2026 Projects
2026 Project: Asia
ASEAN-HeartTwin: Validating Cardiac Digital Twin Models for Sudden Cardiac Death Risk Prediction of Hypertrophic Cardiomyopathy Across Diverse Healthcare Systems
Project Team
- Lei Li, (lead) National University of Singapore
- Ching Hui Sia, National University Heart Centre Singapore
- Pham Hieu, College of Engineering and Computer Science, VinUniversity
- Marni Azira Markom, Universiti Malaysia Perlis
Location
Singapore, Vietnam, Malaysia
Executive Summary
Cardiovascular disease remains the leading cause of mortality across ASEAN countries, where access to advanced diagnostic imaging and personalized risk prediction tools remains highly unequal. Sudden cardiac death (SCD) accounts for a significant portion of this burden, yet risk stratification methods are often based on data and models developed in Western populations, with limited validation in Southeast Asia.
The ASEAN-HeartTwin project aims to establish and validate a cardiac digital twin (CDT) framework for SCD risk prediction across Singapore, Vietnam, and Malaysia, using multi-source clinical and imaging data to ensure cross-regional generalizability and fairness. We plan to use hypertrophic cardiomyopathy (HCM) as a typical example to predict its SCD risk. By integrating patient-specific anatomical and electrophysiological characteristics into a validated digital twin model, this project will lay the foundation for equitable cardiac risk prediction of HCM in ASEAN countries. The proposed work aligns with MICCAI’s focus on geographical health equity, by addressing regional disparities in healthcare technology and demonstrating scalable, data-driven solutions that are both clinically relevant and resource-sensitive.