Medical Physics Seminar – Monday, September 14, 2020
Using big clinical data to advance precision radiotherapy and to uncover the spatial dependence of radiation on treatment related toxicity
Todd McNutt, Ph.D.
Director of Clinical Informatics, Associate Professor of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine
This seminar will allow the participant to demonstrate the ability to understand how big data applications and artificial intelligence will impact radiation therapy. The uses of these tools for clinical quality control, personalized treatment plan quality assessment, and plan automation will be described. These capabilities are beginning to surface in commercial products, and this talk will give an understanding of what is going on underneath these systems. Prediction models for treatment dosimetry will be described. In addition, this talk will present prediction models of treatment related toxicities that utilize more complex features of the radiation dose distribution and how they can be used to advance knowledge in radiotherapy into the impact of how the spatial pattern of dose may influence real world outcomes measured in clinical practice. The overall premise of the talk is how a learning health system in radiation oncology can be created and used with these big data and artificial intelligence models to personalize and improve the quality of radiotherapy.