Grant: Project Grant

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, affects over 300,000 Canadians. Patients require regular CT scans to monitor disease and guide treatment. Currently, radiologists must manually examine these images-a time-consuming process requiring specialized expertise. With IBD prevalence expected to reach 1% of Canada's population by 2035, and many patients in rural areas far from specialists, our current approach cannot meet demand. This project brings together experts in computer science, radiology, gastroenterology, and medical data science to develop artificial intelligence (AI) systems that automatically identify and measure the intestinal tract in IBD patient CT scans. This interdisciplinary collaboration is essential because developing reliable medical AI requires both advanced computational methods and clinical expertise for safe, effective deployment. Our team has assembled an exceptionally large IBD imaging dataset containing over 11,000 CT scans from Alberta patients. We will use cutting-edge AI foundation models and adapt them specifically for IBD. Clinical experts will rigorously validate performance to ensure the AI meets clinical standards. This represents the first step in a two-stage research program. Once we establish reliable intestinal tract identification, future research will develop quantitative biomarkers-automated measurements of bowel wall thickness, inflammation patterns, and complications-enabling objective tracking of disease progression and treatment response. This technology addresses critical healthcare challenges by enabling faster, more consistent assessment across hospitals, particularly benefiting rural patients lacking access to IBD imaging specialists. By automating time-consuming analysis, our AI tools allow radiologists to focus on complex cases while positioning Canada as a leader in AI-assisted digestive disease care.