Article Sidebar
Views PDF: 382
Apply the cad-rads classification in the assessment of chronic coronary artery disease on multislice computed tomography
Main Article Content
Abstract
Purpose: To apply the CAD-RADS classification in the assessment of chronic coronary artery disease on multislice computed tomography.
Material and methods: Cross-sectional description of 179 patientsundergoing coronary computed tomography angiography, diagnosed according to CAD-RADS classification by two physicians independently, the intra-class correlation was used to test the inter-reviewer agreement (IRA), and comparing with results invasive coronary angiography.
Results: There was an excellent IRA between the two for CADRADS (κ=0.904), by each CAD-RADS classification (κ=0.827-1.00), by coronary artery stenosis (κ=0.878-0.931). There is an excellent IRA for modifiers G (κ=1), and S (κ=1), moderate IRA for V (κ=0.574). The best cutoff value for predicting significant CAD was ≥ CAD-RADS 3. The diagnostic value of CAD-RADS classification according to the common segment: sensitivity 77.54%, specificity 87.23%, positive predictive value 89.92%, negative predictive value 72.56%.
Conclusion: There is an excellent inter-reviewer agreement when applying the CAD-RADS classification to clinical practice, with high sensitivity, specificity, and accuracy when compared with invasive coronary angiography.
Article Details
Keywords
coronary artery, CAD-RADS, CT angiography, graft, stent
References
2. Cury RC, Abbara S, Achenbach S, et al. CAD-RADSTM: Coronary Artery Disease – Reporting and Data System: An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology. Journal of the American College of Radiology. 2016;13(12, Part A):1458-1466.e9. doi:10.1016/j.jacr.2016.04.024
3. Abdel Razek AAK, Elrakhawy MM, Yossof MM, Nageb HM. Inter-observer agreement of the Coronary Artery Disease Reporting and Data System (CAD-RADSTM) in patients with stable chest pain. Pol J Radiol. 2018;83:e151-e159. doi:10.5114/pjr.2018.75641
4. Basha MAA, Aly SA, Ismail AAA, Bahaaeldin HA, Shehata SM. The validity and applicability of CAD-RADS in the management of patients with coronary artery disease. Insights Imaging. 2019;10(1):117. doi:10.1186/ s13244-019-0806-7
5. Tesche C, De Cecco CN, Vliegenthart R, et al. Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis. Journal of Cardiovascular Computed Tomography. 2016;10(5):377-383. doi:10.1016/j.jcct.2016.07.005
6. Maroules CD, Hamilton-Craig C, Branch K, et al. Coronary artery disease reporting and data system (CADRADSTM): Inter-observer agreement for assessment categories and modifiers. Journal of Cardiovascular Computed Tomography. 2018;12(2):125-130. doi:10.1016/j.jcct.2017.11.014
7. Puchner SB, Liu T, Mayrhofer T, et al. High-Risk Plaque Detected on Coronary CT Angiography Predicts Acute Coronary Syndromes Independent of Significant Stenosis in Acute Chest Pain: Results From the ROMICAT-II Trial. Journal of the American College of Cardiology. 2014;64(7):684-692. doi:10.1016/j.
jacc.2014.05.039
8. Saremi F, Achenbach S. Coronary Plaque Characterization Using CT. American Journal of Roentgenology. 2015;204(3):W249-W260. doi:10.2214/AJR.14.13760
9. Redondo A, Comas M, Macià F, et al. Inter- and intraradiologist variability in the BI-RADS assessment and breast density categories for screening mammograms. BJR. 2012;85(1019):1465-1470. doi:10.1259/bjr/21256379
10. Rosenkrantz AB, Ginocchio LA, Cornfeld D, et al. Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists. Radiology. 2016;280(3):793-804. doi:10.1148/radiol.2016152542