Cardiac digital twins at scale from MRI: Open tools and representative models from ~ 55000 UK Biobank participants

作者：Devran Uğurlu, Shuang Qian, Elliot Fairweather, Charlène Mauger, Bram Ruijsink, Laura Dal Toso, Yu Deng, Marina Strocchi, Reza Razavi, Alistair A. Young, Pablo Lamata, Steven Niederer, Martin J. Bishop · 发表于：PLoS ONE · 年份：2025 · DOI：10.1371/journal.pone.0327158 · 被引用次数：11 · 研究领域：Cardiovascular Function and Risk Factors、Cardiac Structural Anomalies and Repair、Tissue Engineering and Regenerative Medicine

A cardiac digital twin is a virtual replica of a patient's heart for screening, diagnosis, prognosis, risk assessment, and treatment planning of cardiovascular diseases. This requires an anatomically accurate patient-specific 3D structural representation of the heart, suitable for electro-mechanical simulations or study of disease mechanisms. However, generation of cardiac digital twins at scale is demanding and there are no public repositories of models across demographic groups. We describe an automatic open-source pipeline for creating patient-specific left and right ventricular meshes from cardiovascular magnetic resonance images, its application to a large cohort of [Formula: see text] participants from UK Biobank, and the construction of the most comprehensive cohort of adult heart models to date, comprising 1423 representative meshes across sex (male, female), body mass index (range: 16-42 kg/m2) and age (range: 49-80 years). Our code is available at https://github.com/cdttk/biv-volumetric-meshing/tree/plos2025, and pre-trained networks, representative volumetric meshes with fibers and UVCs are available at https://doi.org/10.5281/zenodo.15649643.