|
1
|
Wang T, Xiang Y, Wang J, Gu J, Yang L, Ma D, Zhu H, Liu T, Li C, Zhang Q, Han J, Ding D, Wang W, Li Q, Wan H, Qi X. A Multi-Scale Computational Model of the Hepatic Circulation Applied to Predict the Portal Pressure After Transjugular Intrahepatic Portosystemic Shunt (TIPS). INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2025; 41:e3908. [PMID: 39853965 DOI: 10.1002/cnm.3908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2024] [Revised: 12/17/2024] [Accepted: 12/29/2024] [Indexed: 01/26/2025]
Abstract
Transjugular intrahepatic portosystemic shunt (TIPS) is a widely used surgery for portal hypertension. In clinical practice, the diameter of the stent forming a shunt is usually selected empirically, which will influence the postoperative portal pressure. Clinical studies found that inappropriate portal pressure after TIPS is responsible for poor prognosis; however, there is no scheme to predict postoperative portal pressure. Therefore, this study aims to develop a computational model applied to predict the portal pressure after TIPS ahead of the surgery. For this purpose, a patient-specific 0-3-D multi-scale computational model of the hepatic circulation was developed based on preoperative clinical data. The model was validated using the prospectively collected clinical data of 18 patients. Besides, the model of a representative patient was employed in the numerical experiment to further investigate the influences of multiple pathophysiological and surgical factors. Results showed that the difference between the simulated and in vivo measured portal pressures after TIPS was -1.37 ± 3.51 mmHg, and the simulated results were significantly correlated with the in vivo measured results (r = 0.93, p < 0.0001). Numerical experiment revealed that the estimated model parameters and the severity of possible inherent portosystemic collaterals slightly influenced the simulated results, while the shunt diameter considerably influenced the results. In particular, the existence of catheter for pressure measurement would markedly influence postoperative portal pressure. These findings demonstrated that this computational model is a promising tool for predicting postoperative portal pressure, which would guide the selection of stent diameter and promote individualization and precision of TIPS.
Collapse
Affiliation(s)
- Tianqi Wang
- School of Gongli Hospital Medical Technology, University of Shanghai for Science and Technology, Shanghai, China
- School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Yi Xiang
- Liver Disease Center of Integrated Traditional Chinese and Western Medicine, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University; State Key Laboratory of Digital Medical Engineering, Nanjing, China
| | - Jitao Wang
- Xingtai Key Laboratory of Precision Medicine for Liver Cirrhosis and Portal Hypertension, Xingtai People's Hospital, Hebei Medical University, Xingtai, China
- School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Jiaqi Gu
- Liver Disease Center of Integrated Traditional Chinese and Western Medicine, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University; State Key Laboratory of Digital Medical Engineering, Nanjing, China
| | - Ling Yang
- Liver Disease Center of Integrated Traditional Chinese and Western Medicine, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China
- Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University; State Key Laboratory of Digital Medical Engineering, Nanjing, China
| | - Deqiang Ma
- Department of Infectious Diseases, Hubei Provincial Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - He Zhu
- First Department of Intervention, The Sixth People's Hospital of Shenyang, Shenyang, China
| | - Tianyu Liu
- Department of Gastroenterology, Suining Central Hospital, Suining, China
| | - Chunlong Li
- Department of Interventional Radiology, The Six Affiliated Hospital of Nantong University (Yancheng Third People's Hospital), Yancheng, China
| | - Qi Zhang
- Department of Interventional and Vascular Surgery, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Jiahao Han
- Department of Ultrasound Medicine, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Deping Ding
- Department of Infectious Diseases, Hubei Provincial Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Wei Wang
- First Department of Intervention, The Sixth People's Hospital of Shenyang, Shenyang, China
| | - Qianlong Li
- Department of Gastroenterology, Suining Central Hospital, Suining, China
| | - Haoguang Wan
- Department of Interventional Radiology, The Six Affiliated Hospital of Nantong University (Yancheng Third People's Hospital), Yancheng, China
| | - Xiaolong Qi
- Hebei Provincial Key Laboratory of Portal Hypertension and Cirrhosis, Xingtai People's Hospital, Xingtai, China; Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| |
Collapse
|