Quantifying HiPSC-CM structural organization at scale with deep learning-enhanced SarcGraph.

ABSTRACT: In cardiac cells, structural organization is an important indicator of cell maturity and healthy function. Healthy and mature cardiomyocytes exhibit a highly organized structure, characterized by well-aligned almost crystalline morphology with densely packed and organized sarcomeres. Immature and/or diseased cardiomyocytes typically lack this highly organized structure. Critically, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) offer a valuable model for studying human cardiac cells in a controlled, patient-specific, and minimally invasive manner. However, these cells often exhibit a disorganized and difficult to quantify structure both in their immature form and as disease models. In this work, we extend the SarcGraph computational framework-designed specifically t

SUBMITTER: Mohammadzadeh S 

PROVIDER: S-EPMC12520406 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature