Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise
SCIE
SCOPUS
- Title
- Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise
- Authors
- Ha, H.; Kang, H.; Huh, H.; Choi, W.; Koo, H.J.; Kwon, J.; Park, K.J.; Cho, Y.C.; Lee, S.J.; Kim, N.; Yang, D.H.
- Date Issued
- 2019-04
- Publisher
- IOS Press
- Abstract
- This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5-3.0mm and noise levels of 0.1-50cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2-4years old) had the errors of0.057,+/- 0.145 and +/- 0.210 at the voxel sizes of 1.0mm, 2.0mm, and 3.0mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to +/- 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/100114
- DOI
- 10.1007/s12650-018-0536-9
- ISSN
- 1343-8875
- Article Type
- Article
- Citation
- Journal of Visualization, vol. 22, no. 2, page. 245 - 257, 2019-04
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- There are no files associated with this item.
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