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Li L, Wang Y, Jin P, Yang T, Zhu G, Li Y, Tang J, Liu Y, Yang J. Hemodynamics in the treatment of pseudoaneurysm caused by extreme constriction of aortic arch with coated stent. Front Cardiovasc Med 2024; 11:1363230. [PMID: 39228660 PMCID: PMC11368758 DOI: 10.3389/fcvm.2024.1363230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 06/24/2024] [Indexed: 09/05/2024] Open
Abstract
Objectives To evaluate the changes in distal vascular morphology and hemodynamics in patients with extremely severe aortic coarctation (CoA) after covered palliative (CP) stent dilation with different surgical strategies. Materials and methods Perioperative computed tomography angiography and digital subtraction angiography were utilized to construct three aortic models with varying stenosis rates and one follow-up model in a patient with extremely severe CoA. The models included: an idealized non-stenosed model (A: 0%), a model post initial stent deployment (B: 28%), a model post balloon expansion (C: 39%), and a model 18 months after post-balloon expansion (D: 39%). Consistent boundary conditions were applied to all models, and hemodynamic simulation was conducted using the pure fluid method. Results The narrowest and distal diameter of the stent increased by 34.71% and 59.29%, respectively, from model B to C. Additionally, the distal diameter of the stent increased by -13.80% and +43.68% compared to the descending aorta diameter, respectively. Furthermore, the ellipticity of the maximum cross-section of the aneurysm region in model A to D continued to increase. The oscillatory shear index at the stenosis to the region of the aneurysm were found to be higher in Models A and B, and lower in Models C and D. At the moment of maximum flow velocity, the blood flow distribution in models A and B was more uniform in the widest section of the blood vessels at the distal end of the stenosis, whereas models C and D exhibited disturbed blood flow with more than 2 eddy currents. The time-averaged wall shear stress (TAWSS) decreased in the distal and basal aneurysms, while it significantly increased at the step position. The aneurysmal region exhibited an endothelial cell activation potential value lower than 0.4 Pa-1. Conclusion In patients with extremely severe CoA, it is crucial to ensure that the expanded diameter at both ends of the CP stent does not exceed the native vascular diameter during deployment. Our simulation results demonstrate that overdilation leads to a decrease in the TAWSS above the injured vessel, creating an abnormal hemodynamic environment that may contribute to the development and enlargement of false aneurysms in the early postoperative period. Clinical Trial Registration ClinicalTrials.gov, (NCT02917980).
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Affiliation(s)
- Lanlan Li
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Yiwei Wang
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Ping Jin
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Tingting Yang
- School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Guangyu Zhu
- School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yuxi Li
- Department of Ultrasound Medicine, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Jiayou Tang
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Yang Liu
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Jian Yang
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
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Xie H, Wu H, Wang J, Mendieta JB, Yu H, Xiang Y, Anbananthan H, Zhang J, Zhao H, Zhu Z, Huang Q, Fang R, Zhu C, Li Z. Constrained estimation of intracranial aneurysm surface deformation using 4D-CTA. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 244:107975. [PMID: 38128464 DOI: 10.1016/j.cmpb.2023.107975] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/08/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND AND OBJECTIVE Intracranial aneurysms are relatively common life-threatening diseases, and assessing aneurysm rupture risk and identifying the associated risk factors is essential. Parameters such as the Oscillatory Shear Index, Pressure Loss Coefficient, and Wall Shear Stress are reliable indicators of intracranial aneurysm development and rupture risk, but aneurysm surface irregular pulsation has also received attention in aneurysm rupture risk assessment. METHODS The present paper proposed a new approach to estimate aneurysm surface deformation. This method transforms the estimation of aneurysm surface deformation into a constrained optimization problem, which minimizes the error between the displacement estimated by the model and the sparse data point displacements from the four-dimensional CT angiography (4D-CTA) imaging data. RESULTS The effect of the number of sparse data points on the results has been discussed in both simulation and experimental results, and it shows that the proposed method can accurately estimate the surface deformation of intracranial aneurysms when using sufficient sparse data points. CONCLUSIONS Due to a potential association between aneurysm rupture and surface irregular pulsation, the estimation of aneurysm surface deformation is needed. This paper proposed a method based on 4D-CTA imaging data, offering a novel solution for the estimation of intracranial aneurysm surface deformation.
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Affiliation(s)
- Hujin Xie
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia.
| | - Hao Wu
- School of Biological Science & Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Jiaqiu Wang
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia; School of Engineering, London South Bank University, London, UK
| | - Jessica Benitez Mendieta
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Han Yu
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Yuqiao Xiang
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Haveena Anbananthan
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Jianjian Zhang
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai, China
| | - Huilin Zhao
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai, China
| | - Zhengduo Zhu
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Qiuxiang Huang
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Runxing Fang
- School of Biological Science & Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Chengcheng Zhu
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, United States
| | - Zhiyong Li
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia; Faculty of Sports Science, Ningbo University, Ningbo, Zhejiang 315211, China.
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