LMU - Ludwig-Maximilians-Universität München
Advanced Monte Carlo and imaging methods
Trainee: Liheng Tian
Supervisor: Katia Parodi
Compared to analytical algorithms traditionally employed in Treatment Planning Systems (TPSs) for proton radiation therapy, Monte Carlo (MC) techniques show great potential for improving the accuracy of dose calculation.
On the other hand, the precision of proton therapy is currently challenged by proton range uncertainties caused by e.g. anatomical changes or patient set-up uncertainties. To reduce such uncertainties, Prompt gamma (PG) is widely investigated to monitor proton range in-vivo by detecting energetic (~MeV) photons emitted by nuclear de-excitation processes in the beam path. However, the performance of PG monitoring is affected by tissue heterogeneities and counting statistics, which are not considered in conventional TPS. Hence, the goal of this project is to improve current TPS accounting for in-vivo proton range verification.
The initial phase of this project focused on quantifying the spot-by-spot conformities between PG (at the production level) and dose profiles and then selecting a few spots to provide reliable dose information, to be boosted above the statistics detection limit in the treatment plan. Relevant work has been published in Physics in Medicine and Biology
Currently the project also focused on further expanding the ability of this approach considering fractional anatomical changes.
Image courtesy of LMU