Diagnostic Performance of a Convolutional Neural Network for Diminutive Colorectal Polyp Recognition

Artificial Intelligence Clinical Trial

— POLAR  

Official title:

Diagnostic Performance of a Convolutional Neural Network for Diminutive Colorectal Polyp Recognition. A Multicentre, Prospective Observational Study

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03822390
• Other study ID #: W18_422
• Status: Completed
• Start date: October 16, 2018
• Est. completion date: October 16, 2021

Study information

• Verified date: December 2021
• Source: Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Rationale: Diminutive colorectal polyps (1-5mm in size) have a high prevalence and very low risk of harbouring cancer. Current practice is to send all these polyps for histopathological assessment by the pathologist. If an endoscopist would be able to correctly predict the histology of these diminutive polyps during colonoscopy, histopathological examination could be omitted and practise could become more time- and cost-effective. Studies have shown that prediction of histology by the endoscopist remains dependent on training and experience and varies greatly between endoscopists, even after systematic training. Computer aided diagnosis (CAD) based on convolutional neural networks (CNN) may facilitate endoscopists in diminutive polyp differentiation. Up to date, studies comparing the diagnostic performance of CAD-CNN to a group of endoscopists performing optical diagnosis during real-time colonoscopy are lacking.

Objective: To develop a CAD-CNN system that is able to differentiate diminutive polyps during colonoscopy with high accuracy and to compare the performance of this system to a group of endoscopist performing optical diagnosis, with the histopathology as the gold standard.

Study design: Multicentre, prospective, observational trial. Study population: Consecutive patients who undergo screening colonoscopy (phase 2)

Main study parameters/endpoints: The accuracy of optical diagnosis of diminutive colorectal polyps (1-5mm) by CAD-CNN system compared with the accuracy of the endoscopists. Histopathology is used as the gold standard.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 292
• Est. completion date: October 16, 2021
• Est. primary completion date: October 16, 2021
• Gender: All
• Age group: 18 Years and older

Eligibility

Phase 1A -

• Patients with one polyp subtype (based on histology)

Phase 1B Patients older than 18 years that underwent colonoscopy in one of the participating centres.

Phase 2:- Validation CAD-CNN system

Inclusion Criteria:

All patients older than 18 years old undergoing screenings colonoscopy in one of the participating centres.

Exclusion Criteria:

• Diagnosis of inflammatory bowel disease, Lynch syndrome or (serrated) polyposis syndrome.

• Boston Bowel Preparation Scale (BBPS) <2 in one of the colon segments

• Patients who are unwilling or unable to give informed consent

Related Conditions & MeSH terms

• Artificial Intelligence
• Colorectal Polyp
• Polyps

Intervention

Device:
• CAD-CNN system
The CAD-CNN system will be trained in predicting the histology of diminutive polyps. Before training, the dataset will be split up into a training set and a test set. To ensure a completely independent test and training set there will be no overlap between patients (i.e. if polyps from a patient A is present in the training set it cannot be in the test set as well).

Locations

Country	Name	City	State
Netherlands	Academic Medical Centre	Amsterdam	Noord-Holland

Sponsors (3)

Lead Sponsor	Collaborator
Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)	Bergman Clinics, Medical Centre Leeuwarden

Country where clinical trial is conducted

Netherlands, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The accuracy of the CAD-CNN system for predicting histology of diminutive colorectal polyps (1-5mm) compared with the accuracy of the prediction of the endoscopist. Both the CAD-CNN system and the endoscopist will use NBI for their predictions.	Accuracy is defined as the percentage of correctly predicted optical diagnoses of the CAD-CNN system and / or endoscopist compared to the gold standard pathology. For the calculation of the accuracy, adenomas and SSLs will be dichotomized as neoplastic polyps, while HPs are considered non-neoplastic	2 year
Secondary	The mean duration in seconds of the CAD-CNN system to make a per polyp diagnosis.	The mean duration in seconds of the CAD-CNN system to make a per polyp diagnosis.	2 year
Secondary	The mean number of attempts of the CAD-CNN to make a diagnosis per polyp	The mean number of attempts of the CAD-CNN to make a diagnosis per polyp	2 year
Secondary	The ratio of unsuccessful diagnosis from all diagnosis of the CAD-CNN system. An unsuccessful diagnosis/failure of the CAD-CNN system is defined as more than 3 unsuccessful attempts	The ratio of unsuccessful diagnosis from all diagnosis of the CAD-CNN system. An unsuccessful diagnosis/failure of the CAD-CNN system is defined as more than 3 unsuccessful attempts	2 year
Secondary	The number of diminutive polyps per colonoscopy that is resected and discarded without histopathological analysis with optical diagnosis strategy (the CAD-CNN system or endoscopist)	The number of diminutive polyps per colonoscopy that is resected and discarded without histopathological analysis with optical diagnosis strategy (the CAD-CNN system or endoscopist)	2 year
Secondary	The percentage of colonoscopies in which diminutive polyps are characterized based on optical diagnosis, removed and discarded without histopathological evaluation (i.e. proportion of polyps assessed with high confidence)	The percentage of colonoscopies in which diminutive polyps are characterized based on optical diagnosis, removed and discarded without histopathological evaluation (i.e. proportion of polyps assessed with high confidence)	2 year
Secondary	The percentage of colonoscopies in which the surveillance interval is based on the optical diagnosis of the CAD-CNN system and the patient can be directly informed of the surveillance interval after colonoscopy	The percentage of colonoscopies in which the surveillance interval is based on the optical diagnosis of the CAD-CNN system and the patient can be directly informed of the surveillance interval after colonoscopy	2 year
Secondary	The percentage of colonoscopies in which diminutive hyperplastic polyps in the rectosigmoid are left in situ.	The percentage of colonoscopies in which diminutive hyperplastic polyps in the rectosigmoid are left in situ.	2 year
Secondary	The diagnostic sensitivity for optical diagnosis of the CAD-CNN system and the endoscopists	The diagnostic sensitivity for optical diagnosis of the CAD-CNN system and the endoscopists	2 year
Secondary	The diagnostic sensitiviy for optical diagnosis of the CAD-CNN system and the endoscopists	The diagnostic sensitiviy for optical diagnosis of the CAD-CNN system and the endoscopists	2 year
Secondary	The accuracy rates on a per polyp basis	Accuracy on a polyp basis is defined as the percentage of correctly predicted optical diagnoses of the CAD-CNN system and / or endoscopist compared to the gold standard pathology. For the calculation of the accuracy on a polyp basis, adenomas, SSLs and HPs are considered different subtypes.	2 year
Secondary	Agreement between recommended surveillance intervals, based on optical diagnosis of diminutive polyps with high confidence, compared to surveillance recommendations based on histology of all polyps	Agreement between recommended surveillance intervals, based on optical diagnosis of diminutive polyps with high confidence, compared to surveillance recommendations based on histology of all polyps	2 year
Secondary	The diagnostic specificity for optical diagnosis of the CAD-CNN system and the endoscopists	The diagnostic specificity for optical diagnosis of the CAD-CNN system and the endoscopists	2 year
Secondary	The diagnostic PPV for optical diagnosis of the CAD-CNN system and the endoscopists	The diagnostic PPV for optical diagnosis of the CAD-CNN system and the endoscopists	2 year
Secondary	The diagnostic NPV for optical diagnosis of the CAD-CNN system and the endoscopists	The diagnostic NPV for optical diagnosis of the CAD-CNN system and the endoscopists	2 year