Artificial Intelligence For Outcomes Research in Crohn's Disease: Digital Pathology Assessment of Fibrosis and Association With Patient History and Clinical Outcomes

The goal of this retrospective observational study is to learn whether artificial intelligence-based digital pathology can measure intestinal fibrosis and help identify patients with Crohn's disease who may be at greater risk of disease progression and surgery. The main questions the study aims to answer are: Does the FibroNest Phenotypic Fibrosis Composite Score \[Ph-FCS(Muc)\], measured from routinely collected ileal biopsies, reflect the severity of fibrosis assessed by a pathologist? * Is Ph-FCS(Muc) associated with Crohn's disease characteristics and history? * Can Ph-FCS help predict whether a patient will subsequently require a first ileal surgical resection for fibrostenotic Crohn's disease? Researchers will retrospectively analyze previously collected ileal biopsies and medical information from adults with Crohn's disease. Biopsy slides will be digitized and analyzed using FibroNest digital pathology, and the resulting fibrosis measurements will be compared with pathologist assessments, clinical characteristics, disease history, and subsequent clinical outcomes.