%0 Generic
%A Bennan, Amit Ben Antony
%C Heidelberg
%D 2022
%F heidok:30888
%R 10.11588/heidok.00030888
%T Combined Photon - Carbon ion Radiotherapy Treatment Planning
%U https://archiv.ub.uni-heidelberg.de/volltextserver/30888/
%X Carbon ion therapy is a promising treatment modality that is not widely accessible to patients due to limited resources and a high cost of treatment. Therefore, it is necessary to consider mixed modality treatments where carbon ions are utilized in combination with the more widely available and accessible, photon therapy. In contemporary clinical combined treatments, photon fractions and carbon ion fractions are separately optimized and simply accumulated based on the RBE weighted dose. Such a “naive” combination does not fully exploit physical and radiobiological advantages emerging from the interplay of both modalities. Carbon ions excel at delivering high RBE conformal dose to the target volume and avoid delivering dose to distal healthy tissue. Photons, besides generally larger integral dose, have a lower RBE and are desirable to irradiate target subvolumes that are adjacent to healthy tissue or have healthy tissue infiltrated by tumour tissue, due to the greater fractionation potential. This thesis presents a novel method to exploit these differences by simultaneously optimizing photon and carbon ion fluence contributions in order to answer the question: what is the ideal combined photon-carbon ion fluence distribution given a specific fraction allocation between photons and carbon ions?  The joint optimization framework allows for the synergistic optimization of photon–carbon ion treatments based on the cumulative biological effect, incorporating both the variable RBE of carbon ions and the fractionation effect within the linear quadratic (LQ) model. As a part of this study, the joint optimization workflow was implemented within the open source treatment planning toolkit matRad.  Joint optimization strategies yield individually non-conformal photon and carbon ion dose distributions that cumulatively deliver a homogeneous conformal biological effect distribution in the target volume. Compared to conventional combined treatments, joint optimized treatments exhibit better conformity and better sparing of critical structures through a spatial redistribution of dose between modalities and a non-uniform fractionation schedule within the target volume. Depending on the fraction allocation between modalities, there exists an optimized temporal distribution of biological effect where parts of the target volume are hypofractionated while areas around dose limiting critical structures are spared through fractionation. The additional degrees of freedom from the spatial and temporal redistribution of fluence enables the exploration of a new spectrum of plans that can better address physical and radiobiological treatment planning challenges.  Apart from a proof of concept, the impact of key underlying treatment parameters were also investigated. With regards to fraction allocation for photon–carbon ion treatments, the joint optimized treatments were shown to benefit from a reduction in carbon ion fractions due to their limited fractionation capacity. The choice of LQ model parameters and an assumed fractionation benefit drives the biological motivation to fractionate dose, without it the joint optimization was purely driven by the physical characteristics and beam angles selected for treatment. Furthermore, the choice of LEM version for carbon ion RBE estimation predicts the fractionation capacity of carbon ions. The clinically used LEM I predicts a higher effectiveness of carbon ions in the entrance region and fragmentation tail as compared to LEM IV. Therefore, the use of LEM I in joint optimization results in a lowering of carbon ion contributions in order to spare healthy tissue located at the entrance channel and fragmentation tail. Finally, the method was demonstrated for six glioblastoma patients, where the CTV contains tumour infiltrated healthy tissue that would benefit from a fractionated treatment. In comparison to the current clinical standard of independently optimized photon–carbon ion plans, the optimal plan dose to CTV was primarily delivered by photons while carbon ions are restricted to the GTV with variations depending on tumour size and location. The joint optimization approach results in a targeted application of carbon ions that (1) reduces dose in normal tissues within the target volume which can only be protected through fractionation and (2) boosts central target volume regions in order to reduce integral dose.  In conclusion, this thesis presents the first joint optimization framework that allows for an evidence based and mathematically optimal allocation of photons and carbon ions in mixed modality treatments.