Precision medicine aims to tailor therapeutic strategies to individual patients by continuously integrating anatomical and physiological data. Digital twins are personalized computational models that reflect a subject's cardiac structure and function. This study proposes the development of a digital twin of the rabbit heart, leveraging the Langendorff perfused heart model, which enables ex vivo analysis of cardiac function. Given the physiological similarities between rabbit and human hearts, this model is widely used in preclinical studies of novel therapies.
The proposed pipeline includes magnetic resonance imaging (MRI) acquisition, segmentation of cardiac structures, and reconstruction of a volumetric anatomical model. A computational model is then generated, incorporating myocardial fiber orientations assigned by the Laplace-Dirichlet ruled based algorithm. Electrophysiological simulations are performed using MonoAlg3D, and ECG signals are computed and compared with experimental recordings.
The simulated ECG closely resembled the experimentally acquired waveform in terms of general morphology. Differences in amplitude and the absence of the P wave were observed and attributed to simplified conductivity parameters for fibrotic tissue, cell homogeneity and the omission of atrial structures in the current model. Despite these limitations, the digital twin was able to replicate key features of ventricular electrophysiology with high fidelity.
This work demonstrates the feasibility of constructing accurate rabbit heart digital twins using data from Langendorff preparations. Such models hold significant promise for in silico drug testing and therapy optimization while reducing the number of animal experiments required.