Impact of Artificial Intelligence (AI) on Adenoma Detection During Colonoscopy in FIT+ Patients.

Polyp of Colon Clinical Trial

— AIFIT  

Official title:

Impact of AI (Artificial Intelligence) on Adenoma Detection During Colonoscopy in FIT+ Patients: a Prospective Randomized Controlled Trial

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04691401
• Other study ID #: 598/2020
• Status: Completed
• Phase: N/A
• Start date: December 20, 2020
• Est. completion date: December 31, 2021

Study information

• Verified date: March 2024
• Source: Valduce Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 750
• Est. completion date: December 31, 2021
• Est. primary completion date: October 31, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 50 Years to 74 Years

Eligibility

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

Related Conditions & MeSH terms

• Adenoma
• Colonic Polyps
• Polyp of Colon

Intervention

Device:
• Artificial Intelligence System (CAD EYE, Fujifilm Co.)
A dedicated CNN-based AI system (CAD EYE, Fujifilm Co, Tokyo, Japan) has been recently developed. The Computer-aided diagnosis (CAD) CAD EYE system is a real-time computer-assisted image analysis that allows automatic polyp identification without modifications to the colonoscope or to the actual endoscopic procedure. When CAD EYE identifies a polyp, both a visual (a green blinking box surrounding the identified polyp, called the detection box) and an acoustic alarm pop up and attract the endoscopist attention. Around the endoscopic image a visual assist circle is shown and lights up in the direction where the suspicious polyp is detected.

Locations

Country	Name	City	State
Italy	Gastroenterology Unit, Valduce Hospital	Como

Sponsors (1)

Lead Sponsor	Collaborator
Valduce Hospital

Country where clinical trial is conducted

Italy, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Impact of Ai on endoscopist with different ADR	The variation in ADR will be stratified according the initial ADR of endoscopists participating in the present study	10 months
Primary	ADR	Adenoma Detection Rate: rate of participants with at least on adenoma detected during colonoscopy	10 months
Primary	APC	Adenoma per Colonoscopy: it is determined by dividing the total number of adenomas removed by the total number of colonoscopies performed	10 months
Secondary	Adv-ADR	Adv-ADR: rate of participants with at least on advanced adenoma detected during colonoscopy	10 months
Secondary	SSL-DR:	SSL-ADR: the serrated lesions with neoplastic potential (sessile serrated lesions-SSA; traditional serrated adenomas - TSA) detection rate.	10 months