Abstract
Atrial fibrillation (AF) frequently accompanies heart failure (HF), however, the causal mechanism underlying their atrial electrophysiological substrates remains unclear. In the present study, we evaluated the effects of abnormal anatomical characteristics on the electrophysiology of rabbit atria with HF. Micro-CT images from adult New Zealand white rabbit hearts (n = 4 HF and n = 4 control) were acquired. Novel imaging methods were used to reconstruct atrial myofiber architecture at a high resolution of 21 µm3/voxel for quantitative analysis of the structural remodelling. Effects of this structural remodelling on the vulnerability to atrial re-entrant waves was analysed using computer simulation. Reconstructed data showed increased chamber lumen and an uneven reduction in wall thickness across the appendages in HF. Anatomically, myofibers in epicardial walls of the appendages were identified to be circumferential, perpendicular to the pectinate muscles (PMs). The relative ratio of average PM thickness to the atrial wall was larger in HF vs. control (right atrial appendages: 3.5 versus 2.7 and left atrial appendages: 4.4 versus 3.7, p < 0.001). Furthermore, the uncoupled myofiber orientation between the PMs and atrial wall was verified using confocal microscopy at a spatial resolution of 0.2 µm3. Computer simulations suggested (1) uncoupled myofiber orientation of the PMs and the atrial wall may increase the vulnerability to AF; and (2) decreased atrial thickness and dilated chambers may amplify the unstable substrates leading to re-entry formation in HF. Our ex-vivo to in-silico results demonstrate that uncoupled myofiber orientation in the atria is an important component of the structural remodelling, facilitating the development and maintenance of AF in HF.
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Agrawal, S. et al. (2024). Inherent Atrial Fibrillation Vulnerability in the Appendages Exacerbated in Heart Failure. In: Camara, O., et al. Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers. STACOM 2023. Lecture Notes in Computer Science, vol 14507. Springer, Cham. https://doi.org/10.1007/978-3-031-52448-6_21
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DOI: https://doi.org/10.1007/978-3-031-52448-6_21
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