Clinical trial · Interventional
Optical Diagnosis of Neoplasia Using Artificial Intelligence
Assistance for Optical Diagnosis of Neoplasia Using Artificial Intelligence (FAIR Study)
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Computer-aided diagnosis (CADx) for colonoscopy aims to enhance optical diagnosis but often underperforms when used alongside humans due to under-reliance on AI. Psychological interventions like cognitive forcing, such as delaying CADx suggestions, may improve human-AI interaction by fostering critical assessment. However, their impact on patient-important outcomes remains unexplored. The investigators will conduct an ex-vivo randomized study with 70 endoscopists assessing 100 polyp videos (≤5 mm) using a CADx tool (GI Genius, Medtronic). Participants will be randomized to either: * Intervention group: CADx suggestions will be shown in the last 3 seconds of the 15 second polyp video. * Control group: CADx suggestions will be shown in real-time throughout the playback of the 15 second polyp video. The primary endpoint is sensitivity for high-confidence neoplasia detection, with secondary endpoints assessing endoscopists' reliance on AI. CADx systems on the market function in various ways, such as real-time, delayed, or on-demand diagnosis. Our study aims to inform users and manufacturers whether cognitive forcing through delayed CADx suggestions enhances human-AI interaction, leading to improved clinical outcomes.
Conditions
Conditions (8)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Behavior Change | — | UNRESOLVED | — |
| Colonoscopy | — | UNRESOLVED | — |
| Colorectal Cancer Control and Prevention | — | UNRESOLVED | — |
| Colorectal Cancer Screening | — | UNRESOLVED | — |
| Optical Biopsy | — | UNRESOLVED | — |
| Polyps Colorectal | — | UNRESOLVED | — |
| Psychological Factors | — | UNRESOLVED | — |
| Psychological Intervention | — | UNRESOLVED | — |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| CADx delayed | Behavioral | — | UNRESOLVED |
| CADx simultaneously | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- ACTIVE_COMPARATOR
- label
- CADx suggestions will be shown in 15 second polyp video.
- description
- CADx suggestions will be shown in real-time throughout the playback of the 15 second polyp video.
- interventionNames
- Device: CADx simultaneously
- type
- EXPERIMENTAL
- label
- CADx suggestions will be shown in the last 3 seconds of the 15 second polyp video.
- description
- CADx suggestions will be shown in the last 3 seconds of the 15 second polyp video.
- interventionNames
- Behavioral: CADx delayed
Primary outcomes (1)
- measure
- Sensitivity of the optical diagnosis of neoplastic lesions.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Endoscopists who meet the following inclusion/exclusion criteria Inclusion criteria * Endoscopists experienced with more than 100 colonoscopies. Exclusion criteria * Endoscopists who are involved in the development of the protocol of the present study. Inclusion and exclusion criteria for the study videos. Inclusion criteria. * Videos with a duration of 15 seconds including both WL and NBI. * Videos with diminutive polyps with confirmed pathology. Exclusion criteria. * Videos with no clear image of the polyps. * Videos with more than one polyp on-screen. * Inflammatory bowel disease * Polyposis * Hereditary colorectal disease * Videos which CADx cannot provide sufficient number of outputs.
References
Publications (13)
- BACKGROUNDZana Buçinca, Maja Barbara Malaya, and Krzysztof Z. Gajos. 2021. To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making. Proc. ACM Hum.-Comput. Interact. 5, CSCW1, Article 188 (April 2021), 21 pages. https://doi.org/10.1145/3449287
- BACKGROUNDKunar MA, Watson DG. Framing the fallibility of Computer-Aided Detection aids cancer detection. Cogn Res Princ Implic. 2023 May 24;8(1):30. doi: 10.1186/s41235-023-00485-y. PMID 37222932
- BACKGROUNDKaminski MF, Anderson J, Valori R, Kraszewska E, Rupinski M, Pachlewski J, Wronska E, Bretthauer M, Thomas-Gibson S, Kuipers EJ, Regula J. Leadership training to improve adenoma detection rate in screening colonoscopy: a randomised trial. Gut. 2016 Apr;65(4):616-24. doi: 10.1136/gutjnl-2014-307503. Epub 2015 Feb 10. PMID 25670810
- BACKGROUNDMori Y, Kudo SE, Chiu PW, Singh R, Misawa M, Wakamura K, Kudo T, Hayashi T, Katagiri A, Miyachi H, Ishida F, Maeda Y, Inoue H, Nimura Y, Oda M, Mori K. Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study. Endoscopy. 2016 Dec;48(12):1110-1118. doi: 10.1055/s-0042-113609. Epub 2016 Aug 5. PMID 27494455
- BACKGROUNDMori Y, Jin EH, Lee D. Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy. Dig Liver Dis. 2024 Jul;56(7):1140-1143. doi: 10.1016/j.dld.2023.11.033. Epub 2023 Dec 16. PMID 38105144
- BACKGROUNDMeinikheim M, Mendel R, Palm C, Probst A, Muzalyova A, Scheppach MW, Nagl S, Schnoy E, Rommele C, Schulz DAH, Schlottmann J, Prinz F, Rauber D, Ruckert T, Matsumura T, Fernandez-Esparrach G, Parsa N, Byrne MF, Messmann H, Ebigbo A. Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett's esophagus: a tandem randomized and video trial. Endoscopy. 2024 Sep;56(9):641-649. doi: 10.1055/a-2296-5696. Epub 2024 Mar 28. PMID 38547927