Artificial Intelligence for Diminutive Polyp Characterization

La Fe University and Polytechnic Hospital

Status: Enrolling

Conditions: Colorectal Neoplasms

Treatments: Device: GI-Genius artificial intelligence

Study type: Interventional

Funder types: Other; Industry

Identifiers

NCT05391477

Oddity

Details and patient eligibility

About

Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.

Full description

The resect-and-discard (R&D) and diagnose-and-leave (D&L) strategies have been proposed as a means to reduce costs in the evaluation of colorectal polyps avoiding a substantial number of pathology evaluations. A pre-requisite for this paradigm shift is an accurate optical diagnosis (HOD). However, performance results for HOD have been highly variable among endoscopists representing a barrier for the adoption of the R&D and the D&L strategies.

Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.

Methods and analysis: The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group or the HOD (control) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.

Enrollment: 643 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients attending a colonoscopy within a population-based CRC screening program (FIT- or colonoscopy-based) or because of post-polypectomy surveillance,
• Written informed consent before the colonoscopy,

Exclusion criteria

• None, patient included
• Previous history of inflammatory bowel disease.
• Previous history of CRC
• Previous CR resection
• Polyposis or hereditary CRC syndrome
• Coagulopathy/Anticoagulants
• Unwillingness to participate

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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643 participants in 2 patient groups

Human optical diagnosis (HOD)

No Intervention group

Description:

The examinator will provide a HOD for every lesion (regardless of their size) found during the examination (adenoma vs non-adenoma) following one of the available validated classifications (NICE, JNET, BASIC). He/she will also give a level of confidence in his/her diagnosis (high/low confidence). However, only diminutive lesions will be considered when analyzing the main outcome. The time to get a HOD will be recorded. An in situ surveillance interval will be provided if possible.

Artificial intelligence optical diagnosis (AIOD):

Experimental group

Description:

GI-Genius will provide an artificial intelligence diagnosis (AIOD) for every lesion detected (adenoma vs non-adenoma). Only diminutive lesions will be considered for the analysis of the main outcome. However, data on larger lesions will be recorded to describe GI-Genius´ performance in detail (secondary outcome). The time to get an AIOD will be recorded. An in situ surveillance interval will be provided if possible

Treatment:

Device: GI-Genius artificial intelligence