Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.

ABSTRACT:

Background

Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and sometimes contraindicated. Thus, in patients with HCM, we aimed to detect LGE on CMR by applying machine learning (ML) algorithm to clinical parameters.

Methods and results

In this trans-Pacific multicenter study of HCM, a ML model was developed to distinguish the presence or absence of LGE on CMR by ridge classification method using 22 clinical parameters including 9 echocardiographic data. Among 742 patients in this cohort, the ML model was constructed in 2 institutions in the United States (training set, n = 554) and tested using d

SUBMITTER: Akita K 

PROVIDER: S-EPMC11725445 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature