Methodology for patient-specific modeling of atrial fibrosis as a substrate for atrial fibrillation |
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Authors: | Kathleen S McDowell Fijoy Vadakkumpadan Robert Blake Joshua Blauer Gernot Plank Rob S MacLeod Natalia A Trayanova |
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Institution: | 1. The Johns Hopkins University, Department of Biomedical Engineering and Institute for Computational Medicine, Baltimore, MD, USA;2. University of Utah, Comprehensive Arrhythmia Research and Management Center, School of Medicine, Salt Lake City, UT, USA;3. Medical University of Graz, Institute of Biophysics, Graz, Austria |
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Abstract: | Personalized computational cardiac models are emerging as an important tool for studying cardiac arrhythmia mechanisms, and have the potential to become powerful instruments for guiding clinical anti-arrhythmia therapy. In this article, we present the methodology for constructing a patient-specific model of atrial fibrosis as a substrate for atrial fibrillation. The model is constructed from high-resolution late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) images acquired in vivo from a patient suffering from persistent atrial fibrillation, accurately capturing both the patient's atrial geometry and the distribution of the fibrotic regions in the atria. Atrial fiber orientation is estimated using a novel image-based method, and fibrosis is represented in the patient-specific fibrotic regions as incorporating collagenous septa, gap junction remodeling, and myofibroblast proliferation. A proof-of-concept simulation result of reentrant circuits underlying atrial fibrillation in the model of the patient's fibrotic atrium is presented to demonstrate the completion of methodology development. |
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Keywords: | Patient-specific modeling Computational model Atrial fibrillation Atrial fibrosis |
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