Optical Diagnosis of Neoplasia Using Artificial Intelligence

Condition(s) studied

Investigational drug(s) / intervention(s)

CADx simultaneously: The investigators showed the CADx suggestion during the 15-second playback of the video

CADx delayed: During the 15-seconds polyp video the CADx suggestion appear only in the last 3 seconds of the video

Study summary

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.

Eligibility

Primary outcome measure(s)

• Sensitivity of the optical diagnosis of neoplastic lesions. — Through study completion, an average of 1 year
  \- Sensitivity of each endoscopist and in each arm in the optical diagnosis of neoplastic or non-neoplastic lesions with high confidence level

Trial sites (2)

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