Clinical trial NCT04691401: Impact of Artificial Intelligence (AI) on Adenoma Detection During Colonoscopy in FIT+ Patients.
Official title: Impact of AI (Artificial Intelligence) on Adenoma Detection During Colonoscopy in FIT+ Patients: a Prospective Randomized Controlled Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Polyp of Colon
Keywords: adenoma detection
Lead sponsor: Valduce Hospital
Sponsor class: OTHER
First posted: 2020-12-31
Enrollment: 750
Sex: ALL
Minimum age (years): 50
Maximum age (years): 74
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: SCREENING

Brief summary: The Italian screening program invites the resident population aged 50-74 for Fecal Immunochemical Test (FIT) every 2 years. Subjects who test positive are referred for colonoscopy. Maximizing adenoma detection during colonoscopy is of paramount importance in the framework of an organized screening program, in which colonoscopy represent the key examination. Initial studies consistently show that Artificial iIntelligence-based systems support the endoscopist in evaluating colonoscopy images potentially increasing the identification of colonic polyps. However, the studies on AI and polyp detection performed so far are mostly focused on technical issues, are based on still images analysis or recorded video segments and includes patients with different indications for colonoscopy. At the best of our knowledge, data on the impact on AI system in adenoma detection in a FIT-based screening program are lacking. The present prospective randomized controlled trial is aimed at evaluating whether the use of an AI system increases the ADR (per patient analysis) and/or the mean number of adenomas per colonoscopy in FIT-positive subjects undergoing screening colonoscopy. Therefore Patients fulfilling the inclusion criteria are randomized (1:1) in two arms: A) patients receive standard colonoscopy (with high definition-HD endoscopes) with white light (WL) in both insertion and withdrawal phase; all polyps identified are removed and sent for histopathology examination; B) patients receive colonoscopy examinations (with HD endoscopes) equipped with an AI system (in both insertion and withdrawal phase); all polyps identified are removed and sent for histopathology examination. In the present study histopathology represents the reference standard.


Eligibility criteria: Inclusion Criteria:

* Consecutive adult (50-74 yrs.) outpatients undergoing colonoscopy in the frame of the FIT-based screening program.

Exclusion Criteria:

* patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer
* patients with inadequate bowel preparation
* patients in which cecal intubation was not achieved or scheduled for partial examinations
* patients with gastrointestinal symptoms
* polyps could not be resected due to ongoing anticoagulation preventing resection and pathological assessment

Primary outcomes:
measure: ADR
timeFrame: 10 months
measure: APC
timeFrame: 10 months
Secondary outcomes:
measure: Adv-ADR
timeFrame: 10 months
measure: SSL-DR:
timeFrame: 10 months
Other outcomes:
measure: Impact of Ai on endoscopist with different ADR
timeFrame: 10 months
Locations:
city: Como
country: Italy
facility: Gastroenterology Unit, Valduce Hospital
Study officials:
References: