Polyp detection and false-positive rates by computer-aided analysis of withdrawal-phase videos of colonoscopy of the right-sided colon segment in a randomized controlled trial comparing water exchange and air insufflation - 16/05/22
Abstract |
Background and Aims |
Water exchange (WE) improves lesion detection but misses polyps because of human limitations. Computer-aided detection (CADe) identifies additional polyps overlooked by the colonoscopist. Additional polyp detection rate (APDR) is the proportion of patients with at least 1 additional polyp detected by CADe. The number of false positives (because of feces and air bubble) per colonoscopy (FPPC) is a major CADe limitation, which might be reduced by salvage cleaning with WE. We compared the APDR and FPPC by CADe between videos of WE and air insufflation in the right-sided colon.
Methods |
CADe used a convolutional neural network with transfer learning. We edited and coded withdrawal-phase videos in a randomized controlled trial that compared right-sided colon findings between air insufflation and WE. Two experienced blinded endoscopists analyzed the CADe-overlaid videos and identified additional polyps by consensus. An artifact triggered by CADe but not considered a polyp by the reviewers was defined as a false positive. The primary outcome was APDR.
Results |
Two hundred forty-five coded videos of colonoscopies inserted with WE (n = 123) and air insufflation (n = 122) methods were analyzed. The APDR in the WE group was significantly higher (37 [30.1%] vs 15 [12.3%], P = .001). The mean [standard deviation] FPPC related to feces (1.78 [1.67] vs 2.09 [2.09], P = .007) and bubbles (.53 [.89] vs 1.25 [2.45], P = .001) in the WE group were significantly lower.
Conclusions |
CADe showed significantly higher APDR and lower number of FPPC related to feces and bubbles in the WE group. The results support the hypothesis that the strengths of CADe and WE complement the weaknesses of each other in optimizing polyp detection.
Le texte complet de cet article est disponible en PDF.Abbreviations : ADR, APDR, CADe, CADx, FP, FPPC, PDR, RCT, WE, YOLO
Plan
| DISCLOSURE: F.W. Leung received research support for this study from VA Clinical Merit and ASGE Clinical Research Funds Research support for this study was provided by the Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation (DTCRD109-E-11) to C. P. Tang and Y. H. Hsieh and the Ministry of Science and Technology (MOST) of Taiwan (project no. 109-2314-B-303-013) to C. P. Tang, Y. H. Hsieh. T. L. Lin, and F. W. Leung. All other authors disclosed no financial relationships. |
Vol 95 - N° 6
P. 1198 - juin 2022 Retour au numéro
Article précédent
- Although depth prediction of colorectal cancer with artificial intelligence is clinically relevant, standardization of histopathologic diagnosis should also be taken care of
- Yutaka Saito, Masayoshi Yamada, Yuichi Mori
- Artificial intelligence complemented by water exchange for right-sided colonic polyp detection: It’s time to dive!
- Alberto Murino, Omer F. Ahmad
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