基于5.5万英国生物样本库数据，构建了大规模心脏数字孪生模型库。
Cardiac Digital Twins at Scale from MRI: Open Tools and Representative Models from ~55000 UK Biobank Participants
- 自动从MRI生成左右心室三维网格，支持电-机械模拟。
- 涵盖1423例代表性模型，覆盖年龄、性别、体重指数全范围。
- 开源工具链+预训练模型，助力心血管疾病研究与个性化诊疗。
心脏数字孪生是患者心脏的虚拟复制品，可用于心血管疾病的筛查、诊断、预后、风险评估和治疗规划，需具备解剖精确的患者特异性三维结构表示，适用于电-机械仿真或疾病机制研究。然而，大规模生成心脏数字孪生仍具挑战性，且缺乏跨人群的公开模型库。本文描述了一种自动化的开源流程，可从心血管磁共振图像中生成患者特异性左右心室网格，并将其应用于约55000名英国生物样本库参与者。构建了迄今为止最全面的成人心脏模型队列，包含1423个代表性网格模型，覆盖性别（男、女）、体质量指数（16–42 kg/m²）和年龄（49–80岁）。代码已公开于https://github.com/cdttk/biv-volumetric-meshing/tree/plos2025，预训练网络及带有纤维和参数化坐标（UVCs）的代表性体积网格将很快发布。
原文摘要 · Abstract (English)
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.
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