TY - JOUR
T1 - A novel computerized tool to stratify risk in carotid atherosclerosis using kinematic features of the arterial wall
AU - Gastounioti, Aimilia
AU - Makrodimitris, Stavros
AU - Golemati, Spyretta
AU - Kadoglou, Nikolaos P.E.
AU - Liapis, Christos D.
AU - Nikita, Konstantina S.
N1 - Publisher Copyright:
© 2014 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - Valid characterization of carotid atherosclerosis (CA) is a crucial public health issue, which would limit the major risks held by CA for both patient safety and state economies. This paper investigated the unexplored potential of kinematic features in assisting the diagnostic decision for CA in the framework of a computer-aided diagnosis (CAD) tool. Tothis end, 15CAD schemes were designed and were fed with a wide variety of kinematic features of the atherosclerotic plaque and the arterial wall adjacent to the plaque for 56 patients from two different hospitals. The CAD schemes were benchmarked in terms of their ability to discriminate between symptomatic and asymptomatic patients and the combination of the Fisher discriminant ratio, as a feature-selection strategy, and support vector machines, in the classification module, was revealedas the optimal motion-based CAD tool. The particular CAD tool was evaluated with severalcross-validationstrategies and yielded higher than 88% classification accuracy; the texture-based CAD performance in the same dataset was 80%. The incorporation of kinematic features of the arterial wall in CAD seems to have a particularly favorable impact on the performance of image-datadriven diagnosis for CA, which remains to be further elucidated in future prospective studies on large datasets.
AB - Valid characterization of carotid atherosclerosis (CA) is a crucial public health issue, which would limit the major risks held by CA for both patient safety and state economies. This paper investigated the unexplored potential of kinematic features in assisting the diagnostic decision for CA in the framework of a computer-aided diagnosis (CAD) tool. Tothis end, 15CAD schemes were designed and were fed with a wide variety of kinematic features of the atherosclerotic plaque and the arterial wall adjacent to the plaque for 56 patients from two different hospitals. The CAD schemes were benchmarked in terms of their ability to discriminate between symptomatic and asymptomatic patients and the combination of the Fisher discriminant ratio, as a feature-selection strategy, and support vector machines, in the classification module, was revealedas the optimal motion-based CAD tool. The particular CAD tool was evaluated with severalcross-validationstrategies and yielded higher than 88% classification accuracy; the texture-based CAD performance in the same dataset was 80%. The incorporation of kinematic features of the arterial wall in CAD seems to have a particularly favorable impact on the performance of image-datadriven diagnosis for CA, which remains to be further elucidated in future prospective studies on large datasets.
KW - Carotid atherosclerosis (CA)
KW - Computer-aided diagnosis (CAD)
KW - Kinematic features
KW - Motion analysis
KW - Ultrasound (US)
UR - http://www.scopus.com/inward/record.url?scp=84929335330&partnerID=8YFLogxK
U2 - 10.1109/JBHI.2014.2329604
DO - 10.1109/JBHI.2014.2329604
M3 - Article
C2 - 24951709
AN - SCOPUS:84929335330
SN - 2168-2194
VL - 19
SP - 1137
EP - 1145
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 3
M1 - 6827920
ER -