Evaluation of the ECG based Selvester scoring method to estimate myocardial scar burden and predict clinical outcome in patients with left bundle branch block, with comparison to late gadolinium enhancement CMR imaging

Evaluating the predictive value of late gadolinium enhancement assessed by cardiac magnetic resonance on sudden cardiac death in patients selected for implantable cardioverter defibrillator and cardiac resynchronization therapy implantation: a systematic review and meta-analysis

AIMS

Late gadolinium enhancement (LGE) assessed by cardiovascular magnetic resonance (CMR) can evaluate myocardial scar associated with a higher risk of sudden cardiac death (SCD), which can guide the selection between cardiac resynchronization therapy with or without a defibrillator (CRT-P/CRT-D). Our aim was to investigate the association between LGE and SCD risk in patients with CRT using the LGE-CMR technique.

METHODS AND RESULTS

We performed a systematic literature search using four databases. The target population was CRT candidates. The primary endpoint was SCD. The risk of bias was assessed using the QUIPS tool. Fifteen eligible articles were included with a total of 2494 patients, of whom 27%, 56%, and 19% had an implantable cardioverter defibrillator (ICD), CRT-D, and CRT-P, respectively. Altogether, 54.71% of the cohort was LGE positive, who had a 72% higher risk for SCD (HR 1.72; 95% CI 1.18-2.50) compared to LGE negatives. In non-ischemic patients, the proportion of LGE positivity was 46.6%, with a significantly higher risk for SCD as compared to LGE negatives (HR 2.42; 95% CI 1.99-2.94). The subgroup of CRT-only patients showed no difference between the LGE-positive vs. negative candidates (HR 1.17; 95% CI 0.82-1.68). Comparable SCD risk was observed between articles with short- (OR 7.47; 95% CI 0.54-103.12) vs. long-term (OR 6.15; 95% CI 0.96-39.45) follow-up time.

CONCLUSION

LGE-CMR positivity was associated with an increased SCD risk; however, in CRT candidates, the difference in risk reduction between LGE positive vs. negative patients was statistically not significant, suggesting a role of reverse remodeling. LGE-CMR before device implantation could be crucial in identifying high-risk patients even in non-ischemic etiology.

Detecting myocardial scar using electrocardiogram data and deep neural networks

Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischaemic heart disease and can be detected with high diagnostic precision by magnetic resonance imaging. However, magnetic resonance imaging scanners are expensive and of limited availability. It is known that presence of myocardial scar has an impact on the well-established, reasonably low cost, and almost ubiquitously available electrocardiogram. However, this impact is non-specific and often hard to detect by a physician. We present an artificial intelligence based approach - namely a deep learning model - for the prediction of myocardial scar based on an electrocardiogram and additional clinical parameters. The model was trained and evaluated by applying 6-fold cross-validation to a dataset of 12-lead electrocardiogram time series together with clinical parameters. The proposed model for predicting the presence of scar tissue achieved an area under the curve score, sensitivity, specificity, and accuracy of 0.89, 70.0, 84.3, and 78.0%, respectively. This promisingly high diagnostic precision of our electrocardiogram-based deep learning models for myocardial scar detection may support a novel, comprehensible screening method.

Vectorcardiography Findings Are Associated with Recurrent Ventricular Arrhythmias and Mortality in Patients with Heart Failure Treated with Implantable Cardioverter-Defibrillator Device

BACKGROUND

There is a need for refined risk stratification of sudden cardiac death and prediction of ventricular arrhythmias to correctly identify patients who are expected to benefit the most from implantable cardioverter-defibrillator (ICD) therapy.

METHODS

We conducted a registry-based retrospective observational study on patients with either ischemic (ICMP) or nonischemic dilated cardiomyopathy (NICMP) treated with ICD between 2002 and 2013 at a tertiary referral center. We evaluated 3 vectorcardiography (VCG) indices; spatial QRS-T angle, QRS vector magnitude (QRSvm), and T-wave vector magnitude (Twvm), and their association with all-cause mortality and ventricular arrhythmias. The VCG indices were automatically computed from resting 12-lead electrocardiograms before ICD implantation.

RESULTS

178 patients were included in the study; 53.4% had ICMP, 79.2% were male, and mean ejection fraction was 27.4%. During the follow-up (median 89 months), 40 patients (23%) died; 31% had appropriate ICD therapy. In multivariate analysis with dichotomized variables, QRS-T angle >152° and Twvm <0.38 mV were significantly associated with increased mortality: HR 2.64 (95% CI 1.14-6.12, p = 0.02) and HR 5.30 (95% CI 2.31-12.11, p < 0.001), respectively. QRSvm <1.54 mV was borderline significant with mortality outcome (p = 0.10). The composite score of all 3 VCG indices, a score of 3, conferred an increased risk of mortality (including heart failure mortality) in multivariate analysis: HR 13.80 (95% CI 3.44-55.39, p < 0.001).

CONCLUSION

The spatial QRS-T angle and Twvm are emerging VCG indices which are independently associated with mortality in patients with reduced left ventricular ejection fraction due to ICMP or NICMP. Using a composite score of all 3 vector indices, a maximum score was associated with poor long-term survival.

Evaluation of the ECG based Selvester scoring method to estimate myocardial scar burden and predict clinical outcome in patients with left bundle branch block, with comparison to late gadolinium enhancement CMR imaging

BACKGROUND

Myocardial scar burden quantification is an emerging clinical parameter for risk stratification of sudden cardiac death and prediction of ventricular arrhythmias in patients with left ventricular dysfunction. We investigated the relationships among semiautomated Selvester score burden and late gadolinium enhancement-cardiovascular magnetic resonance (LGE-CMR) assessed scar burden and clinical outcome in patients with underlying heart failure, left bundle branch block (LBBB) and implantable cardioverter-defibrillator (ICD) treatment.

METHODS

Selvester QRS scoring was performed on all subjects with ischemic and nonischemic dilated cardiomyopathy at Skåne University Hospital Lund (2002-2013) who had undergone LGE-CMR and 12-lead ECG with strict LBBB pre-ICD implantation.

RESULTS

Sixty patients were included; 57% nonischemic dilated cardiomyopathy and 43% ischemic cardiomyopathy with mean left ventricular ejection fraction of 27.6% ± 11.7. All patients had scar by Selvester scoring. Sixty-two percent had scar by LGE-CMR (n = 37). The Spearman correlation coefficient for LGE-CMR and Selvester score derived scar was r = .35 (p = .007). In scar negative LGE-CMR, there was evidence of scar by Selvester scoring in all patients (range 3%-33%, median 15%). Fourteen patients (23%) had an event during the follow-up period; 11 (18%) deaths and six adequate therapies (10%). There was a moderate trend indicating that presence of scar increased the risk of clinical endpoints in the LGE-CMR analysis (p = .045).

CONCLUSION

There is a modest correlation between LGE-CMR and Selvester scoring verified myocardial scar. CMR based scar burden is correlated to clinical outcome, but Selvester scoring is not. The Selvester scoring algorithm needs to be further refined in order to be clinically relevant and reliable for detailed scar evaluation in patients with LBBB.