Artificial Intelligence for Diminutive Polyp Characterization

Colorectal Neoplasms Clinical Trial

Official title:

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)

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05391477
• Other study ID #: Oddity
• Status: Recruiting
• Phase: N/A
• Start date: February 27, 2023
• Est. completion date: December 2024

Study information

• Verified date: May 2023
• Source: Hospital Universitario La Fe
• Contact: Marco Bustamante Balén, M.D., Ph.D.
• Phone: +34 961244000
• Email: bustamante_mar[@]gva.es
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 643
• Est. completion date: December 2024
• Est. primary completion date: May 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

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

Related Conditions & MeSH terms

• Colorectal Neoplasms

Intervention

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.

Locations

Country	Name	City	State
Spain	Hospital Universitari i Politècnic La Fe	Valencia

Sponsors (3)

Lead Sponsor	Collaborator
Hospital Universitario La Fe	European Society of Gastrointestinal Endoscopy, Medtronic

Country where clinical trial is conducted

Spain, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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)
Primary	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	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)
Secondary	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)
Secondary	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)
Secondary	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)