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author:

Zheng, R. (Zheng, R..) [1] (Scholars:郑荣业) | Zhang, S. (Zhang, S..) [2] | Zhu, C. (Zhu, C..) [3] | Zhang, C. (Zhang, C..) [4] | Hong, W. (Hong, W..) [5]

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Abstract:

Background: Anatomical variations of the circle of Willis (CoW) are closely associated with the occurrence of intracranial aneurysms (IAs). However, the impact of anatomical variations on the rupture risk of IAs remains unclear. The purpose of this study was to explore the effect of artery absence on the internal flow and rupture risk of IAs. Methods: A one-dimensional (1D) solver was combined with a 3-dimensional (3D) fluid-structure interaction (FSI) model to effectively quantify the hemodynamic characteristics inside IA under artery absence. Results: The 1D results showed that the absence of anterior cerebral artery A1 segment (ACA-A1) or posterior cerebral artery P1 segment (PCA-P1) will trigger a compensatory blood flow effect, leading to significant blood flow variations of the anterior communicating artery (ACoA) and internal carotid artery (ICA). By FSI calculation, in the absence of ACA-A1, the maximum wall shear stress (WSS) within the ACoA aneurysm increased by 103% or more compared to the complete CoW due to blood inflow jet. In addition, WSS increased by 45% and 12% in the contralateral ICA and posterior communicating artery (PCoA) aneurysm respectively, whereas it decreased by 33% and 35% in the ipsilateral ICA and PCoA aneurysm, respectively. The absence of PCA-P1 had a less significant impact on the global blood flow of the CoW compared to the absence of ACA-A1, but it still led to an increase in WSS within the ipsilateral ICA and PCoA aneurysms (25% and 22%, respectively). Conclusions: The absence of ACA-A1 or PCA-P1 may serve as an IA rupture risk factor. If ACA-A1 or PCA-P1 absence is identified clinically alongside an aneurysm, proactive treatment strategies are advised. © AME Publishing Company.

Keyword:

anatomical variations circle of Willis (CoW) fluid-structure interaction (FSI) Intracranial aneurysm (IA)

Community:

  • [ 1 ] [Zheng R.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Zheng R.]Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China
  • [ 3 ] [Zhang S.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [Zhu C.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 5 ] [Zhang C.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 6 ] [Hong W.]Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China

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Source :

Quantitative Imaging in Medicine and Surgery

ISSN: 2223-4292

Year: 2025

Issue: 8

Volume: 15

Page: 6667-6681

2 . 9 0 0

JCR@2023

Cited Count:

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SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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