Adaptive RT and Prompt Gamma
Adaptive RT and Prompt Gamma
Thyrza Jagt, Netherlands Cancer Institute
Abstract
In this talk we will discuss different online adaptive planning strategies. For both photon and for proton planning, we will go through methods ranging from a fast restoration to the planned dose to a full re-optimization on the daily anatomy. We will also shortly touch upon daily quality assurance for proton therapy treatment delivery through the use of prompt gamma ray emission profiles.
About Thyrza
Thyrza Jagt studied applied mathematics at the Delft University of Technology. After completing an internship on treatment planning in hyperthermia in the Erasmus Medical Center in Rotterdam, and a dissertation of the mathematical modeling of pressure ulcers, she received her Master of Science degree.
She enjoyed the combination of mathematics and medicine, and in 2015 Thyrza started a PhD project on the topic of Online Adaptive Intensity Modulated Proton Therapy in the Erasmus Medical Center in Rotterdam as part of the multi-institutional ADAPTNOW project. Within this project she worked on automated online adaptive strategies to account for day to day anatomical variations. Strategies ranging from a simple and fast dose restoration to a more advanced full re-optimization were developed and tested. During her project she also collaborated within the ADAPTNOW project, where the focus was on fully automated contour propagation, and monitoring treatment delivery using prompt gamma ray emission profiles. Thyrza received her doctorate in 2020.
Thyrza is currently a fourth year PostDoc at the Netherlands Cancer Institute in Amsterdam. Focusing on adaptive treatments using the MR-Linac, she investigates whether the daily adaptive workflow is robust for minimal daily user input, what to do when an adaptive treatment is interrupted midway through, and how the daily workflow can be made as fast as possible while maintaining high quality.
