Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
- Conditions
- Artificial Intelligence
- Interventions
- Device: GI Genius CADe system
- Registration Number
- NCT04589078
- Lead Sponsor
- Cosmo Artificial Intelligence-AI Ltd
- Brief 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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 200
- 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.
- 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.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Interficial Intelligence GI Genius CADe system Each patient will undergo standard white-light colonoscopy with the support of the latest version of the CE marked GI Genius CADe available.
- Primary Outcome Measures
Name Time Method Negative Predictive Value of histology prediction on diminutive (≤5 mm) rectosigmoid polyps 1 day
- Secondary Outcome Measures
Name Time Method Agreement in assignment of post-polypectomy surveillance intervals 1 day Agreement in assignment of post-polypectomy surveillance intervals according to established guidelines between:
* the assignment identified according to the combined
* GI Genius CADx histology prediction for diminutive (≤5 mm) polyps and
* histology for larger polyps (\> 5 mm), and
* the assignment identified according to histology only.
Trial Locations
- Locations (1)
Endoscopy Unit, Humanitas Research Hospital
🇮🇹Rozzano, Milano, Italy