Literature DB >> 24045244

Correlation of coronary atherosclerosis and subclinical plaque phenotype of carotid artery: a 320-row multidetector computed tomographic angiography study.

WeiGuo Zhang1, Hang Jin, WeiZhong Cheng, ShengXiang Rao, XiuLiang Lu, Mengsu Zeng.   

Abstract

OBJECTIVE: This study aimed to evaluate the correlation between coronary atherosclerosis and the phenotype of subclinical carotid artery plaque using 320-row computed tomography via an original single-injection protocol.
METHODS: A total of 122 patients with suspected coronary artery disease but free of transient ischemic attack and stroke underwent computed tomographic angiography of carotid and coronary artery simultaneously. The mean attenuation was measured at each artery. The plaques in either carotid or coronary were classified into noncalcified, calcified, and mixed. Coronary plaque was evaluated with plaque score. Logistic regression analysis was used to determine the predictive value of coronary plaque score to the phenotype of carotid plaque. The prevalence of each phenotype of carotid plaque in different coronary stenosis groups was also analyzed.
RESULTS: The mean (SD) attenuation of carotid and coronary artery was 456.3 (81.7) Hounsfield units (HU), 466.0 (85.5) HU, 446.5 (84.1) HU, and 476.4 (90.0) HU, respectively. There was a significant correlation between the noncalcified coronary plaque score and noncalcified plaque in carotid artery (odds ratio [OR], 2.9; P < 0.05). The coronary calcified plaque scores were significantly correlated with carotid mixed (OR, 1.8; P < 0.05) and calcified plaque (OR, 2.0; P < 0.05). The noncalcified plaque of carotid artery was more frequent (72.5% vs 67%) in the nonsignificant coronary stenosis group.
CONCLUSIONS: The subclinical carotid plaque phenotypes are significantly associated with coronary plaque score and defined grade of stenosis in patients with suspected coronary artery disease. Our tailored computed tomographic angiography protocol may have a positive impact on secondary prevention.

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Year:  2013        PMID: 24045244     DOI: 10.1097/RCT.0b013e318299f006

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


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