Real-World Validation of an Artificial Intelligence Characterization Support (CADx) System

NCT05034185 | Completed

• 1 other identifier: CIRB Ref: 2021/2001
• Study Type: observational
• Target: 450
• Locations: 1 country
• Sites: 1

Brief Summary

Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide, with rates of CRC predicted to increase. Colonoscopy is currently the gold standard of screening for CRC. Artificial intelligence (AI) is seen as a solution to bridge this gap in adenoma detection, which is a quality indicator in colonoscopy. AI systems utilize deep neural networks to enable computer-aided detection (CADe) and computer-aided classification (CADx). CADe is concerned with the detection of polyps during colonoscopy, which in turn is postulated to help decrease the adenoma miss-rate. In contrast, CADx deals with the interpretation of polyp appearance during colonoscopy to determine the predicted histology. Prediction of polyp histology is crucial in helping Clinicians decide on a "resect and discard" or "diagnose and leave strategy". It is also useful for the Clinician to be aware of the predicted histology of a colorectal polyp in determining the appropriate method of resection in terms of safety and efficacy. While CADe has been studied extensively in randomized controlled trials, there is a lack of prospective data validating the use of CADx in a clinical setting to predict polyp histology. The investigators plan to conduct a prospective, multi-centre clinical trial to validate the accuracy of CADx support for prediction of polyp histology in real-time colonoscopy.

Conditions

Colonic Polyp; Colonic Neoplasms; Colonic Dysplasia

Keywords

colonoscopy; computer-aided diagnosis; colorectal polyp; colorectal neoplasm; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• To evaluate the diagnostic performance of the CADx support tool compared to optical prediction of polyp histology by the Clinician in real-time colonoscopy in a clinical setting

  Polyp histology used as gold standard

  1 year

Secondary Outcomes (1)

• To determine the diagnostic performance of CADx versus optical prediction of polyp histology by endoscopist in the subgroup analysis

  1 year

Study Arms (1)

Patients with one or more polyps detected

During colonoscopy, the Clinician inspect for the presence of polyps as per routine clinical practice with the CAD EYE function turned off. When a polyp is encountered, the Clinician will make a prediction on the histology based on the white light and BLI features of the polyp with and without optical magnification, as per routine clinical practice. Following this, the CAD EYE function will be switched on and the Clinician will take note of the CADx prediction for the same polyp, which will be either "neoplastic" or "hyperplastic". In addition, other polyp features such as the size and location will be recorded, which is similar to what is performed in routine clinical practice. The polyp will be resected and sent for pathological examination, which will form the "gold standard" for the diagnosis of polyp histology.

Device: Computer-aided diagnosis (CADx) support tool

Interventions

Computer-aided diagnosis (CADx) support tool DEVICE

The CADx support tool operates when the Clinician switches the preconfigured CAD EYE function on using a button on the controller while the scope system is in BLI mode. This is performed after the Clinician first makes an optical prediction of polyp histology using IEE as described. The CADx support tool will make a prediction of polyp histology as "hyperplastic" or "neoplastic".

Patients with one or more polyps detected

Eligibility Criteria

• Age: 40 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

All patients age 40 years and above and who have indications for colonoscopy will be eligible for the study. The patients who have been identified as eligible for the study will be counselled on the details, risks and benefits prior to the performance of colonoscopy. This counselling may take place in the outpatient or inpatient setting. Patients with one or more polyps detected during colonoscopy will be included in the study. The rest of the inclusion and exclusion criteria are as described.

You may qualify if:

• Patients who have an indication for colonoscopy and who have at least one polyp detected during colonoscopy
• years of age and above
• Consent obtained for the study

You may not qualify if:

• Less than 39 years of age
• Declined participation in study
• Patients with no polyps detected during colonoscopy
• Patients with inflammatory bowel disease
• Patients with known unresected colorectal cancer

Sponsors & Collaborators

• Changi General Hospital: lead
• National University Hospital, Singapore: collaborator
• Singapore General Hospital: collaborator
• Tan Tock Seng Hospital: collaborator

Study Sites (1)

Changi General Hospital, National University Hospital, Singapore General Hospital and Tan Tock Seng Hospital

Singapore, 529889, Singapore

Location

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Biospecimen

Retention: SAMPLES WITHOUT DNA

Colorectal polyps detected during colonoscopy will be resected for final histology, which will form the gold standard for evaluation of the diagnostic accuracy of the Clinician using IEE versus the CADx support tool.

MeSH Terms

Conditions

Colonic Polyps; Colonic Neoplasms; Colorectal Neoplasms

Interventions

Diagnosis, Computer-Assisted

Condition Hierarchy (Ancestors)

Intestinal Polyps; Polyps; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms; Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases

Intervention Hierarchy (Ancestors)

Diagnosis

Study Officials

• Dr James Li

  Changi General Hospital, Singapore Health Services

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Consultant

Study Record Dates

• First Submitted: September 2, 2021
• First Posted: September 5, 2021
• Study Start: March 3, 2021
• Primary Completion: July 31, 2022
• Study Completion: October 1, 2022
• Last Updated: February 22, 2023

Record last verified: 2023-02

Data Sharing

• IPD Sharing: Will not share

Locations

SG (1)