Left ventricular shape predicts arrhythmic risk in fibrotic dilated cardiomyopathy. Issue 7 (15th December 2021)

• Record Type: Journal Article
• Authors: Balaban, Gabriel; Halliday, Brian P; Hammersley, Daniel; Rinaldi, Christopher A; Prasad, Sanjay K; Bishop, Martin J; Lamata, Pablo
• Is Part Of: Europace. Volume 24:Issue 7(2022)
• Page Start: 1137
• Page End: 1147
• Publication Date: 2021-12-15
• Subjects: Non-ischaemic dilated cardiomyopathy -- Cardiac magnetic resonance imaging -- Arrhythmias -- Machine learning -- Shape analysis -- Risk stratification; Arrhythmia -- Treatment -- Periodicals; Cardiac pacing -- Periodicals; Catheter ablation -- Periodicals; Heart -- Physiology -- Periodicals; Electrophysiology -- Periodicals; 617.4120645
• DOI: 10.1093/europace/euab306
• Languages: English
• ISSNs: 1099-5129

Abstract

Abstract: Aims: Remodelling of the left ventricular (LV) shape is one of the hallmarks of non-ischaemic dilated cardiomyopathy (DCM) and may contribute to ventricular arrhythmias and sudden cardiac death. We sought to investigate a novel three dimensional (3D) shape analysis approach to quantify LV remodelling for arrhythmia prediction in DCM. Methods and results: We created 3D LV shape models from end-diastolic cardiac magnetic resonance images of 156 patients with DCM and late gadolinium enhancement (LGE). Using the shape models, principle component analysis, and Cox-Lasso regression, we derived a prognostic LV arrhythmic shape (LVAS) score which identified patients who reached a composite arrhythmic endpoint of sudden cardiac death, aborted sudden cardiac death, and sustained ventricular tachycardia. We also extracted geometrical metrics to look for potential prognostic markers. During a follow-up period of up to 16 years (median 7.7, interquartile range: 3.9), 25 patients met the arrhythmic endpoint. The optimally prognostic LV shape for predicting the time-to arrhythmic event was a paraboloidal longitudinal profile, with a relatively wide base. The corresponding LVAS was associated with arrhythmic events in univariate Cox regression (hazard ratio = 2.0 per quartile; 95% confidence interval: 1.3–2.9), in univariate Cox regression with propensity score adjustment, and in three multivariate models; with LV ejection fraction, New York Heart Association Class III/IV (Model 1), implantable cardioverter-defibrillator receipt (Model 2), and cardiac resynchronization therapy (Model 3). Conclusion: Biomarkers of LV shape remodelling in DCM can help to identify the patients at greatest risk of lethal ventricular arrhythmias. Graphical Abstract: