Does a computer-aided detection algorithm in a second read paradigm enhance the performance of experienced computed tomography colonography readers in a population of increased risk?

We prospectively determined whether computer-aided detection (CAD) could improve the performance characteristics of computed tomography colonography (CTC) in a population of increased risk for colorectal cancer. Therefore, we included 170 consecutive patients that underwent both CTC and colonoscopy. All findings a parts per thousand yen6 mm were evaluated at colonoscopy by segmental unblinding. We determined per-patient sensitivity and specificity for polyps a parts per thousand yen6 mm and a parts per thousand yen10 mm without and with computer-aided detection (CAD). The McNemar test was used for comparison the results without and with CAD. Unblinded colonoscopy detected 50 patients with lesions a parts per thousand yen6 mm and 25 patients with lesions a parts per thousand yen10 mm. Sensitivity of CTC without CAD for these size categories was 80% (40/50, 95% CI: 69-81%) and 64% (16/25, 95% CI: 45-83%), respectively. CTC with CAD detected one additional patient with a lesion a parts per thousand yen6 mm and two with a lesion a parts per thousand yen10 mm, resulting in a sensitivity of 82% (41/50, 95% CI: 71-93%) (p = 0.50) and 72% (18/25, 95% CI: 54-90%) (p = 1.0), respectively. Specificity without CAD for polyps a parts per thousand yen6 mm and a parts per thousand yen10 mm was 84% (101/120, 95% CI: 78-91%) and 94% (136/145, 95% CI: 90-98%), respectively. With CAD, the specificity remained (nearly) unchanged: 83% (99/120, 95% CI: 76-89%) and 94% (136/145, 95% CI: 90-98%), respectively. Thus, although CTC with CAD detected a few more patients than CTC without CAD, it had no statistically significant positive influence on CTC performance