Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study

Cosmo Artificial Intelligence-AI

Status: Completed

Conditions: Artificial Intelligence

Treatments: Device: GI Genius CADe system

Study type: Observational

Funder types: Industry

Identifiers

NCT04589078

CB-17-08/05

Details and patient eligibility

About

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.

Enrollment: 200 patients

Sex: All

Ages: 40 to 80 years old

Volunteers: No Healthy Volunteers

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.

Trial design

200 participants in 1 patient group

Interficial Intelligence

Description:

Each patient will undergo standard white-light colonoscopy with the support of the latest version of the CE marked GI Genius CADe available.

Treatment:

Device: GI Genius CADe system