TY - JOUR
T1 - Cardiac digital twins at scale from MRI
T2 - Open tools and representative models from ∼ 55000 UK Biobank participants
AU - Ugurlu, Devran
AU - Qian, Shuang
AU - Fairweather, Elliot
AU - Mauger, Charlene
AU - Ruijsink, Bram
AU - Toso, Laura Dal
AU - Deng, Yu
AU - Strocchi, Marina
AU - Razavi, Reza
AU - Young, Alistair
AU - Lamata, Pablo
AU - Niederer, Steven
AU - Bishop, Martin
N1 - Copyright: © 2025 Ugurlu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2025/7
Y1 - 2025/7
N2 - 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 ∼ 55k 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.
AB - 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 ∼ 55k 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.
KW - Humans
KW - Male
KW - Middle Aged
KW - Female
KW - Aged
KW - Magnetic Resonance Imaging/methods
KW - United Kingdom
KW - Biological Specimen Banks
KW - Aged, 80 and over
KW - Heart/diagnostic imaging
KW - Heart Ventricles/diagnostic imaging
KW - Models, Cardiovascular
KW - Imaging, Three-Dimensional
KW - UK Biobank
UR - https://www.scopus.com/pages/publications/105010652845
U2 - 10.1371/journal.pone.0327158
DO - 10.1371/journal.pone.0327158
M3 - Article
C2 - 40663525
AN - SCOPUS:105010652845
SN - 1932-6203
VL - 20
JO - PLoS ONE
JF - PLoS ONE
IS - 7
M1 - e0327158
ER -