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

Sponsor
Cosmo Artificial Intelligence-AI Ltd (Industry)
Overall Status
Completed
CT.gov ID
NCT04589078
Collaborator
(none)
200
1
3.4
58

Study Details

Study Description

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.

Condition or Disease Intervention/Treatment Phase
  • Device: GI Genius CADe system

Study Design

Study Type:
Observational
Actual Enrollment :
200 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
Actual Study Start Date :
Sep 8, 2020
Actual Primary Completion Date :
Dec 22, 2020
Actual Study Completion Date :
Dec 22, 2020

Arms and Interventions

Arm Intervention/Treatment
Interficial Intelligence

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

Device: 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.

Outcome Measures

Primary Outcome Measures

  1. Negative Predictive Value of histology prediction on diminutive (≤5 mm) rectosigmoid polyps [1 day]

Secondary Outcome Measures

  1. 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.

Other Outcome Measures

  1. Sensitivity, Specificity, Accuracy, PPV and NPV of GI Genius CADx histology prediction and endoscopist assessment on all the identified lesions [1 day]

Eligibility Criteria

Criteria

Ages Eligible for Study:
40 Years to 80 Years
Sexes Eligible for Study:
All
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.

Contacts and Locations

Locations

Site City State Country Postal Code
1 Endoscopy Unit, Humanitas Research Hospital Rozzano Milano Italy 20089

Sponsors and Collaborators

  • Cosmo Artificial Intelligence-AI Ltd

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Cosmo Artificial Intelligence-AI Ltd
ClinicalTrials.gov Identifier:
NCT04589078
Other Study ID Numbers:
  • CB-17-08/05
First Posted:
Oct 19, 2020
Last Update Posted:
May 12, 2021
Last Verified:
May 1, 2021
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
Yes
Product Manufactured in and Exported from the U.S.:
No

Study Results

No Results Posted as of May 12, 2021