Improving Optical Diagnosis of Colorectal Polyps Using CADx and BASIC.

NCT04349787 | Completed

• 1 other identifier: METC 2019-1231
• Study Type: observational
• Target: 60
• Locations: 1 country
• Sites: 1

Brief Summary

Primary, this study aims to develop and validate a computer-aided diagnosis (CADx) system for the characterization of colorectal polyps. Second, this study evaluates the effect of using a clinical classification model Blue Light Imaging Adenoma Serrated International (BASIC) on the diagnostic accuracy of the optical diagnosis of colorectal polyps compared to intuitive optical diagnosis for both expert endoscopists and novices.

Conditions

Colorectal Cancer; Colorectal Polyp

Keywords

Artificial intelligence; Computer-aided diagnosis; Optical diagnosis; Colorectal polyps; Blue light imaging

Outcome Measures

Primary Outcomes (1)

• Diagnostic accuracy of CADx versus endoscopists

  The diagnostic accuracy of characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx in comparison to the diagnostic accuracy of both expert endoscopists and novices. In which histology is the gold standard.

  6 months

Secondary Outcomes (7)

• Diagnostic accuracy of BASIC versus intuition

  6 months

• Diagnostic metrics of CADx

  6 months

• AUC of CADx

  6 months

• Diagnostic metrics of endoscopists

  6 months

• Diagnostic metrics of endoscopists for high confidence diagnosis

  6 months

Study Arms (1)

Colorectal polyp patients

Patients who have a colonoscopy in regular care as part of the Dutch colorectal screening program, in the context of complaints or in the context of the follow-up of previously diagnosed bowel diseases. And who have at least one colorectal polyp found and resected during the examination.

Other: Computer-aided diagnosis (CADx); Other: BLI Adenoma Serrated International Classification (BASIC)

Interventions

Computer-aided diagnosis (CADx) OTHER

Optical diagnosis of colorectal polyps made with computer-aided diagnosis (CADx) using state-of-the-art machine learning methods and deep learning architectures.

Colorectal polyp patients

BLI Adenoma Serrated International Classification (BASIC) OTHER

Optical diagnosis of colorectal polyps made with BLI Adenoma Serrated International Classification (BASIC), both by exert endoscopists and novices.

Colorectal polyp patients

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients who had a colonoscopy in the Catharina hospital Eindhoven between January 2017 and December 2018 in the context of the regular bowel cancer screening program, in the context of complaints or in the context of the follow-up of previously diagnosed bowel diseases.

You may qualify if:

• Patients with at least one colorectal polyp found and resected during colonoscopy in regular care;
• Availability of at least one high definition white light image and one Blue Light Imaging (BLI) image of the colorectal polyp;
• Overall high quality of the colorectal polyp image;
• Availability of the histological results of the colorectal polyp;
• Minimal age of 18 years old.

You may not qualify if:

• Objection to participate in medical scientific research, reported in the medical file;
• Endoscopic instruments visible at the colorectal polyp image;
• More than one polyp visible at the colorectal polyp image.

Sponsors & Collaborators

• Maastricht University Medical Center: lead
• Catharina Ziekenhuis Eindhoven: collaborator
• Eindhoven University of Technology: collaborator

Study Sites (1)

Maastricht University Medical Center

Maastricht, Limburg, 6202AZ, Netherlands

Location

Related Publications (4)

• ASGE Technology Committee; Abu Dayyeh BK, Thosani N, Konda V, Wallace MB, Rex DK, Chauhan SS, Hwang JH, Komanduri S, Manfredi M, Maple JT, Murad FM, Siddiqui UD, Banerjee S. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc. 2015 Mar;81(3):502.e1-502.e16. doi: 10.1016/j.gie.2014.12.022. Epub 2015 Jan 16.

  PMID: 25597420 BACKGROUND

• Subramaniam S, Hayee B, Aepli P, Schoon E, Stefanovic M, Kandiah K, Thayalasekaran S, Alkandari A, Bassett P, Coron E, Pech O, Hassan C, Neumann H, Bisschops R, Repici A, Bhandari P. Optical diagnosis of colorectal polyps with Blue Light Imaging using a new international classification. United European Gastroenterol J. 2019 Mar;7(2):316-325. doi: 10.1177/2050640618822402. Epub 2019 Jan 6.

  PMID: 31080616 BACKGROUND

• Byrne MF, Chapados N, Soudan F, Oertel C, Linares Perez M, Kelly R, Iqbal N, Chandelier F, Rex DK. Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model. Gut. 2019 Jan;68(1):94-100. doi: 10.1136/gutjnl-2017-314547. Epub 2017 Oct 24.

  PMID: 29066576 BACKGROUND

• van der Zander QEW, Schreuder RM, Fonolla R, Scheeve T, van der Sommen F, Winkens B, Aepli P, Hayee B, Pischel AB, Stefanovic M, Subramaniam S, Bhandari P, de With PHN, Masclee AAM, Schoon EJ. Optical diagnosis of colorectal polyp images using a newly developed computer-aided diagnosis system (CADx) compared with intuitive optical diagnosis. Endoscopy. 2021 Dec;53(12):1219-1226. doi: 10.1055/a-1343-1597. Epub 2021 Mar 10.

  PMID: 33368056 DERIVED

Biospecimen

Retention: SAMPLES WITHOUT DNA

Colorectal polyps are resected for histological evaluation. This specimen is resected because of regular care, not for study purposes.

MeSH Terms

Conditions

Colorectal Neoplasms

Interventions

Diagnosis, Computer-Assisted

Condition Hierarchy (Ancestors)

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

• Ad Masclee, Prof. Dr.

  Maastricht Universitair Medisch Centrum

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 9, 2020
• First Posted: April 16, 2020
• Study Start: November 26, 2019
• Primary Completion: March 8, 2020
• Study Completion: March 8, 2020
• Last Updated: April 16, 2020

Record last verified: 2020-04

Data Sharing

• IPD Sharing: Will not share

Locations

NL (1)