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

Area of Science:

• Cardiovascular Research
• Medical Imaging
• Computational Biology

Background:

• Digital twin technology offers patient-specific cardiac simulations, but mechanistic models are computationally intensive for clinical use.
• Existing digital twin models face limitations in real-time applicability due to high computational costs.
• There is a need for efficient yet high-fidelity cardiac models in clinical settings.

Purpose of the Study:

• To develop a computationally efficient, strain-based digital twin of the left ventricle (LV).
• To integrate myocardial deformation data from speckle-tracking echocardiography for high-fidelity LV wall motion simulation.
• To enable real-time cardiac motion simulation for improved clinical usability.

Main Methods:

• A strain-based digital twin framework was developed for the left ventricle (LV).
• Myocardial deformation data (longitudinal, circumferential, radial strain) from speckle-tracking echocardiography was integrated.
• Patient-derived strain data from literature was used to simulate and animate geometric deformations.

Main Results:

• The digital twin demonstrated strong agreement with literature-derived peak systolic strain values.
• Minor discrepancies were observed in basal anteroseptal and apical regions due to anatomical constraints.
• The model successfully simulated and animated LV wall motion using patient-specific strain data.

Conclusions:

• The proposed strain-based digital twin offers a computationally efficient alternative for real-time cardiac motion simulation.
• This framework bridges the gap between physiological fidelity and clinical usability in cardiovascular research.
• Future work includes left atrial modeling for dynamic, patient-specific digital twins for surgical planning and training.