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CT Colonography: Investigation of the Optimum Reader Paradigm by Using Computer-aided Detection Software¹

¹ From the Department of Specialist X-Ray (S.A.T., S.H.) and Medical Statistics Unit (S.C.C.), University College Hospital, 235 Euston Rd, 2F Podium, London NW1 2BU, England; Department of Radiology, Stedelijk Ziekenhuis, Roeselare, Belgium (P.L.); Department of Radiology, Mallinckrodt Institute of Radiology, St Louis, Mo (E.G.M.); Abdominal Imaging Section, Duke University Medical Center, Durham, NC (E.K.P., C.M.M.); Department of Radiology, San Francisco VA Medical Center, University of California, San Francisco, Calif (J.Y., R.A.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minn (J.M.B.); Department of Intestinal Imaging, St Mark's Hospital, Harrow, United Kingdom (A.G.); and Department of Radiology, University of Wisconsin Medical School, Madison, Wis (D.H.K.). From the 2006 RSNA Annual Meeting. Received January 29, 2007; revision requested March 27; revision received May 9; final version accepted June 11. This work was supported in part by the U.K. Department of Health's NIHR Biomedical Research Centres. Address correspondence to S.A.T. (e-mail: csytaylor{at}yahoo.co.uk).

Purpose: To prospectively compare the diagnostic performance and time efficiency of both second and concurrent computer-aided detection (CAD) reading paradigms for retrospectively obtained computed tomographic (CT) colonography data sets by using consensus reading (three radiologists) of colonoscopic findings as a reference standard.

Materials and Methods: Ethical permission, HIPAA compliance (for U.S. institutions), and patient consent were obtained from all institutions for use of CT colonography data sets in this study. Ten radiologists each read 25 CT colonography data sets (12 men, 13 women; mean age, 61 years) containing 69 polyps (28 were 1–5 mm, 41 were 6 mm) by using workstations integrated with CAD software. Reading was randomized to either "second read" CAD (applied only after initial unassisted assessment) or "concurrent read" CAD (applied at the start of assessment). Data sets were reread 6 weeks later by using the opposing paradigm. Polyp sensitivity and reading times were compared by using multilevel logistic and linear regression, respectively. Receiver operating characteristic (ROC) curves were generated.

Results: Compared with the unassisted read, odds of improved polyp (6 mm) detection were 1.5 (95% confidence interval [CI]: 1.0, 2.2) and 1.3 (95% CI: 0.9, 1.9) by using CAD as second and concurrent reader, respectively. Detection odds by using CAD concurrently were 0.87 (95% CI: 0.59, 1.3) and 0.76 (95% CI: 0.57, 1.01) those of second read CAD, excluding and including polyps 1–5 mm, respectively. The concurrent read took 2.9 minutes (95% CI: –3.8, –1.9) less than did second read. The mean areas under the ROC curve (95% CI) for the unassisted read, second read CAD, and concurrent read CAD were 0.83 (95% CI: 0.78, 0.87), 0.86 (95% CI: 0.82, 0.90), and 0.88 (95% CI: 0.83, 0.92), respectively.

Conclusion: CAD is more time efficient when used concurrently than when used as a second reader, with similar sensitivity for polyps 6 mm or larger. However, use of second read CAD maximizes sensitivity, particularly for smaller lesions.

© RSNA, 2007