NCT04864587

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

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 500 (actual)
• Sponsor: Theresienkrankenhaus und St. Hedwig-Klinik GmbH · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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

Detailed 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.

Conditions

• Pouches, Ileoanal

Interventions

Type	Name	Description
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

Timeline

• Start date: 2021-06-01
• Primary completion: 2023-06-01
• Completion: 2023-06-01
• First posted: 2021-04-29
• Last updated: 2023-08-29

Locations

1 site across 1 country: Germany