4.7 Article

Diagnostic Accuracy of Computed Tomography Coronary Angiography According to Pre-Test Probability of Coronary Artery Disease and Severity of Coronary Arterial Calcification The CORE-64 (Coronary Artery Evaluation Using 64-Row Multidetector Computed Tomography Angiography) International Multicenter Study

Journal

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
Volume 59, Issue 4, Pages 379-387

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jacc.2011.06.079

Keywords

angiography; coronary artery disease; imaging

Funding

  1. Toshiba Medical Systems
  2. Doris Duke Charitable Foundation
  3. National Heart, Lung, and Blood Institute [RO1-HL66075-01, HO1-HC95162-01]
  4. National Institute on Aging [RO1-AG021570-01]
  5. GE Healthcare
  6. Bracco
  7. Guerbet
  8. European Regional Development Fund
  9. German Heart Foundation/German Foundation of Heart Research
  10. German Science Foundation (DFG)
  11. German Federal Ministry of Education and Research (BMBF) for meta-analyses
  12. Cardiac MR Academy Berlin
  13. Bayer-Schering
  14. Vital Images
  15. Toshiba Medical Systems, Asia
  16. GE Biosciences
  17. Bayer-Schering Pharma
  18. Infinitt Systems
  19. CT Core Laboratory
  20. Bristol-Myers Squibb
  21. Sanofi-Aventis
  22. Bracco Diagnostics
  23. GE Medical Systems
  24. Donald W. Reynolds Foundation

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Objectives The purpose of this study was to assess the impact of patient population characteristics on accuracy by computed tomography angiography (CTA) to detect obstructive coronary artery disease (CAD). Background The ability of CTA to exclude obstructive CAD in patients of different pre-test probabilities and in presence of coronary calcification remains uncertain. Methods For the CORE-64 (Coronary Artery Evaluation Using 64-Row Multidetector Computed Tomography Angiography) study, 371 patients underwent CTA and cardiac catheterization for the detection of obstructive CAD, defined as >= 50% luminal stenosis by quantitative coronary angiography (QCA). This analysis includes 80 initially excluded patients with a calcium score >= 600. Area under the receiver-operating characteristic curve (AUC) was used to evaluate CTA diagnostic accuracy compared to QCA in patients according to calcium score and pre-test probability of CAD. Results Analysis of patient-based quantitative CTA accuracy revealed an AUC of 0.93 (95% confidence interval [CI]: 0.90 to 0.95). The AUC remained 0.93 (95% CI: 0.90 to 0.96) after excluding patients with known CAD but decreased to 0.81 (95% CI: 0.71 to 0.89) in patients with calcium score >= 600 (p = 0.077). While AUCs were similar (0.93, 0.92, and 0.93, respectively) for patients with intermediate, high pre-test probability for CAD, and known CAD, negative predictive values were different: 0.90, 0.83, and 0.50, respectively. Negative predictive values decreased from 0.93 to 0.75 for patients with calcium score <100 or >= 100, respectively (p = 0.053). Conclusions Both pre-test probability for CAD and coronary calcium scoring should be considered before using CTA for excluding obstructive CAD. For that purpose, CTA is less effective in patients with calcium score >= 600 and in patients with a high pre-test probability for obstructive CAD. (J Am Coll Cardiol 2012; 59: 379-87) (C) 2012 by the American College of Cardiology Foundation

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