Cosmo Artificial Intelligence - Ai Ltd.

The aim of the study is to assess whether the use of artificial intelligence improves polyp detection in a segment of the colon (the right colon).
To achieve this objective, patients will be divided into two groups: one will undergo a standard colonoscopy, the other a colonoscopy with the artificial intelligence software connected to the machine.
This software does not modify the colonoscopy technique in any way, and does not require the administration of any product to the patient.
The study will compare the detection rate of right colon polyps between the group of patients who underwent standard colonoscopy and those who underwent colonoscopy with artificial intelligence. If this number does not differ between the two groups, the investigators can conclude that there is no point in using artificial intelligence.

Diminutive colorectal polyps (≤ 5 mm) represent most of the polyps detected during colonoscopy, especially in the rectum-sigmoid tract. The characterization of these polyps by virtual chromoendoscopy is recognized as a key element for innovative imaging techniques. As a matter of facts diminutive colorectal polyps are very frequent and, if located in the rectosigmoid colon, they present a very low malignant risk (0.3% of evolution towards advanced adenoma and up to 0.08% of evolution towards invasive carcinoma). The real-time characterization would allow to identify the lowest risk polyps (hyperplastic subtype), to leave them in situ or, if resected, not to send them for histological examination, allowing a huge saving in healthcare associated costs.
Recently, the American Society for Gastrointestinal Endoscopy (ASGE) Technology Committee established the Preservation and Incorporation of Valuable endoscopic Innovations (PIVI) document, specific for real-time histological assessment for tiny colorectal polyps, to establish reference quality thresholds. Two performance standards have been developed to guide the use of advanced imaging:
for diminutive polyps to be resected and discarded without pathologic assessment, endoscopic technology (when used with high confidence) used to determine histology of polyps ≤ 5mm in size, when combined with the histopathology assessment of polyps > 5 mm in size, should provide a ≥ 90% agreement in assignment of post-polypectomy surveillance intervals when compared to decisions based on pathology assessment of all identified polyps;
in order for a technology to be used to guide the decision to leave suspected rectosigmoid hyperplastic polyps ≤ 5 mm in size in place (without resection), the technology should provide ≥ 90% negative predictive value (when used with high confidence) for adenomatous histology.
Computer-Aided-Diagnosis (CAD) is an artificial intelligence-based tool that would allow rapid and objective characterization of these lesions. The GI Genius CADx was developed to help endoscopists in their clinical practices for polyps characterization.

The aim of this study is to assess the performance of the CB-17-08 to help endoscopists find potential mucosal polyps during the colonoscopy procedure, without significant noise disturbing the endoscopist attention, nor negative interference with the lesions detection than with the standard colonoscopy alone: the study will investigate whether the use of the device provides an increase in the number of adenomas per colonoscopy as compared to standard colonoscopy. The study will also evaluate the safety of the CB-17-08, assessing if the use of the system increases the total number of excisions without a commensurate number of adenomas as compared to standard colonoscopy.