Guan, D., Yao, J., Luo, X. and Gao, H. (2020) Effect of myofibre architecture on ventricular pump function by using a neonatal porcine heart model: from DT-MRI to rule-based methods. Royal Society Open Science, 7(4), 191655. (doi: 10.1098/rsos.191655)
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Abstract
Myofibre architecture is one of the essential components when constructing personalized cardiac models. In this study, we develop a neonatal porcine bi-ventricle model with three different myofibre architectures for the left ventricle (LV). The most realistic one is derived from ex vivo diffusion tensor magnetic resonance imaging, and other two simplifications are based on rule-based methods (RBM): one is regionally dependent by dividing the LV into 17 segments, each with different myofibre angles, and the other is more simplified by assigning a set of myofibre angles across the whole ventricle. Results from different myofibre architectures are compared in terms of cardiac pump function. We show that the model with the most realistic myofibre architecture can produce larger cardiac output, higher ejection fraction and larger apical twist compared with those of the rule-based models under the same pre/after-loads. Our results also reveal that when the cross-fibre contraction is included, the active stress seems to play a dual role: its sheet-normal component enhances the ventricular contraction while its sheet component does the opposite. We further show that by including non-symmetric fibre dispersion using a general structural tensor, even the most simplified rule-based myofibre model can achieve similar pump function as the most realistic one, and cross-fibre contraction components can be determined from this non-symmetric dispersion approach. Thus, our study highlights the importance of including myofibre dispersion in cardiac modelling if RBM are used, especially in personalized models.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Luo, Professor Xiaoyu and Guan, Mr Debao and Gao, Dr Hao |
| Authors: | Guan, D., Yao, J., Luo, X., and Gao, H. |
| College/School: | College of Science and Engineering > School of Mathematics and Statistics > Mathematics |
| Journal Name: | Royal Society Open Science |
| Publisher: | The Royal Society |
| ISSN: | 2054-5703 |
| ISSN (Online): | 2054-5703 |
| Published Online: | 08 April 2020 |
| Copyright Holders: | Copyright © 2020 The Authors |
| First Published: | First published in Royal Society Open Science 7(4):191655 |
| Publisher Policy: | Reproduced under a Creative Commons licence |
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