Colebank, M. J., Paun, L. M., Qureshi, M. U., Chesler, N., Husmeier, D. , Olufsen, M. S. and Ellwein Fix, L. (2019) Influence of image segmentation on one-dimensional fluid dynamics predictions in the mouse pulmonary arteries. Journal of the Royal Society: Interface, 16, 20190284. (doi: 10.1098/rsif.2019.0284)
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195566.pdf - Accepted Version 2MB |
Abstract
Computational fluid dynamics (CFD) models are emerging tools for assisting in diagnostic assessment of cardiovascular disease. Recent advances in image segmentation have made subject-specific modelling of the cardiovascular system a feasible task, which is particularly important in the case of pulmonary hypertension, requiring a combination of invasive and non-invasive procedures for diagnosis. Uncertainty in image segmentation propagates to CFD model predictions, making the quantification of segmentation-induced uncertainty crucial for subject-specific models. This study quantifies the variability of one-dimensional CFD predictions by propagating the uncertainty of network geometry and connectivity to blood pressure and flow predictions. We analyse multiple segmentations of a single, excised mouse lung using different pre-segmentation parameters. A custom algorithm extracts vessel length, vessel radii and network connectivity for each segmented pulmonary network. Probability density functions are computed for vessel radius and length and then sampled to propagate uncertainties to haemodynamic predictions in a fixed network. In addition, we compute the uncertainty of model predictions to changes in network size and connectivity. Results show that variation in network connectivity is a larger contributor to haemodynamic uncertainty than vessel radius and length.
| Item Type: | Articles |
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| Additional Information: | This work was supported by the NSF-DMS (grant nos 1246991 and 1615820), the EPSRC (grant no. EP/N014642/1), the Royal Society of Edinburgh (grant no. 62335), the NIH (grant no. R01 HL-086939) and the American Heart Foundation (grant no. 19PRE34380459). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Paun, Dr Mihaela and Husmeier, Professor Dirk and Qureshi, Mr Umar |
| Authors: | Colebank, M. J., Paun, L. M., Qureshi, M. U., Chesler, N., Husmeier, D., Olufsen, M. S., and Ellwein Fix, L. |
| College/School: | College of Science and Engineering > School of Mathematics and Statistics College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Journal of the Royal Society: Interface |
| Publisher: | The Royal Society |
| ISSN: | 1742-5689 |
| ISSN (Online): | 1742-5662 |
| Copyright Holders: | Copyright © 2019 The Authors |
| First Published: | First published in Journal of the Royal Society: Interface 16:20190284 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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