RecruitingNot ApplicableNCT06059378

Using AI-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps

Using Artificial Intelligence-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps


Sponsor

Daniel Von Renteln

Enrollment

204 participants

Start Date

Sep 1, 2023

Study Type

INTERVENTIONAL

Conditions

Summary

This 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.


Eligibility

Min Age: 45 YearsMax Age: 80 Years

Inclusion Criteria3

  • Age 45-80 years
  • Undergoing an outpatient colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM)
  • Signed informed consent form

Exclusion Criteria5

  • Inflammatory Bowel Disease;
  • Active colitis;
  • Hereditary CRC syndrome;
  • Coagulopathy;
  • American Society of Anesthesiologists (ASA) status >3

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Interventions

DEVICEArtificial intelligence-assisted classification (CADx)

CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.


Locations(1)

Centre Hospitalier de l'Université de Montréal

Montreal, Quebec, Canada

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NCT06059378


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