BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).
OBJECTIVES: The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).
METHODS: Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.
RESULTS: Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.
CONCLUSIONS: Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.
|Journal||JACC. Cardiovascular imaging|
|Early online date||11 Jan 2023|
|Publication status||E-pub ahead of print - 11 Jan 2023|
Bibliographical noteCopyright © 2022 by the American College of Cardiology Foundation. Published by Elsevier. This is an open access article distributed under the terms of the Creative Commons Attribution License CC BY [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Funding Support and Author Disclosures: This work was supported by a National Heart and Lung Institute Foundation grant awarded to Drs Prasad and Jones. This work was also supported by a British Heart Foundation grant (FS/ICRF/21/26019) awarded to Dr Halliday and an Engineering and Physical Sciences Research Council grant (2018/19 DTP - EP/R513064/1) awarded to Mr Zaidi. Dr Leyva is a consultant with and has received research funding from Medtronic Inc, Boston Scientific, Abbott, Microport, and Biotronik. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- computational analysis
- sudden cardiac death
- late gadolinium enhancement cardiac magnetic resonance
- coronary artery disease