The implementation of speckle tracking echocardiography for cardiac resynchronization therapy optimization. A rotational myocardial mechanics interpretation

The implementation of speckle tracking echocardiography for cardiac resynchronization therapy optimization. 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A rotational myocardial mechanics interpretation Alexandros Stefanidis, Paraskevi Korlou, Panagiotis Margos, Ignatios Ikonomidis, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4318618/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Cardiac resynchronization therapy (CRT) has an additive therapeutic influence on left ventricular function in heart failure patients, but the underlying mechanisms through which it works are not completely explained. Our aim was to further elucidate the role of this intervention via rotational mechanics using 2D speckle tracking echocardiography (2D-STE). Results: We investigated 46 patients (65 ± 9 years) who received CRT. All enrolled patients were assessed on admission by 2D-STE and 6 minute walk test (6 min WT) and followed in the outpatient device clinic by 2D-STE (at one week and 6-month post-implantation) and 6 min WT (at 6 months post-implantation). On their first appointment all biventricular systems were optimized by atrioventricular delay optimization and by changing the temporal activation of ventricular electrodes aiming to reach the highest left ventricular effective stroke volume across all activation options. A new 2D-STE based index (twist integral) targeting to assess the rotational mechanics of the whole cardiac cycle was also measured to further explain the CRT response. Twenty-two (48%) patients with dilated cardiomyopathy as the predominant aetiology of heart failure were responders at 6-month follow-up. The commonest selected mode that was related with the greatest left ventricular performance response was the simultaneous activation of the 2 ventricular leads (39%). The strongest predictor of CRT response was the improvement of effective stroke volume between admission and first appointment at clinic, followed by the improvement of twist integral, the non-existence of coronary artery disease, and the improvement of peak systolic twist. Conclusions: Additional CRT optimization via changing the temporal activation of ventricular electrodes is beneficial for left ventricular performance in heart failure patients. Rotational mechanics essentially explain the beneficial CRT contribution to these patients. resynchronization therapy rotational mechanics speckle tracking echocardiography Figures Figure 1 Figure 2 Figure 3 Background Cardiac resynchronization therapy (CRT) is currently a well-recognised treatment for heart failure (HF) patients with impaired left ventricular ejection fraction (LVEF) and wide QRS complex who remain symptomatic despite optimal medical treatment ( 1 ). Since a substantial percentage of patients do not respond to CRT favourably, numerous studies have addressed different techniques to improve response rate ( 2 ). These techniques imply individual optimization of atrioventricular and interventricular delay settings, based on left ventricular (LV) filling patterns, stroke volume (SV), and asynchrony. However, despite promising single centre studies, more robust conclusions from larger trials are still needed. Speckle tracking echocardiography (STE) has emerged as a promising imaging tool for the evaluation of regional and global cardiac function in different clinical settings. This additive information provides new perception into cardiac physiology and thus improved patient management ( 3 ). STE has been validated as an accurate tool for the investigation of LV rotational mechanics which is a principal mechanism contributing to myocardial performance and thus SV. Considering the central role of myocardial twist in global heart function, we assumed that impaired LV twist is strongly related to asynchrony and can be restored by CRT explaining the improvement of global LV performance ( 4 , 5 ). The aim of the present study is an attempt to further explain via rotational mechanics the contribution of CRT optimization on LV myocardial performance, by testing the distinct influence of different modes of temporal activation of ventricular electrodes (different VV delay pacing options) with parallel assessment of LV twist. Methods Study design and participants This was a non-randomized, prospective, observational study performed in one centre. Patients indicated for a CRT implantation were consecutively included in the study. Inclusion criteria were sinus rhythm, presence of typical LBBB with QRS duration ≥ 150 ms and symptomatic HF with New York Heart Association (NYHA) functional class II to IV and LVEF ≤35% after optimal medical therapy. Patients were excluded if they had: 1) non-LBBB QRS morphology, 2) persistent atrial fibrillation, 3) PQ duration > 200 ms or 4) inadequate acoustic window for the ensuing echocardiography. This study was approved by the Institutional scientific board of Nikea hospital in accordance with the code of ethics of the world medical association (Declaration of Helsinki) for experiments involving humans. All patients provided informed and written consent. Data collection, device programming and follow up. Baseline characteristics including age, gender, body surface area (BSA), aetiology of HF, ECG, and medication were collected among all the enrolled patients. All enrolled patients were assessed on admission by 2D-STE, and 6 minute walk test (6 min WT) and followed in the outpatient device clinic by 2D-STE (at one week and 6-month post-implantation) and new 6 min WT (at 6 months post-implantation) as the outcome by which to compare changes in myocardial performance and endurance activity. On their first appointment (at 1 week) all biventricular systems were optimized by changing the temporal activation of the ventricular electrodes aiming to reach the highest LV effective stroke volume (eff SV) across all activation options. On their first post implantation appointment, all patients underwent atrioventricular (AV) delay optimization using echocardiography. Optimal AV interval was decided using mitral inflow pulsed wave Doppler based on dissociation of the E- and A- wave, with prevention of A wave truncation, and maximal AQ duration (from the end of A wave to onset of Q wave) [5]. Following AV optimization, interventricular optimization ensued by changing the temporal activation of ventricular electrodes. Five distinct pacing modes were sequentially attempted: exclusively right ventricular (RV) activation, initially RV followed by LV activation after 30 ms (RV-LV), simultaneous RV/LV activation, initially LV followed by RV activation after 30 ms (LV-RV) and exclusively LV activation (LV). Across all these distinct pacing options an immediate left ventricular outflow tract (LVOT) pulsed wave interrogation was attempted aiming to distinguish the greater tracing something that indicates the higher eff SV. Each of the selected interventricular activation modes was randomly assigned and coded by the electrophysiologist during the programming process with differing sequence. Another observer, unaware and thus unbiased for the ensuing LVOT velocity time integral (VTI) assessment performed all other imaging data analysis. Patient response to CRT was defined as 15% improvement in LV end-systolic volume (LVESV) between the baseline and the 6-month echocardiographic assessment. Pacemaker LV lead position, determined radiographically, was scored as basally (non-optimally), medially (modestly), or laterally (optimally) implanted. Two-dimensional and Doppler Echocardiography All patients underwent standard transthoracic echocardiography using an ultrasound machine (model ACCUSON SC2000, Siemens Healthcare, Mountain View, California) with a 1.25 to 4.5 MHz transducer (model 4V1C) and external workstation facility. A single echo operator performed all echocardiographic recordings for later analysis. Another single observer blinded to patient information and pacing status analysed off-line all imaging data. Two-dimensional, colour and spectral Doppler measurements were performed according to current guidelines ( 6 ). The LVEF was calculated using the modified Simpson’s method ( 7 ). Eff SV was calculated as the product of the LVOT cross-sectional area and the pulsed-wave Doppler VTI that was manually traced on the modal curve ( 8 ). LVOT diameter was measured in parasternal long-axis view at the hinge points of the opened aortic valve cusps ( 9 ). Strain and Rotational mechanics analysis All speckle tracking echocardiography off-line analyses were based on initial meticulous definition of cardiac cycle time intervals. Systole was defined from the QRS onset to the instant of aortic valve closure and diastole from this time point until the ensuing QRS onset. Two-dimensional longitudinal strain of the LV was derived from the apical four- chamber, two-chamber, and long-axis views using dedicated software installed on an external computer workstation (Siemens Healthineers eSie VVI velocity vector imaging technology, Erlangen, Germany). The echocardiographic images were recorded with temporal resolution of 60 to 70 fps. The endocardial border was manually traced, and the software automatically tracked the image speckle and produced the longitudinal strain curves in six regional segments from each apical view, respectively. A single beat was analysed, and values from three cardiac cycles were averaged. LV rotational deformation was calculated offline from 2-dimensional loops in the 2 parasternal basal and apical short-axis views, with temporal resolution of 60 to 70 fps. After the endocardial border was initially manually traced, the software was assisted by the user to confirm 6 basal and 4 apical segments. The basal level was recognised by the appearance of mitral leaflets while eliminating the mitral annulus, and the apical level by the presence of LV cavity in the absence of papillary muscles ( 10 ). The 2-dimensional speckle-tracking software calculates apical and basal LV rotation from the relevant short-axis images frame by frame. Positive values were given to counterclockwise rotation and negative values to clockwise rotation when viewed from the LV apex. LV twist was defined as the absolute apex to base difference of LV rotation at isochronal time points. The following measurements were derived exclusively for subepicardial layers: peak LV systolic and diastolic twist and twist integral (TI) of the full cardiac cycle (Fig. 1 ). The subepicardial LV twist assessment was preferred to the other myocardial layers on the basis of being more closely related to mechanical effects of CRT ( 11 ). For the calculation of LV TI of the full cardiac cycle, sequential isochronal apical and basal rotation measurements (twist i in degrees) were exported to a worksheet Excel file (Microsoft Corporation, Redmond, WA) and the final algebraic summation (Σtwist i = twist 1 + twist 2 +...+twist n ) was denoted by the formula: TΙ = systolic ΤΙ – diastolic ΤΙ (Fig. 1 ). The TI was further adjusted for the different duration of cardiac cycles by dividing it with the total number of discrete isochronal twist measurements (n), eliminating the impact of heart rate (Σ twist i /n: mean TI). Only positive twist values were included in the formula for the assessment of TI. The negative twist values during systolic or diastolic time periods were represented in the formula with a zero number since their contribution to an efficient myocardial contraction or relaxation is negligible. Statistical analysis Continuous variables were expressed as mean ± standard deviation (SD) and paired Student’s t-test was used to compare the difference between baseline and follow-up in each group. Categorical variables were presented as number (percentages) by using the Pearson’s χ 2 test or Fisher’s exact test. Only patients with available data at both enrolment, first week and 6-month appointments were included in the final analysis, and no adjustment was made for missing data. All associations among clinical data and echocardiographic were calculated using Pearson’s or Spearman’s correlation coefficient. Backward stepwise linear regression analysis was performed including all significantly related clinical and echocardiographic parameters to recognise predictors of resynchronization response in terms of at least 15% LVESV reduction. Multicollinearity in the regression analysis was examined by computation of in-model tolerance. Collinearity was considered acceptable and regression model stable for tolerance > 0.70. Repeated measures ANOVA method was used to assess group means between responders and non-responders considering dependencies between observations within subjects in the analysis. ROC curves were generated to seek for the optimal cut-off value to predict the CRT response. The intraobserver variability for repeated effective stroke volume measurements has been expressed as coefficient of variability (CV) and performed in 25 participants selected at random. The CV was calculated as SD of the difference divided by the mean of the measurement under consideration. The CV of the eff SV was 8%. All analyses were performed by SPSS version 25 (SPSS, Inc., Chicago, IL, USA) and a two-sided p value < 0.05 was considered statistically significant. Results Of the initially enrolled 50 patients undergoing CRT, 4 were excluded from the final analysis. One was excluded due to device infection, 1 due to CRT discontinuation and 2 since were lost to follow up. Ultimately, a total of 46 consecutive patients (27 men) were included and their follow up was carried out at 6 months. Three (7%) were in NYHA functional class II, 37 (80%) in NYHA III and 6 (13%) in NYHA IV respectively. All patients were on stable, optimal HF medical therapy according to current guidelines. In 33 patients HF had non-ischemic aetiology and the remainder (13 patients) had a history of coronary artery disease. The mean LV EF was 29.2 ± 7.1%, and the mean QRS duration was 173 ± 20 msec. Twenty-two (48%) patients with dilated cardiomyopathy as the predominant aetiology of HF were responders at 6-month follow-up. Baseline clinical and echocardiographic characteristics of responders versus non-responders are summarized in Table 1 . There were no differences in baseline characteristics between responders and non-responders, except for HF aetiology and LV EF. QRS duration of responders was also marginally higher, yet with a trend to statistical significance. Table 1 Baseline clinical and echocardiographic characteristics of CRT responders vs. non-responders Variable CRT responders (22) CRT non responders (24) P value Age 64 ± 10 66 ± 7 0.544 Male 13 (48%) 14 (52%) 0.958 NYHA functional class (II/III/IV) 3/16/3 0/21/3 0.166 Ischemic etiology 1 (4%) 12 (50%) 0.001 Non-ischemic etiology 21 (96%) 12 (50%) 0.001 Hypertension 10 (46%) 14 (58%) 0.382 Mean arterial pressure (mmHg) 97 ± 10 91 ± 13 0.113 Heart rate (bpm) 75 ± 11 69 ± 11 0.102 Creatinine (mg/dl) 1.1 ± 0.4 1.1 ± 0.2 0.570 QRS duration (ms) 179 ± 21 168 ± 18 0.060 Medication ACE inhibitors or ARBs or ARNI 22 (100%) 24 (100%) - β-blockers 16 (73%) 19 (79%) 0.609 Diuretics 19 (86%) 20 (83%) 0.775 MRAs 18 (82%) 21 (88%) 0.592 SGLT2 inh 6 (27%) 8 (33%) 0.754 Baseline echocardiography Mitral regurgitation grade III or IV 8 (36%) 8 (33%) 0.829 LV EF (%) 31 ± 7 27 ± 7 0.048 EDV (ml) 215 ± 49 239 ± 56 0.139 ESV (ml) 151 ± 49 175 ± 52 0.109 Eff SV (ml) 55 ± 14 54 ± 14 0.747 GLS (%) -10 ± -2 -8 ± -3 0.107 Peak twist in systole ( 0 ) 1.34±1.20 1.73±1.13 0.203 Peak twist in diastole ( 0 ) 2.38±1.28 1.46±1.07 0.035 TI ( 0 ) -16.34±11.19 0.53±10.59 < 0.001 mean TI ( 0 ) -0.34±0.23 0.004±0.22 < 0.001 ACE: angiotensin converting enzyme, ARBs: angiotensin receptor blockers, ARNi: angiotensin receptor – neprilysin inhibitor, EDV: end diastolic volume, ESV: end systolic volume, GLS: global longitudinal strain, LV: left ventricular, LV EF: LV ejection fraction, MRAs: mineralocorticoid receptor antagonist, SGLT2: sodium-glucose cotransporter 2 inhibitors, TI: twist integral The LV lead was optimally located in almost all responders (basal, medial and lateral position: 0/1/21 patients) vs. non-responders (3/8/13 respectively, p:0.006). The commonest selected interventricular activation mode was the simultaneous activation of the 2 ventricular leads (39% RV/LV; 7 responders vs. 11 non-responders), followed equally by RVLV (24%; 3 responders vs. 8 non-responders) and LVRV modes (24%; 7 responders vs. 4 non-responders). Interestingly in 6 patients (13%) the optimal eff SV was achieved by LV lead activation only (5 responders vs. 1 non-responder). On the contrary, single RV lead activation was never selected since the provided eff SV was always lower than other pacing options. Among all the demographic, clinical and echocardiographic parameters assessed, the strongest associations with the final improvement in LVESV were noticed in the mean TI on admission (yet with negative sign), the mean TI at one week, the max systolic twist at one week and ischemic etiology HF (negative sign), followed by pre-ejection (negative sign) and ejection time of the RV contraction as shown in Table 2 . Interestingly, the difference (Δ) of several other variables between the first 2 visits of the patients was also associated with LVESV improvement. In particular, Δ mean TI, Δ systolic twist, Δ eff SV Δ GLS and Δ QRS showed significant relationships. Table 2 Relationship and independent predictors among improved LVESV response and demographic, clinical and echocardiographic parameters. Variable r p value Clinical BSA -0.270 0.069 Ischemic etiology HF -0.514 < 0.001 QRS duration 0.261 0.079 QRS difference 0.464 0.0011 HR on admission -0.270 0.070 HR at one week -0.306 0.039 Activation mode 0.343 0.020 Position of electrode implantation 0.306 0.038 Echocardiographic LV Filling time 0.247 0.098 RV preejection time -0.358 0.015 RV ejection time 0.396 0.006 Peak twist during diastole on admission 0.318 0.019 mean TI -0.639 < 0.001 Peak twist during systole at one week 0.665 < 0.001 mean TI at one week 0.707 < 0.001 Difference (Δ) in eff SV 0.646 < 0.001 Δ GLS -0.324 0.028 Δ peak systolic twist 0.635 < 0.001 Δ max diastolic twist -0.240 0.113 Δ mean TI 0.797 < 0.001 Linear regression analysis Variable β p value Difference (Δ) in eff SV 0.410 < 0.001 Δ mean TI 0.265 0.007 Ischemic etiology of HF -0.242 0.002 Δ peak systolic twist 0.219 0.013 RV preejection time -0.174 0.015 Position of electrode implantation 0.169 0.002 BSA: body surface area, GLS: global longitudinal strain, HF: heart failure, HR: heart rate, LV: left ventricular, RV: right ventricular, TI: twist integral, eff SV: effective stroke volume In the subsequent regression analysis (Table 2 ), all significantly associated variables were included as potential predictors of ensuing improvement in LVESV at 6 months. The strongest predictor of LVESV improvement was the change of eff SV between admission and first appointment at clinic, followed by the change of the mean TI and the difference of systolic max twist. Other independent predictors were the apical position of the LV electrode and the short RV preejection time, a finding representing the preserved inotropic state of the RV. Table 3 and Fig. 2 demonstrate the sequential change of several twist-based variables during the 3 appointments of the study patients. Interestingly, the responders showed an immediate post CRT response of the mean TI from negative to positive values, while the peak twist in systole and diastole were also significantly changed, a response to the mechanical effects of resynchronization therapy. Table 3 Sequential change of twist variables during the study period Echocardiography variable Admission 1st appointment 6 months Non-Responders Peak twist in systole* 1.73±1.13 2.01±1.11 1.84±1.00 Peak twist in diastole 1.46±1.07 1.31±1.10 1.06±0.71 TI * 0.53±10.59 9.36±12.09 10.41±6.85 mean TI* 0.004±0.22 0.20±0.25 0.15±0.22 Responders Peak twist in systole* 1.34±1.20 3.86±1.00 3.95±1.10 Peak twist in diastole 2.38±1.28 1.11±0.93 1.25±0.85 TI * -16.34±11.19 29.96±8.47 33.76±9.44 mean TI* -0.34±0.23 0.67±0.21 0.70±0.20 *p < 0.001. The mean TI showed a better performance than GLS (Fig. 3) for the prediction of CRT response (areas under the curve 86,2%; p < 0.001 and 67,4%; p: NS respectively). A mean TI value of -0.11 0 showed the greatest diagnostic accuracy to predict improvement (sensitivity 86.4% and specificity 83.6%), while GLS was considered weak as a predictor. The best GLS value to predict response to CRT was − 9.15% with a sensitivity of 72.7% and a specificity of 75%. Discussion The present study provides two main conclusions. Firstly, it is recommended a new strategy for CRT optimization via adjusted temporal activation of the ventricular pacemaker electrodes guided by the higher effective LV SV. Secondly, we managed to explain the mechanism of this therapeutic maneuver through the improved rotational mechanics of the failing LV. It was pointed out that beyond AV optimization, different temporal activation of the pacing leads can further impact on the effective LV contraction via improved LV twist. The additive contribution of cardiac imaging to detect which patients with HF benefit from CRT has been investigated in numerous studies still with insufficient conclusions ( 1 , 12 – 15 ). The only robust data implemented in the current guidelines as preimplantation criteria and thus requested by the clinician are clinical status, QRS assessment and LV EF. No other echocardiographic or other imaging data of asynchrony is considered essential before CRT ( 1 ). Assessment of LV mechanical asynchrony may provide an additive contribution in patients undergoing CRT. Several studies encourage the concept that it may predict CRT response or at least support CRT indication. However, it is still uncertain what is the best echocardiographic index of cardiac asynchrony, although recently STE and 3D echocardiography have provided reliable and more predictive data than those used prior to these innovative imaging modalities ( 16 ). LV myocardial torsional mechanics are known to be compromised in HF patients ( 17 , 18 , 19 ), though an increasing interest for its role in assessing improvement to CRT is recently noticed ( 20 ). The reasons of this investigating hesitancy might be the low reproducibility of measurements, the complex helical ventricular architecture and contraction and the different vectors’ software tools that frequently provide contradictory data of identical phenomena. The 2 study groups were not comparable in all their baseline clinical and echocardiographic characteristics. As anticipated, the responders were primarily patients with non-ischemic cardiomyopathy with their QRS complex being borderline wider than non-responders. The concomitant medical therapy was optimal in the two groups except for a low percentage of SGLT2 inhibitors usage since the enrolment of the patients completed before the advent of the updated HF guidelines that propagated this therapy ( 21 ). Regarding the echocardiographic data, the LV EF of the responders was higher while their GLS showed a relevant trend for improved LV contractility on admission. STE revealed higher values of peak twist in diastole in responders, a finding that reveals the suspended LV contraction after aortic valve closure and thus the beneficial contribution of CRT therapy to restore this deleterious contractile abnormality. Interestingly, the novel echocardiography variable of TI was remarkably different between the 2 groups, comprising in one number both the contractile systolic and diastolic ventricular twist elements of the cardiac cycle. Linear regression analysis revealed which of the numerous investigated variables can independently predict a beneficial CRT response. The higher contribution was shown by the improvement of both the eff SV and mean TI. Moreover, variables such as non-ischemic CMP as a HF etiology, the improvement of peak systolic twist between admission and the first appointment after system optimization, the RV pre-ejection time and the proper implantation of LV electrode were independently remained valuable predictors of improvement. The short RV prejection time as criterion of good inotropic state supports the clinical assumption that the functional integrity of the RV should not be overlooked before implantation of biventricular pacing systems. In this study we enrolled patients with QRS duration ≥150 ms, since are more likely to respond favourably (class I, level A) than the subgroup of 130 − 129 ms (class IIa, level B) which demonstrates not so strong evidence of CRT effectiveness. Importantly, though QRS complex duration improvement showed an association with the response, this variable was excluded in the ensuing multivariable analysis. This result might be attributed to the strong predictive value of the novel echocardiography index (mean TI) that weakened the contribution of other parameters in the prediction model. Several parameters of LV twist were evaluated with the intention to interpret the beneficial mechanism of CRT. Trying to portray the responder patient on admission, he is the one having lower peak systolic than diastolic twist, while the mean TI shows significantly lower and negative values in general, a finding that depicts the harmful twisting of the LV after the aortic valve closure (Fig. 1 ). These patients modified their LV rotational mechanics post CRT with improved twist in systole and less harmful (positive) twist in diastole as depicted in the sequential follow up of TI values assessment (Fig. 2). The finding of higher admission GLS values in responders can be explained by the fact that several myocardial segments may reach their peak strain in asynchronous cardiac contraction in the diastolic period of the cardiac cycle something that is not usually well apprehended in post study automatic analysis report. Limitations This study was designed to investigate whether the assessment of rotational mechanics via a new proposed index can be utilised as potential predictor for patients treated with CRT. Because of the open, non-randomised type of the study, which was only hypothesis-generating, more randomized clinical prospective trials are encouraged to establish LV twist as a robust step of the screening process for the HF patients for more effective CRT. We also demonstrated a good intraobserver variability for effective SV assessment (a crucial step in the study workflow), however this result represents just the post examination calculations in the workstation and not involving the previous step of the LVOT pulse Doppler measurement. It is well known the variability of measurements with just a minor movement of the cursor during pulse wave Doppler interrogation especially in long lasting and demanding echocardiographic studies. Conclusions The results of the present study showed the importance of biventricular on the top of AV optimization for post-CRT patients. It was also pointed out that twist calculation is of great importance as an additive tool for the better initial assessment and selection of candidates for effective CRT. The findings underscored that the success of biventricular pacing is undoubtedly based on the LV twist improvement mainly via the attenuation of the deleterious contribution of LV twist in diastole. Abbreviations CRT: cardiac resynchronization therapy HF: heart failure LVEF: left ventricular ejection fraction. SV: stroke volume STE: speckle tracking echocardiography BSA: body surface area 6 min WT: six minute walk test LV: left ventricular eff SV: effective stroke volume AV: atrioventricular RV: right ventricular LVOT: left ventricular outflow tract VTI: velocity time integral ESV: end-systolic volume TI: twist integral SD: standard deviation CV: coefficient of variability GLS: global longitudinal strain Declarations No conflicts of interest by anyone of the authors The study was performed at Nikea Hospital with no funding sources. The work presented has been carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans and informed and written consent was taken from all participants of the study. The raw data used and/or analysed of the current study are available from the corresponding author on reasonable request. 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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-4318618","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":299309232,"identity":"ca50e965-99ff-4167-9da5-db3000d59e15","order_by":0,"name":"Alexandros Stefanidis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYDACdhBRIWHHz8DARqQWZgbGBoYzNsmSDSRpYWxLY9xwgFgt5szMzx98YDvMbHwj+dmDDxUM8vxiB/BrsWxmM2ycwXOYz+xGmrnhjDMMhjNnJ+DXYnCYwbCZR+Iws9mNBDNp3jaGBIPbBLWwf2zmMTjMuHlG+jditfAAbUkAel8ih0hbLJt5CmfOOGCTLHHmTZnkjDMShP1izt6+4cPHf8CobE/fJvGhwkaeX5qQw+AsAbBKCfzKUbXwHyCsehSMglEwCkYmAAAYs0E34cue4gAAAABJRU5ErkJggg==","orcid":"","institution":"General Hospital of Nikea ‘Agios Panteleimon’","correspondingAuthor":true,"prefix":"","firstName":"Alexandros","middleName":"","lastName":"Stefanidis","suffix":""},{"id":299309234,"identity":"65f3da54-68f6-45a3-974e-e95251bf64e6","order_by":1,"name":"Paraskevi Korlou","email":"","orcid":"","institution":"General Hospital of Nikea ‘Agios Panteleimon’","correspondingAuthor":false,"prefix":"","firstName":"Paraskevi","middleName":"","lastName":"Korlou","suffix":""},{"id":299309236,"identity":"e23b5935-9680-42fd-88c4-3b1c98616a52","order_by":2,"name":"Panagiotis Margos","email":"","orcid":"","institution":"General Hospital of Nikea ‘Agios Panteleimon’","correspondingAuthor":false,"prefix":"","firstName":"Panagiotis","middleName":"","lastName":"Margos","suffix":""},{"id":299309238,"identity":"87f083fc-f2af-4d10-afd7-4eff6486f8ce","order_by":3,"name":"Ignatios Ikonomidis","email":"","orcid":"","institution":"Attikon Hospital, of the National and Kapodistrian University of Athens","correspondingAuthor":false,"prefix":"","firstName":"Ignatios","middleName":"","lastName":"Ikonomidis","suffix":""},{"id":299309240,"identity":"5f00408e-2e30-4eb8-95bb-41e42aa646b3","order_by":4,"name":"Ioannis Paraskevaidis","email":"","orcid":"","institution":"Alexandra Regional Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ioannis","middleName":"","lastName":"Paraskevaidis","suffix":""},{"id":299309241,"identity":"fc8c3713-1c5f-48eb-bb22-c3bec24e4a02","order_by":5,"name":"Konstantinos Gatzoulis","email":"","orcid":"","institution":"Hippokration Hospital, of the National and Kapodistrian University of Athens","correspondingAuthor":false,"prefix":"","firstName":"Konstantinos","middleName":"","lastName":"Gatzoulis","suffix":""},{"id":299309242,"identity":"5730c018-e47b-477a-83d4-3c25432e0850","order_by":6,"name":"Evmorfia Aivalioti","email":"","orcid":"","institution":"General Hospital of Nikea ‘Agios Panteleimon’","correspondingAuthor":false,"prefix":"","firstName":"Evmorfia","middleName":"","lastName":"Aivalioti","suffix":""},{"id":299309243,"identity":"fd9f204b-3fa3-460d-a5c1-1cd29ef69987","order_by":7,"name":"Konstantinos Kostopoulos","email":"","orcid":"","institution":"General Hospital of Nikea ‘Agios Panteleimon’","correspondingAuthor":false,"prefix":"","firstName":"Konstantinos","middleName":"","lastName":"Kostopoulos","suffix":""}],"badges":[],"createdAt":"2024-04-24 13:36:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4318618/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4318618/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56140188,"identity":"5bfe2aa8-7291-496b-a965-05b58788072b","added_by":"auto","created_at":"2024-05-09 04:09:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38859,"visible":true,"origin":"","legend":"\u003cp\u003eTwist curves between responders and non-responders and methodology of the Twist Integral calculation from the algebraic summation of the green (systolic) and red (diastolic) areas integrals. The negative twist values (grey color) are represented in the formula with zero number and thus excluded from the final calculation. AVC: aortic valve closure\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4318618/v1/6d6e6775343fee01451ccc33.png"},{"id":56140244,"identity":"89a5f3ba-d617-4e22-b63b-fbb208f9e221","added_by":"auto","created_at":"2024-05-09 04:09:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":265656,"visible":true,"origin":"","legend":"\u003cp\u003eSequential change of mean TI and GLS during the study period\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4318618/v1/9b7373c39f2fc61cf75688ac.png"},{"id":56140180,"identity":"94e2a317-1da8-4570-b940-9301fae76a7b","added_by":"auto","created_at":"2024-05-09 04:08:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":233063,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves for mean TI and GLS\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4318618/v1/f5f65ba22ef40dc495f03b8f.png"},{"id":56140815,"identity":"c0fa565c-1054-4d2f-8423-d429d39c0a12","added_by":"auto","created_at":"2024-05-09 04:39:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1146126,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4318618/v1/c00b8fd6-1909-4711-a250-13b96b4bbb06.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The implementation of speckle tracking echocardiography for cardiac resynchronization therapy optimization. A rotational myocardial mechanics interpretation","fulltext":[{"header":"Background","content":"\u003cp\u003eCardiac resynchronization therapy (CRT) is currently a well-recognised treatment for heart failure (HF) patients with impaired left ventricular ejection fraction (LVEF) and wide QRS complex who remain symptomatic despite optimal medical treatment (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Since a substantial percentage of patients do not respond to CRT favourably, numerous studies have addressed different techniques to improve response rate (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). These techniques imply individual optimization of atrioventricular and interventricular delay settings, based on left ventricular (LV) filling patterns, stroke volume (SV), and asynchrony. However, despite promising single centre studies, more robust conclusions from larger trials are still needed.\u003c/p\u003e \u003cp\u003e Speckle tracking echocardiography (STE) has emerged as a promising imaging tool for the evaluation of regional and global cardiac function in different clinical settings. This additive information provides new perception into cardiac physiology and thus improved patient management (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). STE has been validated as an accurate tool for the investigation of LV rotational mechanics which is a principal mechanism contributing to myocardial performance and thus SV. Considering the central role of myocardial twist in global heart function, we assumed that impaired LV twist is strongly related to asynchrony and can be restored by CRT explaining the improvement of global LV performance (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe aim of the present study is an attempt to further explain via rotational mechanics the contribution of CRT optimization on LV myocardial performance, by testing the distinct influence of different modes of temporal activation of ventricular electrodes (different VV delay pacing options) with parallel assessment of LV twist.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis was a non-randomized, prospective, observational study performed in one centre. Patients indicated for a CRT implantation were consecutively included in the study. Inclusion criteria were sinus rhythm, presence of typical LBBB with QRS duration \u0026ge; 150 ms and symptomatic HF with New York Heart Association (NYHA) functional class II to IV and LVEF \u0026le;35% after optimal medical therapy. Patients were excluded if they had: 1) non-LBBB QRS morphology, 2) persistent atrial fibrillation, 3) PQ duration\u0026thinsp;\u0026gt;\u0026thinsp;200 ms or 4) inadequate acoustic window for the ensuing echocardiography. This study was approved by the Institutional scientific board of Nikea hospital in accordance with the code of ethics of the world medical association (Declaration of Helsinki) for experiments involving humans. All patients provided informed and written consent.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData collection, device programming and follow up.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBaseline characteristics including age, gender, body surface area (BSA), aetiology of HF, ECG, and medication were collected among all the enrolled patients.\u003c/p\u003e \u003cp\u003eAll enrolled patients were assessed on admission by 2D-STE, and 6 minute walk test (6 min WT) and followed in the outpatient device clinic by 2D-STE (at one week and 6-month post-implantation) and new 6 min WT (at 6 months post-implantation) as the outcome by which to compare changes in myocardial performance and endurance activity. On their first appointment (at 1 week) all biventricular systems were optimized by changing the temporal activation of the ventricular electrodes aiming to reach the highest LV effective stroke volume (eff SV) across all activation options. On their first post implantation appointment, all patients underwent atrioventricular (AV) delay optimization using echocardiography. Optimal AV interval was decided using mitral inflow pulsed wave Doppler based on dissociation of the E- and A- wave, with prevention of A wave truncation, and maximal AQ duration (from the end of A wave to onset of Q wave) [5]. Following AV optimization, interventricular optimization ensued by changing the temporal activation of ventricular electrodes. Five distinct pacing modes were sequentially attempted: exclusively right ventricular (RV) activation, initially RV followed by LV activation after 30 ms (RV-LV), simultaneous RV/LV activation, initially LV followed by RV activation after 30 ms (LV-RV) and exclusively LV activation (LV). Across all these distinct pacing options an immediate left ventricular outflow tract (LVOT) pulsed wave interrogation was attempted aiming to distinguish the greater tracing something that indicates the higher eff SV. Each of the selected interventricular activation modes was randomly assigned and coded by the electrophysiologist during the programming process with differing sequence. Another observer, unaware and thus unbiased for the ensuing LVOT velocity time integral (VTI) assessment performed all other imaging data analysis.\u003c/p\u003e \u003cp\u003ePatient response to CRT was defined as 15% improvement in LV end-systolic volume (LVESV) between the baseline and the 6-month echocardiographic assessment.\u003c/p\u003e \u003cp\u003ePacemaker LV lead position, determined radiographically, was scored as basally (non-optimally), medially (modestly), or laterally (optimally) implanted.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTwo-dimensional and Doppler Echocardiography\u003c/h2\u003e \u003cp\u003eAll patients underwent standard transthoracic echocardiography using an ultrasound machine (model ACCUSON SC2000, Siemens Healthcare, Mountain View, California) with a 1.25 to 4.5 MHz transducer (model 4V1C) and external workstation facility. A single echo operator performed all echocardiographic recordings for later analysis. Another single observer blinded to patient information and pacing status analysed off-line all imaging data. Two-dimensional, colour and spectral Doppler measurements were performed according to current guidelines (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The LVEF was calculated using the modified Simpson\u0026rsquo;s method (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Eff SV was calculated as the product of the LVOT cross-sectional area and the pulsed-wave Doppler VTI that was manually traced on the modal curve (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). LVOT diameter was measured in parasternal long-axis view at the hinge points of the opened aortic valve cusps (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStrain and Rotational mechanics analysis\u003c/p\u003e \u003cp\u003eAll speckle tracking echocardiography off-line analyses were based on initial meticulous definition of cardiac cycle time intervals. Systole was defined from the QRS onset to the instant of aortic valve closure and diastole from this time point until the ensuing QRS onset.\u003c/p\u003e \u003cp\u003eTwo-dimensional longitudinal strain of the LV was derived from the apical four- chamber, two-chamber, and long-axis views using dedicated software installed on an external computer workstation (Siemens Healthineers eSie VVI velocity vector imaging technology, Erlangen, Germany). The echocardiographic images were recorded with temporal resolution of 60 to 70 fps. The endocardial border was manually traced, and the software automatically tracked the image speckle and produced the longitudinal strain curves in six regional segments from each apical view, respectively. A single beat was analysed, and values from three cardiac cycles were averaged.\u003c/p\u003e \u003cp\u003eLV rotational deformation was calculated offline from 2-dimensional loops in the 2 parasternal basal and apical short-axis views, with temporal resolution of 60 to 70 fps. After the endocardial border was initially manually traced, the software was assisted by the user to confirm 6 basal and 4 apical segments. The basal level was recognised by the appearance of mitral leaflets while eliminating the mitral annulus, and the apical level by the presence of LV cavity in the absence of papillary muscles (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The 2-dimensional speckle-tracking software calculates apical and basal LV rotation from the relevant short-axis images frame by frame. Positive values were given to counterclockwise rotation and negative values to clockwise rotation when viewed from the LV apex. LV twist was defined as the absolute apex to base difference of LV rotation at isochronal time points. The following measurements were derived exclusively for subepicardial layers: peak LV systolic and diastolic twist and twist integral (TI) of the full cardiac cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The subepicardial LV twist assessment was preferred to the other myocardial layers on the basis of being more closely related to mechanical effects of CRT (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). For the calculation of LV TI of the full cardiac cycle, sequential isochronal apical and basal rotation measurements (twist\u003csub\u003ei\u003c/sub\u003e in degrees) were exported to a worksheet Excel file (Microsoft Corporation, Redmond, WA) and the final algebraic summation (Σtwist\u003csub\u003ei\u003c/sub\u003e= twist\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;twist\u003csub\u003e2\u003c/sub\u003e+...+twist\u003csub\u003en\u003c/sub\u003e) was denoted by the formula: TΙ\u0026thinsp;=\u0026thinsp;systolic ΤΙ \u0026ndash; diastolic ΤΙ (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The TI was further adjusted for the different duration of cardiac cycles by dividing it with the total number of discrete isochronal twist measurements (n), eliminating the impact of heart rate (Σ twist\u003csub\u003ei\u003c/sub\u003e/n: mean TI). Only positive twist values were included in the formula for the assessment of TI. The negative twist values during systolic or diastolic time periods were represented in the formula with a zero number since their contribution to an efficient myocardial contraction or relaxation is negligible.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and paired Student\u0026rsquo;s t-test was used to compare the difference between baseline and follow-up in each group. Categorical variables were presented as number (percentages) by using the Pearson\u0026rsquo;s χ\u003csup\u003e2\u003c/sup\u003e test or Fisher\u0026rsquo;s exact test. Only patients with available data at both enrolment, first week and 6-month appointments were included in the final analysis, and no adjustment was made for missing data. All associations among clinical data and echocardiographic were calculated using Pearson\u0026rsquo;s or Spearman\u0026rsquo;s correlation coefficient. Backward stepwise linear regression analysis was performed including all significantly related clinical and echocardiographic parameters to recognise predictors of resynchronization response in terms of at least 15% LVESV reduction. Multicollinearity in the regression analysis was examined by computation of in-model tolerance. Collinearity was considered acceptable and regression model stable for tolerance\u0026thinsp;\u0026gt;\u0026thinsp;0.70. Repeated measures ANOVA method was used to assess group means between responders and non-responders considering dependencies between observations within subjects in the analysis. ROC curves were generated to seek for the optimal cut-off value to predict the CRT response.\u003c/p\u003e \u003cp\u003eThe intraobserver variability for repeated effective stroke volume measurements has been expressed as coefficient of variability (CV) and performed in 25 participants selected at random. The CV was calculated as SD of the difference divided by the mean of the measurement under consideration. The CV of the eff SV was 8%. All analyses were performed by SPSS version 25 (SPSS, Inc., Chicago, IL, USA) and a two-sided p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the initially enrolled 50 patients undergoing CRT, 4 were excluded from the final analysis. One was excluded due to device infection, 1 due to CRT discontinuation and 2 since were lost to follow up. Ultimately, a total of 46 consecutive patients (27 men) were included and their follow up was carried out at 6 months. Three (7%) were in NYHA functional class II, 37 (80%) in NYHA III and 6 (13%) in NYHA IV respectively. All patients were on stable, optimal HF medical therapy according to current guidelines. In 33 patients HF had non-ischemic aetiology and the remainder (13 patients) had a history of coronary artery disease. The mean LV EF was 29.2 \u0026plusmn; 7.1%, and the mean QRS duration was 173 \u0026plusmn; 20 msec. Twenty-two (48%) patients with dilated cardiomyopathy as the predominant aetiology of HF were responders at 6-month follow-up. Baseline clinical and echocardiographic characteristics of responders versus non-responders are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were no differences in baseline characteristics between responders and non-responders, except for HF aetiology and LV EF. QRS duration of responders was also marginally higher, yet with a trend to statistical significance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline clinical and echocardiographic characteristics of CRT responders vs. non-responders\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCRT responders\u003c/p\u003e \u003cp\u003e(22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCRT non responders (24)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 \u0026plusmn; 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 \u0026plusmn; 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA functional class (II/III/IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3/16/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/21/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic etiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-ischemic etiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean arterial pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 \u0026plusmn; 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 \u0026plusmn; 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 \u0026plusmn; 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 \u0026plusmn; 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1 \u0026plusmn; 0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 \u0026plusmn; 0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.570\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQRS duration (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179 \u0026plusmn; 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168 \u0026plusmn; 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE inhibitors or ARBs or ARNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiuretics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGLT2 inh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBaseline echocardiography\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMitral regurgitation grade III or IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV EF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 \u0026plusmn; 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 \u0026plusmn; 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEDV (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215 \u0026plusmn; 49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239 \u0026plusmn; 56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESV (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 \u0026plusmn; 49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 \u0026plusmn; 52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEff SV (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 \u0026plusmn; 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 \u0026plusmn; 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGLS (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-10 \u0026plusmn; -2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8 \u0026plusmn; -3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeak twist in systole (\u003csup\u003e0\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34\u0026plusmn;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u0026plusmn;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeak twist in diastole (\u003csup\u003e0\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.38\u0026plusmn;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.46\u0026plusmn;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTI (\u003csup\u003e0\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-16.34\u0026plusmn;11.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53\u0026plusmn;10.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emean TI (\u003csup\u003e0\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.34\u0026plusmn;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u0026plusmn;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eACE: angiotensin converting enzyme, ARBs: angiotensin receptor blockers, ARNi: angiotensin receptor \u0026ndash; neprilysin inhibitor, EDV: end diastolic volume, ESV: end systolic volume, GLS: global longitudinal strain, LV: left ventricular, LV EF: LV ejection fraction, MRAs: mineralocorticoid receptor antagonist, SGLT2: sodium-glucose cotransporter 2 inhibitors, TI: twist integral\u003c/p\u003e \u003cp\u003eThe LV lead was optimally located in almost all responders (basal, medial and lateral position: 0/1/21 patients) vs. non-responders (3/8/13 respectively, p:0.006). The commonest selected interventricular activation mode was the simultaneous activation of the 2 ventricular leads (39% RV/LV; 7 responders vs. 11 non-responders), followed equally by RVLV (24%; 3 responders vs. 8 non-responders) and LVRV modes (24%; 7 responders vs. 4 non-responders). Interestingly in 6 patients (13%) the optimal eff SV was achieved by LV lead activation only (5 responders vs. 1 non-responder). On the contrary, single RV lead activation was never selected since the provided eff SV was always lower than other pacing options.\u003c/p\u003e \u003cp\u003eAmong all the demographic, clinical and echocardiographic parameters assessed, the strongest associations with the final improvement in LVESV were noticed in the mean TI on admission (yet with negative sign), the mean TI at one week, the max systolic twist at one week and ischemic etiology HF (negative sign), followed by pre-ejection (negative sign) and ejection time of the RV contraction as shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Interestingly, the difference (Δ) of several other variables between the first 2 visits of the patients was also associated with LVESV improvement. In particular, Δ mean TI, Δ systolic twist, Δ eff SV Δ GLS and Δ QRS showed significant relationships.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship and independent predictors among improved LVESV response and demographic, clinical and echocardiographic parameters.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic etiology HF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQRS duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQRS difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR on admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR at one week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivation mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosition of electrode implantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEchocardiographic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV Filling time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV preejection time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV ejection time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeak twist during diastole on admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emean TI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeak twist during systole at one week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emean TI at one week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifference (Δ) in eff SV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ GLS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ peak systolic twist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ max diastolic twist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ mean TI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLinear regression analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eβ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifference (Δ) in eff SV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ mean TI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic etiology of HF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ peak systolic twist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV preejection time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosition of electrode implantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBSA: body surface area, GLS: global longitudinal strain, HF: heart failure, HR: heart rate, LV: left ventricular, RV: right ventricular, TI: twist integral, eff SV: effective stroke volume\u003c/p\u003e \u003cp\u003eIn the subsequent regression analysis (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), all significantly associated variables were included as potential predictors of ensuing improvement in LVESV at 6 months. The strongest predictor of LVESV improvement was the change of eff SV between admission and first appointment at clinic, followed by the change of the mean TI and the difference of systolic max twist. Other independent predictors were the apical position of the LV electrode and the short RV preejection time, a finding representing the preserved inotropic state of the RV.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;2 demonstrate the sequential change of several twist-based variables during the 3 appointments of the study patients. Interestingly, the responders showed an immediate post CRT response of the mean TI from negative to positive values, while the peak twist in systole and diastole were also significantly changed, a response to the mechanical effects of resynchronization therapy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSequential change of twist variables during the study period\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEchocardiography variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdmission\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1st appointment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 months\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eNon-Responders\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeak twist in systole*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u0026plusmn;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.01\u0026plusmn;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.84\u0026plusmn;1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeak twist in diastole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.46\u0026plusmn;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.31\u0026plusmn;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06\u0026plusmn;0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTI\u0026nbsp;*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53\u0026plusmn;10.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.36\u0026plusmn;12.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.41\u0026plusmn;6.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emean TI*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u0026plusmn;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20\u0026plusmn;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026plusmn;0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eResponders\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeak twist in systole*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34\u0026plusmn;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.86\u0026plusmn;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.95\u0026plusmn;1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeak twist in diastole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.38\u0026plusmn;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11\u0026plusmn;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25\u0026plusmn;0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTI\u0026nbsp;*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-16.34\u0026plusmn;11.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.96\u0026plusmn;8.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.76\u0026plusmn;9.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emean TI*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.34\u0026plusmn;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67\u0026plusmn;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u0026plusmn;0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003cp\u003eThe mean TI showed a better performance than GLS (Fig.\u0026nbsp;3) for the prediction of CRT response (areas under the curve 86,2%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and 67,4%; p: NS respectively). A mean TI value of -0.11\u003csup\u003e0\u003c/sup\u003e showed the greatest diagnostic accuracy to predict improvement (sensitivity 86.4% and specificity 83.6%), while GLS was considered weak as a predictor. The best GLS value to predict response to CRT was \u0026minus;\u0026thinsp;9.15% with a sensitivity of 72.7% and a specificity of 75%.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study provides two main conclusions. Firstly, it is recommended a new strategy for CRT optimization via adjusted temporal activation of the ventricular pacemaker electrodes guided by the higher effective LV SV. Secondly, we managed to explain the mechanism of this therapeutic maneuver through the improved rotational mechanics of the failing LV. It was pointed out that beyond AV optimization, different temporal activation of the pacing leads can further impact on the effective LV contraction via improved LV twist.\u003c/p\u003e \u003cp\u003eThe additive contribution of cardiac imaging to detect which patients with HF benefit from CRT has been investigated in numerous studies still with insufficient conclusions (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The only robust data implemented in the current guidelines as preimplantation criteria and thus requested by the clinician are clinical status, QRS assessment and LV EF. No other echocardiographic or other imaging data of asynchrony is considered essential before CRT (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAssessment of LV mechanical asynchrony may provide an additive contribution in patients undergoing CRT. Several studies encourage the concept that it may predict CRT response or at least support CRT indication. However, it is still uncertain what is the best echocardiographic index of cardiac asynchrony, although recently STE and 3D echocardiography have provided reliable and more predictive data than those used prior to these innovative imaging modalities (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). LV myocardial torsional mechanics are known to be compromised in HF patients (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), though an increasing interest for its role in assessing improvement to CRT is recently noticed (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The reasons of this investigating hesitancy might be the low reproducibility of measurements, the complex helical ventricular architecture and contraction and the different vectors\u0026rsquo; software tools that frequently provide contradictory data of identical phenomena.\u003c/p\u003e \u003cp\u003eThe 2 study groups were not comparable in all their baseline clinical and echocardiographic characteristics. As anticipated, the responders were primarily patients with non-ischemic cardiomyopathy with their QRS complex being borderline wider than non-responders. The concomitant medical therapy was optimal in the two groups except for a low percentage of SGLT2 inhibitors usage since the enrolment of the patients completed before the advent of the updated HF guidelines that propagated this therapy (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Regarding the echocardiographic data, the LV EF of the responders was higher while their GLS showed a relevant trend for improved LV contractility on admission. STE revealed higher values of peak twist in diastole in responders, a finding that reveals the suspended LV contraction after aortic valve closure and thus the beneficial contribution of CRT therapy to restore this deleterious contractile abnormality. Interestingly, the novel echocardiography variable of TI was remarkably different between the 2 groups, comprising in one number both the contractile systolic and diastolic ventricular twist elements of the cardiac cycle.\u003c/p\u003e \u003cp\u003eLinear regression analysis revealed which of the numerous investigated variables can independently predict a beneficial CRT response. The higher contribution was shown by the improvement of both the eff SV and mean TI. Moreover, variables such as non-ischemic CMP as a HF etiology, the improvement of peak systolic twist between admission and the first appointment after system optimization, the RV pre-ejection time and the proper implantation of LV electrode were independently remained valuable predictors of improvement.\u003c/p\u003e \u003cp\u003eThe short RV prejection time as criterion of good inotropic state supports the clinical assumption that the functional integrity of the RV should not be overlooked before implantation of biventricular pacing systems.\u003c/p\u003e \u003cp\u003eIn this study we enrolled patients with QRS duration \u0026ge;150 ms, since are more likely to respond favourably (class I, level A) than the subgroup of 130\u0026thinsp;\u0026minus;\u0026thinsp;129 ms (class IIa, level B) which demonstrates not so strong evidence of CRT effectiveness. Importantly, though QRS complex duration improvement showed an association with the response, this variable was excluded in the ensuing multivariable analysis. This result might be attributed to the strong predictive value of the novel echocardiography index (mean TI) that weakened the contribution of other parameters in the prediction model.\u003c/p\u003e \u003cp\u003eSeveral parameters of LV twist were evaluated with the intention to interpret the beneficial mechanism of CRT. Trying to portray the responder patient on admission, he is the one having lower peak systolic than diastolic twist, while the mean TI shows significantly lower and negative values in general, a finding that depicts the harmful twisting of the LV after the aortic valve closure (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These patients modified their LV rotational mechanics post CRT with improved twist in systole and less harmful (positive) twist in diastole as depicted in the sequential follow up of TI values assessment (Fig.\u0026nbsp;2). The finding of higher admission GLS values in responders can be explained by the fact that several myocardial segments may reach their peak strain in asynchronous cardiac contraction in the diastolic period of the cardiac cycle something that is not usually well apprehended in post study automatic analysis report.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study was designed to investigate whether the assessment of rotational mechanics via a new proposed index can be utilised as potential predictor for patients treated with CRT. Because of the open, non-randomised type of the study, which was only hypothesis-generating, more randomized clinical prospective trials are encouraged to establish LV twist as a robust step of the screening process for the HF patients for more effective CRT. We also demonstrated a good intraobserver variability for effective SV assessment (a crucial step in the study workflow), however this result represents just the post examination calculations in the workstation and not involving the previous step of the LVOT pulse Doppler measurement. It is well known the variability of measurements with just a minor movement of the cursor during pulse wave Doppler interrogation especially in long lasting and demanding echocardiographic studies.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results of the present study showed the importance of biventricular on the top of AV optimization for post-CRT patients. It was also pointed out that twist calculation is of great importance as an additive tool for the better initial assessment and selection of candidates for effective CRT. The findings underscored that the success of biventricular pacing is undoubtedly based on the LV twist improvement mainly via the attenuation of the deleterious contribution of LV twist in diastole.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCRT: cardiac resynchronization therapy\u003c/p\u003e\n\u003cp\u003eHF: heart failure\u003c/p\u003e\n\u003cp\u003eLVEF: left ventricular ejection fraction.\u003c/p\u003e\n\u003cp\u003eSV: stroke volume\u003c/p\u003e\n\u003cp\u003eSTE: speckle tracking echocardiography\u003c/p\u003e\n\u003cp\u003eBSA: body surface area\u003c/p\u003e\n\u003cp\u003e6 min WT: six minute walk test\u003c/p\u003e\n\u003cp\u003eLV: left ventricular\u003c/p\u003e\n\u003cp\u003eeff SV: effective stroke volume\u003c/p\u003e\n\u003cp\u003eAV: atrioventricular\u003c/p\u003e\n\u003cp\u003eRV: right ventricular\u003c/p\u003e\n\u003cp\u003eLVOT:\u0026nbsp;left ventricular outflow tract\u003c/p\u003e\n\u003cp\u003eVTI: velocity time integral\u003c/p\u003e\n\u003cp\u003eESV: end-systolic volume\u003c/p\u003e\n\u003cp\u003eTI: twist integral\u003c/p\u003e\n\u003cp\u003eSD: standard deviation\u003c/p\u003e\n\u003cp\u003eCV: coefficient of variability\u003c/p\u003e\n\u003cp\u003eGLS: global longitudinal strain\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eNo conflicts of interest by anyone of the authors\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed at Nikea Hospital with no funding sources.\u003c/p\u003e\n\u003cp\u003eThe work presented has been carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans and informed and written consent was taken from all participants of the study.\u003c/p\u003e\n\u003cp\u003eThe raw data used and/or analysed of the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests and they consent for publication of the study.\u003c/p\u003e\n\u003cp\u003eAS and PK wrote the main manuscript text. PM, II, IP, KG, EA and KK reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGlikson M, Nielsen JC, Kronborg MB, Michowitz Y, Auricchio A, Barbash IM, Barrab\u0026eacute;s JA, Boriani G, Braunschweig F, Brignole M, Burri H, Coats A, Deharo JC, Delgado V, Diller GP, Israel CW, Keren A, Knops RE, Kotecha D, Leclercq C, Merkely B, Starck C, Thyl\u0026eacute;n I, Tolosana JM; 2021 ESC Guidelines on cardiac pacing and cardiac resynchronization therapy. Eur Heart J 2021;42(35):3427-3520\u003c/li\u003e\n\u003cli\u003eSyed Yaseen Naqvi SY, Jawaid A, Goldenberg \u0026Iota;, Kutyifa V. Heart Fail Rep 2018;15(5):315-321\u003c/li\u003e\n\u003cli\u003eBiswas M, Sudhakar S, Nanda N, Buckberg G, Pradhan M, Roomi AU, Gorissen W, Houle H. Two- and Three-Dimensional Speckle Tracking Echocardiography: Clinical Applications and Future Directions. Echocardiography 2013; 30:88-105\u003c/li\u003e\n\u003cli\u003eLamia B, Tanabe M, Tanaka H, Kim HK, Gorcsan J III, Pinsky M. Left ventricular systolic torsion correlates global cardiac performance during dyssynchrony and cardiac resynchronization therapy. Am J Physiol Heart Circ Physiol 300: H853\u0026ndash;H858, 2011.\u003c/li\u003e\n\u003cli\u003eMullens W, Tang W, Grimm R. Using echocardiography in cardiac resynchronization therapy. Am Heart J 2007; 154:1011-1020.\u003c/li\u003e\n\u003cli\u003eRecommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, Flachskampf FA, Foster E, Goldstein SA, Kuznetsova T, Lancellotti P, Muraru D, Picard MH, Rietzschel ER, Rudski L, Spencer KT, Tsang W, Voigt JU. Eur Heart J \u0026ndash; Cardiovasc Imaging. 2015; 16, 233\u0026ndash;271\u003c/li\u003e\n\u003cli\u003eSchiller N, Shah P, Crawford M, DeMaria A, Devereux R, Feigenbaum H, Gutgesell H, Reichek N, Sahn D, Schnittger I. Recommendations for quantitation of the left ventricle by two-dimensional echocardiography. American Society of Echocardiography Committee on Standards, Subcommittee on Quantitation of Two-Dimensional Echocardiograms. J Am Soc Echocardiogr 1989; 2:358-367.\u003c/li\u003e\n\u003cli\u003eOtto CM, Pearlman AS, Comess KA, Reamer RP, Janko CL, Huntsman LL. Determination of the stenotic aortic valve area in adults using Doppler echocardiography. J Am Coll Cardiol 1986;7:509-17.\u003c/li\u003e\n\u003cli\u003eEstimation of Stroke Volume and Aortic Valve Area in Patients with Aortic Stenosis: A Comparison of Echocardiography versus Cardiovascular Magnetic Resonance. Guzzetti E, Capoulade R, Tastet L, Garcia J, Le Ven F, Arsenault M, B\u0026eacute;dard E, Larose E, Clavel MA, Pibarot P.J Am Soc Echocardiogr. 2020;33(8):953-963\u003c/li\u003e\n\u003cli\u003ePrzewlocka-Kosmala M, Marwick TH, Yang H, Wright L, Negishi K, Kosmala W. Association of reduced apical untwisting with incident heart failure in asymptomatic patients with heart failure risk factors. JACC Cardiovasc Imaging. 2020;13:187-194\u003c/li\u003e\n\u003cli\u003eBertini M, Delgado V, Nucifora G, et al. Effect of cardiac resynchronization therapy on subendo- and subepicardial left ventricular twist mechanics and relation to favorable outcome. Am J Cardiol 2010;106:682\u0026ndash;687.\u003c/li\u003e\n\u003cli\u003eRisum N, Tayal B, Hansen TF, Bruun NE, Jensen MT, Lauridsen TK et al. Identification of typical left bundle branch block contraction by strain echocardiography is additive to electrocardiography in prediction of long-term outcome after cardiac resynchronization therapy. J Am Coll Cardiol 2015; 66:631\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eVidal B, Delgado V, Mont L, Poyatos S, Silva E, Angeles Castel M et al. Decreased likelihood of response to cardiac resynchronization in patients with severe heart failure. Eur J Heart Fail 2010; 12:283\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eSilva E, Sitges M, Doltra A, Mont L, Vidal B, Castel MA et al. Analysis of temporal delay in myocardial deformation throughout the cardiac cycle: utility for selecting . candidates for cardiac resynchronization therapy. Heart Rhythm 2010; 7:1580\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eVoigt JU. Cardiac resynchronization therapy responders can be better identified by specific signatures in myocardial function. Eur Heart J Cardiovasc Imaging 2016; 17:132\u0026ndash;354.\u003c/li\u003e\n\u003cli\u003eMele D, Luisi GA, Malag\u0026ugrave; M, Laterza A, Ferrari R, Bertini M. Echocardiographic evaluation of cardiac dyssynchrony: Does it still matter? Echocardiography. 2018;35 (5): 707-715\u003c/li\u003e\n\u003cli\u003eBuckberg G. The helix and the heart. J Thorac Cardiovasc Surg 2002;124:863-83\u003c/li\u003e\n\u003cli\u003eKanzaki H, Nakatani S, Yamada N, Urayama S, Miyatake K, Kitakaze M. Impaired systolic torsion in dilated cardiomyopathy: Reversal of apical rotation at mid-systole characterized with magnetic resonance tagging method. Basic Res Cardiol 2006; 101: 465 \u0026ndash; 470.\u003c/li\u003e\n\u003cli\u003eLee Y, Mori N, Nakamura D, Yoshimura T, Taniike M, Makino N, et al. New approach for rotational dyssynchrony using three-dimensional speckle tracking echocardiography. Echocardiography 2014; 4: 492 \u0026ndash; 498.\u003c/li\u003e\n\u003cli\u003eSartori C, Degiovanni A, Devecchi F, Devecchi P, Marino P. Acute Modifications of Left Ventricular Torsional Mechanics Induced by Cardiac Resynchronization Therapy Affect Short-Term Reverse Remodeling. Circ J 2019; 83: 386\u0026ndash;394\u003c/li\u003e\n\u003cli\u003eMcDonagh T, Metra M, Adamo M, Gardner R, Baumbach A, B\u0026ouml;hm M, et al. 2023 Focused Update of the 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure Eur Heart J 2023; 44: 3627\u0026ndash;3639\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"echo-research-and-practice","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Echo Research \u0026 Practice](https://echo.biomedcentral.com/)","snPcode":"44156","submissionUrl":"https://submission.nature.com/new-submission/44156/3","title":"Echo Research \u0026 Practice","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"resynchronization therapy, rotational mechanics, speckle tracking echocardiography","lastPublishedDoi":"10.21203/rs.3.rs-4318618/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4318618/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Cardiac resynchronization therapy (CRT) has an additive therapeutic influence on left ventricular function in heart failure patients, but the underlying mechanisms through which it works are not completely explained. Our aim was to further elucidate the role of this intervention via rotational mechanics using 2D speckle tracking echocardiography (2D-STE).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe investigated 46 patients (65 ± 9 years) who received CRT. All enrolled patients were assessed on admission by 2D-STE and 6 minute walk test (6 min WT) and followed in the outpatient device clinic by 2D-STE (at one week and 6-month post-implantation) and 6 min WT (at 6 months post-implantation). On their first appointment all biventricular systems were optimized by atrioventricular delay optimization and by changing the temporal activation of ventricular electrodes aiming to reach the highest left ventricular effective stroke volume across all activation options. A new 2D-STE based index (twist integral) targeting to assess the rotational mechanics of the whole cardiac cycle was also measured to further explain the CRT response.\u003c/p\u003e\n\u003cp\u003eTwenty-two (48%) patients with dilated cardiomyopathy as the predominant aetiology of heart failure were responders at 6-month follow-up. The commonest selected mode that was related with the greatest left ventricular performance response was the simultaneous activation of the 2 ventricular leads (39%). The strongest predictor of CRT response was the improvement of effective stroke volume between admission and first appointment at clinic, followed by the improvement of twist integral, the non-existence of coronary artery disease, and the improvement of peak systolic twist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eAdditional CRT optimization via changing the temporal activation of ventricular electrodes is beneficial for left ventricular performance in heart failure patients. Rotational mechanics essentially explain the beneficial CRT contribution to these patients.\u003c/p\u003e","manuscriptTitle":"The implementation of speckle tracking echocardiography for cardiac resynchronization therapy optimization. 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