Relative Biological Effectiveness Model Research Articles

Implementation of spot scanning dose optimization and dose calculation for helium ions in Hyperion.

Helium ions ((4)He) may supplement current particle beam therapy strategies as they possess advantages in physical dose distribution over protons. To assess potential clinical advantages, a dose calculation module accounting for relative biological effectiveness (RBE) was developed and integrated into the treatment planning system Hyperion. Current knowledge on RBE of (4)He together with linear energy transfer considerations motivated an empirical depth-dependent "zonal" RBE model. In the plateau region, a RBE of 1.0 was assumed, followed by an increasing RBE up to 2.8 at the Bragg-peak region, which was then kept constant over the fragmentation tail. To account for a variable proton RBE, the same model concept was also applied to protons with a maximum RBE of 1.6. Both RBE models were added to a previously developed pencil beam algorithm for physical dose calculation and included into the treatment planning system Hyperion. The implementation was validated against Monte Carlo simulations within a water phantom using γ-index evaluation. The potential benefits of (4)He based treatment plans were explored in a preliminary treatment planning comparison (against protons) for four treatment sites, i.e., a prostate, a base-of-skull, a pediatric, and a head-and-neck tumor case. Separate treatment plans taking into account physical dose calculation only or using biological modeling were created for protons and (4)He. Comparison of Monte Carlo and Hyperion calculated doses resulted in a γ mean of 0.3, with 3.4% of the values above 1 and γ 1% of 1.5 and better. Treatment plan evaluation showed comparable planning target volume coverage for both particles, with slightly increased coverage for (4)He. Organ at risk (OAR) doses were generally reduced using (4)He, some by more than to 30%. Improvements of (4)He over protons were more pronounced for treatment plans taking biological effects into account. All OAR doses were within tolerances specified in the QUANTEC report. The biological (4)He model proposed above is a first approach matching biological data published so far. The advantage of (4)He seems to lie in the reduction of dose to surrounding tissue and to OARs. Nevertheless, additional biological experiments and treatment planning studies with larger patient numbers and more tumor indications are necessary to study the possible benefits of helium ion beam therapy in detail.

TU-EF-304-08: LET-Based Inverse Planning for IMPT

Purpose: Cell survival experiments suggest that the relative biological effectiveness (RBE) of proton beams depends on linear energy transfer (LET), leading to higher RBE near the end of range. With intensity-modulated proton therapy (IMPT), multiple treatment plans that differ in the dose contribution per field may yield a similar physical dose distribution, but the RBE-weighted dose distribution may be disparate. RBE models currently do not have the required predictive power to be included in an optimization model due to the variations in experimental data. We propose an LET-based planning method that guides IMPT optimization models towards plans with reduced RBE-weighted dose in surrounding organs at risk (OARs) compared to inverse planning based on physical dose alone. Methods: Optimization models for physical dose are extended with a term for dose times LET (doseLET). Monte Carlo code is used to generate the physical dose and doseLET distribution of each individual pencil beam. The method is demonstrated for an atypical meningioma patient where the target volume abuts the brainstem and partially overlaps with the optic nerve. Results: A reference plan optimized based on physical dose alone yields high doseLET values in parts of the brainstem and optic nerve. Minimizing doseLET in these critical structures as an additional planning goal reduces the risk of high RBE-weighted dose. The resulting treatment plan avoids the distal fall-off of the Bragg peaks for shaping the dose distribution in front of critical stuctures. The maximum dose in the OARs evaluated with RBE models from literature is reduced by 8–14\% with our method compared to conventional planning. Conclusion: LET-based inverse planning for IMPT offers the ability to reduce the RBE-weighted dose in OARs without sacrificing target dose. This project was in part supported by NCI - U19 CA 21239

SU‐F‐BRD‐13: A Phenomenological Relative Biological Effectiveness (RBE) Model for Proton Therapy Based On All Published in Vitro Cell Survival Data

Purpose:Proton therapy treatments are currently planned and delivered using the assumption that the proton relative biological effectiveness (RBE) relative to photons is 1.1. This assumption ignores strong experimental evidence that suggests the RBE varies. A recent review study (Paganetti 2014), collected over 72 experimental reports on proton RBE, providing a comprehensive dataset for predicting proton RBE. Using this dataset we develop a model to predict RBE based on dose, linear energy transfer (LET) and the tissue specific parameter (α/β)x.Methods:The relationship of the RBE on dose, dose average LET (LETd) and (α/β)x was explored using 290 experimental data points. The RBE was calculated for each experimental point for doses ranging from 1 to 10 Gy. An RBE model, based on the linear‐quadratic model, was derived using a nonlinear regression fit to the experimental data.Results:The proposed RBE model predicts that the RBE increases with LET and decreases with (α/β)x. The model additionally predicts a decrease in RBE with increasing dose for low (α/β)x values (< 3 Gy). However the model predicts an increase in RBE with increasing dose for large (α/β)x (> 4 Gy). Previous phenomenological models were based on a small subset of experimental data and deviate significantly from our findings.Conclusion:The proposed RBE model is derived using the most comprehensive collection of proton RBE experimental data to date. The model agrees with previous theoretical predictions on the relationship between RBE, LETd and (α/β)x and also makes predictions on the relationship between RBE and dose. The proposed model shows a relationship between α and LETd but no significant relationship between β and LETd. Previously published phenomenological models based on a limited data set might have to be revised.

TU-EF-304-12: Proton Radiation Therapy for Left-Sided Breast Cancer: LET and RBE Considerations for Cardiac Toxicity

Purpose: Increased risk of coronary artery disease has been documented for patients treated with radiation for left-sided breast cancer. Proton therapy (PRT) has been shown to significantly decrease cardiac irradiation, however variations in relative biological effectiveness (RBE) have been ignored so far. In this study we evaluate the impact of accounting for RBE variations on sensitive structures located within high linear energy transfer (LET) areas (distal end) of the proton treatment fields, for this treatment site. Methods: Three patients treated in our institution with PRT for left-sided breast cancer were selected. All patients underwent reconstructive surgery after mastectomy and treated to a total dose of 50.4Gy with beam(s) vertical to the chest wall. Dose and LET distributions were calculated using Monte Carlo (MC-TOPAS - TOol for PArticle Simulation). The LET-based, variable-RBE-weighted dose was compared to the analytical calculation algorithm (ACA) and MC dose distributions for a constant RBE of 1.1, based on volume histograms and mean values for the target, heart and left anterior descending coronary artery (LAD). Results: Assuming a constant RBE and compared to the ACA dose, MC predicted lower mean target and heart doses by 0.5% to 2.7% of the prescription dose. For variable RBE, plan evaluation showed increased mean target dose by up to 5%. Mean variable-RBE-weighted doses for the LAD ranged from 2.7 to 5.9Gy(RBE) among patients increased by 41%–64.2% compared to constant RBE ACA calculation (absolute dose: 1.7–3.9Gy(RBE)). Smaller increase in mean heart doses was noticed. Conclusion: ACA overestimates the target mean dose by up to 2.7%. However, disregarding variations in RBE may lead to significant underestimation of the dose to sensitive structures at the distal end of the proton treatment field and could thus impact outcome modeling for cardiac toxicities after proton therapy. These results are subject to RBE model and parameter uncertainties.

SU‐E‐T‐549: Modeling Relative Biological Effectiveness of Protons for Radiation Induced Brain Necrosis

Purpose:To develop a model of the relative biological effectiveness (RBE) of protons as a function of dose and linear energy transfer (LET) for induction of brain necrosis using clinical data.Methods:In this study, treatment planning information was exported from a clinical treatment planning system (TPS) and used to construct a detailed Monte Carlo model of the patient and the beam delivery system. The physical proton dose and LET were computed in each voxel of the patient volume using Monte Carlo particle transport. A follow‐up magnetic resonance imaging (MRI) study registered to the treatment planning CT was used to determine the region of the necrosis in the brain volume. Both, the whole brain and the necrosis volumes were segmented from the computed tomography (CT) dataset using the contours drawn by a physician and the corresponding voxels were binned with respect to dose and LET. The brain necrosis probability was computed as a function of dose and LET by dividing the total volume of all necrosis voxels with a given dose and LET with the corresponding total brain volume resulting in a set of NTCP‐like curves (probability as a function of dose parameterized by LET).Results:The resulting model shows dependence on both dose and LET indicating the weakness of the constant RBE model for describing the brain toxicity. To the best of our knowledge the constant RBE model is currently used in all clinical applications which may Result in increased rate of brain toxicities in patients treated with protons.Conclusion:Further studies are needed to develop more accurate brain toxicity models for patients treated with protons and other heavy ions.

Carbon Ion Irradiation of the Rat Spinal Cord: Dependence of the Relative Biological Effectiveness on Linear Energy Transfer

To measure the relative biological effectiveness (RBE) of carbon ions in the rat spinal cord as a function of linear energy transfer (LET). As an extension of a previous study, the cervical spinal cord of rats was irradiated with single doses of carbon ions at 6 positions of a 6-cm spread-out Bragg peak (16-99 keV/μm). The TD50 values (dose at 50% complication probability) were determined according to dose-response curves for the development of paresis grade 2 within an observation time of 300 days. The RBEs were calculated using TD50 for photons of our previous study. Minimum latency time was found to be dose-dependent, but not significantly LET-dependent. The TD50 values for the onset of paresis grade 2 within 300 days were 19.5 ± 0.4 Gy (16 keV/μm), 18.4 ± 0.4 Gy (21 keV/μm), 17.7 ± 0.3 Gy (36 keV/μm), 16.1 ± 1.2 Gy (45 keV/μm), 14.6 ± 0.5 Gy (66 keV/μm), and 14.8 ± 0.5 Gy (99 keV/μm). The corresponding RBEs increased from 1.26 ± 0.05 (16 keV/μm) up to 1.68 ± 0.08 at 66 keV/μm. Unexpectedly, the RBE at 99 keV/μm was comparable to that at 66 keV/μm. The data suggest a linear relation between RBE and LET at high doses for late effects in the spinal cord. Together with additional data from ongoing fractionated irradiation experiments, these data will provide an extended database to systematically benchmark RBE models for further improvements of carbon ion treatment planning.

Relative Biological Effectiveness Variation Along Monoenergetic and Modulated Bragg Peaks of a 62-MeV Therapeutic Proton Beam: A Preclinical Assessment

The biological optimization of proton therapy can be achieved only through a detailed evaluation of relative biological effectiveness (RBE) variations along the full range of the Bragg curve. The clinically used RBE value of 1.1 represents a broad average, which disregards the steep rise of linear energy transfer (LET) at the distal end of the spread-out Bragg peak (SOBP). With particular attention to the key endpoint of cell survival, our work presents a comparative investigation of cell killing RBE variations along monoenergetic (pristine) and modulated (SOBP) beams using human normal and radioresistant cells with the aim to investigate the RBE dependence on LET and intrinsic radiosensitvity. Human fibroblasts (AG01522) and glioma (U87) cells were irradiated at 6 depth positions along pristine and modulated 62-MeV proton beams at the INFN-LNS (Catania, Italy). Cell killing RBE variations were measured using standard clonogenic assays and were further validated using Monte Carlo simulations and the local effect model (LEM). We observed significant cell killing RBE variations along the proton beam path, particularly in the distal region showing strong dose dependence. Experimental RBE values were in excellent agreement with the LEM predicted values, indicating dose-averaged LET as a suitable predictor of proton biological effectiveness. Data were also used to validate a parameterized RBE model. The predicted biological dose delivered to a tumor region, based on the variable RBE inferred from the data, varies significantly with respect to the clinically used constant RBE of 1.1. The significant RBE increase at the distal end suggests also a potential to enhance optimization of treatment modalities such as LET painting of hypoxic tumors. The study highlights the limitation of adoption of a constant RBE for proton therapy and suggests approaches for fast implementation of RBE models in treatment planning.

A Monte Carlo-based treatment-planning tool for ion beam therapy

Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), the MCTP tool is able to perform TP studies using ions with atomic numbers Z ≤ 8. Example treatment plans created with the MCTP tool are presented for carbon ions in comparison with a certified analytical treatment-planning system. Furthermore, the usage of the tool to compute and optimize mixed-ion treatment plans, i.e. plans including pencil beams of ions with different atomic numbers, is demonstrated. The tool is aimed for future use in research applications and to support treatment planning at ion beam facilities.

TH‐F‐105‐05: Comparison of Results for RBE‐Weighted Dose From Two RBE Models for Proton Therapy Treatment Plans

Purpose: To evaluate the differences between relative biological effectiveness (RBE)‐weighted doses calculated with either the linear quadratic (LQ) or repair‐misrepair‐fixation (RMF) RBE model for intensity modulated proton therapy (IMPT) treatment plans. Methods: The commercial treatment planning system (TPS) used at MD Anderson Cancer Center (MDACC) does not provide the LET information necessary in order to utilize variable RBE models to calculate RBE‐weighted dose for treatment plans. To obtain this information the Monte Carlo code MCNPX was used to recalculate IMPT treatment plans for patients with central nervous system (CNS) disease taken from the TPS and record the track‐averaged LET in each voxel of the dose distribution. The dose‐averaged LET was approximated from the track‐averaged LET by use of an appropriate scaling factor. The Monte Carlo Damage Simulation (MCDS) software was used to parameterize the number of double‐strand breaks generated in cells by protons according to their stopping power. This information, along with relevant biological coefficients, was then used to generate RBE‐weighted dose distributions according to the LQ and RMF RBE models. Plan evaluation metrics, such as a conformality index and heterogeneity index, were used for plan comparison. Results: The LQ RBE model produces higher RBE‐weighted doses, particularly in the target volume, compared to the RMF model. Doses predicted by the RMF model in nearby organs at risk can at times be several Gray lower than those predicted by the LQ model. Both models predict equivalently heterogeneous target dose distributions, while the RMF model predicts more conformal target dose. Conclusion: Calculation of proton treatment plan dose incorporating either the LQ or RMF models of variable RBE produces observable differences in the resultant dose distributions. Further investigation, including utilization of different biological coefficients, is required to determine the implications for all of the associated normal tissues. UTMDACC Sister Institution Network Fund Grant (SINF MDACC‐DKFZ)

TU‐G‐108‐08: Variable RBE and Incidence of Radiation Pneumonitis in Lung Patients Treated with Proton Therapy

Purpose: To determine the correlation between the Relative Biological Effectiveness (RBE)‐weighted dose and radiation pneumonitis (RP) incidence in cancer patients treated with proton therapy. Methods: The Monte Carlo proton dose calculation system MC2 based on MCNPX was used to recalculate treatment plans taken from the clinical treatment planning system (TPS) and compute the dose‐averaged LET in each voxel of the CT based patient model. The linear scaling model (LSM) for proton RBE was used with biological coefficients for RP to compute the variable RBE‐weighted dose distributions. These were compared with the constant RBE‐weighted doses computed by the TPS and currently used in our clinical practice. A restaging FDG PET/CT was registered to the treatment planning CT and the standard uptake values (SUV) were used as a measure of radiation dose response. Results: The variable RBE model results in higher biological dose at the distal ends of proton beams and the corresponding lung volumes receiving elevated doses can be significant if the beam is terminating inside the low density lung tissue. Preliminary results for the first two patients in the study show that the regions of elevated variable RBE‐weighted doses inside the lung are well correlated to the high SUV values in the restaging PET. Both patients were diagnosed with grade 3 RP after completing the treatment. Conclusion: The preliminary results indicate that variable RBE‐weighted doses may provide additional insight into toxicity risk for patients treated with proton radiotherapy. The complete study will include the analysis of many more patients diagnosed with grade 3 RP or higher, treated with protons in our institution. NCI grant P01CA021239

Clinical consequences of relative biological effectiveness variations in proton radiotherapy of the prostate, brain and liver

Proton relative biological effectiveness (RBE) is known to depend on the (α/β)x of irradiated tissues, with evidence of ∼60% variation over (α/β)x values from 1–10 Gy. The range of (α/β)x values reported for prostate tumors (1.2–5.0 Gy), brain tumors (10–15 Gy) and liver tumors (13–17 Gy) imply that the proton RBE for these tissues could vary significantly compared to the commonly used generic value of 1.1. Our aim is to evaluate the impact of this uncertainty on the proton dose in Gy(RBE) absorbed in normal and tumor tissues. This evaluation was performed for standard and hypofractionated regimens. RBE-weighted total dose (RWTD) distributions for 15 patients (five prostate tumors, five brain tumors and five liver tumors) were calculated using an in-house developed RBE model as a function of dose, dose-averaged linear energy transfer (LETd) and (α/β)x. Variations of the dose–volume histograms (DVHs) for the gross tumor volume (GTV) and the organs at risk due to changes of (α/β)x and fractionation regimen were calculated and the RWTD received by 10% and 90% of the organ volume reported. The goodness of the plan, bearing the uncertainties, was then evaluated compared to the delivered plan, which considers a constant RBE of 1.1. For standard fractionated regimens, the prostate tumors, liver tumors and all critical structures in the brain showed typically larger RBE values than 1.1. However, in hypofractionated regimens lower values of RBE than 1.1 were observed in most cases. Based on DVH analysis we found that the RBE variations were clinically significant in particular for the prostate GTV and the critical structures in the brain. Despite the uncertainties in the biological input parameters when estimating RBE values, the results show that the use of a variable RBE with dose, LETd and (α/β)x could help to further optimize the target dose in proton treatment planning. Most importantly, this study shows that the consideration of RBE variations could influence the comparison of proton and photon treatments in clinical trials, in particular in the case of the prostate.

Relative Biological Effectiveness of Carbon Ions in a Rat Prostate Carcinoma In Vivo: Comparison of 1, 2, and 6 Fractions

To determine the relative biological effectiveness (RBE) and the effective α/β ratio for local tumor control of a radioresistant rat prostate tumor (Dunning subline R3327-AT1) after 6 fractions of carbon ions and photons. A total of 82 animals with tumors in the distal thigh were treated with 6 fractions of either photons or carbon ions, by use of increasing dose levels and a 2-cm spread-out Bragg peak. Endpoints of the study were local control (no tumor recurrence within 300 days) and volumetric changes after irradiation. The resulting values for dose at 50% tumor control probability were used to determine RBE values. Including data for 1 and 2 fractions from a previous study, we estimated α/β ratios. For 6 fractions, the values for dose at 50% tumor control probability were 116.6 ± 3.0 Gy for photons and 43.7 ± 2.3 Gy for carbon ions and the resulting RBE was 2.67 ± 0.15. The α/β ratio was 84.7 ± 13.8 Gy for photons and 66.0 ± 21.0 Gy for carbon ions. Using these data together with the linear-quadratic model, we estimated the maximum RBE to be 2.88 ± 0.27. The study confirmed the increased effectiveness of carbon ions relative to photons over the whole dose range for a highly radioresistant tumor. The maximum RBE below 3 is in line with other published invivo data. The RBE values may be used to benchmark RBE models. Hypoxia seems to have a major impact on the radiation response, although this still has to be confirmed by dedicated experiments.

Systematic analysis of RBE and related quantities using a database of cell survival experiments with ion beam irradiation

For tumor therapy with light ions and for experimental aspects in particle radiobiology the relative biological effectiveness (RBE) is an important quantity to describe the increased effectiveness of particle radiation. By establishing and analysing a database of ion and photon cell survival data, some remarkable properties of RBE-related quantities were observed. The database consists of 855 in vitro cell survival experiments after ion and photon irradiation. The experiments comprise curves obtained in different labs, using different ion species, different irradiation modalities, the whole range of accessible energies and linear energy transfers (LETs) and various cell types. Each survival curve has been parameterized using the linear-quadratic (LQ) model. The photon parameters, α and β, appear to be slightly anti-correlated, which might point toward an underlying biological mechanism. The RBE values derived from the survival curves support the known dependence of RBE on LET, on particle species and dose. A positive correlation of RBE with the ratio α/β of the photon LQ parameters is found at low doses, which unexpectedly changes to a negative correlation at high doses. Furthermore, we investigated the course of the β coefficient of the LQ model with increasing LET, finding typically a slight initial increase and a final falloff to zero. The observed fluctuations in RBE values of comparable experiments resemble overall RBE uncertainties, which is of relevance for treatment planning. The database can also be used for extensive testing of RBE models. We thus compare simulations with the local effect model to achieve this goal.

Dose prescription in carbon ion radiotherapy: a planning study to compare NIRS and LEM approaches with a clinically-oriented strategy

In carbon ion radiotherapy there is an urgent clinical need to develop objective tools for the conversion of relative biological effectiveness (RBE)-weighted doses based on different models. In this work we introduce a clinically oriented method to compare NIRS-based and LEM-based GyE systems, minimizing differences in physical dose distributions between treatment plans. Carbon ion plans were optimized on target volumes of cubic and spherical shapes, for RBE-weighted dose prescription levels ranging from 3.6 to 4.4 GyE. Plans were calculated for target sizes from 4 to 12 cm defining three beam geometries: single beam, opposed beam and orthogonal beam configurations. The two treatment planning systems currently employed in clinical practice were used, providing the NIRS-based and LEM-based GyE calculations. Physical dose distributions of NIRS-based and LEM-based treatment plans were compared. LEM-based prescription doses that minimize differences in physical dose distributions between the two systems were found. These doses were compared with the mean RBE-weighted dose obtained with a Monte Carlo code (FLUKA) interfaced with LEM I. In the investigated dose range, LEM-based RBE-weighted prescription doses, that minimize differences with NIRS plans, should be higher than NIRS reported prescription doses. The optimal dose depends on target size, shape and position, number of beams and dose level. The opposed beam configuration resulted in the smallest average prescription dose difference (0.45 ± 0.09 GyE). The second approach of recalculating NIRS RBE-weighted dose with a Monte Carlo code interfaced with LEM resulted in no significant difference with the results obtained from the planning study. The delivery of a voxel by voxel iso-effective plan, if different RBE models are employed, is not feasible; it is however possible to minimize differences in a treatment plan with the simple approach presented here. Dose prescription ultimately represents a clinical task under the responsibility of the radiation oncologist, the presented analysis intends to be a quantitative and objective way to assist the clinical decision.

Is Constant RBE Accurate Enough for Determination of Biological Effects in Proton Therapy?

The relative biological effectiveness (RBE) of protons currently used in clinical practice is assigned a constant value of 1.1, despite the evidence that the actual RBE of protons varies as a function of proton energy, linear energy transfer (LET), dose per treatment fraction, tissue type, and clinical endpoint. The purpose of this study is to compare the performance of the traditional, constant RBE model, and two variable RBE models in explaining the radiation induced brain necrosis indicated on follow-up imaging studies for a patient treated with postoperative proton radiation therapy for malignant meningioma. In this study, treatment plan information is extracted from a clinical treatment planning system (TPS) and used to recalculate physical proton dose and linear energy transfer (LET) distributions using Monte Carlo simulations. One constant and two variable RBE models which account for tissue specific parameters, LET, biological endpoint, and dose per treatment fraction are applied on a voxel-by-voxel basis to compute three biologically effective dose distributions. These dose distributions are subsequently correlated to follow-up imaging studies which have indicated the presence of radiation induced necrosis in the treated region of the patient being analyzed. Corresponding areas of toxicity and dose/RBE computed with three different models are compared to determine which model performs the best in explaining the radiation induced toxicity. Areas of increased biologically effective dose computed using variable RBE models compared to the original dose distribution calculated by the clinical TPS using a constant RBE model are found to correspond to areas of radiation induced brain necrosis. Variable RBE doses were up to 8% higher in the region of toxicity. Variable RBE models perform better in explaining the radiation induced brain necrosis.

TH‐C‐213AB‐05: Correlating Areas of Radiation Toxicity with Relative Biological Effectiveness‐Weighted Dose Distributions in Proton Radiotherapy

Purpose: To determine if biologically effective proton dose calculated using a relative biological effectiveness (RBE) model with multiple parameters may be used to explain areas of radiation induced brain necrosis indicated on follow‐up imaging studies for a patient treated with postoperative intensity modulated proton radiotherapy for malignant meningioma. Methods: In this study, treatment plan information is extracted from a clinical treatment planning system (TPS) and used to recalculate physical proton dose and linear energy transfer (LET) distributions using Monte Carlo simulations. An RBE model which accounts for tissue specific parameters, LET, biological endpoint, and dose per treatment fraction is applied on a voxel‐by‐voxel basis to compute a biological effective dose distribution. This dose distribution is subsequently compared to follow‐up imaging studies which have indicated the presence of radiation induced necrosis in the treated region of the patient being analyzed. Corresponding areas of toxicity and dose/RBE are compared to determine the governing relationship. Results: Areas of increased biological effective dose compared to the original dose distribution calculated by the clinical TPS are found to correspond to areas of radiation induced necrosis identified on follow‐up imaging. Biologically effective dose is found to be increased over TPS dose by as much as 8% of the prescribed dose for the patient. Conclusions: Dose distributions which account for the variable nature of proton RBE may provide insight into toxicity risk for patients treated with proton radiotherapy.

Clinical Consequences of Relative Biological Effectiveness (RBE) Variations in Proton Radiotherapy of the Prostate, Brain, and Liver

The large range of (α/β)x-rays values reported for prostate (1.2Gy-5.0Gy), brain (10Gy-15Gy) and liver (13Gy-17Gy) imply that the proton RBE for these tissues could differ from the commonly used value of 1.1. Our aim was to evaluate the impact of this uncertainty on the RBE-weighted total dose (RWTD) to normal and tumor tissues when proton doses are delivered using standard or hypofractionated isoeffective regimes. RWTD distributions for five prostate, brain and liver patients were calculated using an in-house developed RBE model as a function of dose, Linear Energy Transfer (LET) and (α/β)x-rays. Variation on the DVH for the GTV and the organs-at-risk due to changes of (α/β)x-rays or fractionation regime were calculated and the RWTD received by 10% and 90% of the organ volume reported. The goodness of the plan, bearing the uncertainties, was then evaluated compared to the delivered plan with assumed RBE = 1.1. Table 1 summaries values of RWTD10 and RWTD90 when RBE is assumed to be equal to 1.1 and when RBE changes with the specified values of (α/β)x-rays. Standard fractionated regimes assuming an RBE varying with (α/β)x-rays provide RWTD10 values in organs-at-risk always smaller than those obtained in the case RBE = 1.1 except for the case of the chiasm, brainstem and the optical nerves. However, in hypofractionated regimes, the total doses received by normal tissues when RBE = 1.1 are in all cases larger than in the case of a variable RBE. The results show that, except for the case of prostate, large variations of (α/β)x-rays are not accompanied by large variations of RBE and, in standard fractionation regimes, the RWTD values derived from RBE = 1.1 or a variable RBE do not differ substantially. However, this difference increases in hypofractionated regimes, with a clear advantage for the case of a flexible RBE as in this case the RWTD delivered to the normal tissues is substantially smaller than in the case of RBE = 1.1. The results show that the use of a variable RBE with dose, LET and (α/β) x-rays would help to optimize the dose delivered to the target. The consideration of RBE variations could also influence the comparison of proton and photon treatments in clinical trials.Tabled 1GTV (1.2Gy< α/β <5.0Gy) Prescribed Dose (Standard Fractionation): 78.3GyANT RECTUM (2.5Gy< α/β <5.0Gy)BLADDER (3.0Gy< α/β <7.0Gy)GTV (10Gy< α/β <15Gy) Prescribed Dose (Standard Fractionation): 52.1GyCHIASM (1.5Gy< α/β <3.9Gy)BRAINSTEM (1.5Gy< α/β <3.9Gy)LT OPTICAL NERVE (1.5Gy< α/β <3.9Gy)RT OPTICAL NERVE (1.5Gy< α/β <3.9Gy)GTV (13Gy< α/β <17Gy) Prescribed Dose (Standard Fractionation): 60.2GyLUNG (1.6Gy< α/β <6.9Gy)HEALTHY LIVER (1.5Gy< α/β <3.0Gy)n = 3RWTD10RBE≠1.136 - 4931 - 3229.6 - 29.831.8 - 32.530.9 - 31.530.1 - 30.823.7 - 24.522.7 - 23.530.9 - 31.314.6 - 14.811.6 - 11.8RBE = 1.135.533.932.433.733.632.525.5824.532.415.812.3RWTD90RBE≠1.135 - 478 - 90.129.9 - 30.630 - 30.60.040.090.0929.2 - 29.60.010RBE = 1.134.59.10.1232.332.60.030.080.0830.60.010n = 10RWTD10RBE≠1.157 - 8049 - 5046 - 4752 - 5451 - 5350 - 5239 - 4137.7 - 39.848.6 - 49.423.1 - 23.518.6 - 19.8RBE = 1.155.552.950.555.154.853.041.839.950.524.619.2RWTD90RBE≠1.156 - 7713 - 140.2049 - 5149 - 510.050.160.1945.8 - 46.70.010.01RBE = 1.153.814.10.2052.853.20.050.150.1747.60.010.01Standard FractionationRWTD10RBE≠1.194 - 13979 - 8274.9 - 77.256 - 5955 - 5954 - 5843 - 4841 - 4665 - 6631.1 - 31.625 - 26.7RBE = 1.188.2684.280.457.957.755.843.94267.532.925.6RWTD90RBE≠1.191 - 13322 - 240.31 - 0.3454 - 5753.5 - 57.50.160.160.1661 - 620.010.01RBE = 1.185.720.70.3255.555.90.070.150.1663.70.010.01PROSTATE RWTD [Gy(RBE)]BRAIN RWTD [Gy(RBE)]LIVER RWTD [Gy(RBE)] Open table in a new tab

TU‐G‐BRA‐04: Biological Optimization in Carbon Therapy

The application of high linear energy transfer (LET) radiation in modern radiation oncology, like carbon‐ion therapy, requires different concepts of treatment plan optimization when compared RT‐planning for photon beams. Although, by far not perfect, the standard strategy employs the concept of relative biological effectiveness (RBE), which converts the delivered physical particle dose into a radio‐biologically equivalent dose of low LET beams. In order to introduce the respective RBE models into the inverse planning process of particle therapy one directly aims to optimize the biological effect, mostly expressed in terms of a linear quadratic model (LQM) for a dose‐effect relationship.We will first introduce the general framework of biological optimization for inverse planning of intensity modulated particle therapy (IMPT). The effects of the intrinsic radiation quality on the design of treatment plans will be demonstrated for various forms of dose delivery methods, like spread‐out Bragg peaks (SOBP), distal edge‐tracking (DET) or 3D‐spot scanning and different clinical treatment sites. So far, the employed models only account for the most important radiobiological factor, the anticipated local LET distribution, while other additional factors like the oxygen enhancement ratio or the influence of different fractionation schemes are not considered explicitly.Finally, another important issue will be briefly mentioned, the robustness of biologically optimized treatment plans versus uncertainties in the dose delivery process or even the limited knowledge of the biological input parameters of the employed models that are predicting the biological effect. Some results in the framework of the worst‐case optimization will be discussed.Learning Objectives:1. To review the framework of biological inverse planning of carbon therapy2. To understand the potential and inherent limitations of the optimization approach

Application of Constant vs. Variable Relative Biological Effectiveness in Treatment Planning of Intensity-Modulated Proton Therapy

To investigate in a simulation study whether using a variable relative biological effectiveness (RBE) in calculation and optimization of intensity-modulated proton therapy (IMPT) instead of using an RBE of 1.1 would result in significant changes in the RBE-weighted dose (RWD) distributions. For 4 patients with head-and-neck tumors, three IMPT plans were prepared respectively. The first plan was physically optimized (IMPT-PO plan), and the RWD was calculated with a constant RBE of 1.1. Then the plan's RWD was recalculated (IMPT-R plan) using a variable RBE model taking into account the linear energy transfer (LET) and tissue-specific radiobiological parameters. The third IMPT plan was optimized using a biological optimization routine (IMPT-BO plan). Comparing the IMPT-PO and IMPT-R plans, we observed that the RWD in radioresistant tissues was more sensitive to the LET than in radiosensitive tissues. The IMPT-R plans were in general more inhomogeneous than the IMPT-PO plans. The differences of RWD distributions for all volumes between IMPT-PO and IMPT-BO plans complied with predefined dose-volume constraints. The average LET was significantly lower in IMPT-BO plans than in IMPT-R plans. In radioresistant normal tissues caution has to be used regarding the LET distribution because these are most sensitive to changes in the LET. Biological optimization of IMPT plans based on the organ-specific biological parameters and LET distributions is feasible.

SU-FF-T-162: Significance of RBE Optimization in Proton Radiotherapy and Its Impact in the Low Energy Treatment Case

Purpose: Current treatment planning systems use a constant Relative Biological Effectiveness (RBE) value of 1.1 for protonradiotherapy treatments ‐ irrespective of the tumor volume, location, tissue type, initial energy of the proton beam or dose/fraction. However, research shows that the RBE value is not constant and it increases significantly in particular, over the distal falloff region of the Bragg peak. Uncertainty associated with both the calculation and effect of dose delivered to the tumor region compels physicians to consider a relatively larger Clinical Treatment Volume (CTV). This error margin may be reduced by incorporating appropriate variable RBE corrections and thereby facilitating optimization of the CTV. Method and Materials: In order to most effectively make use of this treatment modality, we suggest it is important to adopt biological cellular dose response models for tumors for implementation into treatment planning systems. An RBE model based on the existing Microdosimetric‐Kinetic (MKM) based model with a modification in one of its parameters namely beta(p), in the high LET range (20–33 keV per micrometer) can be used for the calculation of biological dose.Results: The described model is able to calculate the biological dose distribution of the clinical proton energies, taking into consideration both the physical and biological parameters of the incoming beam line and tissue type. The models accuracy in RBE calculations and computational speed makes it convenient for implementation purposes. Conclusions: The existing MKM based RBE model, making use of both the linear quadratic and track structure models, is a viable candidate for high energy (>70 MeV) treatments. Similarly, a modified version of this MKM based model has to be used for low energy (∼up to 70 MeV) applications, such as the treatment of ocular tumors.