Cardiac Digital Twins at Scale from MRI: Open Tools and Representative Models from ~55000 UK Biobank Participants

TL;DR

This paper presents an open-source pipeline for creating detailed, patient-specific cardiac models from MRI data, applied to a large UK Biobank cohort, enabling scalable and diverse digital twin generation.

Contribution

It introduces a fully automated, open-source method for generating comprehensive cardiac meshes from MRI, applied to the largest diverse cohort to date.

Findings

Created 1423 representative heart models across demographic groups

Developed an open-source pipeline for scalable cardiac mesh generation

Provided publicly available code and plans for data sharing

Abstract

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 ~55000 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/m$^2$) 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 will be made available soon.