Personalized multiscale modeling of left atrial mechanics and blood flow

We present a personalized multiscale mechanics model of the left atrium (LA) to simulate its deformation throughout the cardiac cycle and drive blood flow. Our patient data-driven model tightly integrates 3D structural mechanics of the LA myocardium, incorporating both passive and active components, with a 0D closed-loop lumped parameter network (LPN)-based circulatory system model. A finite element (FE) model of LA tissue is constructed from the patient’s images, assuming uniform thickness and employing rule-based fiber directions. We then adopted a multi-step personalization approach, in which the LPN parameters with a surrogate LA model are first optimized to match cuff-based blood pressures and cardiac lumen volumes derived from time-resolved 3D gated computed tomography angiography (CTA) images. The surrogate LA pressure during passive expansion is used to estimate myocardial passive mechanics parameters and the reference unloaded configuration using an inverse finite element analysis (iFEA) framework. Finally, a robust multiscale coupling is applied between the iFEA-optimized FE model and the tuned 0D LPN model to characterize LA contraction. This effectively captures the physiological LA pressure-volume curve and reasonably aligns with the image-based cavity volumes and deformation. We then imposed the resulting simulation-predicted deformation as a moving-wall boundary condition to model atrial hemodynamics. We analyzed the model sensitivities to various simplifications to demonstrate its robustness and versatility and discussed potential future improvements. Overall, this comprehensive digital twinning platform could be applied to study LA biomechanics in health and disease and assist in devising personalized treatment plans.