Echocardiographic Assessment of Left Bundle Branch-Related Strain Dyssynchrony: A Comparison With Tagged MRI

Assessment of myocardial strain patterns in patients with left bundle branch block using cardiac magnetic resonance

Recently, a classification with four types of septal longitudinal strain patterns was described using echocardiography, suggesting a pathophysiological continuum of left bundle branch block (LBBB)-induced left ventricle (LV) remodeling. The aim of this study was to assess the feasibility of classifying these strain patterns using cardiovascular magnetic resonance (CMR), and to evaluate their association with LV remodeling and myocardial scar. Single center registry included LBBB patients with septal flash (SF) referred to CMR to assess the cause of LV systolic dysfunction. Semi-automated feature-tracking cardiac resonance (FT-CMR) was used to quantify myocardial strain and detect the four strain patterns. A total of 115 patients were studied (age 66 ± 11 years, 57% men, 28% with ischemic heart disease). In longitudinal strain analysis, 23 patients (20%) were classified in stage LBBB-1, 37 (32.1%) in LBBB-2, 25 (21.7%) in LBBB-3, and 30 (26%) in LBBB-4. Patients at higher stages had more prominent septal flash, higher LV volumes, lower LV ejection fraction, and lower absolute strain values (p < 0.05 for all). Late gadolinium enhancement (LGE) was found in 55% of the patients (n = 63). No differences were found between the strain patterns regarding the presence, distribution or location of LGE. Among patients with LBBB, there was a good association between strain patterns assessed by FT-CMR analysis and the degree of LV remodeling and LV dysfunction. This association seems to be independent from the presence and distribution of LGE.

Clinical and Experimental Evidence for a Strain-Based Classification of Left Bundle Branch Block-Induced Cardiac Remodeling

BACKGROUND

Septal strain patterns measured by echocardiography reflect the severity of left bundle branch block (LBBB)-induced left ventricular (LV) dysfunction. We investigated whether these LBBB strain stages predicted the response to cardiac resynchronization therapy in an observational study and developed a sheep model of LBBB-induced cardiomyopathy.

METHODS

The clinical study enrolled cardiac resynchronization therapy patients who underwent echocardiographic examination with speckle-tracking strain analysis before cardiac resynchronization therapy implant. In an experimental sheep model with pacing-induced dyssynchrony, LV remodeling and strain were assessed at baseline, at 8 and 16 weeks. Septal strain curves were classified into 5 patterns (LBBB-0 to LBBB-4).

RESULTS

The clinical study involved 250 patients (age 65 [58; 72] years; 79% men; 89% LBBB) with a median LV ejection fraction of 25 [21; 30]%. Across the stages, cardiac resynchronization therapy resulted in a gradual volumetric response, ranging from no response in LBBB-0 patients (ΔLV end-systolic volume 0 [-12; 15]%) to super-response in LBBB-4 patients (ΔLV end-systolic volume -44 [-64; -18]%) (P<0.001). LBBB-0 patients had a less favorable long-term outcome compared with those in stage LBBB≥1 (log-rank P=0.003). In 13 sheep, acute right ventricular pacing resulted in LBBB-1 (23%) and LBBB-2 (77%) patterns. Over the course of 8-16 weeks, continued pacing resulted in progressive LBBB-induced dysfunction, coincident with a transition to advanced strain patterns (92% LBBB-2 and 8% LBBB-3 at week 8; 75% LBBB-3 and 25% LBBB-4 at week 16) (P=0.023).

CONCLUSIONS

The strain-based LBBB classification reflects a pathophysiological continuum of LBBB-induced remodeling over time and is associated with the extent of reverse remodeling in observational cardiac resynchronization therapy-eligible patients.

LVNet: Lightweight Model for Left Ventricle Segmentation for Short Axis Views in Echocardiographic Imaging

Lightweight segmentation models are becoming more popular for fast diagnosis on small and low cost medical imaging devices. This study focuses on the segmentation of the left ventricle (LV) in cardiac ultrasound (US) images. A new lightweight model [LV network (LVNet)] is proposed for segmentation, which gives the benefits of requiring fewer parameters but with improved segmentation performance in terms of Dice score (DS). The proposed model is compared with state-of-the-art methods, such as UNet, MiniNetV2, and fully convolutional dense dilated network (FCdDN). The model proposed comes with a post-processing pipeline that further enhances the segmentation results. In general, the training is done directly using the segmentation mask as the output and the US image as the input of the model. A new strategy for segmentation is also introduced in addition to the direct training method used. Compared with the UNet model, an improvement in DS performance as high as 5% for segmentation with papillary (WP) muscles was found, while showcasing an improvement of 18.5% when the papillary muscles are excluded. The model proposed requires only 5% of the memory required by a UNet model. LVNet achieves a better trade-off between the number of parameters and its segmentation performance as compared with other conventional models. The developed codes are available at https://github.com/navchetanawasthi/Left_Ventricle_Segmentation.

Strain-based discoordination imaging during exercise in heart failure with reduced ejection fraction: Feasibility and reproducibility

PURPOSE

Various parameters of mechanical dyssynchrony have been proposed to improve patient selection criteria for cardiac resynchronization therapy, but sensitivity and specificity are lacking. However, echocardiographic parameters are consistently investigated at rest, whereas heart failure (HF) symptoms predominately manifest during submaximal exertion. Although strain-based predictors of response are promising, feasibility and reproducibility during exercise has yet to be demonstrated.

METHODS

Speckle-tracking echocardiography was performed in patients with HF at two separate visits. Echocardiography was performed at rest, during various exercise intensity levels, and during recovery from exercise. Systolic rebound stretch of the septum (SRSsept), systolic shortening, and septal discoordination index (SDI) were calculated.

RESULTS

Echocardiography was feasible in about 70-80% of all examinations performed during exercise. Of these acquired views, 84% of the cine-loops were suitable for analysis of strain-based mechanical dyssynchrony. Test-retest variability and intra- and inter-operator reproducibility at 30% and 60% of the ventilatory threshold (VT) were about 2.5%. SDI improved in the majority of patients at 30% and 60% of the VT, with moderate to good agreement between both intensity levels.

CONCLUSION

Although various challenges remain, exercise echocardiography with strain analysis appears to be feasible in the majority of patients with dyssynchronous heart failure. Inter- and intra-observer agreement of SRSsept and SDI up to 60% of the VT were comparable to resting values. During exercise, the extent of SDI was variable, suggesting a heterogeneous response to exercise. Further research is warranted to establish its clinical significance.

A rapid electromechanical model to predict reverse remodeling following cardiac resynchronization therapy

Cardiac resynchronization therapy (CRT) is an effective therapy for patients who suffer from heart failure and ventricular dyssynchrony such as left bundle branch block (LBBB). When it works, it reverses adverse left ventricular (LV) remodeling and the progression of heart failure. However, CRT response rate is currently as low as 50-65%. In theory, CRT outcome could be improved by allowing clinicians to tailor the therapy through patient-specific lead locations, timing, and/or pacing protocol. However, this also presents a dilemma: there are far too many possible strategies to test during the implantation surgery. Computational models could address this dilemma by predicting remodeling outcomes for each patient before the surgery takes place. Therefore, the goal of this study was to develop a rapid computational model to predict reverse LV remodeling following CRT. We adapted our recently developed computational model of LV remodeling to simulate the mechanics of ventricular dyssynchrony and added a rapid electrical model to predict electrical activation timing. The model was calibrated to quantitatively match changes in hemodynamics and global and local LV wall mass from a canine study of LBBB and CRT. The calibrated model was used to investigate the influence of LV lead location and ischemia on CRT remodeling outcome. Our model results suggest that remodeling outcome varies with both lead location and ischemia location, and does not always correlate with short-term improvement in QRS duration. The results and time frame required to customize and run this model suggest promise for this approach in a clinical setting.

A demonstration of high field-of-view stability in hands-free echocardiography

Background

Exercise stress echocardiography is clinically used to assess cardiovascular diseases. For accurate cardiac evaluation, a stable field-of-view is required. However, transducer orientation and position are difficult to preserve. Hands-free acquisitions might provide more consistent and reproducible results. In this study, the field-of-view stability and variability of hands-free acquisitions are objectively quantified in a comparison with manually obtained images, based on image structural and feature similarities. In addition, the feasibility and consistency of hands-free strain imaging is assessed.

Methods

In twelve healthy males, apical and parasternal images were acquired hands-free, using a fixation device, and manually, during semi-supine exercise sessions. In the final ten seconds of every exercise period, the image structural similarity and cardiac feature consistency were computed using a steerable pyramid employing complex, oriented wavelets. An algorithm discarding images displaying lung artifacts was created. Hands-free strain consistency was analyzed.

Results

Hands-free acquisitions were possible in 9 of the 12 subjects, whereas manually 10 out of 12 could be imaged. The image structural similarity was significantly improved in the hands-free apical window acquisitions (0.91 versus 0.82), and at least equally good in the parasternal window (0.90 versus 0.82). The change in curvature and orientation of the interventricular septum also appeared to be lower in the hands-free acquisitions. The variability in field-of-view was similar in both acquisitions. Longitudinal, septal strain was shown to be at least as consistent when obtained hands-free compared to manual acquisitions.

Conclusions

The field-of-view was shown to be more or equally stable and consistent in the hands-free data in comparison to manually obtained images. The variability was similar, thus respiration- and exercise-induced motions were comparable for manual and hands-free acquisitions. Additionally, the feasibility of hands-free strain has been demonstrated. Furthermore, the results suggest the hands-free measurements to be more reproducible, though further analysis is required.