Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
Trial ID: NCT04589078
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2020-09-08
Completion date: 2020-12-22
Sponsor: Cosmo Artificial Intelligence-AI Ltd
Conditions: Artificial Intelligence
Interventions: GI Genius CADe system
Locations: Endoscopy Unit, Humanitas Research Hospital
Countries: Italy
Enrollment: 200
Age range: 40 Years - 80 Years
Sex: ALL

Summary:
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:

1. 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;
2. 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.

Eligibility criteria:
Inclusion Criteria:

* Patients aged 40-80 undergoing screening colonoscopy for CRC
* Ability to provide written, informed consent (approved by EC) and understand the responsibilities of trial participation.

Exclusion Criteria:

* subjects positive to Fecal Immunochemical Test or Fecal Occult Blood Test;
* subjects undergoing CRC surveillance colonoscopy
* subject at high risk for CRC
* subjects with a personal history of CRC, IBD or hereditary polyposic or non-polyposic syndromes;
* patients with previous resection of the sigmoid rectum;
* patients on anticoagulant therapy, which precludes resection / removal operations due to histopathological findings;
* patients who perform an emergency colonoscopy.

Outcomes:
Negative Predictive Value of histology prediction on diminutive (≤5 mm) rectosigmoid polyps