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Clinical Trial Summary

The research group have previously evaluated the benefit of serial consecutive capsule endoscopy as monitoring tool for Crohn's disease in remission, demonstrating its superior accuracy for disclosing inflammation and for prediction of flares in comparison to other diagnostic modalities such as magnetic resonance enterography and inflammatory biomarkers. Subsequently, deep learning algorithms had developed to provide excellent accuracy for identification and grading of ulcers and intestinal strictures on capsule endoscopy still images. The investigators will advance this knowledge using a parallel two-parts approach.


Clinical Trial Description

Part I - A retrospective study will use stored capsule and clinical datasets from 120 previously enrolled CD patients in remission, who underwent capsule based 24-months monitoring as part of two prior similar research projects (60 in each of the Israeli Inflammatory bowel disease Research Nucleus (IIRN), IIRN-I and IIRN-II-CURE- projects), aiming to predict and prevent flares based on capsule studies. The investigators will now utilize the accumulated visual data to develop AI-based complete film readouts and integrate the resultant visual omics data with previously derived microbiome and biomarker data, to serve as a discovery cohort for machine learning models predicting clinical exacerbation in patients in remission, which was witnessed in 27% of IIRN-I cohort within the 24m study. Part II - A prospective observational study will enroll a new IIRN-III cohort of 60 (+6 attrition-considered) Crohn's Disease patients>16 years old in clinical remission. The investigators will deliberately use similar inclusion, monitoring design and outcome definitions as IIRN-I & II studies, to allow cross-cohort comparative validity. Procedures will include baseline colonoscopy, pan-enteric capsule and magnetic resonance enterography/Intestinal ultrasound, and thereafter serial capsule studies or every 6 months for 24 months. Newly acquired Omics will include baseline mucosal +colonic wash transcriptomics obtained during the baseline colonoscopy, serial dense stool microbiome and blood metabolomics, and a computerized frequency questionnaire, diet omics data. A densely sampled 24 months stool will be used to develop novel multi-omics tools predicting flares. The investigators will also use the datasets to explore the mechanisms and pathways involved in triggering remission transition into a clinical flare. Follow- up can optionally extend to 36 months. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT06362174
Study type Observational
Source Sheba Medical Center
Contact
Status Active, not recruiting
Phase
Start date February 7, 2023
Completion date December 31, 2025

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