Wouter M. van Everdingen

Comparison of septal strain patterns in dyssynchronous heart failure between speckle tracking echocardiography vendor systems

AIM To analyze inter-vendor differences of speckle tracking echocardiography (STE) in imaging cardiac deformation in patients with dyssynchronous heart failure. METHODS AND RESULTS Eleven patients (all with LBBB, median age 60.7 years, 9 males) with implanted cardiac resynchronization therapy devices were prospectively included. Ultrasound systems of two vendors (i.e. General Electric and Philips) were used to record images in the apical four chamber view. Regional longitudinal strain patterns were analyzed with vendor specific software in the basal, mid and apical septal segments. Systolic strain (SS), time to peak strain (TTP) and septal rebound stretch (SRS) were determined during four pacing settings, resulting in 44 unique strain patterns per segment (total 132 patterns). Cross correlation was used to analyze the comparability of the shape of 132 normalized strain patterns. Correlation of strain patterns of the two systems was high (R(2) median: 0.68, interquartile range: 0.53-0.82). Accordingly, strain patterns of intrinsic rhythm were recognized equally using both systems, when divided into three types. GE based SS (18.9 ± 4.7%) was significantly higher than SS determined by the Philips system (13.4 ± 4.3%). TTP was slightly but non-significantly lower in GE (384 ± 77 ms) compared to Philips (404 ± 83 ms) derived strain signals. Correlation of SRS between the systems was poor, due to minor differences in the strain signal and timing of aortic valve closure. CONCLUSIONS The two systems provide similar shape of strain patterns. However, important differences are found in the amplitude, timing of systole and SRS. Until STE is standardized, clinical decision making should be restricted to pattern analysis.

Volumetric response beyond six months of cardiac resynchronization therapy and clinical outcome

Aims Response to cardiac resynchronization therapy (CRT) is often assessed six months after implantation. Our objective was to assess the number of patients changing from responder to non-responder between six and 14 months, so-called late non-responders, and compare them to patients who were responder both at six and 14 months, so-called stable responders. Furthermore, we assessed predictive values of six and 14-month response concerning clinical outcome. Methods 105 patients eligible for CRT were enrolled. Clinical, laboratory, ECG, and echocardiographic parameters and patient-reported health status (Kansas City Cardiomyopathy Questionnaire [KCCQ]) were assessed before, and six and 14 months after implantation. Response was defined as ≥15% LVESV decrease as compared to baseline. Major adverse cardiac events (MACE) were registered until 24 months after implantation. Predictive values of six and 14-month response for MACE were examined. Results In total, 75 (71%) patients were six-month responders of which 12 (16%) patients became late non-responder. At baseline, late non-responders more often had ischemic cardiomyopathy and atrial fibrillation, higher BNP and less dyssynchrony compared to stable responders. At six months, late non-responders showed significantly less LVESV decrease, and higher creatinine levels. Mean KCCQ scores of late non-responders were lower than those of stable responders at every time point, with the difference being significant at 14 months. The 14 months response was a better predictor of MACE than six months response. Conclusions The assessment of treatment outcomes after six months of CRT could be premature and response rates beyond might better correlate to long-term clinical outcome.

Echocardiographic Prediction of Cardiac Resynchronization Therapy Response Requires Analysis of Both Mechanical Dyssynchrony and Right Ventricular Function: A Combined Analysis of Patient Data and Computer Simulations

Background: Pronounced echocardiographically measured mechanical dyssynchrony is a positive predictor of response to cardiac resynchronization therapy (CRT), whereas right ventricular (RV) dysfunction is a negative predictor. The aim of this study was to investigate how RV dysfunction influences the association between mechanical dyssynchrony and left ventricular (LV) volumetric remodeling following CRT. Methods: One hundred twenty‐two CRT candidates (mean LV ejection fraction, 19 ± 6%; mean QRS width, 168 ± 21 msec) were prospectively enrolled and underwent echocardiography before and 6 months after CRT. Volumetric remodeling was defined as percentage reduction in LV end‐systolic volume. RV dysfunction was defined as RV fractional area change < 35%. Mechanical dyssynchrony was assessed as time to peak strain between the septum and LV lateral wall, interventricular mechanical delay, and septal systolic rebound stretch. Simulations of heart failure with an LV conduction delay in the CircAdapt computer model were used to investigate how LV and RV myocardial contractility influence LV dyssynchrony and acute CRT response. Results: In the entire patient cohort, higher baseline septal systolic rebound stretch, time to peak strain between the septum and LV lateral wall, and interventricular mechanical delay were all associated with LV volumetric remodeling in univariate analysis (R = 0.599, R = 0.421, and R = 0.410, respectively, P < .01 for all). The association between septal systolic rebound stretch and LV volumetric remodeling was even stronger in patients without RV dysfunction (R = 0.648, P < .01). However, none of the mechanical dyssynchrony parameters were associated with LV remodeling in the RV dysfunction subgroup. The computer simulations showed that low RV contractility reduced CRT response but hardly affected mechanical dyssynchrony. In contrast, LV contractility changes had congruent effects on mechanical dyssynchrony and CRT response. Conclusions: Mechanical dyssynchrony parameters do not reflect the negative impact of reduced RV contractility on CRT response. Echocardiographic prediction of CRT response should therefore include parameters of mechanical dyssynchrony and RV function. HighlightsThe authors investigated the associations among RV function, dyssynchrony, and CRT response.In patients with RV dysfunction, dyssynchrony was not associated with CRT response.In computer simulations, dyssynchrony was not affected by RV myocardial dysfunction.In the simulations, RV myocardial dysfunction limited CRT response.Measuring RV function can improve prediction of response by mechanical dyssynchrony.

Comparison of strain imaging techniques in CRT candidates: CMR tagging, CMR feature tracking and speckle tracking echocardiography

Parameters using myocardial strain analysis may predict response to cardiac resynchronization therapy (CRT). As the agreement between currently available strain imaging modalities is unknown, three different modalities were compared. Twenty-seven CRT-candidates, prospectively included in the MARC study, underwent cardiac magnetic resonance (CMR) imaging and echocardiographic examination. Left ventricular (LV) circumferential strain was analysed with CMR tagging (CMR-TAG), CMR feature tracking (CMR-FT), and speckle tracking echocardiography (STE). Basic strain values and parameters of dyssynchrony and discoordination obtained with CMR-FT and STE were compared to CMR-TAG. Agreement of CMR-FT and CMR-TAG was overall fair, while agreement between STE and CMR-TAG was often poor. For both comparisons, agreement on discoordination parameters was highest, followed by dyssynchrony and basic strain parameters. For discoordination parameters, agreement on systolic stretch index was highest, with fair intra-class correlation coefficients (ICC) (CMR-FT: 0.58, STE: 0.55). ICC of septal systolic rebound stretch (SRSsept) was poor (CMR-FT: 0.41, STE: 0.30). Internal stretch factor of septal and lateral wall (ISFsep–lat) showed fair ICC values (CMR-FT: 0.53, STE: 0.46), while the ICC of the total LV (ISFLV) was fair for CMR-FT (0.55) and poor for STE (ICC: 0.32). The CURE index had a fair ICC for both comparisons (CMR-FT: 0.49, STE 0.41). Although comparison of STE to CMR-TAG was limited by methodological differences, agreement between CMR-FT and CMR-TAG was overall higher compared to STE and CMR-TAG. CMR-FT is a potential clinical alternative for CMR-TAG and STE, especially in the detection of discoordination in CRT-candidates.

Comment on the article by Trolese T et al

The recent introduction of quadripolar leads for cardiac resynchronization therapy raises the question which pacing vector is most beneficial to response and which parameter gives insight into the optimal vector. The study conducted by Trolese et al. is therefore of important value and unique in its kind.1 The found correlation between maximal difference of the QRS-width (ΔQRS) and acute haemodynamic response (AHR) (ΔLV d P /d t max) is an important finding to aid vector selection. However, their results give rise to questions. Figure 1A of Trolese et al. shows an equal QRS morphology comparing M3M2 and M3P4 indicating cathodal stimulation from M3 and no effect of the anodal electrode. However, comparing D1M2 …

Atrioventricular optimization in cardiac resynchronization therapy with quadripolar leads: should we optimize every pacing configuration including multi-point pacing?

Aims This study aims to define an atrioventricular (AV) delay optimization method for cardiac resynchronization therapy (CRT) with a quadripolar left ventricular (LV) lead based on intrinsic conduction intervals. Methods and results Heart failure patients with a left bundle branch block underwent CRT implantation with a quadripolar LV lead. Invasive LV pressure-volume loops were recorded during four biventricular and three multi-point pacing (MPP) settings, using four patient-specific paced AV delays. Haemodynamic response was defined as change in stroke work (Δ%SW) compared to intrinsic rhythm and was related to the following conduction intervals: right atrial pacing to right ventricular sensing interval (RAp-RVs), Q to LV sensing interval normalized to QRS duration (QLV/QRSd), PR-interval, and P-wave duration. In 44 patients, the largest Δ%SW (104 ± 76%) occurred at a paced AV delay of 128 ± 32 ms, at 47 ± 9% of RAp-RVs. Optimal AV delay of biventricular pacing (126 ± 26 ms) did not differ from MPP (126 ± 21 ms, P = 0.29). Intra-class correlation coefficient between optimal AV delays of different pacing configurations was 0.64 (0.45-0.78, P < 0.001). Although not statistically significant, Δ%SW at 50% of RAp-RVs (98 ± 74%) was closer to the maximal achievable Δ%SW increase than a fixed interval of 120 ms (96 ± 73%, P = 0.60). RAp-RVs, QLV/QRSd, PR interval, and P-wave duration were associated with the optimal AV delay in univariate analysis, but only RAp-RVs remained significantly associated in multivariate analysis (R = 0.69). Conclusion The AV delay that provides highest haemodynamic response is similar for various LV pacing configurations and for MPP. An AV delay ∼50% of RAp-RVs creates an acute haemodynamic response close to the maximal patient-specific response.

Strain imaging to predict response to cardiac resynchronization therapy: a systematic comparison of strain parameters using multiple imaging techniques: Strain imaging techniques in cardiac resynchronization therapy

Various strain parameters and multiple imaging techniques are presently available including cardiovascular magnetic resonance (CMR) tagging (CMR‐TAG), CMR feature tracking (CMR‐FT), and speckle tracking echocardiography (STE). This study aims to compare predictive performance of different strain parameters and evaluate results per imaging technique to predict cardiac resynchronization therapy (CRT) response.

Can We Use the Intrinsic Left Ventricular Delay (QLV) to Optimize the Pacing Configuration for Cardiac Resynchronization Therapy With a Quadripolar Left Ventricular Lead

Background: Previous studies indicated the importance of the intrinsic left ventricular (LV) electric delay (QLV) for optimal benefit to cardiac resynchronization therapy. We investigated the use of QLV for achieving optimal acute hemodynamic response to cardiac resynchronization therapy with a quadripolar LV lead. Methods and Results: Forty-eight heart failure patients with a left bundle branch block were prospectively enrolled (31 men; age, 66±10 years; LV ejection fraction, 28±8%; QRS duration, 176±14 ms). Immediately after cardiac resynchronization therapy implantation, invasive LV pressure–volume loops were recorded during biventricular pacing with each separate electrode at 4 atrioventricular delays. Acute cardiac resynchronization therapy response, measured as change in stroke work (&Dgr;%SW) compared with intrinsic conduction, was related to intrinsic interval between Q on the ECG and LV sensing delay (QLV), normalized for QRS duration (QLV/QRSd), and electrode position. QLV/QRSd was 84±9% and variation between the 4 electrodes 9±5%. &Dgr;%SW was 89±64% and varied by 39±36% between the electrodes. In univariate analysis, an anterolateral or lateral electrode position and a high QLV/QRSd had a significant association with a large &Dgr;%SW (all P <0.01). In a combined model, only QLV/QRSd remained significantly associated with &Dgr;%SW (P<0.05). However, a direct relation between QLV/QRSd and &Dgr;%SW was only seen in 24 patients, whereas 24 patients showed an inverse relation. Conclusions: The large variation in acute hemodynamic response indicates that the choice of the stimulated electrode on a quadripolar lead is important. Although QLV/QRSd was associated with acute hemodynamic response at group level, it cannot be used to select the optimal electrode in the individual patient.

Combining computer modelling and cardiac imaging to understand right ventricular pump function

Right ventricular (RV) dysfunction is a strong predictor of outcome in heart failure and is a key determinant of exercise capacity. Despite these crucial findings, the RV remains understudied in the clinical, experimental, and computer modelling literature. This review outlines how recent advances in using computer modelling and cardiac imaging synergistically help to understand RV function in health and disease. We begin by highlighting the complexity of interactions that make modelling the RV both challenging and necessary, and then summarize the multiscale modelling approaches used to date to simulate RV pump function in the context of these interactions. We go on to demonstrate how these modelling approaches in combination with cardiac imaging have improved understanding of RV pump function in pulmonary arterial hypertension, arrhythmogenic right ventricular cardiomyopathy, dyssynchronous heart failure and cardiac resynchronization therapy, hypoplastic left heart syndrome, and repaired tetralogy of Fallot. We conclude with a perspective on key issues to be addressed by computational models of the RV in the near future.