A Novel Strain-based Dynamic Left Ventricle Model for Surgical Planning and Training

Digital twin technology is revolutionizing cardiovascular research by enabling patient-specific cardiac simulations. However, existing models often rely on computationally expensive mechanistic models, limiting their real-time clinical applicability. This study proposes a strain-based left ventricle (LV) digital twin that integrates myocardial deformation data from speckle-tracking echocardiography to achieve computational efficiency while maintaining high-fidelity LV wall motion. The LV wall was regionally divided according to standard echocardiographic views and modeled for longitudinal, circumferential, and radial strain components. Geometric deformations were simulated and animated using patient-derived strain data derived from the literature. Model validation against literature-derived peak systolic strain values demonstrated strong agreement, with minor discrepancies in the basal anteroseptal and apical regions due to anatomical constraints and modeling assumptions. The proposed framework offers a viable alternative for real-time cardiac motion simulation, bridging the gap between physiological fidelity and clinical usability. Future developments will focus on left atrial modeling, paving the way for digital twins that adapt dynamically to patient-specific data for enhanced intraoperative interventional planning and surgical training.