Relationship Between Cerebral Aneurysm Development and Cerebral Artery Shape
Author(s) -
Marin Yasugi,
Belayat Hossain,
Manabu Nii,
Syoji Kobashi
Publication year - 2018
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2018.p0249
Subject(s) - aneurysm , cerebral arteries , sensitivity (control systems) , middle cerebral artery , medicine , magnetic resonance imaging , anterior cerebral artery , radiology , bifurcation , magnetic resonance angiography , cardiology , physics , ischemia , nonlinear system , quantum mechanics , electronic engineering , engineering
Lifestyle and genetics are known to be the major factors causing cerebral aneurysms, but some studies suggest that the shape of cerebral arteries might be correlated with the risk of aneurysm occurrence. This study focuses on the shape of cerebral arteries where cerebral aneurysms tend to occur. First, it extracts the shape feature of the cerebral artery ring, which is a predilection site of cerebral aneurysm, from 3-D magnetic resonance angiography images, and calculates four types of shape feature vectors – 3-D shape, bifurcation angle, degree of meandering, and direction of the branch points. Then, it estimates the risk of cerebral aneurysms occurring, based on the extracted features using support vector machine. To validate the proposed method, we conducted a leave-one-out cross validation test using 80 subjects (40 subjects with and 40 subjects without cerebral aneurysms). The method using a 3-D artery shape achieved 75% sensitivity and 75% specificity; the one using the bifurcation angle showed 47% sensitivity and 41% specificity. The method using the degree of meandering showed 55% sensitivity and 53% specificity, and the one that used the direction of the six branch points showed 30% sensitivity and 27% specificity. These results show that the 3-D artery shape could be a possible indicator for predicting the risk of developing cerebral aneurysms.
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