In Vivo Deformation of the Human Basilar Artery.

B-spline surface deformation methods Basilar artery In vivo arterial mechanics Neurovascular mechanics

Journal

Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512

Informations de publication

Date de publication:
06 Sep 2024
Historique:
received: 27 05 2024
accepted: 14 08 2024
medline: 6 9 2024
pubmed: 6 9 2024
entrez: 6 9 2024
Statut: aheadofprint

Résumé

An estimated 6.8 million people in the United States have an unruptured intracranial aneurysms, with approximately 30,000 people suffering from intracranial aneurysms rupture each year. Despite the development of population-based scores to evaluate the risk of rupture, retrospective analyses have suggested the limited usage of these scores in guiding clinical decision-making. With recent advancements in imaging technologies, artery wall motion has emerged as a promising biomarker for the general study of neurovascular mechanics and in assessing the risk of intracranial aneurysms. However, measuring arterial wall deformations in vivo itself poses several challenges, including how to image local wall motion and deriving the anisotropic wall strains over the cardiac cycle. To overcome these difficulties, we first developed a novel in vivo MRI-based imaging method to acquire cardiac gated images of the human basilar artery (BA) over the cardiac cycle. Next, complete BA endoluminal surfaces from each frame were segmented, producing high-resolution point clouds of the endoluminal surfaces. From these point clouds we developed a novel B-spline-based surface representation, then exploited the local support nature of B-splines to determine the local endoluminal surface strains. Results indicated distinct regional and temporal variations in BA wall deformation, highlighting the heterogeneous nature BA function. These included large circumferential strains (up to

Identifiants

pubmed: 39240472
doi: 10.1007/s10439-024-03605-x
pii: 10.1007/s10439-024-03605-x
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s) under exclusive licence to Biomedical Engineering Society.

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Auteurs

Jaemin Kim (J)

James T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.

Kaiyu Zhang (K)

Vascular Imaging Lab, Department of Radiology, School of Medicine, University of Washington, Seattle, WA, USA.

Gador Canton (G)

Vascular Imaging Lab, Department of Radiology, School of Medicine, University of Washington, Seattle, WA, USA.

Niranjan Balu (N)

Vascular Imaging Lab, Department of Radiology, School of Medicine, University of Washington, Seattle, WA, USA.

Kenneth Meyer (K)

James T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.

Reza Saber (R)

Department of Neurology, Dell School of Medicine, University of Texas, Austin, TX, USA.

David Paydarfar (D)

Department of Neurology, Dell School of Medicine, University of Texas, Austin, TX, USA.

Chun Yuan (C)

Vascular Imaging Lab, Department of Radiology, School of Medicine, University of Washington, Seattle, WA, USA.

Michael S Sacks (MS)

James T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA. msacks@oden.utexas.edu.

Classifications MeSH