Deep Learning-Based Confocal Laser Microendoscopy Feature Atlas Construction and Its Application in Intelligent Diagnosis of Irritable Bowel Syndrome

In this study, the healthy control group and IBS patients are taken as the research subjects, and CLE is applied to image and analyze the enrolled persons respectively, to derive and compare the characteristic microstructural images of the healthy control group with those of the IBS patients, to establish a diagnostic model of IBS by using deep learning and to evaluate the diagnostic efficacy of the model for IBS.Participants will undergo colonoscopy and confocal laser microendoscopy, and IBS patients will undergo targeted biopsy in CLE to observe suspicious lesions and lesion margins, and specimens will undergo HE staining and immunohistochemistry testing. Translated with DeepL.com (free version)

NCT Number	NCT07051226
Lead Sponsor	Daping Hospital and the Research Institute of Surgery of the Third Military Medical University
Conditions	Irritable Bowel Syndrome (IBS)
Enrollment	90 participants
Start Date	2025-07-01
Primary Completion	2027-12-31 (estimated)
Study Completion	2027-12-31 (estimated)
Updated on ClinicalTrials.gov	2025-07-04