Coronary artery calcification-does it predict the CAD-RADS category?

(2022) Coronary artery calcification-does it predict the CAD-RADS category? Emerg Radiol. pp. 1-9. ISSN 1070-3004 (Print) 1070-3004

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Abstract

PURPOSE: Coronary calcium scores (CCSs) in cardiac-gated computed tomography (CCT) are diagnostic for coronary artery disease (CAD). This study aims to investigate if CCSs can foretell CAD-reporting and data system (CAD-RADS) without performing computed tomography angiography (CTA). METHODS: Profiles of 544 patients were studied who had gone through CCT and CTA; the number of calcified regions of interest (ROIs), the Agatston, area, volume, and mass CCSs were calculated. Among the CAD-RADS categories (1 to 5), the mean values were compared for each CCS separately. A cut-offfor each CCS was declared using ROC curve analysis, more than which could predict significant CAD (CAD-RADS 3 to 5). Also, logistic regression models indicated the most probable CAD-RADS category based on the CCSs. P < 0.05 was considered significant. RESULTS: Among 53 male and 47 female participants with a mean (SD) age of 62.57 (0.84) years, numbers of calcified ROIs were significantly different between each pair of CAD-RADS categories. While other CCSs did not show a significant difference between CAD-RADS 1 and 2 or 2 and 3. All CCSs were significantly different between the non-significant and significant CAD groups; cut-offs for the number of calcified ROIs, the Agatston, area, volume, and mass scores were 9, 128, 44mm(2), 111mm(3), and 22 mg, respectively. Formulae A and B predicted the most probable CAD-RADS category (accuracy: 79) and the probability of significant/non-significant CAD (accuracy: 81), respectively. CONCLUSION: CCSs could predict CAD-RADS with an accuracy of 80. Further studies are needed to introduce more predictive calcium indices.

Item Type: Article
Keywords: Atherosclerosis Computed tomography angiography Coronary artery disease Vascular calcification
Page Range: pp. 1-9
Journal or Publication Title: Emerg Radiol
Journal Index: Pubmed
Identification Number: https://doi.org/10.1007/s10140-022-02082-w
ISSN: 1070-3004 (Print) 1070-3004
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/16321

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