View : 508 Download: 52

Prediction of rupture risk in cerebral aneurysms by comparing clinical cases with fluid-structure interaction analyses

Title
Prediction of rupture risk in cerebral aneurysms by comparing clinical cases with fluid-structure interaction analyses
Authors
Cho, Kwang-ChunYang, HyeondongKim, Jung-JaeOh, Je HoonKim, Yong Bae
Ewha Authors
김정재
SCOPUS Author ID
김정재scopus
Issue Date
2020
Journal Title
SCIENTIFIC REPORTS
ISSN
2045-2322JCR Link
Citation
SCIENTIFIC REPORTS vol. 10, no. 1
Publisher
NATURE RESEARCH
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Cerebral aneurysms should be treated on the basis of accurate rupture risk prediction. Nowadays, the rupture risk in aneurysms has been estimated using hemodynamic parameters. In this paper, we suggest a new way to predict the rupture risks in cerebral aneurysms by using fluid-structure interaction (FSI) analysis for better decision-making regarding treatment. A patient-specific model was constructed using digital subtraction angiography of 51 cerebral aneurysms. For each model, a thin-walled area (TWA) was first predicted using computational fluid dynamics (CFD), and then the highest equivalent strain in the TWA was calculated with FSI by varying wall thicknesses and mechanical properties. A critical curve was made from 16 FSI results for each patient-specific model to estimate the rupture risk. On average, the equivalent strains of the ruptured aneurysms were higher than those of the unruptured aneurysms. Furthermore, the patterns of critical curves between unruptured and ruptured aneurysms were clearly distinguishable. From the rupture risk evaluation based on the cut-off value, 24 of the 27 unruptured aneurysms and 15 of the 24 ruptured aneurysms were matched with actual-clinical setting cases. The critical curve proposed in the present study could be an effective tool for the prediction of the rupture risk of aneurysm.
DOI
10.1038/s41598-020-75362-5
Appears in Collections:
의료원 > 의료원 > Journal papers
Files in This Item:
s41598-020-75362-5.pdf(1.52 MB) Download
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

BROWSE