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Coronary Artery Calcification—Does It Predict the Cad-Rads Category? Publisher Pubmed



Moradi M1 ; Rafiei E1 ; Rasti S1 ; Haghbin H2
Authors
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Authors Affiliations
  1. 1. Department of Radiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran
  2. 2. Department of Statistics, Faculty of Intelligent Systems Engineering and Data Sciences, Persian Gulf University, Bushehr, 7516913817, Iran

Source: Emergency Radiology Published:2022


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, 44mm2, 111mm3, 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. © 2022, The Author(s), under exclusive licence to American Society of Emergency Radiology (ASER).
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