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Endoleak Assessment Using Computational Fluid Dynamics and Image Processing Methods in Stented Abdominal Aortic Aneurysm Models
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Endoleak Assessment Using Computational Fluid Dynamics and Image Processing Methods in Stented Abdominal Aortic Aneurysm Models

Yueh-Hsun Lu, Karthick Mani, Bivas Panigrahi, Wen-Tang HsuChia-Yuan Chen
Computational and mathematical methods in medicine, 卷.2016(2016), 頁碼.1-9
01/01/2016
PMID: 27660648
Web of Science ID: WOS:000383072400001

摘要

Life Sciences & Biomedicine Mathematical & Computational Biology Science & Technology
Endovascular aortic aneurysm repair (EVAR) is a predominant surgical procedure to reduce the risk of aneurysm rupture in abdominal aortic aneurysm (AAA) patients. Endoleak formation, which eventually requires additional surgical reoperation, is a major EVAR complication. Understanding the etiology and evolution of endoleak from the hemodynamic perspective is crucial to advancing the current posttreatments for AAA patients who underwent EVAR. Therefore, a comprehensive flow assessment was performed to investigate the relationship between endoleak and its surrounding pathological flow fields through computational fluid dynamics and image processing. Six patient-specific models were reconstructed, and the associated hemodynamics in these models was quantified three-dimensionally to calculate wall stress. To provide a high degree of clinical relevance, the mechanical stress distribution calculated from the models was compared with the endoleak positions identified from the computed tomography images of patients through a series of imaging processing methods. An endoleak possibly forms in a location with high local wall stress. An improved stent graft (SG) structure is conceived accordingly by increasing the mechanical strength of the SG at peak wall stress locations. The presented analytical paradigm, as well as numerical analysis using patient-specific models, may be extended to other common human cardiovascular surgeries.

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https://doi.org/10.1155/2016/9567294檢視
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