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Gastrointestinal Imaging |
1 From the Department of Diagnostic Radiology, Warren Grant Magnuson Clinical Center, National Institutes of Health, 10 Center Dr, MSC 1182, Bldg 10, Rm 1C660, Bethesda, MD 20892-1182 (R.M.S., A.K.J., M.F., J.D.M.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.D.J.). Received October 2, 2001; revision requested December 18; revision received February 4, 2002; accepted March 14. Supported by the intramural research programs of the Department of Diagnostic Radiology, Warren Grant Magnuson Clinical Center. Supported in part by NIH grant RO1CA75333. Address correspondence to R.M.S. (e-mail: rms@nih.gov).
PURPOSE: To apply a computer-aided detection (CAD) algorithm to supine and prone multisection helical computed tomographic (CT) colonographic images to confirm if there is any added benefit provided by CAD over that of standard clinical interpretation.
MATERIALS AND METHODS: CT colonography (with patients in both supine and prone positions) was performed with a multisection helical CT scanner in 40 asymptomatic high-risk patients. There were two consecutive series of patients, 20 of whom had at least one polyp 1.0 cm in size or larger and 20 of whom had normal colons at conventional colonoscopy performed the same day. The CT colonographic images were interpreted with an automated CAD algorithm and by two radiologists who were blinded to colonoscopy findings.
RESULTS: For 25 polyps at least 1.0 cm in size ("large" polyps), sensitivity for detection by at least one radiologist was 48% (12 of 25). The sensitivity of CAD for detecting large polyps was also 48% (12 of 25), but the CAD algorithm detected four of 13 large polyps that were not detected by either radiologist (31%, 95% two-sided CI: 9, 61), increasing the potential sensitivity to 64% (16 of 25). For polyps identifiable retrospectively, sensitivity of CAD was 67% (12 of 18), and sensitivity of the combination of detection with the CAD algorithm or by at least one radiologist was 89% (16 of 18). There were an average of 11 false-positive detections per patient for CAD.
CONCLUSION: In this series of patients in whom radiologists had difficulties detecting polyps (compared with sensitivities of 75%90% reported in the literature), this CAD algorithm played a complementary role to conventional interpretation of CT colonographic images by detecting a number of large polyps missed by trained observers.
© RSNA, 2002
Index terms: Colon, CT, 75.12115, 75.12117 Colon neoplasms, 75.311 Colonoscopy, 75.1299 Computers, diagnostic aid
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