A U-shaped type II contraction pattern in patients with strict left bundle branch block predicts super-response to cardiac resynchronization therapy

Evaluating the predictive efficacy of real-time 3D echocardiography in cardiac resynchronization therapy

BACKGROUND

The aim of this study is to assess the predictive efficacy of real-time three-dimensional echocardiography (RT-3DE) and QRS wave duration in determining the response to cardiac resynchronization therapy (CRT) and assessing left ventricular systolic function pre- and post-CRT device implantation.

METHOD

A total of 51 patients with heart failure undergoing CRT at the Second Affiliated Hospital of Nantong University between January 1, 2013, and October 31, 2020, were enrolled in this study. Traditional two-dimensional echocardiography and RT-3DE were performed pre and post-CRT, with QRS wave width data from electrocardiograms and additional clinical information collected. Patients were categorized into CRT responder (n = 36) and CRT non-responder (n = 15) groups based on their response to CRT device implantation. Comparative analyses were conducted on the general characteristics of both groups, as well as the predictive efficacy of RT-3DE and QRS wave width for CRT responsiveness and left ventricular systolic function. Data on the standard deviation (Tmsv16-SD, Tmsv12-SD, Tmsv6-SD) and maximum difference (Tmsv16-Dif, Tmsv12-Dif, Tmsv6-Dif) of left ventricular end-systolic volume (LVESV) at segments 16, 12, and 6, as well as QRS wave width, were collected and analyzed.

RESULTS

The indicators Tmsv6-Dif, Tmsv12-Dif, Tmsv16-Dif, Tmsv6-SD, Tmsv12-SD, Tmsv16-SD, and QRS wave width exhibited significantly higher values in the CRT responder group when compared to the CRT non-responder group (P < 0.05). Among these, Tmsv16-SD demonstrated superior predictive performance for post-CRT response, with a sensitivity of 88.9%, specificity of 80.0%, and a diagnostic cut-off value of 6.19%. This predictive capability exceeded that of the conventional indicator, QRS wave width.

CONCLUSION

RT-3DE enables accurate prediction of post-CRT patient response and significantly facilitates quantitative assessment of CRT therapy efficacy.

Redefining left bundle branch block from high-density electroanatomical mapping

BACKGROUND

The existing ECG criteria for diagnosing left bundle branch block (LBBB) are insufficient to distinguish between true and false blocks accurately.

METHODS

We hypothesized that the notch width of the QRS complex in the lateral leads (I, avL, V5, V6) on the LBBB-like ECG could further confirm the diagnosis of true complete left bundle branch block (t-LBBB). We conducted high-density, three-dimensional electroanatomical mapping in the cardiac chambers of 37 patients scheduled to undergo CRT. These patients' preoperative electrocardiograms met the ACC/AHA/HRS guidelines for the diagnosis of complete LBBB. If the left bundle branch potential could be mapped from the base of the heart to the apex on the left ventricular septum, it was defined as a false complete left bundle branch block (f-LBBB). Otherwise, it was categorized as a t-LBBB. We conducted a comparative analysis between the two groups, considering the clinical characteristics, real-time correspondence between the spread of ventricular electrical excitation and the QRS wave, QRS notch width of the lateral leads (I, avL, V5, V6), and the notch width/left ventricular end-diastolic diameter (Nw/LVd) ratio. We performed the ROC correlation analysis of Nw/LVd and t-LBBB to determine the sensitivity and specificity for diagnostic authenticity.

RESULTS

Twenty-five patients were included in the t-LBBB group, while 12 patients were assigned to the f-LBBB group. Within the t-LBBB group, the first peak of the QRS notch correlated with the depolarization of the right ventricle and septum, the trough corresponded to the depolarization of the left ventricle across the left ventricle, and the second peak aligned with the depolarization of the left ventricular free wall. In contrast, within the f-LBBB group, the first peak coincided with the depolarization of the right ventricle and a majority of the left ventricle, the second peak occurred due to the depolarization of the latest, locally-activated myocardium in the left ventricle, and the trough was a result of delayed activation of the left ventricle that did not align with the usual peak timing. The QRS notch width (45.2 ± 12.3 ms vs. 52.5 ± 9.2 ms, P < 0.05) and the Nw/LVd ratio (0.65 ± 0.19 ms/mm vs. 0.81 ± 0.17 ms/mm, P < 0.05) were compared between the two groups. After conducting the ROC correlation analysis, a sensitivity of 56% and a specificity of 91.7% for diagnosing t-LBBB using Nw/LVd were obtained.

CONCLUSION

By utilizing the current diagnostic criteria for LBBB, an increased Nw/LVd value can enhance the effectiveness of diagnosing LBBB.

Myocardial Perfusion SPECT Imaging Radiomic Features and Machine Learning Algorithms for Cardiac Contractile Pattern Recognition

A U-shaped contraction pattern was shown to be associated with a better Cardiac resynchronization therapy (CRT) response. The main goal of this study is to automatically recognize left ventricular contractile patterns using machine learning algorithms trained on conventional quantitative features (ConQuaFea) and radiomic features extracted from Gated single-photon emission computed tomography myocardial perfusion imaging (GSPECT MPI). Among 98 patients with standard resting GSPECT MPI included in this study, 29 received CRT therapy and 69 did not (also had CRT inclusion criteria but did not receive treatment yet at the time of data collection, or refused treatment). A total of 69 non-CRT patients were employed for training, and the 29 were employed for testing. The models were built utilizing features from three distinct feature sets (ConQuaFea, radiomics, and ConQuaFea + radiomics (combined)), which were chosen using Recursive feature elimination (RFE) feature selection (FS), and then trained using seven different machine learning (ML) classifiers. In addition, CRT outcome prediction was assessed by different treatment inclusion criteria as the study's final phase. The MLP classifier had the highest performance among ConQuaFea models (AUC, SEN, SPE = 0.80, 0.85, 0.76). RF achieved the best performance in terms of AUC, SEN, and SPE with values of 0.65, 0.62, and 0.68, respectively, among radiomic models. GB and RF approaches achieved the best AUC, SEN, and SPE values of 0.78, 0.92, and 0.63 and 0.74, 0.93, and 0.56, respectively, among the combined models. A promising outcome was obtained when using radiomic and ConQuaFea from GSPECT MPI to detect left ventricular contractile patterns by machine learning.

The role of cardiac magnetic resonance in identifying appropriate candidates for cardiac resynchronization therapy - a systematic review of the literature

Despite the strict indications for cardiac resynchronization therapy (CRT) implantation, a significant proportion of patients will fail to adequately respond to the treatment. This systematic review aims to present the existing evidence about the role of cardiac magnetic resonance (CMR) in identifying patients who are likely to respond better to the CRT. A systematic search in the MedLine database and Cochrane Library from their inception to August 2021 was performed, without any limitations, by two independent investigators. We considered eligible observational studies or randomized clinical trials (RCTs) that enrolled patients > 18 years old with heart failure (HF) of ischaemic or non-ischaemic aetiology and provided data about the association of baseline CMR variables with clinical or echocardiographic response to CRT for at least 3 months. This systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA Statement). Following our search strategy, 47 studies were finally included in our review. CMR appears to have an additive role in identifying the subgroup of patients who will respond better to CRT. Specifically, the presence and the extent of myocardial scar were associated with increased non-response rates, while those with no scar respond better. Furthermore, existing data show that scar location can be associated with CRT response rates. CMR-derived markers of mechanical desynchrony can also be used as predictors of CRT response. CMR data can be used to optimize the position of the left ventricular lead during the CRT implantation procedure. Specifically, positioning the left ventricular lead in a branch of the coronary sinus that feeds an area with transmural scar was associated with poorer response to CRT. CMR can be used as a non-invasive optimization tool to identify patients who are more likely to achieve better clinical and echocardiographic response following CRT implantation.

A multimodal deep learning model for cardiac resynchronisation therapy response prediction

We present a novel multimodal deep learning framework for cardiac resynchronisation therapy (CRT) response prediction from 2D echocardiography and cardiac magnetic resonance (CMR) data. The proposed method first uses the 'nnU-Net' segmentation model to extract segmentations of the heart over the full cardiac cycle from the two modalities. Next, a multimodal deep learning classifier is used for CRT response prediction, which combines the latent spaces of the segmentation models of the two modalities. At test time, this framework can be used with 2D echocardiography data only, whilst taking advantage of the implicit relationship between CMR and echocardiography features learnt from the model. We evaluate our pipeline on a cohort of 50 CRT patients for whom paired echocardiography/CMR data were available, and results show that the proposed multimodal classifier results in a statistically significant improvement in accuracy compared to the baseline approach that uses only 2D echocardiography data. The combination of multimodal data enables CRT response to be predicted with 77.38% accuracy (83.33% sensitivity and 71.43% specificity), which is comparable with the current state-of-the-art in machine learning-based CRT response prediction. Our work represents the first multimodal deep learning approach for CRT response prediction.

A Mild Dyssynchronous Contraction Pattern Detected by SPECT Myocardial Perfusion Imaging Predicts Super-Response to Cardiac Resynchronization Therapy

Background

Using single photon emission computed tomography myocardial perfusion imaging (SPECT MPI) with phase analysis (PA), we aimed to identify the predictive value of a new contraction pattern in cardiac resynchronization therapy (CRT) response.

Methods

Left ventricular mechanical dyssynchrony (LVMD) was evaluated using SPECT MPI with PA in non-ischemic dilated cardiomyopathy (DCM) patients with left bundle branch block (LBBB) indicated for CRT. CRT super-response was defined as LV ejection fraction (EF) ≥50% or an absolute increase of LVEF >15%. The LV contraction was categorized as the mild dyssynchronous pattern when the phase standard deviation (PSD) ≤ 40.3° and phase histogram bandwidth (PBW) ≤ 111.9°, otherwise it was defined as severe dyssynchronous pattern which was further characterized as U-shaped, heterogeneous or homogenous pattern.

Results

The final cohort comprised 74 patients, including 32 (43.2%) in mild dyssynchronous group, 17 (23%) in U-shaped group, 19 (25.7%) in heterogeneous group, and 6 (8.1%) in homogenous group. The mild dyssynchronous group had lower PSD and PBW than U-shaped, heterogeneous, and homogenous groups (P < 0.0001). Compared to patients with the heterogeneous pattern, the odds ratios (ORs) with 95% confidence intervals (CIs) for CRT super-response were 10.182(2.43–42.663), 12.8(2.545–64.372), and 2.667(0.327–21.773) for patients with mild dyssynchronous, U-shaped, and homogenous pattern, respectively. After multivariable adjustment, mild dyssynchronous group remained associated with increased CRT super-response (adjusted OR 5.709, 95% CI 1.152–28.293). Kaplan-Meier curves showed that mild dyssynchronous group demonstrated a better long-term prognosis.

Conclusions

The mild dyssynchronous pattern in patients with DCM is associated with an increased CRT super-response and better long-term prognosis.

Segment length in cine (SLICE) strain analysis: a practical approach to estimate potential benefit from cardiac resynchronization therapy

BACKGROUND

Segment length in cine (SLICE) strain analysis on standard cardiovascular magnetic resonance (CMR) cine images was recently validated against gold standard myocardial tagging. The present study aims to explore predictive value of SLICE for cardiac resynchronization therapy (CRT) response.

METHODS AND RESULTS

Fifty-seven patients with heart failure and left bundle branch block (LBBB) were prospectively enrolled in this multi-center study and underwent CMR examination before CRT implantation. Circumferential strains of the septal and lateral wall were measured by SLICE on short-axis cine images. In addition, timing and strain pattern parameters were assessed. After twelve months, CRT response was quantified by the echocardiographic change in left ventricular (LV) end-systolic volume (LVESV). In contrast to timing parameters, strain pattern parameters being systolic rebound stretch of the septum (SRSsep), systolic stretch index (SSIsep-lat), and internal stretch factor (ISFsep-lat) all correlated significantly with LVESV change (R - 0.56; R - 0.53; and R - 0.58, respectively). Of all strain parameters, end-systolic septal strain (ESSsep) showed strongest correlation with LVESV change (R - 0.63). Multivariable analysis showed ESSsep to be independently related to LVESV change together with age and QRSAREA.

CONCLUSION

The practicable SLICE strain technique may help the clinician to estimate potential benefit from CRT by analyzing standard CMR cine images without the need for commercial software. Of all strain parameters, end-systolic septal strain (ESSsep) demonstrates the strongest correlation with reverse remodeling after CRT. This parameter may be of special interest in patients with non-strict LBBB morphology for whom CRT benefit is doubted.

Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction

Advances in deep learning (DL) have resulted in impressive accuracy in some medical image classification tasks, but often deep models lack interpretability. The ability of these models to explain their decisions is important for fostering clinical trust and facilitating clinical translation. Furthermore, for many problems in medicine there is a wealth of existing clinical knowledge to draw upon, which may be useful in generating explanations, but it is not obvious how this knowledge can be encoded into DL models - most models are learnt either from scratch or using transfer learning from a different domain. In this paper we address both of these issues. We propose a novel DL framework for image-based classification based on a variational autoencoder (VAE). The framework allows prediction of the output of interest from the latent space of the autoencoder, as well as visualisation (in the image domain) of the effects of crossing the decision boundary, thus enhancing the interpretability of the classifier. Our key contribution is that the VAE disentangles the latent space based on 'explanations' drawn from existing clinical knowledge. The framework can predict outputs as well as explanations for these outputs, and also raises the possibility of discovering new biomarkers that are separate (or disentangled) from the existing knowledge. We demonstrate our framework on the problem of predicting response of patients with cardiomyopathy to cardiac resynchronization therapy (CRT) from cine cardiac magnetic resonance images. The sensitivity and specificity of the proposed model on the task of CRT response prediction are 88.43% and 84.39% respectively, and we showcase the potential of our model in enhancing understanding of the factors contributing to CRT response.

The Temporal Relation between Cardiomyopathy and LBBB and Response to Cardiac Resynchronization Therapy: Case Series and Literature Review

Background: Left bundle branch block (LBBB)-induced cardiomyopathy has been proposed, but the association between LBBB and cardiac resynchronization therapy (CRT) response remains unclear and practical criteria for selecting CRT candidates are needed.Methods: One hundred and seventeen consecutive heart failure patients were reviewed, 24 of whom received CRT. Only two patients had a clear temporal relation between cardiomyopathy and LBBB.Results: Compared with the patient with “cardiomyopathy-induced LBBB,” the patient with “LBBB-induced cardiomyopathy” had higher left ventricular (LV) wall thickness, higher LV wall thickening rate, higher peak circumferential strain, and longer peak circumferential strain delay. The LV deformation patterns in the two patients were obviously distinct on cardiovascular magnetic resonance tissue tracking. During follow-up, the patient with LBBB-induced cardiomyopathy had a good response to CRT (LV ejection fraction 23 before CRT vs. 30% at 6 months vs. 29 at 12 months vs. 32% at 18 months; LV end-diastolic diameter 77 mm before CRT vs. 66 mm at 6 months vs. 62 mm at 12 months vs. 63 mm at 18 months), and the other patient had no response to CRT (LV ejection fraction 29 before CRT vs. 29% at 6 months vs. 26 at 12 months vs. 22% at 24 months; LV end-diastolic diameter 85 mm before CRT vs. 88 mm at 6 months vs. 85 mm at 12 months vs. 84 mm at 24 months).Conclusion: The temporal relation between cardiomyopathy and LBBB could be a determinant for CRT response. Cardiovascular magnetic resonance tissue tracking may be a useful tool to identify the chronological order and a principal consideration for selecting candidates for CRT. Larger prospective clinical trials are needed to study the prevalence of, time course of, and risk factors for LBBB-induced cardiomyopathy.

[Assessment of myocardial electrical dissynchrony by noninvasive activation mapping and its role in achieving the success of cardiac resynchronization]

PURPOSE

To assess and to compare the ventricular myocardium activation patern obtained by non-invasive epi- and endocardial mapping (NIEEM), as well as electrocardiographic (ECG) variants of lef bundle branch block (LBBB) and to estimate the value of these data for the success of cardiac resynchronization therapy (CRT).

MATERIALS AND METHODS

Te study included 23 patients (mean age 59,6±9,9 years) with LBBB, QRS duration ≥ 130 ms, lef ventricular ejection fraction (LVEF) ≤ 35%, heart failure (HF) NYHA II-IV despite optimal pharmacological therapy during 3 month. All patients had undergone CRT-D implantation. Depending on presence or absence of LBBB ECG-criteria, proposed by Strauss D.G. et. al, patients were divided into 2 groups: 1group - strict LBBB, proposed by Strauss D.G. et. al. (n=14) and 2 group - other ECG morphologies of LBBB (n=9). NIEEM by the Amycard 01C system with an analysis of epi- and endocardial ventricular electrical activation was performed in all patients and 5 healthy volunteers (mean age 29±1,0years). Response to CRT was estimated by echo and was defned as decrease in lef ventricular (LV) end-systolic volume by &gt; 15% afer 6 months of follow-up.

RESULTS

LBBB ECG-criteria, proposed by Strauss D.G. et. al, was detected in 14 patients (61% of all included). According to the results of NIEEM, these patients had more pronounced ventricular electrical uncoupling (VEU) (р=0,002). Most ofen the line of block was detected in the anteroseptal or posterolateral region of the LV. Te zone of late LV activation, which is the most optimal position for the LV pacing electrode, was located in the basal and middle segments of the lateral and posterior walls. Afer 6 months of CRT 15 patients (65%) were included in the "response" group, the remaining 8 patients (35%) formed the "non-response" group according to echo criteria. In the "response" group the morphology of the QRS complex more frequently met the criteria, proposed by Strauss D.G. et al, than other ECG variants of LBBB (12 vs. 3 respectively, p = 0.023). Initially, VEU was more pronounced in the "response" group (VEU 55 [51, 64] ms in the "response" group vs 22 [8, 38] ms in the "non-response" group).Сonclusions. LBBB ECG criteria, proposed by Strauss D.G., identify patients with delayed transseptal interventricular conduction due to complete LBBB, what is a good target for CPT. Identifcation of individual ventricular activation properties may help to reveal responders to CRT in patients with LBBB.

Assessment of left ventricular contraction patterns using gated SPECT MPI to predict cardiac resynchronization therapy response

BACKGROUND

The U-shaped left ventricular (LV) contraction pattern, identified by MRI or echocardiography, is associated with improved CRT response. Gated SPECT MPI can measure both myocardial viability and mechanical dyssynchrony in a single scan. The aim of this study is to examine the relationship of the LV contraction pattern and the response of CRT in patients with left bundle branch block (LBBB).

METHODS

Fifty-eight patients who met CRT guidelines and who had pre-CRT MPI were enrolled. Myocardial segments with tracer uptake < 50% of maximum were considered as scar. The LV contraction pattern was considered as U-shaped or non-U-shaped (U-shaped has a block line in the direction of contraction propagation). CRT response was defined as an increase in left ventricular ejection fraction ≥ 5% after 6-month follow-up.

RESULTS

Twenty-eight patients (48%) had a U-shaped contraction pattern and thirty patients (52%) had a non-U-shaped contraction pattern. The U-shaped group showed a significantly higher response rate than the non-U-shaped group (90% vs. 57%; P = 0.005). By univariate and multivariate logistic regression analysis, the U-shaped pattern was an independent predictor of CRT response.

CONCLUSION

Non-invasive gated SPECT MPI can characterize LV mechanical contraction patterns. A U-shaped contraction pattern identified is associated with improved CRT response. This may prove useful for improved patient selection for CRT.

Mitral regurgitation: anatomy is destiny

Mitral regurgitation (MR) occurs when any of the valve and ventricular mitral apparatus components are disturbed. As MR progresses, left ventricular remodelling occurs, ultimately causing heart failure when the enlarging left ventricle (LV) loses its conical shape and becomes globular. Heart failure and lethal ventricular arrhythmias may develop if the left ventricular end-systolic volume index exceeds 55 ml/m2. These adverse changes persist despite satisfactory correction of the annular component of MR. Our goal was to describe this process and summarize evolving interventions that reduce the volume of the left ventricle and rebuild its elliptical shape. This 'valve/ventricle' approach addresses the spherical ventricular culprit and offsets the limits of treating MR by correcting only its annular component.

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

Aims

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.

Methods and results

Twenty‐seven patients were prospectively enrolled and underwent CMR and echocardiographic examination before CRT implantation. Strain analysis was performed in circumferential (CMR‐TAG, CMR‐FT, and STE‐circ) and longitudinal (STE‐long) orientations. Regional strain values, parameters of dyssynchrony, and discoordination were calculated. After 12 months, CRT response was measured by the echocardiographic change in left ventricular (LV) end‐systolic volume (LVESV). Twenty‐six patients completed follow‐up; mean LVESV change was −29 ± 27% with 17 (65%) patients showing ≥15% LVESV reduction. Measures of dyssynchrony (SD‐TTP_LV) and discoordination (ISF_LV) were strongly related to CRT response when using CMR‐TAG (R² 0.61 and R² 0.57, respectively), but showed poor correlations for CMR‐FT and STE (all R² ≤ 0.32). In contrast, the end‐systolic septal strain (ESS_sep) parameter showed a consistent high correlation with LVESV change for all techniques (CMR‐TAG R² 0.60; CMR‐FT R² 0.50; STE‐circ R² 0.43; and STE‐long R² 0.43). After adjustment for QRS duration and QRS morphology, ESS_sep remained an independent predictor of response per technique.

Conclusions

End‐systolic septal strain was the only parameter with a consistent good relation to reverse remodelling after CRT, irrespective of assessment technique. In clinical practice, this measure can be obtained by any available strain imaging technique and provides predictive value on top of current guideline criteria.

Current role of echocardiography in cardiac resynchronization therapy

Cardiac resynchronization therapy (CRT) is an established treatment for patients with heart failure and left ventricular systolic dysfunction. Patients are usually assessed by echocardiography, which provides a number of anatomical and functional information used for cardiac dyssynchrony assessment, prognostic stratification, identification of the optimal site of pacing in the left ventricle, optimization of the CRT device, and patient follow-up. Compared to other cardiac imaging techniques, echocardiography has the advantage to be non-invasive, repeatable, and safe, without exposure to ionizing radiation or nefrotoxic contrast. In this article, we review current evidence about the role of echocardiography before, during, and after the implantation of a CRT device.

Comparison of triple-site ventricular pacing versus conventional cardiac resynchronization therapy in patients with systolic heart failure: A meta-analysis of randomized and observational studies

Background

Conventional cardiac resynchronization therapy (CRT, Bi‐V) is associated with no response in about 40% patients due to an insufficient resynchronization. Some studies showed triple‐site ventricular (Tri‐V) pacing had greater benefits compared with Bi‐V pacing, but the results of these studies were conflicting. We hypothesized that Tri‐V pacing had greater benefits on long‐term outcomes compared with Bi‐V pacing in patients with heart failure.

Methods

PubMed, EMBASE, and the Cochrane Library were searched for clinical studies with related outcomes. Weighted mean differences (WMD) and 95% confidence intervals (CIs) were calculated to compare the change in left ventricular ejection fraction (LVEF), left ventricular geometry, functional capacity, and quality of life between Tri‐V pacing group and control group.

Results

Five trials with 251 patients were included in the analysis. Patients in the Tri‐V pacing group had a greater improvement in LVEF (WMD 4.04; 95% CI 2.15‐5.92, P < .001) and NYHA classes (WMD −0.27; 95% CI −0.42 to −0.11, P = .001) compared with control group. However, there were no significant differences in left ventricular geometry, six‐min walk distance, or Minnesota Living With Heart Failure Questionnaire score between the two groups. The subgroup analyses showed there might be a greater improvement in LVEF in the Tri‐V pacing group in patients with QRS duration ≥ 155 ms (WMD 5.60; 95% CI 3.09‐8.10, P < .001).

Conclusions

The present analysis suggests that Tri‐V pacing has greater benefits in terms of an improvement in LVEF and functional capacity in patients with systolic heart failure, especially in patients with the duration of QRS ≥ 155 ms.

Myocardial strain computed at multiple spatial scales from tagged magnetic resonance imaging: Estimating cardiac biomarkers for CRT patients

Abnormal cardiac motion can indicate different forms of disease, which can manifest at different spatial scales in the myocardium. Many studies have sought to characterise particular motion abnormalities associated with specific diseases, and to utilise motion information to improve diagnoses. However, the importance of spatial scale in the analysis of cardiac deformation has not been extensively investigated. We build on recent work on the analysis of myocardial strains at different spatial scales using a cardiac motion atlas to find the optimal scales for estimating different cardiac biomarkers. We apply a multi-scale strain analysis to a 43 patient cohort of cardiac resynchronisation therapy (CRT) patients using tagged magnetic resonance imaging data for (1) predicting response to CRT, (2) identifying septal flash, (3) estimating QRS duration, and (4) identifying the presence of ischaemia. A repeated, stratified cross-validation is used to demonstrate the importance of spatial scale in our analysis, revealing different optimal spatial scales for the estimation of different biomarkers.

Contemporary Review of Left Bundle Branch Block in the Failing Heart - Pathogenesis, Prognosis, and Therapy

Cardiac resynchronisation therapy (CRT) is a cornerstone in the contemporary management of heart failure. The most effective way of predicting response to this therapy remains electrocardiographic (ECG) criteria of electromechanical dyssynchrony. The left bundle branch block (LBBB) pattern is currently the most robust ECG criterion in predicting improvement in symptoms and reduction in mortality. However, recent studies using three-dimensional (3D) mapping and cardiac magnetic resonance imaging (CMR) have demonstrated heterogeneous left ventricular activation patterns in patients with LBBB. This has led to intense debate on the activation pattern of "true LBBB" and resulted in the proposal of stricter criteria for defining LBBB. This review will focus on the definitions and implications of LBBB in the CRT era. At a minimum, the use of stricter ECG criteria appears warranted, and adjunctive pre-implant imaging or mapping may further identify patient-specific electrophysiological patterns that determine response to CRT.

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

BACKGROUND

Current guidelines suggest that patients with left bundle branch block (LBBB) be treated with cardiac resynchronization therapy (CRT); however, one-third do not have a significant activation delay, which can result in nonresponse. By identifying characteristic opposing wall contraction, 2-dimensional strain echocardiography (2DSE) may detect true LBBB activation.

OBJECTIVES

This study sought to investigate whether the absence of a typical LBBB mechanical activation pattern by 2DSE was associated with unfavorable long-term outcome and if this is additive to electrocardiographic (ECG) morphology and duration.

METHODS

From 2 centers, 208 CRT candidates (New York Heart Association classes II to IV, ejection fraction ≤35%, QRS duration ≥120 ms) with LBBB by ECG were prospectively included. Before CRT implantation, longitudinal strain in the apical 4-chamber view determined whether typical LBBB contraction was present. The pre-defined outcome was freedom from death, left ventricular assist device, or heart transplantation over 4 years.

RESULTS

Two-thirds of patients (63%) had a typical LBBB contraction pattern. During 4 years, 48 patients (23%) reached the primary endpoint. Absence of a typical LBBB contraction was independently associated with increased risk of adverse outcome after adjustment for ischemic heart disease and QRS width (hazard ratio [HR]: 3.1; 95% CI: 1.64 to 5.88; p < 0.005). Adding pattern assessment to a risk prediction model including QRS duration and ischemic heart disease significantly improved the net reclassification index to 0.14 (p = 0.04) and improved the C-statistics (0.63 [95% CI: 0.54 to 0.72] vs. 0.71 [95% CI: 0.63 to 0.80]; p = 0.02). Use of strict LBBB ECG criteria was not independently associated with outcome in the multivariate model (HR: 1.72; 95% CI: 0.89 to 3.33; p = 0.11. Assessment of LBBB contraction pattern was superior to time-to-peak indexes of dyssynchrony (p < 0.01 for all).

CONCLUSIONS

Contraction pattern assessment to identify true LBBB activation provided important prognostic information in CRT candidates.

A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction

We present a framework for combining a cardiac motion atlas with non-motion data. The atlas represents cardiac cycle motion across a number of subjects in a common space based on rich motion descriptors capturing 3D displacement, velocity, strain and strain rate. The non-motion data are derived from a variety of sources such as imaging, electrocardiogram (ECG) and clinical reports. Once in the atlas space, we apply a novel supervised learning approach based on random projections and ensemble learning to learn the relationship between the atlas data and some desired clinical output. We apply our framework to the problem of predicting response to Cardiac Resynchronisation Therapy (CRT). Using a cohort of 34 patients selected for CRT using conventional criteria, results show that the combination of motion and non-motion data enables CRT response to be predicted with 91.2% accuracy (100% sensitivity and 62.5% specificity), which compares favourably with the current state-of-the-art in CRT response prediction.

Can Pulmonary Vascular Resistance Predict Response to Cardiac Resynchronization Therapy in Patients with Heart Failure?

BACKGROUND

To evaluate if pulmonary vascular resistance (PVR) calculated by echocardiography can be a novel criterion to predict the response to cardiac resynchronization therapy (CRT).

METHODS

Forty-five patients with heart failure who underwent CRT were retrospectively analyzed. Based on CRT response, which was defined by a decrease of left ventricular end-systolic volume by at least 15% after 6 months, the patients were assigned to the responder or nonresponder groups. The peak tricuspid regurgitant velocity (TRV) and time velocity integral of the right ventricular outflow tract (TVIRVOT ) were obtained. The relation between TRV, PVR, and CRT response were analyzed using univariate and multivariate analyses.

RESULTS

Twenty-seven patients (60%) were responders and 18 patients (40%) were nonresponders to CRT. At baseline, responders had lower PVR (3.57±1.65 vs 2.32 ± 1.28 wood; P = 0.01), or lower PVR1 (3.26 ± 1.32 vs 1.83 ± 0.79 wood; P = 0.01) compared with nonresponders. Multivariate analysis has shown that PVR and PVR1 were independent factors for CRT response. The optimal cutoff point of PVR to predict nonresponse to CRT was 2.39 wood, with a sensitivity of 0.78 and a specificity of 0.81 (95% confidence interval [CI]: 53.4-88.2). The optimal cutoff point of PVR1 calculated by the other model was 3.55 wood, determined at a sensitivity of 0.72 and a specificity of 0.82 (95%CI: 56.7-90.7). In nonresponders, patients demonstrated higher PVR, TVIA , and TVIRVOT , and decreased TRV.

CONCLUSIONS

PVR could be used to predict response to CRT after 6 months as a novel criterion, and higher PVR may indicate nonresponse.