Electrophysiological Characterization of Subclinical and Overt Hypertrophic Cardiomyopathy by Magnetic Resonance Imaging-Guided Electrocardiography
- PMID: 38385929
- PMCID: PMC10945386
- DOI: 10.1016/j.jacc.2024.01.006
Electrophysiological Characterization of Subclinical and Overt Hypertrophic Cardiomyopathy by Magnetic Resonance Imaging-Guided Electrocardiography
Abstract
Background: Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)-guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties.
Objectives: The purpose of this study was to establish whether in subclinical HCM (genotype [G]+ left ventricular hypertrophy [LVH]-), ECGI detects early EP abnormality, and in overt HCM, whether the EP substrate relates to genetic status (G+/G-LVH+) and structural phenotype.
Methods: This was a prospective 211-participant CMR-ECGI multicenter study of 70 G+LVH-, 104 LVH+ (51 G+/53 G-), and 37 healthy volunteers (HVs). Local activation time (AT), corrected repolarization time, corrected activation-recovery interval, spatial gradients (GAT/GRTc), and signal fractionation were derived from 1,000 epicardial sites per participant. Maximal wall thickness and scar burden were derived from CMR. A support vector machine was built to discriminate G+LVH- from HV and low-risk HCM from those with intermediate/high-risk score or nonsustained ventricular tachycardia.
Results: Compared with HV, subclinical HCM showed mean AT prolongation (P = 0.008) even with normal 12-lead electrocardiograms (ECGs) (P = 0.009), and repolarization was more spatially heterogenous (GRTc: P = 0.005) (23% had normal ECGs). Corrected activation-recovery interval was prolonged in overt vs subclinical HCM (P < 0.001). Mean AT was associated with maximal wall thickness; spatial conduction heterogeneity (GAT) and fractionation were associated with scar (all P < 0.05), and G+LVH+ had more fractionation than G-LVH+ (P = 0.002). The support vector machine discriminated subclinical HCM from HV (10-fold cross-validation accuracy 80% [95% CI: 73%-85%]) and identified patients at higher risk of sudden cardiac death (accuracy 82% [95% CI: 78%-86%]).
Conclusions: In the absence of LVH or 12-lead ECG abnormalities, HCM sarcomere gene mutation carriers express an aberrant EP phenotype detected by ECGI. In overt HCM, abnormalities occur more severely with adverse structural change and positive genetic status.
Keywords: ECG imaging; cardiac magnetic resonance imaging; electrophysiology; hypertrophic cardiomyopathy.
Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
Funding Support and Author Disclosures Drs Joy, Webber, Guger, Orini, and Captur, and Prof Lambiase are coinventors of the patented capturECGI vest. Dr Joy is funded by a British Heart Foundation Clinical Research Training Fellowship (FS/CRTF/21/2469). Dr Lopes is supported by a Medical Research Council UK Research and Innovation Clinical Academic Research Partnership award (MR/T005181/1). Dr Dall’Armellina has received funding from a BHF Intermediate Clinical Research Fellowship (FS/13/71/30378). Prof Manisty receives funding directly and indirectly from the National Institutes of Health Research Biomedical Research Centres at University College London Hospitals and Barts Health NHS Trusts. Prof Rudy is the inventor of ECGI and receives royalties from Case Western Reserve University and Washington University in St Louis. Prof Lambiase is funded from University College London/University College London Hospitals Biomedicine National Institute for Health and Care Research, Barts Biomedical Research Centre; and has received educational grants from Abbott and Boston Scientific. Prof Moon receives funding directly and indirectly from the National Institutes of Health and Care Research Biomedical Research Centres at University College London Hospitals and Barts Health NHS trusts; is the chief executive officer of MyCardium AI Ltd; and has served on advisory boards for Sanofi and Genzyme. Dr Captur is supported by the SCMR Seed Grant Programme, the British Heart Foundation special project grant (SP/20/2/34841), the National Institute for Health and Care Research innovation for innovation iFAST grant, and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
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