Terminal-ileum Centerline Extraction from Magnetic Resonance Enterography Data of Crohn's Disease Patients

Crohn's disease (CD), a chronic inflammatory bowel disorder, often affects the terminal ileum (TI) and leads to digestive tract inflammation and complications like bowel obstruction. Accurately determining the 3D extent of CD from 2D Magnetic Resonance Enterography (MRE) images requires approximations, as no automated 3D measurement system exists. We developed an intelligent MRE reading application for virtual unfolding and 3D visualization of MRE data. We introduce a semi-automatic algorithm to predict the TI centerline from MRE data to reduce radiologist interaction time. The algorithm involves constructing an orientation classifier and implementing a shortest path algorithm to determine the TI centerline. We evaluated the algorithm's effectiveness on a database of 123 MRE scans using a k-fold cross-validation experimental setup, comparing the predicted centerline with a radiologist-annotated centerline considered as ground-truth. The results showed good alignment with the ground-truth centerline with minimal interaction time.Clinical relevance: This study introduces a semi-automatic algorithm that accurately predicts the terminal ileum centerline from MRE data, streamlining the diagnostic process for Crohn's disease. By reducing radiologist interaction time in assessing the 3D extent of the disease from 2D images, the algorithm holds promise for improving early diagnosis and treatment strategies for affected patients.