Computer-aided Detection During Screening Colonoscopy (Experts)

NCT ID: NCT04915833

Last Updated: 2022-03-31

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: NA
• Total Enrollment: 209 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-04-26
• Study Completion Date: 2022-06-28

Brief Summary

Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).

The endoscopy images will be seen on a 27inch, flat-panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.

The number, location, and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare.

The same patient will be submitted to a second, the same session, computed aided real-time colonoscopy using the DISCOVERY, AI-assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.

Detailed Description

Screening colonoscopy has decreased the incidence of colorectal carcinoma in the previous decades. However, there are reports of missed polyps and interval CRC following screening colonoscopy. Several factors may affect the ADR, PDR, and missed lesions rates, such as bowel preparation, percentage of mucosal surface evaluation, and the training levels of operators.

Artificial intelligence using deep-learning algorithms has been implemented in gastrointestinal endoscopy, mainly for the detection and diagnosis of GI tract lesions such as colonic polyps and adenomas. The implementation of automated polyp detection software during screening colonoscopy may prevent the missing of polyp and adenoma during screening colonoscopy. Therefore, improving the ADR and PDR during colonoscopies. All of this, with the aim of decrease the incidence of interval colorectal carcinoma (CRC), and CRC-related morbidity and mortality.

The Discovery Artificial Intelligence assisted polyp detector (Pentax Medical, Hoya Group) was recently launched for clinical practice. This AI software was trained with 120,000 files from approximately 300 clinical cases. The visual aided detection (bounding box locating a polyp on the monitor) will alert the endoscopist if a polyp/adenoma was missed during the standard, screening procedure.

To the best of our knowledge, this may be the first study evaluating the Discovery AI-assisted polyp detector on clinical practice in the western hemisphere. The investigators aim to evaluate the real-world effectiveness of AI-assisted colonoscopy in clinical practice. The investigators will also evaluate the role of endoscopists' levels of training in the ADR, PDR, and missed lesion rate.

Conditions

Colorectal Neoplasms; Colon Polyp; Colon Adenoma

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Patients for CRC screening and diagnostic colonoscopy

Consecutive patients \>45 years of age submitted for diagnostic colonoscopy

Group Type: EXPERIMENTAL

Standard high-definition colonoscopy

Intervention Type: DIAGNOSTIC_TEST

Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).

The endoscopy images will be seen on a 27inch, flat panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.

The number, location and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare and forceps biopsy.

Colonoscopy with real-time AI assisted automated polyp detection

Intervention Type: DIAGNOSTIC_TEST

The same patient will be submitted to a second, same session, computed aided real-time colonoscopy using the DISCOVERY, AI assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.

Interventions

Standard high-definition colonoscopy

Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).

The endoscopy images will be seen on a 27inch, flat panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.

The number, location and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare and forceps biopsy.

Intervention Type: DIAGNOSTIC_TEST

Colonoscopy with real-time AI assisted automated polyp detection

The same patient will be submitted to a second, same session, computed aided real-time colonoscopy using the DISCOVERY, AI assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Provided informed written consent
• Age greater than 45 years of age
• Adequate Bowel preparation

Exclusion Criteria

• History of inflammatory bowel disease, familial polyposis syndrome
• History of colorectal carcinoma, colorectal surgery
• History of uncontrolled coagulopathy
• History of previously failed attempt colonoscopy

• Minimum Eligible Age: 45 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Instituto Ecuatoriano de Enfermedades Digestivas

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Carlos Robles-Medranda, MD FASGE

Role: PRINCIPAL_INVESTIGATOR

Ecuadorian Institute of Digestive Diseases

Locations

Ecuadorian Institute of Digestive Diseases

Guayaquil, Guayas, Ecuador

Site Status: RECRUITING

Countries

Ecuador

Central Contacts

Carlos Robles-Medranda, MD

Role: CONTACT

carlosoakm@yahoo.es

+59342109180

Facility Contacts

Carlos A Robles-Medranda, MD

Role: primary

carlosoakm@yahoo.es

+593989158865

References

Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.

Reference Type: BACKGROUND

PMID: 30814121 (View on PubMed)

Vinsard DG, Mori Y, Misawa M, Kudo SE, Rastogi A, Bagci U, Rex DK, Wallace MB. Quality assurance of computer-aided detection and diagnosis in colonoscopy. Gastrointest Endosc. 2019 Jul;90(1):55-63. doi: 10.1016/j.gie.2019.03.019. Epub 2019 Mar 26.

Reference Type: BACKGROUND

PMID: 30926431 (View on PubMed)

Other Identifiers

IECED-042621

Identifier Type: -

Identifier Source: org_study_id