Using AI-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps
Artificial IntelligenceThis is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard.
The primary aim of this study is to show the accuracy of intracolonoscopy AI-assisted optical diagnosis (CADx; autonomous or with human input) when the AI-assisted optical diagnosis made by the expert endoscopists is used as the reference standard. The specific aims are:
1. To evaluate the accuracy of intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) by comparing it to the obtained optical histology diagnoses provided by two independent expert endoscopists as the reference standard.
2. To evaluate the agreement between the intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) and the AI-assisted optical diagnosis performed by two independent expert endoscopists.
3. To determine whether AI-assisted optical polyp diagnosis for diminutive (1-5 mm) polyps can be implemented in routine clinical practice by demonstrating that at least 70% of the approached patients are interested in undergoing AI-assisted optical diagnosis (autonomous or with human input).
4. To evaluate the cost savings resulting from replacing pathology with AI-assisted optical diagnosis.
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Participation Requirements
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Sex:
ALL -
Eligible Ages:
45 to 80
Participation Criteria
Inclusion Criteria:
* Age 45-80 years
* Undergoing an outpatient colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM)
* Signed informed consent form
Exclusion Criteria:
* Inflammatory Bowel Disease;
* Active colitis;
* Hereditary CRC syndrome;
* Coagulopathy;
* American Society of Anesthesiologists (ASA) status \>3
Study Location
Centre Hospitalier de l'Université de Montréal
Centre Hospitalier de l'Université de MontréalMontréal, Quebec
Canada
Contact Study Team
- Study Sponsored By
- Centre hospitalier de l'Université de Montréal (CHUM)
- Participants Required
- More Information
- Study ID:
NCT06059378