Diagnostic accuracy of coronary angiography using 64-slice computed tomography in coronary artery disease

Saudi Med J. 2015 Oct;36(10):1156-62. doi: 10.15537/smj.2015.10.12415.

Abstract

Objectives: To conduct a meta-analysis and investigate the diagnostic value of 64-slice computed tomography (CT) angiography for diagnosing coronary artery disease (CAD) in patients.

Methods: A comprehensive literature search from March 2005 to August 2014 was performed on the following databases: Cochrane Library; Medline; EmBase; PubMed; and BioMed Central database. As a reference standard, studies that assessed 64-slice CT angiography in detecting coronary artery stenosis (CAS) with invasive coronary angiography were included. Coronary artery stenosis was defined as ≥50% diameter stenosis. Diagnostic value was determined by pooling sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) values at segment-level analysis. Diagnostic accuracy was undertaken using area under the curve (AUC) value and summary receiver operating characteristic (SROC) curves. Publication bias was examined by Deek's funnel plot asymmetry test.

Results: Eight studies were included in the analysis, enrolling a total of 579 patients (7,407 segment coronary vessels). At segment-level, pooled sensitivity value was 90% (95% confidence interval [CI]: 83-95%), specificity was 91% (95% CI: 61-98%), PLR value was 9.7 (95% CI: 1.8-53.3), and NLR value was 0.11 (95% CI: 0.05-0.22) for CAS. Optimal cut-off point of sensitivity was 90%, and specificity under the SROC curve was 91%. The AUC value was 0.94.

Conclusion: The 64-slice CT angiography is a reliable tool for detection of CAD when using a cut-off of more than or equal to 50% diameter stenosis in elderly population.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Coronary Angiography / methods*
  • Coronary Artery Disease / diagnostic imaging*
  • Coronary Stenosis / diagnostic imaging*
  • Humans
  • Multidetector Computed Tomography*
  • ROC Curve
  • Sensitivity and Specificity