Grant: Doctoral Research Award: Canada Graduate Scholarships

Lymphoma is a type of blood cancer, developing in the lymphatic system, with a significant global disease burden. Treatment usually involves chemotherapy, immunotherapy, and radiotherapy, with PET/CT scans being used to assess the extent of disease and to monitor treatment response. However, these current methods are limited in their ability to predict patient outcomes, as aggressive lymphomas vary greatly between individuals. My research aims to use artificial intelligence (AI) methods to improve how lymphoma is diagnosed and treated. Specifically, I will develop AI tools that can be integrated into the clinical workflow, helping physicians better understand characteristics of tumors and predict patient outcomes. By involving physicians in the process of model development and incorporating clinical considerations, these AI tools can better meet the needs of real-world clinical settings. The two main objectives of my project are to create AI models that can accurately outline tumors in PET/CT scans with minimal manual input and to identify tumor characteristics that suggest disease recurrence or relapse. Additionally, these tumor features, such as surface area and texture, will be correlated with clinical information and genetic markers like circulating tumor DNA (ctDNA), to better understand how these features relate to lymphoma physiology. These insights could lead to improved patient outcomes through more personalized treatment plans. In the long term, as AI models become integrated into routine clinical practice, these scalable solutions can improve lymphoma patient outcomes globally.