ✓ LVM (g) −1.8 10 −4.98 1.38 ✓ LVEF (%) −1.2 5 −2.69 0.29 ✓ RVEDV (mL) −0.5 15 −1.33 0.33 ✓ RVESV (mL) 1.4 8 −1.15 3.95 ✓ RVSV (mL) −0.6 10 −2.75 1.55 ✓ RVCO(L/min) −0.05 0.8 −0.25 0.15 ✓ RVEF (%) −0.54 5 −1.18 0.10 ✓ LVGLS (%) 0.7 3 −2.89 4.29 ✓ LVGCS (%) 0.0 3 −2.63 2.63 ✓ LVGRS (%) 0.3 3 −2.36 2.96 ✓ 2D:2-dimensional,3D:3-dimensional, LV: left ventricle, EDV: left ventricular end-diastolic volume, ESV: end-systolic volume, SV: left ventricular stroke volume, CO: cardiac output, EF: left ventricular ejection fraction, RV: right ventricl, GCS: global circumferential strain, GLS: global longitudinal strain, GRS: global radial strain TABLE 4 Absolute Agreement and Consistency Agreement ICC and 95% CI for Comparisons Between 2D and 3D ESSOS groups ICC Measured Variable Absolute Agreement (95% CI) Consistency Agreement (95% CI) LVEDV(ml) 0.95(0.90,0.97) 0.95(0.91,0.97) LVESV(ml) 0.86(0.82,0.95) 0.91(0.84,0.95) LVSV(ml) 0.94(0.85,0.98) 0.97(0.94,0.98) LVCO( L/min ) 0.91(0.80,0.96) 0.92(0.86,0.96) LVM (g) 0.83(0.79,0.94) 0.91(0.84,0.95) LVEF(%) 0.94(0.90,0.97) 0.94(0.89,0.97) RVEDV(ml) 0.93(0.87,0.96) 0.93(0.87,0.96) RVESV(ml) 0.93(0.78,0.97) 0.95(0.91,0.97) RVSV(ml) 0.97(0.96,0.99) 0.98(0.96,0.99) RVCO( L/min ) 0.87(0.74,0.93) 0.88(0.78,0.93) RVEF(%) 0.92(0.86,0.96) 0.92(0.86,0.96) GLS(%) 0.89(0.81,0.94) 0.89(0.80,0.94) GCS(%) 0.81(0.78,0.93) 0.88(0.80,0.94) GRS(%) 0.82(0.68,0.90) 0.84(0.79,0.91) 2D:2-dimensional,3D:3-dimensional, LV: left ventricle, EDV: left ventricular end-diastolic volume, ESV: end-systolic volume, SV: left ventricular stroke volume, CO: cardiac output, EF: left ventricular ejection fraction, RV: right ventricl, GCS: global circumferential strain, GLS: global longitudinal strain, GRS: global radial strain Additional Declarations Competing interest reported. Jianxiu Lian is an employee of Philips Healthcare. The other authors have no competing interests to declare. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 Apr, 2026 Reviews received at journal 31 Mar, 2026 Reviewers agreed at journal 28 Mar, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers invited by journal 30 Jan, 2026 Editor assigned by journal 29 Jan, 2026 Submission checks completed at journal 29 Jan, 2026 First submitted to journal 13 Jan, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8587794","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583185278,"identity":"6d103aeb-f991-4bd5-8870-97aff2d51176","order_by":0,"name":"Wei Chen","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Chen","suffix":""},{"id":583185279,"identity":"f05ef37f-75d3-4cc2-8184-1ae52024cbc9","order_by":1,"name":"Shuo Liu","email":"","orcid":"","institution":"Baoding No.7 Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuo","middleName":"","lastName":"Liu","suffix":""},{"id":583185280,"identity":"b3472112-d348-4d1e-9563-a26c002ca34b","order_by":2,"name":"Wei Li","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Li","suffix":""},{"id":583185281,"identity":"c1650abb-6f43-4330-b28c-cd42dd1f6a00","order_by":3,"name":"Hui Wang","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Wang","suffix":""},{"id":583185282,"identity":"3311dcaa-c153-4407-b370-eabde737c784","order_by":4,"name":"Shuang Li","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Li","suffix":""},{"id":583185283,"identity":"d3086c6a-0d38-45d6-9c79-ee27fe7bca80","order_by":5,"name":"Yike Zhao","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yike","middleName":"","lastName":"Zhao","suffix":""},{"id":583185284,"identity":"b2eb4352-7092-4065-9d9d-9f241a10c19b","order_by":6,"name":"Xinyan Tao","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xinyan","middleName":"","lastName":"Tao","suffix":""},{"id":583185286,"identity":"ba8053e6-44ba-4981-9fd1-a1dabb560a6d","order_by":7,"name":"Jianxiu Lian","email":"","orcid":"","institution":"Philips (China)","correspondingAuthor":false,"prefix":"","firstName":"Jianxiu","middleName":"","lastName":"Lian","suffix":""},{"id":583185290,"identity":"e3b91550-d179-4a68-9624-65085b2172a1","order_by":8,"name":"Rui Wang","email":"","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Wang","suffix":""},{"id":583185293,"identity":"c88171a6-fbaf-445f-88dc-113716d24c8b","order_by":9,"name":"Lei Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIie3PsQqCUBSA4SPCcTnoesKwVzAuNEW9ShI0XZqLhgrBlh6h53BWHFxsb8yEtoZeILo6h9bWcP/xcj7uOQA63R9mg7EDWDGhdWweyO4i2JBi7NlUACSKYDdRGdFCeCwbAt3ECiOXMAui3iOtnnLSRzDL26WNUBoKIkXc5dxP47laDIWQbYSDfUVcEzniNDYVIXRbyaDcZeTXixU12X5B2FC/zBYCmWqSfUEoCIenZOwhSeGf45zQ7LjFsfI7P15Mg0MxvK7jzdSxwrJqIx8yfxvX6XQ63Yfe0Yw/mQoBm+sAAAAASUVORK5CYII=","orcid":"","institution":"Beijing Anzhen Hospital","correspondingAuthor":true,"prefix":"","firstName":"Lei","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-01-13 06:08:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8587794/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8587794/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101790002,"identity":"3ccdc276-4618-4ce7-b73b-0b2698fdf42b","added_by":"auto","created_at":"2026-02-03 16:02:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":201158,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant flow diagram illustrating the enrollment, exclusion, and final analysis cohort.\u003c/p\u003e\n\u003cp\u003eMRI magnetic resonance imaging\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8587794/v1/f66a6368b07c0faafc26b882.png"},{"id":101880496,"identity":"5c44b5c0-7aa4-4714-9c15-627e55fa9161","added_by":"auto","created_at":"2026-02-04 15:02:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":678762,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative Case Images. a-c Case 1: A 12-year-old boy with chest pain. Comparisons show no significant difference in image quality or cardiac measurements between 2D and 3D ESSOS. No LGE was observed. d-f Case 2: A 14-year-old boy with myocarditis. Note the comparable image quality. Subtle high signal intensity is visible in the delayed enhancement of the right ventricular insertion point (inferior septum).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8587794/v1/98dc3c812893b9c33d65b9b4.png"},{"id":101790003,"identity":"3a623562-68e4-4552-8ad9-684ba12aab3b","added_by":"auto","created_at":"2026-02-03 16:02:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":934260,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plots comparing left ventricular (LV) parameters between 2D and 3D ESSOS protocols. a LVEDV, b LVESV, c LVSV, d LVCO, e LVM, f LVEF. Solid lines indicate mean bias; dashed lines indicate 95% limits of agreement.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8587794/v1/055eff82553e072c6e6968b1.png"},{"id":101790000,"identity":"41158cc1-342e-48a5-b98e-bbd6761cb151","added_by":"auto","created_at":"2026-02-03 16:02:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":817731,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plots comparing right ventricular (RV) parameters between 2D and 3D ESSOS protocols. a RVEDV, b RVESV, c RVSV, d RVCO, e RVEF\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8587794/v1/41673d2599f424f217233e07.png"},{"id":101790004,"identity":"70958800-2cfb-413f-bf27-e010b8b53a2c","added_by":"auto","created_at":"2026-02-03 16:02:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":470577,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman plots comparing LV strain parameters. a Global Longitudinal Strain (LVGLS), b Global Circumferential Strain (LVGCS), c Global Radial Strain (LVGRS).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8587794/v1/484925856f9b41af2d0b5b17.png"},{"id":101882187,"identity":"b492822f-5d49-4389-aba8-b2ee5713f822","added_by":"auto","created_at":"2026-02-04 15:21:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4641432,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8587794/v1/170be84c-a496-4ba7-91dc-19981328cba2.pdf"}],"financialInterests":"Competing interest reported. Jianxiu Lian is an employee of Philips Healthcare. The other authors have no competing interests to declare.","formattedTitle":"Validation of a novel three-dimensional ultrafast cardiac MRI protocol in adolescents: a non-inferiority study compared with the 2D gold standard","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular diseases (CVDs) in pediatric populations encompass a range of conditions, including congenital heart disease (CHD), cardiomyopathy, myocarditis, Kawasaki disease, and arrhythmia. Recent advances in diagnostic and therapeutic techniques have led to a substantial increase in the survival rates of children diagnosed with CVD [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Accurate characterization of cardiac anatomy, hemodynamics, function, and myocardial tissue before and after treatment is crucial for clinical decision-making and long-term follow-up [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Echocardiography is the primary imaging tool for evaluating CVD in children. However, it exhibits certain limitations, especially in the detailed assessment of extracardiac vascular imaging, retrosternal structures, and myocardial tissue characteristics. Moreover, its effectiveness is influenced by operator dependence and consistency [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCardiac magnetic resonance (CMR) is recognized as the gold standard for quantifying ventricular morphology and functional features. Accurate assessment of morphological and functional alterations is crucial for treatment planning, determining efficacy, and monitoring follow-up [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, CMR has emerged as an essential diagnostic modality in the evaluation of CVD in pediatric patients. Nevertheless, one limitation of CMR examination is its prolonged scanning time and the fact that specific sequences are acquired using the breath-holding method, which is not well-suited for children across various age groups [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, CMR examinations characterized by rapid acquisition, free breathing, reduced breath-holding times, and shortened scanning times are urgently needed, particularly for the diagnosis of CVD in children [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecently, isotropic three-dimensional (3D) cine (enhanced sensitivity encoding [SENSE]) (ESSOS) and 3D late gadolinium enhancement (LGE) sequences have been introduced, enabling the accurate assessment of the heart anatomy, function, and myocardial characteristics in a shorter time compared with conventional two-dimensional (2D) sequences [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, whether this fast 3D CMR protocol is suitable for pediatric and adolescent patients remains unclear. In addition, the strain analysis ability should be compared between 3D and 2D cine sequences. Therefore, our study aimed to validate a new 3D ultrafast CMR protocol for determining cardiac anatomy, function, and LGE.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003e The study protocol complied with the Declaration of Helsinki and was approved by the local Institutional Review Board (No. KS20220585). The parents or guardians of all participants provided written informed consent.\u003c/p\u003e \u003cp\u003eA total of 50 adolescents were screened, and 43 were finally enrolled in the program. They were able to undergo magnetic resonance examination either alone or in the presence of a guardian and could cooperate with breath-holding. Pediatric patients who required CMR examinations for clinical reasons were recruited, including those with suspected or confirmed myocarditis; those presenting with chest tightness, chest pain, or palpitations; those suspected of or diagnosed with hypertrophic cardiomyopathy; those with hypertension; those referred owing to abnormal electrocardiograms; those with CHD; and those on follow-up after cardiac surgery.\u003c/p\u003e \u003cp\u003eThe exclusion criteria were as follows: ① patients with claustrophobia; ② patients who were restless during the examination and could not complete it; ③ patients who could not tolerate the MRI scanning noise; and ④ patients with severe arrhythmia or spontaneous interruption of scanning.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCMR protocols\u003c/h3\u003e\n\u003cp\u003eCMR examinations were conducted using a 3-T scanner (Ingenia CX, Philips Healthcare, Best, the Netherlands) equipped with a 16-element phased-array cardiac coil. Routine breath-hold 2D cine and LGE sequences were acquired. The 3D CMR protocol comprised enhanced sensitivity encoding by static outer volume subtraction (ESSOS) and isotropic 3D LGE sequences.\u003c/p\u003e \u003cp\u003eRoutine standard 2D cine scans were performed before injecting the gadolinium contrast agent. Balanced turbo field echo (TFE) steady-state free precession sequences with the following parameters were used: field of view (FOV), 270 \u0026times; 270 \u0026times; 96 mm; voxel size, 1.8 \u0026times; 1.8 mm; repetition time (TR), 2.8 ms; echo time (TE), 1.41 ms; flip angle, 45\u0026deg;; SENSE 2.8, and a slice thickness of 5 mm, with no gap between the slices.\u003c/p\u003e \u003cp\u003eESSOS was acquired after the intravenous administration of 0.10 mmol/kg gadoteric acid contrast agent (Gadovist, Bayer AG). The parameters of the ESSOS sequence included a nonregulated 3D coronal volume with an FOV of 300 \u0026times; 321 \u0026times; 340 mm (FH-AP-RL). The 3D k-space was acquired via centric spiral ky-kz profile order with a voxel size of 2.60 \u0026times;2.66 \u0026times;2.74 mm (reconstructed to 1.34\u0026times;1.34\u0026times;1.70 mm) and 20 cardiac phases (triggered retrospectively). Nonselective radiofrequency excitation pulses were utilized to obtain a short TR (2.8 ms) with a relatively high flip angle (45\u0026deg;) while using full echo acquisition (TE\u0026thinsp;=\u0026thinsp;1.35 ms).\u003c/p\u003e \u003cp\u003eBriefly, the principle of ESSOS reconstruction is based on acquiring two interleaved datasets, one static and the other dynamic. The static dataset is obtained with a relatively low SENSE factor and is acquired only once during the cardiac cycle, as it does not require any temporal information. In contrast, the dynamic (cine) dataset is acquired with a higher SENSE factor for each cardiac phase. ESSOS automatically selects static regions in the image domain and subtracts them from the dynamic dataset. Subsequently, the dynamic dataset is reconstructed and added to the static region in the image domain. After static region subtraction, the dynamic regions occupy a smaller volume in the FOV, resulting in a reduced effective SENSE factor.\u003c/p\u003e \u003cp\u003eAfter 10 minutes of gadoteric acid contrast agent injection, a Look-Locker scan was performed to determine the appropriate inversion time for acquiring 3D and 2D LGE images. 3D LGE imaging was conducted in the sagittal orientation using inversion recovery spoiled TFE acquisition (TR\u0026thinsp;=\u0026thinsp;2.2 ms; TE\u0026thinsp;=\u0026thinsp;1.08 ms; flip angle\u0026thinsp;=\u0026thinsp;7\u0026deg;). A 3D volume of 350 \u0026times; 350 \u0026times; 141 mm (FH-AP-LR) was acquired, with a spatial resolution of 2.2 \u0026times; 2.2 \u0026times; 2.2 mm. The acquisition was triggered at end-diastole with a mean shot interval of 185 ms, and the entire acquisition was accelerated using a parallel acquisition factor of 4 (2 \u0026times; 2 in the AP and LR directions), resulting in a breath-hold time of 13 s. For comparison, multiple 2D slices were acquired using an equivalent acquisition technique. The in-plane resolution of the 2D images was 1.55 \u0026times; 0.55 mm, the slice thickness was 8 mm, and the images were acquired with an FOV of 380 \u0026times; 380 mm and a parallel acquisition factor of 2, resulting in a 15-s breath-hold per slice.\u003c/p\u003e\n\u003ch3\u003eImage Analysis\u003c/h3\u003e\n\u003cp\u003eAll CMR data were transferred to an offline workstation with the commercial post-processing software CVI42 (Circle Cardiovascular Imaging). Image quality was evaluated by two radiologists (both with over 10 years of experience) via a subjective visual assessment before image analysis.\u003c/p\u003e \u003cp\u003eSubjective image quality was rated on a five-point Likert scale, as follows: 5\u0026thinsp;=\u0026thinsp;excellent image quality, interpretable with no artifacts; 4\u0026thinsp;=\u0026thinsp;good image quality, interpretable with minimal artifacts; 3\u0026thinsp;=\u0026thinsp;average image quality, interpretation mildly compromised by image artifacts; 2\u0026thinsp;=\u0026thinsp;below-average image quality, interpretable but moderately compromised; and 1\u0026thinsp;=\u0026thinsp;poor image quality, uninterpretable images [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Detailed qualitative scoring (scores of 0\u0026ndash;3) was performed according to the standardized criteria of the European Cardiovascular Magnetic Resonance Registry, considering image artifacts or impaired image quality, with lower scores indicating better image quality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Interobserver and intraobserver variability were assessed in 20 randomly selected patients, with a minimum of 1 week between evaluations.\u003c/p\u003e \u003cp\u003eIn all cardiac phases, 3D cine images were reformatted by radiologists in the short-axis view using a slice thickness of 5 mm with no gap, mimicking the coverage of 2D cine images. Images were obtained from 2D and 3D cine for functional and strain analysis, whereas the presence of LGE was obtained from 2D and 3D LGE images. The left ventricular end-diastolic volume (LVEDV), right ventricular end-diastolic volume (RVEDV), left ventricular end-systolic volume (LVESV), right ventricular end-systolic volume (RVESV), left ventricular mass (LVM), left ventricular stroke volume (LVSV), and right ventricular stroke volume (RVSV) were measured.\u003c/p\u003e \u003cp\u003eTo measure strain, the endocardial and epicardial borders were traced on the entire stack of 2D and ESSOS cine short-axis and two- and four-chamber long-axis images using artificial intelligence (AI). Subsequently, these contours were tracked throughout the cardiac cycle. Manual correction was performed when the output provided by the AI was inadequate. The following myocardial strain parameters were derived: peak systolic global longitudinal strain (GLS), peak global radial strain (GRS), and peak global circumferential strain (GCS) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The presence of LGE was evaluated, and diagnostic confidence was assigned a score. Where present, LGE was semiautomatically quantified using the full-width half-maximum method [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS software, version 26 (IBM, Armonk, NY). Normality was assessed using the Shapiro\u0026ndash;Wilk test. Continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for normally distributed data and as median with interquartile range (IQR) for non-normally distributed data. Categorical variables are expressed as frequencies and percentages. Continuous variables were compared between groups using paired t-tests or Wilcoxon signed-rank tests, as appropriate.The primary analysis was a non-inferiority test comparing the 3D ESSOS protocol to the 2D gold standard for cardiac function parameters, adhering to regulatory guidelines for new medical diagnostics [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Pre-specified non-inferiority margins (Δ) were defined based on clinical rationale and established CMR thresholds: LVEDV 15 mL, LVESV 8 mL, LVSV 10 mL, LVCO 0.8 L/min, LVM 10 g, LVEF 5%, RVEDV 15 mL, RVESV 8 mL, RVSV 10 mL, RVCO 0.8 L/min, RVEF 5%, and 3% for all strain parameters (LVGLS, LVGCS, LVGRS) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Non-inferiority was established if the relevant limit of the 95% confidence interval (lower or upper bound, as appropriate) met the pre-specified margins. Specifically, considering the potential for underestimation, non-inferiority was confirmed if the lower bound of the 95% CI was greater than the negative margin (Δ)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgreement was evaluated using Bland\u0026ndash;Altman analysis to determine mean bias and 95% limits of agreement (LoA). Inter- and intra-observer reliability were assessed using intraclass correlation coefficients (ICCs), with values\u0026thinsp;\u0026gt;\u0026thinsp;0.75 considered good and \u0026gt;\u0026thinsp;0.90 excellent. A two-sided P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eParticipant characteristics\u003c/h2\u003e \u003cp\u003eThe screening and enrollment process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Of 50 screened individuals, 43 were enrolled. Two participants withdrew, and two were excluded due to suboptimal image quality, resulting in a final cohort of 39 patients (22 males, 17 females; mean age 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6 years). Clinical indications included chest symptoms (n\u0026thinsp;=\u0026thinsp;10), suspected/confirmed myocarditis (n\u0026thinsp;=\u0026thinsp;8), hypertrophic cardiomyopathy (n\u0026thinsp;=\u0026thinsp;5), hypertension (n\u0026thinsp;=\u0026thinsp;2), abnormal ECG (n\u0026thinsp;=\u0026thinsp;5), congenital heart disease (n\u0026thinsp;=\u0026thinsp;4), and history of cardiac surgery (n\u0026thinsp;=\u0026thinsp;5). Demographic data are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison of acquisition time\u003c/h3\u003e\n\u003cp\u003eThe 3D ultrafast CMR protocol (ESSOS\u0026thinsp;+\u0026thinsp;3D LGE) required a total scanning time of 75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0 s. The 3D cine sequence required repetition in only two patients. In contrast, the conventional 2D sequences required 734.4\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6 s. The 3D acquisition time was significantly shorter than that of the 2D protocol (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003ch3\u003eImage quality and LGE diagnostic confidence\u003c/h3\u003e\n\u003cp\u003eRepresentative cases are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Subjective general image quality scores were identical between sequences (median 4.0; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.74). No significant differences were found for specific artifacts (respiratory/cardiac ghosting, blurring) (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Diagnostic confidence for LGE was high and comparable between techniques (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.99).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCardiac function and strain parameters\u003c/h2\u003e \u003cp\u003eThe 3D ESSOS sequence demonstrated non-inferiority to the 2D sequence for all key parameters (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For LVEF, the mean difference was \u0026minus;\u0026thinsp;1.2% (95% CI: -2.69 to 0.29%); the lower bound (-2.69%) was greater than the negative margin (-5%), and the upper bound was well below the 5% margin. Similarly, volumetric parameters met non-inferiority criteria: LVEDV (mean difference 1.5 mL; upper bound 3.87 mL\u0026thinsp;\u0026lt;\u0026thinsp;Δ15 mL), LVESV (mean difference 2.0 mL; upper bound 4.17 mL\u0026thinsp;\u0026lt;\u0026thinsp;Δ8 mL), and LVM (mean difference\u0026thinsp;\u0026minus;\u0026thinsp;1.8 g; upper bound 1.38 g\u0026thinsp;\u0026lt;\u0026thinsp;Δ10 g). Notably, for LVCO, the mean difference was \u0026minus;\u0026thinsp;0.15 L/min with a 95% CI of -0.45 to 0.15 L/min, falling entirely within the \u0026plusmn;\u0026thinsp;0.8 L/min margin.\u003c/p\u003e \u003cp\u003eRight ventricular parameters also demonstrated non-inferiority: RVEDV (mean difference\u0026thinsp;\u0026minus;\u0026thinsp;0.5 mL) and RVSV (mean difference\u0026thinsp;\u0026minus;\u0026thinsp;0.6 mL) had confidence intervals within margins. RVCO showed a minimal mean difference of -0.05 L/min. For myocardial strain, LVGLS showed a mean difference of 0.7%. The lower bound of the 95% CI (-2.89%) was greater than the pre-specified negative margin (-3%), thereby meeting the non-inferiority criterion.LVGCS (mean difference 0.0%) and LVGRS (mean difference 0.3%) also demonstrated good consistency.\u003c/p\u003e \u003cp\u003e Bland\u0026ndash;Altman analysis showed excellent agreement. The mean bias for LVEF was \u0026minus;\u0026thinsp;1.2% and for LVM was \u0026minus;\u0026thinsp;1.8 g. The mean bias for LVEDV was 1.5 mL. These minimal biases indicate no substantial systematic error between the 3D and 2D protocols. ICC analysis corroborated these findings, with absolute agreement and consistency ICC values exceeding 0.80 for most parameters (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study highlights the significant clinical advantages of the 3D ultrafast CMR protocol over conventional 2D cine sequences in adolescent patients. First, the 3D protocol achieves diagnostic non-inferiority across all core cardiac functional and strain parameters, matching the reliability of the 2D gold standard that underpins clinical decision-making. Second, it preserves equivalent image quality and diagnostic confidence, ensuring no compromise in identifying clinically relevant findings such as myocardial fibrosis. Third, it delivers a dramatic reduction in scan time and simplifies the imaging workflow. These features collectively position the 3D ultrafast CMR protocol as a robust, practical alternative for routine clinical practice, addressing the challenges of patient cooperation and expanding access to high-quality cardiac imaging in pediatric populations.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first study to rigorously validate the non-inferiority of the ESSOS-based 3D ultrafast CMR protocol against the 2D gold standard in an adolescent cohort. Unlike previous studies that reported only a lack of statistical difference, we employed a rigorous framework with predefined margins (Δ). Our results demonstrate that 3D ESSOS meets clinically acceptable equivalence standards while achieving an approximate 90% reduction in scan time, marking a paradigm shift toward a \"fast, accurate, and patient-friendly\" model in pediatric CMR [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe core strength of this study lies in establishing statistical non-inferiority. For LVEF, the upper bound of the 95% CI for the mean difference (0.29%) was far below the 5% margin\u0026mdash;a result superior to 3D-2D differences reported in adult literature. Volumetric parameters (LVEDV, LVESV) also showed excellent performance, with variability significantly lower than that reported by Maredia et al [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] using k-t SENSE technology. Notably, our LVM measurement bias was only\u0026thinsp;\u0026minus;\u0026thinsp;1.8 g, demonstrating higher precision than the 3 g deviation reported in deep learning-accelerated 3D CMR studies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]; this is likely attributable to the optimized signal-to-noise ratio provided by ESSOS static outer volume subtraction. Furthermore, hemodynamic assessment proved highly reliable; LVCO and RVCO demonstrated minimal mean biases of -0.15 L/min and \u0026minus;\u0026thinsp;0.05 L/min, respectively, with confidence intervals falling entirely within the strict\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 L/min margin. Right ventricular assessment\u0026mdash;historically challenging in pediatric CMR\u0026mdash;also achieved non-inferiority, confirming the feasibility of rapid imaging for accurate biventricular quantification.\u003c/p\u003e \u003cp\u003eRegarding myocardial strain, we are the first to demonstrate in adolescents that 3D strain analysis maintains high consistency with the gold standard (LVGLS bias of 0.7%), offering a reliable tool for detecting subclinical dysfunction. Although the confidence interval for LVGLS was slightly wider, the lower bound (-2.89%) remained within the clinically acceptable non-inferiority range (\u0026gt;-3%), indicating that the 3D protocol does not clinically underestimate strain values. Comprehensive agreement analysis further supported these findings. Bland\u0026ndash;Altman plots demonstrated narrow 95% LoA for all parameters, supporting interchangeability between the 2 techniques. For LVEF, the mean bias was \u0026minus;\u0026thinsp;1.2% (95% LoA: -10.2% to 7.8%), notably narrower than values reported in previous pediatric CMR imaging validation studies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The minimal bias and uniform distribution of differences across the measurement range confirmed the absence of systematic error proportional to disease severity, a critical consideration for monitoring progressive conditions such as cardiomyopathy. ICC analysis corroborated these results, with absolute agreement values\u0026thinsp;\u0026gt;\u0026thinsp;0.80 for all key parameters, demonstrating excellent reliability and exceeding ICCs reported for free-breathing 3D sequences [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe 3D ESSOS sequence represents a transformative advancement in pediatric CMR imaging, combining ultrafast acquisition, high-resolution coverage, and comprehensive functional assessment while overcoming key limitations of conventional 2D multislice strategies. In pediatric practice, the 3D ESSOS sequence reduces breath-hold requirements, which streamlines the imaging process, enhances patient comfort, and improves compliance\u0026mdash;key advantages for pediatric populations, who often struggle with prolonged stillness and have limited tolerance for lengthy examinations [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Additionally, the sequence\u0026rsquo;s nondirectional acquisition protocol eliminates the need for prescan cardiac axis alignment, a step that accounts for 28% of examination time in pediatric 2D imaging. By removing this workflow barrier, the 3D ESSOS sequence not only shortens the total scan time but also minimizes motion artifacts and errors caused by poor patient cooperation, directly addressing 2 key challenges in pediatric CMR imaging: anxiety-driven noncompliance and motion-related image degradation. These advances collectively improve imaging efficiency, enhance the patient experience, and preserve high image quality.\u003c/p\u003e \u003cp\u003eNotably, the 3D ESSOS sequence preserves image quality comparable to that of the 2D cine sequence, with no considerable differences in left ventricular coverage, respiratory ghosts, cardiac ghosts, or image blurring. This consistency is remarkable considering its single-breath-hold acquisition and shortened scan time, highlighting that increased efficiency does not compromise diagnostic clarity [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Collectively, the 3D ESSOS sequence with its ultrafast single-breath-hold acquisition, isotropic resolution, comprehensive anatomical coverage, and robust functional, strain, and LGE assessment represents a uniquely valuable tool in pediatric CMR imaging. Its benefits are particularly pronounced in the diagnosis and postoperative follow-up of complex CHDs, where detailed anatomical information on the heart and great vessels is essential [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. By overcoming the limitations of 2D imaging while maintaining or improving diagnostic performance, the 3D sequence addresses unmet needs in pediatric cardiac imaging, providing a rapid, reliable, and patient-centered solution tailored to the unique challenges of evaluating pediatric and adolescent populations.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study had several limitations. The sample size was relatively small, and the cohort included heterogeneous cardiac pathologies. Although the number of patients with LGE was small, preventing quantitative analysis of the fibrosis burden, the comparable diagnostic confidence remains a notable preliminary finding. The non-inferiority margins were predefined based on clinical rationale and literature. Various margins could yield distinct conclusions, a common consideration in non-inferiority trial design. Future studies with larger, more homogeneous patient groups are needed to further validate these results and specifically investigate the potential benefits of ESSOS imaging in complex anatomical assessments.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study validates the novel 3D ultrafast CMR protocol as statistically non-inferior to the conventional 2D gold standard for assessing cardiac function and strain in adolescent patients. The protocol offers comparable diagnostic quality while substantially reducing scanning time, thereby enhancing patient comfort and broadening the clinical applicability of CMR in pediatric cardiology.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e3D-three-dimensional\u003c/p\u003e\n\u003cp\u003e2D-two-dimensional\u003c/p\u003e\n\u003cp\u003eCMR- cardiac magnetic resonance\u003c/p\u003e\n\u003cp\u003eSENSE- sensitivity encoding\u003c/p\u003e\n\u003cp\u003eESSOS-enhanced sensitivity encoding by static outer volume subtraction\u003c/p\u003e\n\u003cp\u003eEF- ejection fraction\u003c/p\u003e\n\u003cp\u003eLV- left ventricular\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRV-right ventricular\u003c/p\u003e\n\u003cp\u003eGCS- global circumferential strain\u003c/p\u003e\n\u003cp\u003eGLS-global longitudinal strain\u003c/p\u003e\n\u003cp\u003eGRS-global radial strain\u003c/p\u003e\n\u003cp\u003eLGE- late gadolinium enhancement\u003c/p\u003e"},{"header":"Declarations","content":"\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eJianxiu Lian is an employee of Philips Healthcare. The other authors have no competing interests to declare.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.X. and R.W. contributed to the study conception and design. Y.Z. and X.T. performed the MRI examinations and data acquisition. Material preparation and data analysis were performed by W.C., S.Liu, H.W., and S.Li. W.Li assisted with patient recruitment and clinical consultation. J.L. provided technical support for the ESSOS sequence optimization. The first draft of the manuscript was written by W.C. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCao J, Daanen J, Rutsaert S et al (2021) Four-dimensional flow magnetic resonance imaging in congenital heart disease: a systematic review and meta-analysis. Radiology 301:364\u0026ndash;376. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1148/radiol.2021203792\u003c/span\u003e\u003cspan address=\"10.1148/radiol.2021203792\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Agostino RB, Massaro JM et al (2003) Non-inferiority trials \u0026mdash; challenges and methodological issues. 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Eur Heart J Imaging Methods Pract 2:e50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ehjimp/zfad054\u003c/span\u003e\u003cspan address=\"10.1093/ehjimp/zfad054\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"444\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 444px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eParticipant Characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eTotal no. of participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eMale(n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eFemale(n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eMean age (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003e12.2\u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eMean height (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003e158.4\u0026plusmn;15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 281px;\"\u003e\n \u003cp\u003eMean weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003e48.9\u0026plusmn;14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u0026nbsp;\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 553px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eComparison of Image Quality Scores, Detailed qualitative scoring, and LGE diagnostic confidence between 2D and 3D Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasure Variable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e3D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImage quality scores\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eGeneral image quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4.0(4.0,5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.0(4.0,5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDetailed qualitative scoring\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eLeft ventricular coverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026gt;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eWraparound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026gt;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eRespiratory ghost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eCardiac ghost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1(0,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eImage blurring or mistriggering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1(0,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1(0,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eMetallic artifacts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eSignal loss (coil inactive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eSection thickness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eGap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0(0,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnostic confidence for LGE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eDiagnostic confidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2.0(2.0,2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e2.0(2.0,2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026gt;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 553px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2D:2-dimensional,3D:3-dimensional, LGE: late gadolinium enhancement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eNon-inferiority comparative analysis between the 3D group and the 2D group\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean diff(3D\u0026ndash;2D)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eLower limit of 95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eUpper limit of 95%CI\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eNon-inferiority\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVEDV (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVESV (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVSV (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVCO(L/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVM (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVEF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eRVEDV (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eRVESV (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eRVSV (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eRVCO(L/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eRVEF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026minus;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVGLS (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVGCS (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eLVGRS (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026minus;2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e2D:2-dimensional,3D:3-dimensional, LV: left ventricle, EDV: left ventricular end-diastolic volume, ESV: end-systolic volume, SV: left ventricular stroke volume, CO: cardiac output, EF: left ventricular ejection fraction, RV: right ventricl, GCS: global circumferential strain, GLS: global longitudinal strain, GRS: global radial strain\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"585\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 585px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTABLE 4\u0026nbsp;\u003c/strong\u003eAbsolute Agreement and Consistency Agreement ICC and 95% CI for Comparisons Between 2D and 3D ESSOS groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 390px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eICC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eMeasured Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eAbsolute Agreement\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eConsistency Agreement\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLVEDV(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.95(0.90,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.95(0.91,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLVESV(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.86(0.82,0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.91(0.84,0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLVSV(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.94(0.85,0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.97(0.94,0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLVCO(\u0026nbsp;L/min\u0026nbsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.91(0.80,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.92(0.86,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLVM (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.83(0.79,0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.91(0.84,0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLVEF(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.94(0.90,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.94(0.89,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eRVEDV(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.93(0.87,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.93(0.87,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eRVESV(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.93(0.78,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.95(0.91,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eRVSV(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.97(0.96,0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.98(0.96,0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eRVCO(\u0026nbsp;L/min\u0026nbsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.87(0.74,0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.88(0.78,0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eRVEF(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.92(0.86,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.92(0.86,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eGLS(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.89(0.81,0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.89(0.80,0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eGCS(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.81(0.78,0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.88(0.80,0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003eGRS(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.82(0.68,0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 195px;\"\u003e\n \u003cp\u003e0.84(0.79,0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 585px;\"\u003e\n \u003cp\u003e2D:2-dimensional,3D:3-dimensional, LV: left ventricle, EDV: left ventricular end-diastolic volume, ESV: end-systolic volume, SV: left ventricular stroke volume, CO: cardiac output, EF: left ventricular ejection fraction, RV: right ventricl, GCS: global circumferential strain, GLS: global longitudinal strain, GRS: global radial strain\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"}],"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":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cardiac magnetic resonance, Adolescents, 3D imaging, ESSOS, Non-inferiority","lastPublishedDoi":"10.21203/rs.3.rs-8587794/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8587794/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCardiac magnetic resonance (CMR) is the gold standard for assessing cardiac anatomy and function. However, long acquisition times and multiple breath-holds pose significant challenges in pediatric imaging.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo perform a non-inferiority analysis comparing a novel three-dimensional (3D) ultrafast CMR protocol against the conventional two-dimensional (2D) gold standard for evaluating cardiac function, strain, and tissue characterization in adolescents.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eThirty-nine adolescents (mean age 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6 years) underwent both a standard 2D protocol and a 3D ultrafast protocol at 3.0 T. The 3D protocol comprised Enhanced Sensitivity Encoding by Static Outer Volume Subtraction (ESSOS) cine and 3D Late Gadolinium Enhancement (LGE). Image quality and diagnostic confidence were compared. A pre-specified non-inferiority margin (Δ) was used to assess functional and strain parameters. Agreement was evaluated using Bland-Altman analysis and intraclass correlation coefficients (ICCs).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe total scan time was significantly shorter for the 3D protocol compared to the 2D protocol (75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0 s vs. 734.4\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6 s, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Image quality scores were comparable between protocols (median score 4.0, P\u0026thinsp;=\u0026thinsp;0.74). The 3D protocol demonstrated statistical non-inferiority for all functional and strain metrics. Bland-Altman analysis showed minimal bias for key parameters, and the 95% confidence intervals for differences met the pre-specified non-inferiority margins.ICCs indicated good to excellent agreement for all parameters.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe novel 3D ultrafast CMR protocol is non-inferior to the conventional 2D gold standard for quantitative assessment of cardiac function and strain in adolescents. It offers comparable image quality with significantly reduced acquisition times, potentially improving clinical feasibility in pediatric populations.\u003c/p\u003e","manuscriptTitle":"Validation of a novel three-dimensional ultrafast cardiac MRI protocol in adolescents: a non-inferiority study compared with the 2D gold standard","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 16:02:54","doi":"10.21203/rs.3.rs-8587794/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-04T04:42:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-31T23:24:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"281630644934593521025168421811995925089","date":"2026-03-28T20:31:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262126168737965992700351802115997793313","date":"2026-02-02T13:51:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-30T16:17:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-29T05:29:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-29T05:29:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pediatric Radiology","date":"2026-01-13T06:00:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7357887c-25c1-4681-8b8e-931de38bd70c","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T18:54:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 16:02:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8587794","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8587794","identity":"rs-8587794","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}