Key result
Automated image registration successfully maps patient-specific atrial fibers with simulations comparable to manual modeling.
Why the study?
Appropriate local fiber architecture is required for patient-specific electromechanical simulation, but reliably measuring in vivo fiber directions in human atria is not yet possible.
An automated image registration method successfully maps atrial fiber orientations to patient-specific geometries, enabling detailed computational modeling of cardiac electromechanics.
May facilitate scalable patient-specific atrial modeling; extends computational tools while leaving clinical translation open.
Knowledge of appropriate local fiber architecture is necessary to simulate patient-specific electromechanics in the human heart. However, it is not yet possible to reliably measure in vivo fiber directions especially in human atria. Thus, we present a method that defines the fiber architecture in arbitrarily shaped atria using image registration and reorientation methods based on atlas atria with fibers predefined from detailed histological observations. Thereby, it is possible to generate detailed fiber families in every new patient-specific geometry in an automated, time-efficient process. We demonstrate the good performance of the image registration and fiber definition on 10 differently shaped human atria. Additionally, we show that characteristics of the electrophysiological activation pattern that appear in the atlas atria also appear in the patients' atria. We arrive to analogous conclusions for coupled electro-mechano-hemodynamical computations.
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Hoermann et al. (2019) studied Atrial arrhythmia / Patient-specific electromechanical modeling (n=10). Automated image registration and fiber reorientation method vs. Manually defined fiber orientation (in validation models) was evaluated on Electrophysiological activation pattern and mechanical contraction (computational validation). An automated image registration method successfully mapped predefined atrial fiber architectures onto 10 patient-specific geometries, producing physiologically reasonable electromechanical simulations comparable to manually defined fiber models.
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