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Small Pulmonary Nodules: Effect of Two Computer-aided Detection Systems on Radiologist Performance¹

¹ From the Department of Diagnostic Radiology (M.D., G.M., A.H.M., R.W.G., J.E.W.), Institute of Medical Statistics (S.S.), and Department of Occupational Health (T.K.), Rheinisch-Westfâlische Technische Hochschule Aachen University, Pauwelsstrasse 30, D-52074 Aachen, Germany; and Department of Computed Tomography, Siemens Medical Solutions, Forchheim, Germany (T.G.F., L.G.). Received July 6, 2005; revision requested September 6; revision received December 15; accepted January 11, 2006; final version accepted February 26. Address correspondence to M.D. (e-mail: das{at}rad.rwth-aachen.de).

Purpose: To prospectively compare the effects of two computer-aided detection (CAD) systems on the detection of small pulmonary nodules at multi–detector row computed tomography (CT) by using a consensus panel decision as the reference standard.

Materials and Methods: Institutional review board approval and informed consent were obtained. Multi–detector row CT scans were randomly chosen and prospectively evaluated in 25 patients. Two dedicated CAD systems—ImageChecker CT (R2 Technologies, Sunnyvale, Calif) and Nodule Enhanced Viewing (NEV) (Siemens Medical Solutions, Forchheim, Germany)—were used. Results were interpreted by three radiologists with 1, 3, and 6 years of experience. Images were evaluated without and with CAD software. The reference standard was assessed by a consensus panel consisting of all three radiologists and an adjudicator with 8 years of experience.

Results: A total of 116 pulmonary nodules (average diameter, 3.4 mm; average volume, 32.05 mm³) were found in all data sets during consensus interpretation, which included findings from the CAD software and all radiologists. Overall sensitivity was 73% with ImageChecker CT and 75% with NEV. Overall sensitivity without CAD was 68% for radiologist 1, 78% for radiologist 2, and 82% for radiologist 3. With ImageChecker CT, sensitivity increased to 79% for radiologist 1, 90% for radiologist 2, and 84% for radiologist 3. With NEV, sensitivity increased to 79% for radiologist 1, 90% for radiologist 2, and 86% for radiologist 3. The average number of false-positive findings was six (range, 0–14) with ImageChecker CT and eight (range, 0–22) with NEV.

Conclusion: Radiologist performance in the interpretation of multi–detector row CT scans can be improved by using CAD systems, with a reduction in the number of false-negative diagnoses. No statistically significant difference in sensitivity was found between the two CAD systems.

© RSNA, 2006

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