Vertebral artery fusiform aneurysm geometry in predicting rupture risk.

dc.contributor.author

Zhao, Xiukun

dc.contributor.author

Gold, Nathan

dc.contributor.author

Fang, Yibin

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Xu, Shixin

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Zhang, Yongxin

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Liu, Jianmin

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Gupta, Arvind

dc.contributor.author

Huang, Huaxiong

dc.date.accessioned

2020-07-28T12:20:36Z

dc.date.available

2020-07-28T12:20:36Z

dc.date.issued

2018-10-31

dc.date.updated

2020-07-28T12:20:34Z

dc.description.abstract

Cerebral aneurysms affect a significant portion of the adult population worldwide. Despite significant progress, the development of robust techniques to evaluate the risk of aneurysm rupture remains a critical challenge. We hypothesize that vertebral artery fusiform aneurysm (VAFA) morphology may be predictive of rupture risk and can serve as a deciding factor in clinical management. To investigate the VAFA morphology, we use a combination of image analysis and machine learning techniques to study a geometric feature set computed from a depository of 37 (12 ruptured and 25 un-ruptured) aneurysm images. Of the 571 unique features we compute, we distinguish five features for use by our machine learning classification algorithm by an analysis of statistical significance. These machine learning methods achieve state-of-the-art classification performance (81.43 ± 13.08%) for the VAFA morphology, and identify five features (cross-sectional area change of aneurysm, maximum diameter of nearby distal vessel, solidity of aneurysm, maximum curvature of nearby distal vessel, and ratio of curvature between aneurysm and its nearby proximal vessel) as effective predictors of VAFA rupture risk. These results suggest that the geometric features of VAFA morphology may serve as useful non-invasive indicators for the prediction of aneurysm rupture risk in surgical settings.

dc.identifier

rsos180780

dc.identifier.issn

2054-5703

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2054-5703

dc.identifier.uri

https://hdl.handle.net/10161/21200

dc.language

eng

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The Royal Society

dc.relation.ispartof

Royal Society open science

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10.1098/rsos.180780

dc.subject

aneurysm geometry

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machine learning

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rupture risk prediction

dc.title

Vertebral artery fusiform aneurysm geometry in predicting rupture risk.

dc.type

Journal article

duke.contributor.orcid

Xu, Shixin|0000-0002-8207-7313

pubs.begin-page

180780

pubs.issue

10

pubs.organisational-group

Duke Kunshan University

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Duke Kunshan University Faculty

pubs.organisational-group

Duke

pubs.publication-status

Published

pubs.volume

5

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