Uncertainties In Proton Therapy Research Articles

Benefit of range uncertainty reduction in robust optimisation for proton therapy of brain, head-and-neck and breast cancer patients

Background and PurposeThe primary cause of range uncertainty in proton therapy is inaccuracy in estimating the stopping-power ratio from computed tomography. This study examined the impact on dose-volume metrics by reducing range uncertainty in robust optimisation for a diverse patient cohort and determined the level of range uncertainty that resulted in a relevant reduction in doses to organs-at-risk (OARs). Materials and MethodsThe effect of reducing range uncertainty on OAR doses was evaluated by robustly optimising six proton plans with varying range uncertainty levels (ranging from 3.5% in the original plan to 1.0%), keeping setup uncertainty fixed. All plans used the initial clinical treatment plan’s beam directions and optimisation objectives and were optimised until a clinically acceptable plan was achieved across all setup and range scenarios. The effect of reduced range uncertainty on dose-volume metrics for OARs near the target was evaluated. This study included 30 brain cancer patients, as well as five head-and-neck and five breast cancer patients, investigating the relevance of reducing range uncertainty when different setup uncertainties were used. ResultsLowering range uncertainty slightly reduced the nominal dose to surrounding tissue. For body volume receiving 80% of the prescribed dose, reducing range uncertainty from 3.5% to 2.0% resulted in a median decrease of 4 cm3 for the brain, 17 cm3 for head-and-neck, and 27 cm3 for breast cancer patients. ConclusionsReducing range uncertainty in robust optimisation showed a reduction in dose to OARs. The clinical relevance depends on the affected organs and the clinical dose constraints.

Impact of and interplay between proton arc therapy and range uncertainties in proton therapy for head-and-neck cancer

Objective. Proton therapy reduces the integral dose to the patient compared to conventional photon treatments. However, in vivo proton range uncertainties remain a considerable hurdle. Range uncertainty reduction benefits depend on clinical practices. During intensity-modulated proton therapy (IMPT), the target is irradiated from only a few directions, but proton arc therapy (PAT), for which the target is irradiated from dozens of angles, may see clinical implementation by the time considerable range uncertainty reductions are achieved. It is therefore crucial to determine the impact of PAT on range uncertainty reduction benefits. Approach. For twenty head-and-neck cancer patients, four different treatment plans were created: an IMPT and a PAT treatment plan assuming current clinical range uncertainties of 3.5% (IMPT3.5% and PAT3.5%), and an IMPT and a PAT treatment plan assuming that range uncertainties can be reduced to 1% (IMPT1% and PAT1%). Plans were evaluated with respect to target coverage and organ-at-risk doses as well as normal tissue complication probabilities (NTCPs) for parotid glands (endpoint: parotid gland flow <25%) and larynx (endpoint: larynx edema). Main results. Implementation of PAT (IMPT3.5%−PAT3.5%) reduced mean NTCPs in the nominal and worst-case scenario by 3.2 percentage points (pp) and 4.2 pp, respectively. Reducing range uncertainties from 3.5% to 1% during use of IMPT (IMPT3.5%−IMPT1%) reduced evaluated NTCPs by 0.9 pp and 2.0 pp. Benefits of range uncertainty reductions subsequently to PAT implementation (PAT3.5%−PAT1%) were 0.2 pp and 1.0 pp, with considerably higher benefits in bilateral compared to unilateral cases. Significance. The mean clinical benefit of implementing PAT was more than twice as high as the benefit of a 3.5%–1% range uncertainty reduction. Range uncertainty reductions are expected to remain beneficial even after PAT implementation, especially in cases with target positions allowing for full leveraging of the higher number of gantry angles during PAT.

The dirty and clean dose concept: Towards creating proton therapy treatment plans with a photon-like dose response.

Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1. This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses. The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives. In the water phantom studies, LET thresholds between 1.5 and 2.5keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45Gy(RBE), patient 2: 0.08Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81Gy(RBE), patient 2: 0.53Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp). The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.

Improved sub-milimeter range-verification method for proton therapy using a composite hadron tumour marker (HTM)

Objective. The results of a follow-up experiment investigating a novel method for sub-milimetre range verification (RV) in proton therapy (PT) are presented. Approach. The method consists of implanting a hadron tumour marker (HTM) near the planned treatment volume, and measuring the γ-ray signals emitted as a result of activation by the proton beam. These signals are highly correlated with the energy of the beam impinging on the HTM and can provide an absolute measurement of the range of the beam relative to the position of the HTM, which is independent of any uncertainties in beam delivery. Main results. Three candidate HTM materials were identified and combined into a single composite HTM, which makes use of the strongest reaction in each material. The setup of the previous experiment was improved on by using high-purity germanium detectors to measure the γ-ray signal with a higher resolution than was previously achieved. A PMMA phantom was also used to simulate the γ-ray background from tissue activation. HTM RV using the data collected in this study yielded range measurements whose average deviation from the expected value was 0.13(22)mm. Significance. Range uncertainty in PT limits the prescribed treatment plan for cancer patients with large safety margins and constrains the direction of the proton beam in relation to any organ at risk. The sub-milimetre range uncertainty achieved in this study using HTM RV, if implemented clinically, would allow for a reduction in the size of safety margins, increasing the therapeutic window for PT.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination using ex vivo animal tissues and tissue-mimicking phantoms

Objective. Range uncertainty in proton therapy is an important factor limiting clinical effectiveness. Magnetic resonance imaging (MRI) can measure voxel-wise molecular composition and, when combined with kilovoltage CT (kVCT), accurately determine mean ionization potential (I m ), electron density, and stopping power ratio (SPR). We aimed to develop a novel MR-based multimodal method to accurately determine SPR and molecular compositions. This method was evaluated in tissue-mimicking and ex vivo porcine phantoms, and in a brain radiotherapy patient. Approach. Four tissue-mimicking phantoms with known compositions, two porcine tissue phantoms, and a brain cancer patient were imaged with kVCT and MRI. Three imaging-based values were determined: SPRCM (CT-based Multimodal), SPRMM (MR-based Multimodal), and SPRstoich (stoichiometric calibration). MRI was used to determine two tissue-specific quantities of the Bethe Bloch equation (I m , electron density) to compute SPRCM and SPRMM. Imaging-based SPRs were compared to measurements for phantoms in a proton beam using a multilayer ionization chamber (SPRMLIC). Main results. Root mean square errors relative to SPRMLIC were 0.0104(0.86%), 0.0046(0.45%), and 0.0142(1.31%) for SPRCM, SPRMM, and SPRstoich, respectively. The largest errors were in bony phantoms, while soft tissue and porcine tissue phantoms had <1% errors across all SPR values. Relative to known physical molecular compositions, imaging-determined compositions differed by approximately ≤10%. In the brain case, the largest differences between SPRstoich and SPRMM were in bone and high lipids/fat tissue. The magnitudes and trends of these differences matched phantom results. Significance. Our MR-based multimodal method determined molecular compositions and SPR in various tissue-mimicking phantoms with high accuracy, as confirmed with proton beam measurements. This method also revealed significant SPR differences compared to stoichiometric kVCT-only calculation in a clinical case, with the largest differences in bone. These findings support that including MRI in proton therapy treatment planning can improve the accuracy of calculated SPR values and reduce range uncertainties.

Tackling range uncertainty in proton therapy: Development and evaluation of a new multi-slit prompt-gamma camera (MSPGC) system

In theory, the sharp dose falloff at the distal end of a proton beam allows for high conformal dose to the target. However, conformity has not been fully achieved in practice, primarily due to beam range uncertainty, which is approximately 4% and varies slightly across institutions. To address this issue, we developed a new range verification system prototype: a multi-slit prompt-gamma camera (MSPGC). This system features high prompt-gamma detection sensitivity, an advanced range estimation algorithm, and a precise camera positioning system. We evaluated the range measurement precision of the prototype for single spot beams with varying energies, proton quantities, and positions, as well as for spot-scanning proton beams in a simulated SSPT treatment using a phantom. Our results demonstrated high accuracy (<0.4 mm) in range measurement for the tested beam energies and positions. Measurement precision increased significantly with the number of protons, achieving 1% precision with 5 × 108 protons. For spot-scanning proton beams, the prototype ensured more than 5 × 108 protons per spot with a 7 mm or larger spot aggregation, achieving 1% range measurement precision. Based on these findings, we anticipate that the clinical application of the new prototype will reduce range uncertainty (currently approximately 4%) to 1% or less.

Quantitative and qualitative evaluation of density resolution of pCT images using Cirs062m phantom simulation in Geant4

Accuracy in the treatment planning (TP) of proton therapy (PT) depends on the precision of the information employed to calculate the relative stopping power (RSP) of the tissues in the patient's body. This information is obtained from the x-ray computed tomography (xCT) images and the calibration curve needed to convert the Hounsfield unit to RSP values. Using xCT bears errors in proton range estimation and dose calculation of TP. Proton computed tomography (pCT) can decrease the inherent uncertainty in PT by directly measuring RSP. Though by using pCT in the integral mode of energy loss, this error is removed, and the RSP map of tissues is calculated directly. This study simulated a modern pCT imaging system with particle-by-particle tracking capability using Geant4 Monte Carlo code. This simulation sought to improve the density resolution of tissue images without increasing the dose. The CIRS062M standard phantom was irradiated with 300 MeV protons, and the energy, position, and direction of the particle were recorded before and after the phantom. The matrix of the RSP image was modified using the normalization algorithm of the amount of integral energy loss and the correction of the angles of the projections.

In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO.

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam’s Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan.

Radiation shielding assessment of high‐energy proton imaging at a proton therapy facility

BackgroundProton imaging makes use of high‐energy, low‐intensity proton beams that fully traverse the patient and has been suggested to reduce range uncertainty in proton therapy. Upright patient positioning with proton imaging is being considered for a fixed beam room of a new proton therapy facility currently under construction. Considering that the yield and energy spectrum of secondary radiation from high‐energy proton beams is proton beam energy dependent, an assessment of radiation shielding at the energies required for proton imaging should be performed prior to use. Furthermore, NCRP 144 recommends that pion production be considered for proton energies greater than 300 MeV, which are not typically utilized for proton therapy but may be required for proton imaging.PurposeThe purpose of this work was to determine whether proton treatment and imaging with an upright patient positioning system on a fixed beamline were acceptable from a radiation shielding perspective. This is the first report on radiation shielding assessment of proton imaging applications and includes consideration of pion production at the proton beam energy of 330 MeV.MethodsThe Geant4 Monte Carlo toolkit was used for the radiation shielding assessment. The calculations consisted of the generation of secondary particle phase‐space files by simulating the passage of high‐energy proton beams in two target materials, and subsequent simulation of the secondary particles in the proton therapy facility geometry. Particle fluence was converted to operational and protection radiation safety quantities with a custom python script for assessment of instantaneous and annual doses, respectively.ResultsThe total yields of pions from a 330‐MeV proton beam were many orders of magnitude less than that of neutrons and photons. Three‐dimensional maps of ambient dose rate for a 330‐MeV proton beam showed doses arising from secondary neutrons and photons far exceed those arising from pion production. Incorporating representative annual workloads into the calculation demonstrated that proton imaging doses outside the shielded area were negligible compared to those arising from proton therapy.ConclusionsPion production has a negligible impact on the radiation shielding of proton imaging at 330 MeV relative to neutron and photon production. Radiation shielding designed for proton therapy is adequate for high‐energy proton imaging applications.

PO-1498 Reduction of setup uncertainty in proton therapy for mediastinal lymphoma patients.

PO-1498 Reduction of setup uncertainty in proton therapy for mediastinal lymphoma patients.

NTCP Modeling of Late Effects for Head and Neck Cancer: A Systematic Review.

NTCP Modeling of Late Effects for Head and Neck Cancer: A Systematic Review.

Variance-based sensitivity analysis for uncertainties in proton therapy: A framework to assess the effect of simultaneous uncertainties in range, positioning, and RBE model predictions on RBE-weighted dose distributions.

Treatment plans in proton therapy are more sensitive to uncertainties than in conventional photon therapy. In addition to setup uncertainties, proton therapy is affected by uncertainties in proton range and relative biological effectiveness (RBE). While to date a constant RBE of 1.1 is commonly assumed, the actual RBE is known to increase toward the distal end of the spread-out Bragg peak. Several models for variable RBE predictions exist. We present a framework to evaluate the combined impact and interactions of setup, range, and RBE uncertainties in a comprehensive, variance-based sensitivity analysis (SA). The variance-based SA requires a large number (104 -105 ) of RBE-weighted dose (RWD) calculations. Based on a particle therapy extension of the research treatment planning system CERR we implemented a fast, graphics processing unit (GPU) accelerated pencil beam modeling of patient and range shifts. For RBE predictions, two biological models were included: The mechanistic repair-misrepair-fixation (RMF) model and the phenomenological Wedenberg model. All input parameters (patient position, proton range, RBE model parameters) are sampled simultaneously within their assumed probability distributions. Statistical formalisms rank the input parameters according to their influence on the overall uncertainty of RBE-weighted dose-volume histogram (RW-DVH) quantiles and the RWD in every voxel, resulting in relative, normalized sensitivity indices (S=0: noninfluential input, S=1: only influential input). Results are visualized as RW-DVHs with error bars and sensitivity maps. The approach is demonstrated for two representative brain tumor cases and a prostate case. The full SA including RWD calculations took 39, 11, and 55min, respectively. Range uncertainty was an important contribution to overall uncertainty at the distal end of the target, while the relatively smaller uncertainty inside the target was governed by biological uncertainties. Consequently, the uncertainty of the RW-DVH quantile D98 for the target was governed by range uncertainty while the uncertainty of the mean target dose was dominated by the biological parameters. The SA framework is a powerful and flexible tool to evaluate uncertainty in RWD distributions and DVH quantiles, taking into account physical and RBE uncertainties and their interactions. The additional information might help to prioritize research efforts to reduce physical and RBE uncertainties and could also have implications for future approaches to biologically robust planning and optimization.

OpenPR - A computational tool for CT conversion assessment with proton radiography.

One of the main sources of uncertainty in proton therapy is the conversion of the Hounsfield Units of the planning CT to (relative) proton stopping powers. Proton radiography provides range error maps but these can be affected by other sources of errors as well as the CT conversion (e.g., residual misalignment). To better understand and quantify range uncertainty, it is desirable to measure the individual contributions and particularly those associated to the CT conversion. A workflow is proposed to carry out an assessment of the CT conversion solely on the basis of proton radiographs of real tissues measured with a multilayer ionization chamber (MLIC). The workflow consists of a series of four stages: (a) CT and proton radiography acquisitions, (b) CT and proton radiography registration in postprocessing, (c) sample-specific validation of the semi-empirical model both used in the registration and to estimate the water equivalent path length (WEPL), and (d) WEPL error estimation. The workflow was applied to a pig head as part of the validation of the CT calibration of the proton therapy center PARTICLE at UZ Leuven, Belgium. The CT conversion-related uncertainty computed based on the well-established safety margin rule of 1.2mm+2.4% were overestimated by 71% on the pig head. However, the range uncertainty was very much underestimated where cavities were encountered by the protons. Excluding areas with cavities, the overestimation of the uncertainty was 500%. A correlation was found between these localized errors and HUs between -1000 and -950, suggesting that the underestimation was not a consequence of an inaccurate conversion but was probably rather due to the resolution of the CT leading to material mixing at interfaces. To reduce these errors, the CT calibration curve was adapted by increasing the HU interval corresponding to the air up to -950. The application of the workflow as part of the validation of the CT conversion to RSPs showed an overall overestimation of the expected uncertainty. Moreover, the largest WEPL errors were found to be related to the presence of cavities which nevertheless are associated with low WEPL values. This suggests that the use of this workflow on patients or in a generalized study on different types of animal tissues could shed sufficient light on how the contributions to the CT conversion-related uncertainty add up to potentially reduce up to several millimeters the uncertainty estimations taken into account in treatment planning. All the algorithms required to perform the workflow were implemented in the computational tool named openPR which is part of openREGGUI, an open-source image processing platform for adaptive proton therapy.

OC-0705: Dose restoration: an online adaptive strategy to fight against range uncertainties in proton therapy

OC-0705: Dose restoration: an online adaptive strategy to fight against range uncertainties in proton therapy

SP-0748: The worst-case scenario survival guide: uncertainties in proton therapy.

SP-0748: The worst-case scenario survival guide: uncertainties in proton therapy.

Current status of proton therapy techniques for lung cancer.

Proton beams have been used for cancer treatment for more than 28 years, and several technological advancements have been made to achieve improved clinical outcomes by delivering more accurate and conformal doses to the target cancer cells while minimizing the dose to normal tissues. The state-of-the-art intensity modulated proton therapy is now prevailing as a major treatment technique in proton facilities worldwide, but still faces many challenges in being applied to the lung. Thus, in this article, the current status of proton therapy technique is reviewed and issues regarding the relevant uncertainty in proton therapy in the lung are summarized.

Sparse deconvolution of proton radiography data to estimate water equivalent thickness maps.

In proton therapy, the conversion of the planning computed tomography (CT) into proton stopping powers is tainted by uncertainties which may jeopardize dose conformity. Proton radiography provides a direct information on the energy reduction of protons in the patient. However, it is currently limited by the degradation ("blurring") of the one-dimensional depth-dose deposition profiles which constitute the pixels. An iterative algorithm is implemented to extract high-resolution water equivalent thickness (WET) maps from the measurements of depth-dose profiles acquired with a multilayer ionization chamber. The method relies on the assumption that those curves are a function of the WET, which can benefit from a sparse representation. When used without relying on any prior knowledge derived from the planning CT, the method already outperforms the published one in terms of accuracy. We also propose a variant which integrates the planning CT in a robust fashion to further improve the deconvolution result and reach an accuracy of 1.5mm on the estimated WET. The methods are applied to both synthetic data and actual proton radiography acquisitions on phantoms. Besides the increase in accuracy achieved in the estimation of WET maps from proton radiography data, we demonstrate that the proposed deconvolution algorithm is also more robust with respect to confounding factors such as residual setup errors or changes in the anatomy. Therefore, proton radiography using a range probe provides both the required accuracy to assess and reduce range uncertainty in proton therapy and the simplicity of integrated-mode proton radiography.

Effects of the Bragg peak degradation due to lung tissue in proton therapy of lung cancer patients

PurposeTo quantify the effects of the Bragg peak degradation due to lung tissue on treatment plans of lung cancer patients with spot scanning proton therapy and to give a conservative approximation of these effects.Methods and materialsTreatment plans of five lung cancer patients (tumors of sizes 2.7–46.4 cm3 at different depths in the lung) were optimized without consideration of the Bragg peak degradation. These treatment plans were recalculated with the Monte Carlo code TOPAS in two scenarios: in a first scenario, the treatment plans were calculated without including the Bragg peak degradation to reproduce the dose distribution predicted by the treatment-planning system (TPS). In a second scenario, the treatment plans were calculated while including the Bragg peak degradation. Subsequently, the plans were compared by means of Dmean, D98% and D2% in the clinical target volume (CTV) and organs at risk (OAR). Furthermore, isodose lines were investigated and a gamma index analysis was performed.ResultsThe Bragg peak degradation leads to a lower dose in the CTV and higher doses in OARs distal to the CTV compared to the prediction from the TPS. The reduction of the mean dose in the CTV was − 5% at maximum and − 2% on average. The deeper a tumor was located in the lung and the smaller its volume the bigger was the effect on the CTV. The enhancement of the mean dose in OARs distal to the CTV was negligible for the cases investigated.ConclusionsEffects of the Bragg peak degradation due to lung tissue were investigated for lung cancer treatment plans in proton therapy. This study confirms that these effects are clinically tolerable to a certain degree in the current clinical context considering the various more critical dose uncertainties due to motion and range uncertainties in proton therapy.

Protonthérapie des carcinomes épidermoïdes des voies aérodigestives supérieures : de la physique à la clinique

Intensity-modulated radiation therapy (IMRT) is presently the recommended technique for the treatment of locally advanced head and neck carcinomas. Proton therapy would allow to reduce the volume of irradiated normal tissue and, thus, to decrease the risk of late dysphagia, xerostomia, dysgeusia and hypothyroidism. An exhaustive research was performed with the search engine PubMed by focusing on the papers about the physical difficulties that slow down use of proton therapy for head and neck carcinomas. Range uncertainties in proton therapy (±3 %) paradoxically limit the use of the steep dose gradient in distality. Calibration uncertainties can be important in the treatment of head and neck cancer in the presence of materials of uncertain stoichiometric composition (such as with metal implants, dental filling, etc.) and complex heterogeneities. Dental management for example may be different with IMRT or proton therapy. Some uncertainties can be somewhat minimized at the time of optimization. Inter- and intrafractional variations and uncertainties in Hounsfield units/stopping power can be integrated in a robust optimization process. Additional changes in patient's anatomy (tumour shrinkage, changes in skin folds in the beam patch, large weight loss or gain) require rescanning. Dosimetric and small clinical studies comparing photon and proton therapy have well shown the interest of proton therapy for head and neck cancers. Intensity-modulated proton therapy is a promising treatment as it can reduce the substantial toxicity burden of patients with head and neck squamous cell carcinoma compared to IMRT. Robust optimization will allow to perform an optimal treatment and to use proton therapy in current clinical practice.

Dependence of LET on material and its impact on current RBE model

Biological uncertainty remains one of the main sources of uncertainties in proton therapy, and is encapsulated in a scalar quantity known as relative biological effective (RBE). It is currently recognised that a constant RBE of 1.1 is not consistent with radiobiological experiment and may lead to sub-optimal exploitation of the benefits of proton therapy. To overcome this problem, several RBE models have been developed, and in most of these models, there is a dependence of RBE on dose-averaged linear energy transfer (LET), . In this work, we show that the estimation in these models during the data-fitting (or parameter estimation) phase could be subjected to a huge uncertainty due to not taking into account cellular materials during simulation, and this uncertainty can propagate down to the resulting RBE models. The dosimetric impact of this uncertainty is then evaluated on a simple clinical spread out Bragg peak (SOBP) and a prostate example. Our simulation shows that uncertainty due to the use of water as cellular material is non-negligible under low and low dose (2 Gy), and can be neglected otherwise. Thus, this study indicates that further dose and range margins may be required for low target under low dose. This is due to greater uncertainties in RBE model associated with incomplete knowledge of cellular composition for computation.