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Abstract #3038

Diameter-Independent Computer-Aided Classification of Mesorectal Lymph Nodes in Rectal Cancer: Preliminary Results

Wael Shabana1, Dilkash Kajal1, Rebecca E. Thornhill1

1Medical Imaging, The Ottawa Hospital, Ottawa, Ontario, Canada

The clinical MRI assessment of metastatic mesorectal lymph nodes plays an important role in predicting prognosis in rectal cancer. However, radiologic assessment offers limited sensitivity to predict the malignant potential of lymph nodes, particularly when conventional diameter criteria are used. We identified several diameter-independent shape and textural features from contrast enhanced T1-weighted MR images of mesorectal lymph nodes that were capable of delineating nodes with high malignant potential with 85% sensitivity, 78% specificity and 85% accuracy. With further optimization, these advanced shape and textural features promise to provide improved sensitivity compared to conventional radiologic methods.