Artificial Intelligence for Diminutive Polyp Characterization

Efficacy and Cost-effectiveness of an Artificial Intelligence System (GI-Genius) on the Characterization of Diminutive Colorectal Polyps Within a Colorectal Cancer Screening Program: a Multicenter Randomized Controlled Trial (ODDITY Trial)

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.

Study Overview

• Status: Recruiting
• Conditions: Colorectal Neoplasms
• Intervention / Treatment: Device: GI-Genius artificial intelligence

Detailed 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.

• Study Type: Interventional
• Enrollment (Estimated): 643
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Marco Bustamante Balén, M.D., Ph.D.; Phone Number: 440225 +34 961244000; Email: bustamante_mar@gva.es
• Study Contact Backup: Name: Sylwia Jaworska Fernandez; Phone Number: 9621244262; Email: sylwia_jaworska@iislafe.es

Study Locations

• Spain
  • Valencia, Spain, 46026
    • Recruiting
    • Hospital Universitari i Politecnic La Fe
    • Contact: Sylwia Jaworska Fernandez; Phone Number: 9621244262; Email: sylwia_jaworska@iislafe.es
    • Contact: Marco Bustamante Balén, M.D.;Ph.D.; Phone Number: 440225 961244000; Email: bustamante_mar@gva.es
    • Principal Investigator: Marco Bustamante Balén, M.D.; Ph.D.

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Human optical diagnosis (HOD); 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.
Experimental: Artificial intelligence optical diagnosis (AIOD): 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	Device: GI-Genius artificial intelligence; The software allows for the real-time characterization of framed polyps during a colonoscopy classifying them on adenoma or non-adenoma.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology	A surveillance interval will be assigned using optical diagnosis of ≤ 5 mm polyps (Arm 1: AIOD; Arm 2: HOD of polyps diagnosed with high confidence) plus histopathology of > 5 mm polyps and polyps ≤ 5 mm diagnosed with low confidence. For each patient included, the optical-diagnosis surveillance assignment will be matched with the histology-directed one, and a concordance rate will be calculated. The post-polypectomy surveillance interval will be calculated using the ESGE 2020 and the USMSTF 2020 guidelines. Per-patient analysis.	At the end of the study (2 years)
Comparison of the AIOD and HOD negative predictive value (NPV) for adenoma in rectosigmoid polyps ≤ 5 mm with respect to histology	The optical diagnosis of ≤ 5 mm rectosigmoid polyps (Arm 1: AIOD; Arm 2: HOD, only high-confidence diagnosis) reliability on ruling out the presence of an adenoma will be calculated using histopathology as the gold standard. Per-lesion analysis. NPV = number of confirmed hyperplastic polyps/number of hyperplastic optical diagnosis	At the end of the study (2 years)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Comparison of the AIOD and HOD diagnostic accuracy parameters of polyps ≤ 5 mm (Arm 1: AIOD; Arm 2: HOD) with respect to histology	Operative characteristics (sensitivity, specificity, positive and negative predictive value and positive likely hood ratio) using histopathology as the gold standard. Per-lesion analysis	Interim analysis (when half of the sample size had been included). At the end of the study (2 years)
Cost-effectiveness of AIOD	The economic burden of applying the AIOD and HOD to assign the post-polypectomy surveillance intervals compared to the histology-driven strategy. A direct cost evaluation will be performed including medical and non-medical costs. Per-patient analysis.	At the end of the study (2 years)
Comparison of the proportion of adverse events in colonoscopies with and without the AIOD device.	The occurrence and severity of adverse events in colonoscopies with and without the AIOD device will be monitored during the 30-days period after the procedure. Adverse events are defined as: abdominal pain or discomfort, post-polypectomy bleeding, perforation, post-polypectomy syndrome and infection. Per-patient analysis	30 days after the colonoscopy (Day 30)
Proportion of patients accepting to have their polyps diagnosed by the AI system or human optical diagnosis (designed questionnaire)	The proportion of patients willing to have their polyps diagnosed by an AI system or HOD will be assessed using a structured questionnaire. Per-patient analysis.	Day of colonoscopy (Day 1)

Collaborators and Investigators

• Sponsor: Hospital Universitario La Fe
• Collaborators: Medtronic; European Society of Gastrointestinal Endoscopy
• Investigators: Principal Investigator: Marco Bustamante Balén, M.D., Ph.D., Hospital Universitario la Fe

Study record dates

Study Major Dates

• Study Start (Actual): February 27, 2023
• Primary Completion (Estimated): May 1, 2024
• Study Completion (Estimated): December 1, 2024

Study Registration Dates

• First Submitted: April 5, 2022
• First Submitted That Met QC Criteria: May 24, 2022
• First Posted (Actual): May 26, 2022

Study Record Updates

• Last Update Posted (Actual): May 31, 2023
• Last Update Submitted That Met QC Criteria: May 30, 2023
• Last Verified: May 1, 2023

More Information

Terms related to this study

• Keywords: Colorectal cancer; Artificial Intelligence; Polyp; Characterization
• Additional Relevant MeSH Terms: Digestive System Diseases; Neoplasms; Neoplasms by Site; Gastrointestinal Neoplasms; Digestive System Neoplasms; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Intestinal Neoplasms; Rectal Diseases; Colorectal Neoplasms
• Other Study ID Numbers: Oddity

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No