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

NCT ID: NCT04589078

Last Updated: 2021-05-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-09-08

Study Completion Date

2020-12-22

Brief Summary

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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

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Conditions

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Artificial Intelligence

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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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.

GI Genius CADe system

Intervention Type DEVICE

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

Interventions

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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.

Intervention Type DEVICE

Eligibility Criteria

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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.
Minimum Eligible Age

40 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Cosmo Artificial Intelligence-AI Ltd

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Endoscopy Unit, Humanitas Research Hospital

Rozzano, Milano, Italy

Site Status

Countries

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Italy

Other Identifiers

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CB-17-08/05

Identifier Type: -

Identifier Source: org_study_id

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