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

Autor: Donna Kam, Henley Wu, Michael Kam, Roman Goldenberg, Joshua Ring, Summer Ferraro, Vinay Malhotra, Melissa A. Daubert, Alexander J. Abramowicz, Aimee Minton, Michael Poon
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: Heart International, Vol 8, Iss 1, Pp e2-e2 (2013)
Druh dokumentu: article
ISSN: 1826-1868
2036-2579
DOI: 10.4081/hi.2013.e2
Popis: 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.
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