Real-time Diagnosis of Diminutive Colorectal Polyps Using AI

Colorectal Neoplasms Clinical Trial

— COMET-OPTICAL  

Official title:

Real Time Computer-aided Diagnosis (CADx) of Diminutive Colorectal Polyps Using Artificial Intelligence

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05349110
• Other study ID #: METC2021-3036
• Status: Recruiting
• Start date: August 20, 2021
• Est. completion date: December 2022

Study information

• Verified date: April 2022
• Source: Maastricht University Medical Center
• Contact: Quirine van der Zander, Drs MD
• Phone: 031433882241
• Email: q.vanderzander[@]maastrichtuniversity.nl
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Artificial intelligence has great potential in image analysis in gastrointestinal endoscopy. Aim of this study is to investigate the real-time diagnostic performance of AI4CRP for the classification of diminutive colorectal polyps, and to compare it with the real-time diagnostic performance of commercially available CADx systems.

Description:

Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Despite additional training, even experienced endoscopists continue to fail meeting international thresholds set for safe implementation of treatment strategies based on optical diagnosis.

Multiple machine learning techniques - computer-aided diagnosis (CADx) systems - have been developed for applications in medical imaging within colonoscopy and can improve endoscopic classification of colorectal polyps.

Aim of this study is to explore the feasibility of the workflow using AI4CRP (a CNN based CADx system) real-time in the endoscopy suite, and to investigate the real-time diagnostic performance of AI4CRP for the diagnosis of diminutive (<5mm) colorectal polyps. Secondary, the real-time performance of commercially available CADx systems will be investigated and compared with AI4CRP performance.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 105
• Est. completion date: December 2022
• Est. primary completion date: September 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Age >18 years;

• Patients with at least one colorectal polyps encountered during colonoscopy;

• Patients referred for a colonoscopy by the Dutch bowel cancer screening program, patients undergoing a colonoscopy for endoscopic surveillance, or patients undergoing a colonoscopy because of complaints;

• Written informed consent.

Exclusion Criteria:

• Patients with prior history of inflammatory bowel diseases (IBD) or polyposis syndromes;

• Patients with inadequate bowel preparations after adequate washing, suctioning, and cleaning manoeuvres have been performed by the endoscopist;

• Patients undergoing an emergency colonoscopy;

• Written objection in the patient file for participation in scientific research.

Related Conditions & MeSH terms

• Colorectal Neoplasms
• Colorectal Polyp
• Polyps

Intervention

Device:
• Computer-aided diagnosis (CADx) systems
AI4CRP (artificial intelligence for colorectal polyps), a CNN based computer-aided diagnosis system for diagnosis of colorectal polyps (COMET-OPTICAL research group); CAD EYE, a computer-aided diagnosis system for diagnosis of colorectal polyps (Fujifilm® Corporation, Tokyo, Japan).

Locations

Country	Name	City	State
Netherlands	Catharina Ziekenhuis Eindhoven	Eindhoven	Noord-Brabant
Netherlands	Maastricht University Medical Center	Maastricht	Limburg

Sponsors (3)

Lead Sponsor	Collaborator
Maastricht University Medical Center	Catharina Ziekenhuis Eindhoven, Eindhoven University of Technology

Country where clinical trial is conducted

Netherlands, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Technical feasibility of real-time use of AI4CRP.	The technical feasibility of real-time use of AI4CRP in the endoscopy suite regarding a proper reception of the video output from the local endoscopy processor towards AI4CRP (in high definition quality, without any delays in time).	6 months
Primary	User interface feasibility of real-time use of AI4CRP.	The user interface feasibility of real-time use of AI4CRP in the endoscopy suite regarding a correct alignment of the user interface of AI4CRP with the video output from the local endoscopy system (resizing image pixels and anonymization).	6 months
Primary	The diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	The real-time diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan). Diagnostic accuracy defined as the percentage of correctly optically diagnosed colorectal polyps.	1 year
Primary	The sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	The real-time sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	1 year
Primary	The specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	The real-time specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	1 year
Primary	The negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	The real-time negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	1 year
Primary	The positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	The real-time positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	1 year
Primary	The Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	The real-time Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).	1 year
Secondary	The diagnostic accuracy of AI4CRP per polyp.	The real-time diagnostic accuracy of AI4CRP per polyp (comprising the combination of different imaging modalities).	1 year
Secondary	The sensitivity of AI4CRP per polyp.	The real-time sensitivity of AI4CRP per polyp (comprising the combination of different imaging modalities).	1 year
Secondary	The specificity of AI4CRP per polyp.	The real-time specificity of AI4CRP per polyp (comprising the combination of different imaging modalities).	1 year
Secondary	The negative predictive value of AI4CRP per polyp.	The real-time negative predictive value of AI4CRP per polyp (comprising the combination of different imaging modalities).	1 year
Secondary	The positive predictive value of AI4CRP per polyp.	The real-time positive predictive value of AI4CRP per polyp (comprising the combination of different imaging modalities).	1 year
Secondary	The Area Under ROC Curve (AUC) of AI4CRP per polyp.	The real-time Area Under ROC Curve (AUC) of AI4CRP per polyp (comprising the combination of different imaging modalities).	1 year
Secondary	The diagnostic accuracy of CAD EYE in BLI mode, per polyp.	The real-time diagnostic accuracy of CAD EYE in BLI mode, per polyp.	1 year
Secondary	The sensitivity of CAD EYE in BLI mode, per polyp.	The real-time sensitivity of CAD EYE in BLI mode, per polyp.	1 year
Secondary	The specificity of CAD EYE in BLI mode, per polyp.	The real-time specificity of CAD EYE in BLI mode, per polyp.	1 year
Secondary	The negative predictive value of CAD EYE in BLI mode, per polyp.	The real-time negative predictive value of CAD EYE in BLI mode, per polyp.	1 year
Secondary	The positive predictive value of CAD EYE in BLI mode, per polyp.	The real-time positive predictive value of CAD EYE in BLI mode, per polyp.	1 year
Secondary	The Area Under ROC Curve (AUC) of CAD EYE in BLI mode, per polyp.	The real-time Area Under ROC Curve (AUC) of CAD EYE in BLI mode, per polyp.	1 year
Secondary	The diagnostic accuracy of AI4CRP per patient.	The real-time diagnostic accuracy of AI4CRP per patient (in case of multiple polyps per patient).	1 year
Secondary	The diagnostic accuracy of CAD EYE per patient.	The real-time diagnostic accuracy of CAD EYE per patient (in case of multiple polyps per patient).	1 year
Secondary	The localization score of AI4CRP.	The localization score of AI4CRP regarding the number of images in which the heatmap produced by AI4CRP pointed out the area of interest (scale: correct, incorrect, or partly correct area of interest).	1 year
Secondary	The difference in diagnostic accuracy of endoscopists per polyp before and after AI.	The difference in real-time diagnostic accuracy of endoscopists per polyp before and after AI.	1 year
Secondary	The difference in sensitivity of endoscopists per polyp before and after AI.	The difference in real-time sensitivity of endoscopists per polyp before and after AI.	1 year
Secondary	The difference in specificity of endoscopists per polyp before and after AI.	The difference in real-time specificity of endoscopists per polyp before and after AI.	1 year
Secondary	The difference in negative predictive value of endoscopists per polyp before and after AI.	The difference in real-time negative predictive value of endoscopists per polyp before and after AI.	1 year
Secondary	The difference in positive predictive value of endoscopists per polyp before and after AI.	The difference in real-time positive predictive value of endoscopists per polyp before and after AI.	1 year
Secondary	The agreement in surveillance interval based on optical diagnosis and histopathology.	The agreement in surveillance interval based on optical diagnosis of diminutive colorectal polyps and histopathology of small and large colorectal polyps, compared to the surveillance interval based on histopathology of all colorectal polyps (diminutive, small, and large).	1 year