Residential College | false |
Status | 已發表Published |
Towards a Non-invasive Diagnosis of Portal Hypertension Based on an Eulerian CFD Model with Diffuse Boundary Conditions | |
Ren, Lixin1,3; Wan, Shang2; Wei, Yi2; He, Xiaowei1,3; Song, Bin2; Wu, Enhua1,3,4 | |
2021 | |
Conference Name | 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 |
Source Publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume | 12905 LNCS |
Pages | 107-116 |
Conference Date | SEP 27-OCT 01, 2021 |
Conference Place | Virtual, Online |
Author of Source | de Bruijne M., Cattin P.C., Cotin S., Padoy N., Speidel S., Zheng Y., Essert C. |
Publication Place | BERLIN, GERMANY |
Publisher | Springer Science and Business Media Deutschland GmbH |
Abstract | Portal hypertension is one of the major complications in patients with chronic liver diseases (CLD) which induces the increase in portal vein gradient pressure. At advanced stage, it can cause the esophageal varices and variceal hemorrhage. Therefore, portal hypertension has been the leading cause of mortality in CLD patients. To diagnose portal hypertension, the invasive hepatic venous pressure gradient (HVPG) measurement is still the only validated technique to accurately evaluate changes in portal pressure and regarded as the standard reference. However, it entails the limitation of invasive procedure and have the risk of further bleeding and inflammation. In this paper we propose an Eulerian computational fluid dynamics (CFD) model to facilitate hemodynamics analysis. To enable consistent simulation results with different boundary conditions, a diffuse boundary handling technique was proposed to impose smooth boundary conditions for both the pressure and velocity fields. We also propose a computational workflow for quantifying patient-specific hemodynamics in portal vein systems non-invasively. The simulation is performed on patient-specific PV models reconstructed from CT angiographic images. Experiments show that pressure changes in the PV of patients with portal hypertension due to blockage of the RPV are significantly lower than that of normal subjects. |
Keyword | Diffuse Boundary Conditions Pressure Change Non-invasive Diagnosis Portal Hypertension Cfd |
DOI | 10.1007/978-3-030-87240-3_11 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science ; Engineering ; Medical Informatics ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Engineering, Biomedical ; Medical Informatics ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging |
WOS ID | WOS:000712025900011 |
Scopus ID | 2-s2.0-85116448616 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | Faculty of Science and Technology |
Corresponding Author | He, Xiaowei; Song, Bin |
Affiliation | 1.SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China 2.Department of Radiology, West China Hospital, Sichuan University, Chengdu, China 3.University of Chinese Academy of Sciences, Beijing, China 4.Faculty of Science and Technology, University of Macau, Macao, Macao |
Recommended Citation GB/T 7714 | Ren, Lixin,Wan, Shang,Wei, Yi,et al. Towards a Non-invasive Diagnosis of Portal Hypertension Based on an Eulerian CFD Model with Diffuse Boundary Conditions[C]. de Bruijne M., Cattin P.C., Cotin S., Padoy N., Speidel S., Zheng Y., Essert C., BERLIN, GERMANY:Springer Science and Business Media Deutschland GmbH, 2021, 107-116. |
APA | Ren, Lixin., Wan, Shang., Wei, Yi., He, Xiaowei., Song, Bin., & Wu, Enhua (2021). Towards a Non-invasive Diagnosis of Portal Hypertension Based on an Eulerian CFD Model with Diffuse Boundary Conditions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12905 LNCS, 107-116. |
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