December 31st, 2018
I present an automated method for computing the spatial similarity of tumor location with respect to organs at risk between multiple head and neck cancer patients and ranking the patients accordingly. I use this method and resulting metric to predict, for each patient, a radiation dose distribution across organs in the head and neck. Furthermore, I go over the design and implementation of a visual analysis tool used to help validate the method.
The resulting method and interface, CAMP-RT (Correlations Across Multiple Patients in Radiation Therapy) is continuously being evaluated by domain experts from the MD Anderson Cancer Center. I report their qualitative feedback regarding the method and interface. I further evaluate quantitatively the results of the prediction using a dataset of 101 head-and-neck cancer patients. The results indicate the method has good predictive capabilities.
P. Hanula, CAMP - RT: A Patient Similarity-Based Method for Predicting Radiation Dosage in Head and Neck Radiation Oncology, Submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, Graduate College of the University of Illinois at Chicago, December 31st, 2018.