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Computer Applications |
1 From the Department of Radiology, University of Michigan Hospital, UH B1F510, 1500 E Medical Center Dr, Ann Arbor, MI 48109-0030. From the 1997 RSNA scientific assembly. Received August 10, 1998; revision requested September 8; revision received November 30; accepted January 21, 1999. Supported in part by United States Public Health Service grant CA 48129 and by U.S. Army Medical Research and Materiel Command grant DAMD 17-96-1-6254. B.S. supported by Career Development award DAMD 17-96-1-6012 from the U.S. Army Medical Research and Materiel Command. N.P. supported by a grant from the Whitaker Foundation. Address reprint requests to H.P.C. (e-mail: chanhp@umich.edu).
PURPOSE: To evaluate the effects of computer-aided diagnosis (CAD) on radiologists' classification of malignant and benign masses seen on mammograms.
MATERIALS AND METHODS: The authors previously developed an automated computer program for estimation of the relative malignancy rating of masses. In the present study, the authors conducted observer performance experiments with receiver operating characteristic (ROC) methodology to evaluate the effects of computer estimates on radiologists' confidence ratings. Six radiologists assessed biopsy-proved masses with and without CAD. Two experiments, one with a single view and the other with two views, were conducted. The classification accuracy was quantified by using the area under the ROC curve, Az.
RESULTS: For the reading of 238 images, the Az value for the computer classifier was 0.92. The radiologists' Az values ranged from 0.79 to 0.92 without CAD and improved to 0.87–0.96 with CAD. For the reading of a subset of 76 paired views, the radiologists' Az values ranged from 0.88 to 0.95 without CAD and improved to 0.93–0.97 with CAD. Improvements in the reading of the two sets of images were statistically significant (P = .022 and .007, respectively). An improved positive predictive value as a function of the false-negative fraction was predicted from the improved ROC curves.
CONCLUSION: CAD may be useful for assisting radiologists in classification of masses and thereby potentially help reduce unnecessary biopsies.
Index terms: Breast neoplasms, 00.31, 00.32 • Breast neoplasms, radiography, 00.111, 00.119 • Breast radiography, 00.111, 00.119 • Computers, diagnostic aid • Receiver operating characteristic curve (ROC)
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