Impact on Polyp Detection of a Computer Aided Detection System (CADEYE) Combined With a Balloon Mucosal Exposure Device (G-EYE 760R) in Individuals Participating in a Organized Colorectal Cancer Screening Program

The Italian Colorectal Cancer (CRC) screening program invites the resident population aged 50-74 years for Fecal Immunochemical Test (FIT) every 2 years. Subjects who test positive are referred for colonoscopy. Colonoscopy and polypectomy prevent incident cases of colorectal cancer by their detection at an early and curable stage, and by identification and removal of colorectal precancerous lesions (i.e. adenomas). Taking into account the number and the histological features of polyps identified, colonoscopy also allows to stratify individuals according to the risk of developing colorectal cancer over time (low-risk vs. high-risk subjects), thus allowing to plan a balanced risk-based follow-up schedule: high-risk individuals are scheduled for a surveillance colonoscopy in 3 years, whereas low-risk individuals are scheduled for a further FIT test in five years or for a new colonoscopy in 10 years. However, colonoscopy is far from being a flawless tool. Studies that have measured the incidence of colorectal cancer diagnosed in subjects who have recently undergone colonoscopy with negative results (the so-called interval cancers) have shown that a significant portion of interval cancers is related to pre-neoplastic, or frankly neoplastic colonic lesions, missed during the endoscopic procedure.

In the last few years, it has been shown that in patients undergoing colonoscopy for mixed indications AI-based systems can effectively support the endoscopist by decreasing the adenoma miss rate and by increasing the identification of colonic polyps, thus potentially lowering the rate of interval cancer and increasing the rate of individuals scheduled for a short follow-up. A recent study demonstrated that AI-assisted colonoscopy is effective also in the framework of a FIT-based organized CRC screening program resulting in an absolute difference of 8.3% and 0.23 for adenoma detection rate (ADR) and for adenomas per colonoscopy (APC), when compared to standard colonoscopy performed without the assistance of AI. Nevertheless, tandem studies have shown that despite the use of AI systems the miss rate of colonic adenomas is still about 15-20%. In fact, AI systems only allow to highlight polyps that are framed by the endoscopist within the screen. Therefore, the use of computerized AI-based system cannot disregard an accurate retraction technique, focused on exploring in an extensive and effective way the space between the folds. Several tools, mostly consisting of distal attachments or plastic caps, aimed at facilitating the evaluation of the space between the folds favoring their smoothing during the endoscope withdrawal, have been developed to maximize mucosal exposure. Among them, the G-EYE system includes a balloon integrated at the distal tip of a standard colonoscope, which flattens haustral folds, centralizes the colonoscope's optics, and reduces bowel slippage during endoscope withdrawal. Initial studies showed that G-EYE balloon system, when compared with standard colonoscopy, increases not only adenoma detection rate but also the detection of advanced, flat, and sessile serrated adenomas/polyps. Recently, a new user friendly G-EYE balloon system (G-EYE 760R endoscope) has been marketed: it consists of a standard last-generation colonoscope with a permanently integrated balloon, placed at the bending section of the endoscope, which can be gradually insufflated on-demand by the endoscopist through a pedal control. It can be hypothesized that the combination of AI systems with mucosal exposure devices might further decrease the polyp miss rate, by maximizing the detection of adenomas. Moreover, initial studies based on such a strategy, combining AI with mucosal exposure devices, yielded encouraging results. However, the combination of CADEYE with G-EYE 760R endoscopes has not been evaluated so far.

The present prospective randomized controlled trial is aimed at evaluating whether in individuals scheduled for colonoscopy in the framework of a structured FIT-based colorectal cancer screening program, the combination of an AI system (CADEYE) with a mucosal exposure device (G-EYE 760R endoscope) increases the identification of subjects at high risk to develop colorectal cancer, when compared to colonoscopy performed with the support of AI only. In addition, it will be also evaluated whether the use of an AI system combined with a mucosal exposure device, increases:

• the adenoma detection rate (i.e. the rate of individuals with at least one histologically confirmed adenoma)
• the number of adenomas per colonoscopy (i.e. the number of adenomas detected divided by the number of all colonoscopies performed)
• the serrated lesions with neoplastic potential (sessile serrated lesions-SSA; traditional serrated adenomas - TSA) detection rate.
• the detection rate of right colon adenomas
• the detection rate on non-polypoid colonic lesions. Individuals fulfilling the inclusion criteria are randomized (1:1) in two arms (see below). Randomization is based on a computer-generated randomized blocks sequence, stratified according to age (50-61 vs. 62-74) and gender (male vs. female); size of the blocks (10 individuals) is not communicated to the investigator. Allocation is concealed and kept in a sealed envelope, which is opened just before starting the procedure.

Randomization groups: