Leveraging calcium score CT radiomics for heart failure risk prediction.

ABSTRACT: Studies have used extensive clinical information to predict time-to-heart failure (HF) in patients with and without diabetes mellitus (DM). We aimed to determine a screening method using only computed tomography calcium scoring (CTCS) to assess HF risk. We analyzed CTCS scans from 1,998 patients (336 with type 2 diabetes) from a no-charge coronary artery calcium score registry (CLARIFY Study, Clinicaltrials.gov NCT04075162). We used deep learning to segment epicardial adipose tissue (EAT) and engineered radiomic features of calcifications ("calcium-omics") and EAT ("fat-omics"). We developed models incorporating radiomics to predict risk of incident HF in patients with and without type 2 diabetes. At a median follow-up of 1.7 years, 5% had incident HF. In the overall cohort, fat-omics (C-i

SUBMITTER: Singh P 

PROVIDER: S-EPMC11541497 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature