Non-invasive assessment of patient-specific aortic haemodynamics from four-dimensional flow MRI data
We introduce a parameter estimation framework for automatically and robustly personalizing aortic haemodynamic computations from four-dimensional magnetic resonance imaging data. The framework is based on a reduced-order multiscale fluid–structure interaction blood flow model, and on two calibration...
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Published in | Interface focus Vol. 8; no. 1; p. 20170006 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
The Royal Society
06.02.2018
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Subjects | |
Online Access | Get full text |
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Summary: | We introduce a parameter estimation framework for automatically and robustly personalizing aortic haemodynamic computations from four-dimensional magnetic resonance imaging data. The framework is based on a reduced-order multiscale fluid–structure interaction blood flow model, and on two calibration procedures. First, Windkessel parameters of the outlet boundary conditions are personalized by solving a system of nonlinear equations. Second, the regional mechanical wall properties of the aorta are personalized by employing a nonlinear least-squares minimization method. The two calibration procedures are run sequentially and iteratively until both procedures have converged. The parameter estimation framework was successfully evaluated on 15 datasets from patients with aortic valve disease. On average, only 1.27 ± 0.96 and 7.07 ± 1.44 iterations were required to personalize the outlet boundary conditions and the regional mechanical wall properties, respectively. Overall, the computational model was in close agreement with the clinical measurements used as objectives (pressures, flow rates, cross-sectional areas), with a maximum error of less than 1%. Given its level of automation, robustness and the short execution time (6.2 ± 1.2 min on a standard hardware configuration), the framework is potentially well suited for a clinical setting. |
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Bibliography: | Theme issue ‘The virtual physiological human: translating the VPH to the clinic’ organised by Alfons Hoekstra, Frank Gijsen, Ed van Bavel, Marie Siebes and Liesbet Geris ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 One contribution of 9 to a theme issue ‘The virtual physiological human: translating the VPH to the clinic’. Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.figshare.c.3928315. |
ISSN: | 2042-8898 2042-8901 |
DOI: | 10.1098/rsfs.2017.0006 |