Computer-aided analysis of 64-slice coronary computed tomography angiography: A comparison with manual interpretation

Journal Article (Journal Article)

Coronary computed tomography angiography (CCTA) is increasingly used for the assessment of coronary heart disease (CHD) in symptomatic patients. Software applications have recently been developed to facilitate efficient and accurate analysis of CCTA. This study aims to evaluate the clinical application of computer-aided diagnosis (CAD)software for the detection of significant coronary stenosis on CCTA in populations with low (8%), moderate (13%), and high (27%) CHD prevalence. A total of 341 consecutive patients underwent 64-slice CCTA at 3 clinical sites in the United States. CAD software performed automatic detection of significant coronary lesions (>50% stenosis). CAD results were then compared to the consensus manual interpretation of 2 imaging experts. Data analysis was conducted for each patient and segment. The CAD had 100% sensitivity per patient across all 3 clinical sites. Specificity in the low, moderate, and high CHD prevalence populations was 64%, 41%, and 38%, respectively. The negative predictive value at the 3 clinical sites was 100%. The positive predictive value was 22%, 21%, and 38% for the low, moderate, and high CHD prevalence populations, respectively. This study demonstrates the utility of CAD software in 3 distinct clinical settings. In a low-prevalence population, such as seen in the emergency department, CAD can be used as a Computer-Aided Simple Triage tool to assist in diagnostic delineation of acute chest pain. In a higher prevalence population, CAD software is useful as an adjunct for both the experienced and inexperienced reader. © A.J. Abramowiczet al., 2013 Licensee PAGEPress, Italy.

Full Text

Duke Authors

Cited Authors

  • Abramowicz, AJ; Daubert, MA; Malhotra, V; Ferraro, S; Ring, J; Goldenberg, R; Kam, M; Wu, H; Kam, D; Minton, A; Poon, M

Published Date

  • January 1, 2013

Published In

Volume / Issue

  • 8 / 1

Start / End Page

  • 4 - 8

Electronic International Standard Serial Number (EISSN)

  • 2036-2579

International Standard Serial Number (ISSN)

  • 1826-1868

Digital Object Identifier (DOI)

  • 10.4081/hi.2013.e2

Citation Source

  • Scopus