Artificial Intelligence in Image Recognition of Pouchoscopies in Patients With Restorative Proctocolectomy

Pouches, Ileoanal Clinical Trial

— PouchVision  

Official title:

Artificial Intelligence in Image Recognition of Pouchoscopies in Patients With Restorative Proctocolectomy

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04864587
• Other study ID #: PouchVision1.0
• Status: Completed
• Start date: June 1, 2021
• Est. completion date: June 1, 2023

Study information

• Verified date: August 2023
• Source: Theresienkrankenhaus und St. Hedwig-Klinik GmbH
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The application of artificial intelligence in pouchoscopy of patients with restorative proctocolectomy might improve the diagnosis of pouchitis and neoplasms. The aim of this pilot study is to develop a convolutional neural network algorithm for pouchoscopy

Description:

Restorative proctocolectomy is the standard procedure for treatment of refractory severe colitis in inflammatory bowel disease as well as the standard procedure for carcinoma preventive treatment of patients with inflammatory bowel disease with colonic neoplasia and patients with familial adenomatous polyposis coli (FAP). Pouchoscopy can be used to monitor the success of therapy and to detect complications such as pouchitis or neoplasia. Artificial Intelligence assisted image recognition programs can support the examiner in finding a diagnosis and train physicians in training, objectify endoscopic findings in the context of studies and might make biopsies unnecessary, thus saving costs. The application of Artificial Intelligence in pouchoscopy has not been demonstrated to date. The aim of this study is to develop, an image recognition algorithm that reliably detects the different graduations of pouch inflammation. This requires training and fine-tuning of the image recognition program PiTorch using the largest possible amount of image data, which will be recruited from the image databases of the UMM and the Theresienkrankenhaus Mannheim. A test run for statistical evaluation will be performed on an independent cohort.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 500
• Est. completion date: June 1, 2023
• Est. primary completion date: June 1, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• All patients aged = 18 years with inflammatory bowel disease and status after restorative proctocolectomy with ileoanal pouch who had received a pouchoscopy

Exclusion Criteria:

• Very poor endoscopic image quality

Related Conditions & MeSH terms

• Pouches, Ileoanal

Intervention

Diagnostic Test:
• Artificial intelligence used for image recognition in pouchoscopy
The aim of this study is to develop an image recognition algorithm that reliably detects the different graduations of pouch inflammation and neoplasms in the pouch

Locations

Country	Name	City	State
Germany	Theresienkrankenhaus und St. Hedwigkliniken GmbH	Mannheim	BW

Sponsors (2)

Lead Sponsor	Collaborator
Theresienkrankenhaus und St. Hedwig-Klinik GmbH	Universitätsmedizin Mannheim

Country where clinical trial is conducted

Germany, 

References & Publications (1)

van der Sommen F, de Groof J, Struyvenberg M, van der Putten J, Boers T, Fockens K, Schoon EJ, Curvers W, de With P, Mori Y, Byrne M, Bergman JJGHM. Machine learning in GI endoscopy: practical guidance in how to interpret a novel field. Gut. 2020 Nov;69(11):2035-2045. doi: 10.1136/gutjnl-2019-320466. Epub 2020 May 11. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	AI versus endoscopist	Detection of pouchitis by AI versus assessment by endoscopist in pouchoscopy	Immediately after application of AI algorithm or after assessment of the endoscopic image by the endoscopist
Primary	AI versus pathologist	Detection of pouchitis by AI versus pathologist in pouchoscopy	Immediately after application of AI algorithm or after assessment of the microscopic image of the pouch biopsy by the pathologist