Medical Physics Seminar – Monday, October 5, 2015
Concurrent Monte Carlo Transport and Fluence Optimization Therapy, Development, and Applications
Youming Yang (student of Dr. Bryan Bednarz)
Research Assistant, Dept of Medical Physics, UW-School of Medicine & Public Health, Madison, WI - USA
Future radiation treatment technology will require new inverse planning solutions to account for an increasing num-ber of physical and biological parameters used for advanced delivery modes. The difficult challenge of preserving dosi-metric accuracy while finding an optimal treatment plan over a vast search space would greatly benefit from Monte Carlo based dose calculation methods, which can offer improvements in dosimetric accuracy of up to 20% compared to deterministic methods. However, the dosimetric accuracy afforded by conventional Monte Carlo treatment plan-ning methods come at the cost of being computationally time-consuming and memory-intensive to implement. This has largely relegated Monte Carlo treatment planning to research endeavors, where the computational time and memory considerations are less important than the accuracy afforded by Monte Carlo. While advancements in com-puter hardware and software have greatly improved the speed of Monte Carlo dose calculation methods, the compu-tational demands of newer radiation therapy optimization problems still outpace the scalability of the current optimi-zation paradigm. Therefore, the overarching goal of this research is to develop a novel approach to fluence optimiza-tion that directly incorporates optimization into the Monte Carlo transport process itself, in a manner that reduces both the computational time and memory penalties of performing transport and optimization separately. Additionally, the Monte Carlo methods and optimization theory developed in this work was applied to the novel MRI guided radiation therapy delivery modality, an emerging subset of image guided radiation therapy for which Monte Carlo dose calculation methods will be essential in generating safe and robust treatment plans.