Improving Optical Diagnosis of Colorectal Polyps Using CADx and BASIC.

Improving Optical Diagnosis of Colorectal Polyps Using Computer-aided Diagnosis (CADx) and the BLI Adenoma Serrated International Classification (BASIC).

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.

Study Overview

• Status: Completed
• Conditions: Colorectal Cancer; Colorectal Polyp
• Intervention / Treatment: Other: Computer-aided diagnosis (CADx); Other: BLI Adenoma Serrated International Classification (BASIC)

Detailed Description

Optical diagnosis of colorectal polyps, the in-vivo characterization of the histology by endoscopists, is of increasing interest for clinical endoscopy practice. Recent studies have shown that thresholds for optical diagnosis are met in highly selected groups of expert endoscopists, but the same is not true in community endoscopy practices. In order to improve optical diagnosis, imaging enhancement techniques and the use of artificial intelligence are proposed.

This observational study developes a computer-aided diagnosis (CADx) system to differentiate between benign and (pre-)malignant CRPs, using state-of-the-art machine learning methods and deep learning architectures. For the development, HDWL and BLI images are used. The CADx is trained using histology as gold standard. The CADx is externally validated using on a set of 60 colorectal polyps. This study will evaluate if the optical diagnosis of colorectal polyps can be improved with the aid of CADx.

In addition, both expert endoscopists and novices optically diagnose the colorectal polyps. In the first, pre-training phase, endoscopists optically diagnose colorectal polyps based on intuition. Afterwards, in the post-training phase, the same set of colorectal polyps is optically diagnosed based on a clinical classification system; BLI Adenoma Serrated International Classification (BASIC). This study will evaluate if the optical diagnosis of colorectal polyps can be improved with the aid of BASIC in both expert and non-expert hands.

• Study Type: Observational
• Enrollment (Actual): 60

Contacts and Locations

Study Locations

• Netherlands
  • Limburg
    • Maastricht, Limburg, Netherlands, 6202AZ
      • Maastricht University Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• 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.

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

• 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.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

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); Optical diagnosis of colorectal polyps made with computer-aided diagnosis (CADx) using state-of-the-art machine learning methods and deep learning architectures.; Other: BLI Adenoma Serrated International Classification (BASIC); Optical diagnosis of colorectal polyps made with BLI Adenoma Serrated International Classification (BASIC), both by exert endoscopists and novices.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic accuracy of BASIC versus intuition	The diagnostic accuracy of both expert endoscopists and novices in characterizing colorectal polyps (into hyperplastic polyp, adenoma, sessile serrated adenoma, or adenocarcinoma) based on the clinical classification model BASIC, in comparison to the diagnostic accuracy based on intuition. In which histology is the gold standard.	6 months
Diagnostic metrics of CADx	The sensitivity, specificity, negative and positive predictive value of characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx.	6 months
AUC of CADx	Area Under ROC Curve (AUC) of CADx for characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx.	6 months
Diagnostic metrics of endoscopists	The sensitivity, specificity, negative and positive predictive value of characterizing colorectal polyps (into hyperplastic polyp, adenoma, sessile serrated adenoma, or adenocarcinoma) of both expert endoscopists and novices.	6 months
Diagnostic metrics of endoscopists for high confidence diagnosis	The diagnostic accuracy, sensitivity, specificity, negative and positive predictive value of both expert endoscopists and novices for optical diagnosis made with high (>90%) confidence.	6 months
Interobserver agreement	The interobserver agreement of experts, novices and CADx for characterizing colorectal polyps.	6 months
Computation time of CADx	The computation time per image of CADx for characterizing colorectal polyps.	6 months

Collaborators and Investigators

• Sponsor: Maastricht University Medical Center
• Collaborators: Catharina Ziekenhuis Eindhoven; Eindhoven University of Technology
• Investigators: Principal Investigator: Ad Masclee, Prof. Dr., Maastricht Universitair Medisch Centrum

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Actual): November 26, 2019
• Primary Completion (Actual): March 8, 2020
• Study Completion (Actual): March 8, 2020

Study Registration Dates

• First Submitted: April 9, 2020
• First Submitted That Met QC Criteria: April 14, 2020
• First Posted (Actual): April 16, 2020

Study Record Updates

• Last Update Posted (Actual): April 16, 2020
• Last Update Submitted That Met QC Criteria: April 14, 2020
• Last Verified: April 1, 2020

More Information

Terms related to this study

• Keywords: Artificial intelligence; Colorectal polyps; Blue light imaging; Optical diagnosis; Computer-aided diagnosis
• Additional Relevant MeSH Terms: Pathologic Processes; Pathological Conditions, Anatomical; Disease; Polyps
• Other Study ID Numbers: METC 2019-1231

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: At this moment, there is no plan to share individual participant data.

Drug and device information, study documents

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