Computational Modeling for Cardiac Resynchronization Therapy

Figures

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  Fig. 1. Schematic of the modeling pipeline for biophysical simulations of LBBB and CRT response. Patient data and prior knowledge can be used to create and parameterize the anatomical, electrophysiology, biomechanical, circulatory, or growth models of the heart. The model outputs can be used to infer and integrate information regarding the diseased heart, generate hypotheses, and predict responses to LBBB and CRT. Current state-of-the-art models do not encompass this entire theoretical framework, but rather only aspects of it depending on the availability of data, computational resources, and clinical question of interest

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  Fig. 2. A schematic of a workflow for the generation of patient-specific anatomical model of the heart from medical images. Segmentations of the anatomical image are used to generate patient-specific meshes. Scar segmentations (from contrast-enhanced MR) and fiber information (from rule-based or image-based methods) can then be mapped onto the mesh

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  Fig. 3. A schematic representation of the electrophysiology models is shown. Personalized shape models of the heart and electrical measures, such as the ECG, Electro-anatomical Maps (EAM), or Body Surface Potential Maps (BSPM) are used as inputs into multi-scale electrophysiology models of the heart to simulate the electrical activation times across the ventricles. The model outcomes can be evaluated in terms of clinical measures such as ECG traces and QRS duration

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  Fig. 4. A schematic of representation of the electromechanical workflow is shown. Personalized shape models of the heart, electrophysiology models, and circulatory models are used as inputs into the biomechanical models of the heart which use finite elasticity equations to model dynamic cardiac deformations. Mechano-electric feedback via stretch activated ionic channels feedback into the electrophysiology modeling of the electrical activation time input into the mechanical model simulations. The model outcomes can be evaluated in terms of the mechanical and hemodynamic responses, and potentially the anatomical response (mediated with growth models)

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  Fig. 5. A schematic representation of the CircAdapt model together with the TriSeg and the MultiPatch models as its extensions is given in the orange box. Known physiological adaptation rules are used to adapt geometry parameters with the aim to match clinical measurements for mean systemic pressure and flow given in input to the model. The model gives in output hemodynamic and anatomical response in the form of geometry parameters as a consequence of adaptation, and pressure-volume relationships. When extended to the MultiPatch model, local electrical activation is needed as an additional input to provide information about stress, strain, and work within ventricular walls