An interventional study of Artificial Intelligence System (CAD EYE, Fujifilm Co.) in Polyp of Colon, sponsored by Valduce Hospital. Completed at 1 site in Italy. Open to participants aged 50 Years to 74 Years. Per ClinicalTrials.gov, last updated 2024-03-26.
Sponsored by Valduce Hospital · Not applicable, Interventional, and Screening
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.
377 studies on the registry are indexed under Colonic Polyps; 57 are open to participants now.
This study's enrollment of 750 is above the median of 274 across 250 interventional studies indexed under Colonic Polyps.
Browse Colonic Polyps studies →Valduce Hospital is the lead sponsor of 29 studies on the registry; none are open to participants now.
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Exclusion Criteria:
all 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.
all patients receive colonoscopy examinations (with HD endoscopes) equipped with an Ai system (CAD-EYE, Fujifilm Co, Tokyo, Japan) in both insertion and withdrawal phase). This 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.All polyps identified are removed and sent for histopathology examination.
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.
ADR
Adenoma Detection Rate: rate of participants with at least on adenoma detected during colonoscopy
Time frame: 10 months
APC
Adenoma per Colonoscopy: it is determined by dividing the total number of adenomas removed by the total number of colonoscopies performed
Time frame: 10 months
Adv-ADR
Adv-ADR: rate of participants with at least on advanced adenoma detected during colonoscopy
Time frame: 10 months
SSL-DR:
SSL-ADR: the serrated lesions with neoplastic potential (sessile serrated lesions-SSA; traditional serrated adenomas - TSA) detection rate.
Time frame: 10 months
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
Time frame: 10 months
Plan to share: No
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This study is completed, as verified in Mar 2024. You cannot join it, but the record below documents what was studied.
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Valduce Hospital