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Breast Imaging |
1 From the Division of Imaging Research, Department of Radiology (B.Z., D.G.), the Departments of Radiology (C.A.B., M.A.G., C.M.H., L.A.H., T.S.C.) and Biostatistics (H.E.R.), University of Pittsburgh, 300 Halket St, Suite 4200, Pittsburgh, PA 15213; and the Magee Womens Hospital, University of Pittsburgh Medical Center Health System, Pa (M.A.G., C.M.H., L.A.H.). Received January 12, 2001; revision requested March 5; revision received March 29; accepted May 1. Supported in part by the U.S. Army Medical Research Acquisition Activity under contracts DAMD17-98-1-8018 and DAMD17-00-1-0410 and by grant CA77850 from the National Cancer Institute, National Institutes of Health. Address correspondence to B.Z. (e-mail: bzheng@radserv.arad.upmc.edu).
PURPOSE: To assess the performance of radiologists in the detection of masses and microcalcification clusters on digitized mammograms by using different computer-assisted detection (CAD) cuing environments.
MATERIALS AND METHODS: Two hundred nine digitized mammograms depicting 57 verified masses and 38 microcalcification clusters in 85 positive and 35 negative cases were interpreted independently by seven radiologists using five display modes. Except for the first mode, for which no CAD results were provided, suspicious regions identified with a CAD scheme were cued in all the other modes by using a combination of two cuing sensitivities (90% and 50%) and two false-positive rates (0.5 and 2.0 per image). A receiver operating characteristic study was performed by using soft-copy images.
RESULTS: CAD cuing at 90% sensitivity and a rate of 0.5 false-positive region per image improved observer performance levels significantly (P < .01). As accuracy of CAD cuing decreased so did observer performances (P < .01). Cuing specificity affected mass detection more significantly, while cuing sensitivity affected detection of microcalcification clusters more significantly (P < .01). Reduction of cuing sensitivity and specificity significantly increased false-negative rates in noncued areas (P < .05). Trends were consistent for all observers.
CONCLUSION: CAD systems have the potential to significantly improve diagnostic performance in mammography. However, poorly performing schemes could adversely affect observer performance in both cued and noncued areas.
Index terms: Breast neoplasms, diagnosis, 00.30, 00.81 • Cancer screening, 00.11 • Computers, diagnostic aid • Diagnostic radiology, observer performance
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