Clinical trial · Observational

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).

NCT04349787CI-TRIAL-00044703completedClinicalTrials.gov clinicaltrialsPublishedExplore in graph →

Summary

Brief summary (as posted)

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

Conditions (2)

Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.

Condition (as posted)	Mapped entity	Match	Confidence
Colorectal Cancer	Malignant Colorectal Neoplasm	CURATED_BROADER	0.80
Colorectal Polyp	—	UNRESOLVED	—

Interventions

Interventions (2)

Intervention	Type	Mapped drug	Match
BLI Adenoma Serrated International Classification (BASIC)	Other	—	UNRESOLVED
Computer-aided diagnosis (CADx)	Other	—	UNRESOLVED

Design

Arms and outcomes

Arms (1)

label
Colorectal polyp patients
description
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.
interventionNames
1. Other: Computer-aided diagnosis (CADx)
2. Other: BLI Adenoma Serrated International Classification (BASIC)

Primary outcomes (1)

measure
Diagnostic accuracy of CADx versus endoscopists
timeFrame
6 months
description
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.

Secondary outcomes (7)

measure
Diagnostic accuracy of BASIC versus intuition

Eligibility

Eligibility (as posted)

Sex: All
Minimum age: 18 Years

Show eligibility criteria text

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.

References

Publications (4)

BACKGROUNDASGE 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
BACKGROUNDSubramaniam 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
BACKGROUNDByrne 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
DERIVEDvan 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

Registry

Dates and enrollment

Start: Nov 26, 2019
Primary completion: Mar 8, 2020
Completion: Mar 8, 2020
First posted: Apr 16, 2020
Last update posted: Apr 16, 2020
Enrollment: 60 (actual)
Lead sponsor: Maastricht University Medical Center OTHER
Collaborators: Catharina Ziekenhuis Eindhoven; Eindhoven University of Technology
Keywords: Artificial intelligence, Computer-aided diagnosis, Optical diagnosis, Colorectal polyps, Blue light imaging

Data updated 22 days agoSource updated Apr 16, 2020source: clinicaltrials

Locations

Locations by country (1)

Country	Sites	Recruiting
Netherlands	1	0

Trial listing is informational. Eligibility is decided by the study team; contact information is on ClinicalTrials.gov.