Digital Twin Frameworks for Treatment Planning in Congenital Heart Disease

This review summarizes the current state-of-the-art in cardiovascular digital twins and discusses their potential to improve treatment planning for congenital heart disease (CHD). We provide an overview of the digital twin workflow, from medical images to virtual procedures and simulations, and review representative applications in pulmonary vascular disease, single-ventricle treatment planning, and electrophysiological interventions. Advances in computational modeling, high-performance computing, and machine learning have enabled the development of cardiovascular digital twins that reproduce cardiovascular biomechanics and physiology with increasing accuracy and on clinically relevant timescales. Examples of current applications include stenting procedures for pulmonary vascular disease, evaluation of Fontan conduit configurations, and optimization of electrophysiological interventions. Although clinical translation remains in its early stages, continued technological advances and clinical validation position digital twins as a promising tool for personalized CHD care.