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A Visual LGE Extent Cutoff for Mortality Risk Stratification in Ischemic Cardiomyopathy
Alexandre Unger1, Jérôme Garot2, Suzanne Duhamel3
1Department of Cardiology, Hôpital universitaire de Bruxelles, Hôpital Erasme, Université libre de Bruxelles, Brussels, Belgium; Université Paris Cité, Department of Cardiology, University Hospital of Lariboisiere, (Assistance Publique des Hôpitaux de Paris, AP-HP), 75010, Paris, France; Inserm MASCOT - UMRS 942, University Hospital of Lariboisiere, 75010, Paris, France; MIRACL.ai laboratory, Multimodality Imaging for Research and Analysis Core Laboratory and Artificial Intelligence, University Hospital of Lariboisiere (AP-HP), 75010, Paris, France; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 91300, Massy, France.
Background:
Late gadolinium enhancement (LGE) extent has been linked to adverse outcomes in ischemic cardiomyopathy (ICM). While quantitative methods of LGE assessment are widely accepted, semi-quantitative methods remain debated but still hold value. This study aimed to determine an optimal LGE segments cutoff for ICM patients with left ventricular ejection fraction (LVEF) <50% in a large bicentric cohort.
Methods:
This bicentric retrospective French study included 3,591 patients with ICM (defined by prior myocardial infarction and/or coronary revascularization), LVEF <50%, and ischemic-LGE on cardiovascular magnetic resonance performed between 2008 and 2022. Ischemic LGE extent was assessed semi-quantitatively using the 17-segment model. An optimal cutoff for LGE extent was derived in the derivation cohort (Center 1, N=2,900) using a conditional inference tree and externally validated in an independent cohort (Center 2, N=691). The primary outcome was all-cause mortality. Prognostic performance was compared between a conventional model based on LVEF ≤35% alone and a combined model integrating LVEF ≤35% with the newly identified ischemic-LGE cutoff. Model discrimination and reclassification were assessed using Harrell's C-index, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI).
Results:
During a median follow-up of 9 years, 549 patients (15.3%) died. The optimal cutoff of visual LGE extent to predict mortality was 5 segments. Patients with high ischemic LGE extent (>5 segments) had a markedly increased risk of all-cause mortality compared with those with ≤5 segments (adjusted hazard ratio, 3.8; 95% CI: 3.0-4.8; p<0.001). Survival discrimination according to this cutoff was consistent across derivation and validation cohorts. Compared with the conventional LVEF ≤35% model alone, the combined model integrating the >5 ischemic-LGE segment cutoff significantly improved risk discrimination and patient reclassification (ΔC-index: +16%; continuous NRI: +36%; IDI: +4%; all p<0.001).
Conclusion:
In patients with ICM, reduced LVEF (<50%), and detectable ischemic LGE, a visually assessed segment-based cutoff of >5 ischemic-LGE segments was independently associated with all-cause mortality and validated in an independent second-center cohort. This pragmatic, software-independent assessment may complement conventional risk stratification, although prospective studies are required before integration into clinical decision-making.