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

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

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
NL-OMON
Registry ID
NL-OMON26387
Enrollment
292
Registered
2020-06-09
Start date
2018-10-16
Completion date
Unknown
Last updated
2024-02-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colorectal cancer, colorectal polyps

Interventions

None

Sponsors

Amsterdam UMC, location AMC
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: - Patients older than 18 years undergoing a screening colonoscopy. - Signed informed consent

Exclusion criteria

Exclusion criteria: - Boston bowel preparation score < 6 - Incomplete colonosopy - Diagnosis of inflammatory bowel disease, Lynch syndrome or (serrated) polyposis syndrome.

Design outcomes

Primary

MeasureTime frame
The primary outcome of the study is 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 dichotomised as neoplastic polyps, while HPs and other non-neoplastic histology are considered non-neoplastic.

Secondary

MeasureTime frame
- The mean duration in seconds of the CAD-CNN system to make a per polyp diagnosis. - The mean number of attempts of the CAD-CNN to make a diagnosis per polyp. - The ratio of unsuccessful diagnoses from all diagnoses of the CAD-CNN system. An unsuccessful diagnosis/failure of the CAD-CNN system is defined as more than 3 unsuccessful attempts. - The number of diminutive polyps per colonoscopy that is resected and discarded without histopathological analysis with the optical diagnosis strategy (the CAD-CNN system or endoscopist). - The percentage of colonoscopies in which diminutive polyps are characterised 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 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 diminutive hyperplastic polyps in the rectosigmoid are left in situ. - The diagnostic tests for optical diagnosis: sensitivity, specificity, positive and negative predictive value (PPV and NPV), and area under the curve (AUC). - 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. PIVI-criteria - 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. - The NPV of neoplastic lesions in the rectosigmoid, based on optical diagnosis of diminutive polyps with high confidence, compared to histology. All outcome measures for HDWLE instead of NBI endoscopy li

Contacts

Public ContactBritt Houwen

AUMC, location AMC

b.b.houwen@amsterdamumc.nl020566260

Outcome results

None listed

Source: NL-OMON (via WHO ICTRP)