Study On RBE Uncertainty And Biological Dose Optimization In Carbon Ion Radiotherapy

Heavy ion radiotherapy technology has gradually become a research hotspot in the field of radiotherapy due to its unique advantages in physics and radiobiology,as well as the rich clinical experience accumulated in the past 30 years.The uncertainty in carbon ion radiotherapy sometimes leads to the phenomenon that the dose distribution received by the patient is inconsistent with the dose distribution generated by the treatment plan.At present,the negative effects of setup uncertainty and range uncertainty on radiotherapy have been basically solved by robust optimization methods and other technical means.However,the research on RBE uncertainty has not been completed.Therefore,it is of great significance to explore the possible sources of RBE uncertainty in carbon ion radiotherapy and develop new techniques to reduce the negative effects caused by RBE uncertainty.In this paper,the effects of different data processing methods onαandβparameters of the linear quadratic（LQ）model fitting the cell survival curve were explored,and the effects on the treatment planning results were also explored.It was proved that there was a large RBE uncertainty in carbon ion radiotherapy.Then,in order to reduce the negative impact of RBE uncertainty on the treatment planning of carbon ion radiotherapy,an algorithm using multiple sets of RBE model data for plan optimization was proposed.The treatment planning results were compared between using only MKM model data for plan optimization and using both MKM and LEM RBE model data for plan optimization.The specific methods and processes of the two main works of this paper are as follows:1)The survival curve of T98G cells irradiated with carbon ion was fitted according to the linear square（LQ）model.According to whether the standard deviations of cell survival rate were considered during the fitting process and whether the 0 Gy plating efficiency or the multi-dose plating efficiency was considered during the fitting work,different data processing methods were used.Four sets of LET-αand LET-βrelationships were obtained,and three of them were selected to construct three sets of basedata of mat Rad treatment planning system.Treatment planning was carried out in a self-made spherical target cube with homogeneous water phantom.2)Firstly,the depth-（integral）physical dose distribution and line energy spectra at different water equivalent depths at each energy for 121 monoenergetic carbon ions were obtained by Monte Carlo simulation.Then,according to the line energy spectra of carbon ion,the corresponding depth-αcoefficient distribution was calculated according to the MKM model formula.In order to ensure that the basedata of MKM model based on Monte Carlo simulation can be used to optimize the biological dose distribution simultaneously with the basedata of LEM model of mat Rad treatment planning system,it was necessary to optimize the depth-physical dose distribution of monoenergy carbon ion beam by taking the depth-physical dose distribution in the basedata of LEM model as the optimization objective.Thus,the corresponding depth-physical dose distribution and optimized weight of the broadened carbon ion beam were obtained.Based on the optimized weights obtained,the depth-αcoefficient distribution of the MKM model for the monoenergetic carbon ion beam was processed,and the mat Rad basedata containing the depth-αcoefficient distribution of the MKM model was finally obtained.Then,the algorithm framework of using two groups of RBE model data to optimize the plan was implemented in mat Rad,and the treatment plans were developed respectively in TG119 model and an anonymous prostate case in CORT data set.In order to compare the treatment plan optimization using only MKM data and the plan optimization using both MKM and LEM RBE model data,effects on biological dose distribution results of MKM and LEM models.Key findings included:1)When only the plating efficiency of 0 Gy was considered,whether the standard deviation fitting of cell survival rate is considered has little effect on theαvalue and a large effect on theβvalue when the LET was low;When the LET got larger,it had a large effect on theαvalue and a small effect on theβvalue.When considering the standard deviations of cell survival rate,the deviations of the results of the two different methods considering the plating efficiency fitting were small.Except for 200 ke V/μm,the relative deviations ofαvalues between the two groups did not exceed±10%.The results showed that whether the standard deviations of cell survival rate were considered or not had a greater impact on theαandβcoefficients than whether the plating efficiency was considered in two different ways.Due to the error transfer effect of RBE calculation formula,the relative deviation ranges of the calculated values of biological dose distribution among different basedata in the treatment planning system were smaller than the relative deviation range ofα,βvalues obtained by fitting the experimental data.2)In TG119 water phantom and the anonymous prostate case,when only the basedata of MKM were used for plan optimization,the conformity index and homogeneity index of the target were significantly deteriorated by using the MKM’s scanning point weights to calculate the biological dose distribution of LEM,and the D₉₅,D_max and D_min of the target also deteriorated to varying degrees.When using both the basedata of MKM and LEM models for plan optimization,the new optimization method significantly improved the homogeneity index of the target area of LEM with little effect on the quality of the MKM plan,and reduced the negative effect of the RBE uncertainty introduced by switching different RBE models on the biological dose distribution of treatment plans.In general,the use of both MKM model and LEM model data for plan optimization can reduce the deterioration of treatment plan results caused by RBE uncertainty introduced by switching LEM model data to recalculate biological dose distribution when only MKM data was used for plan optimization,which has preliminarily realized the research purpose of this section.In summary,the study in this paper has shown that the different processing methods of experimental data and the recalculation of the biological dose distribution of the treatment plan by replacing the RBE model in carbon ion radiotherapy can lead to large RBE uncertainty,which has a negative impact on the quality of the treatment plan.Therefore,this paper proposes an algorithm to optimize the treatment plan using multiple sets of RBE model data can reduce the negative impact of RBE uncertainty on treatment planning to a certain extent.This paper provides a new idea and technical route for the technical upgrading of the domestic treatment planning system.