Precision, prognosis, and clinical performance of rounded and trabecular segmentation of cine cardiovascular magnetic resonance.

ABSTRACT:

Background

Measurements of cardiac size and function drive clinical decisions. Left ventricular (LV) metrics can be derived from cardiac MR images by delineating the blood pool and myocardium, by either drawing a rounded contour to approximate the compacted myocardial border, or by delineating the papillary muscles and trabeculae (trabecular segmentation). There is no consensus as to which is best, particularly in the emergent AI era. We developed machine-learning (ML) approaches for both and compared them for clinically important metrics (error rate, precision, and prognosis).

Methods

Separate ML models were developed for rounded and trabecular segmentation, using U-net models trained on 1923 subjects (mixed pathology, multiple scanners, multiple centers). Blood and myocard

SUBMITTER: Joy G 

PROVIDER: S-EPMC12811440 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature