RBE-weighted Dose Distributions Research Articles

Quantifying the Dosimetric Impact of Proton Range Uncertainties on RBE-Weighted Dose Distributions in Intensity-Modulated Proton Therapy for Bilateral Head and Neck Cancer.

In current clinical practice, intensity-modulated proton therapy (IMPT) head and neck cancer (HNC) plans are generated using a constant relative biological effectiveness (cRBE) of 1.1. The primary goal of this study was to explore the dosimetric impact of proton range uncertainties on RBE-weighted dose (RWD) distributions using a variable RBE (vRBE) model in the context of bilateral HNC IMPT plans. The current study included the computed tomography (CT) datasets of ten bilateral HNC patients who had undergone photon therapy. Each patient's plan was generated using three IMPT beams to deliver doses to the CTV_High and CTV_Low for doses of 70 Gy(RBE) and 54 Gy(RBE), respectively, in 35 fractions through a simultaneous integrated boost (SIB) technique. Each nominal plan calculated with a cRBE of 1.1 was subjected to the range uncertainties of ±3%. The McNamara vRBE model was used for RWD calculations. For each patient, the differences in dosimetric metrices between the RWD and nominal dose distributions were compared. The constrictor muscles, oral cavity, parotids, larynx, thyroid, and esophagus showed average differences in mean dose (Dmean) values up to 6.91 Gy(RBE), indicating the impact of proton range uncertainties on RWD distributions. Similarly, the brachial plexus, brain, brainstem, spinal cord, and mandible showed varying degrees of the average differences in maximum dose (Dmax) values (2.78-10.75 Gy(RBE)). The Dmean and Dmax to the CTV from RWD distributions were within ±2% of the dosimetric results in nominal plans. The consistent trend of higher mean and maximum doses to the OARs with the McNamara vRBE model compared to cRBE model highlighted the need for consideration of proton range uncertainties while evaluating OAR doses in bilateral HNC IMPT plans.

β-delayed multiple-particle emitters minibeam radiation therapy: first dosimetric evaluation with Monte Carlo simulations

Radiation therapy, one of the most effective methods for cancer treatment, is still limited by the tolerances of normal tissues surrounding the tumor. Innovative techniques like spatially fractionated radiation therapy (SFRT) have been shown to increase normal tissue dose resistance. Heavy ions also offer high-dose conformity and increased relative biological effectiveness (RBE) when compared to protons and X-rays. The alliance of heavy ions and spatial fractionation of the dose has the potential to further increase the therapeutic index for difficult-to-treat cases today. In particular, the use of β-delayed multiple-particle emitters might further improve treatment response, as it holds the potential to increase high linear energy transfer (LET) decay products in the valleys of SFRT (low-dose regions) at the end of the range. To verify this hypothesis, this study compares β-delayed multiple-particle emitters (8Li, 9C, 31Ar) with their respective stable isotopes (7Li, 12C, 40Ar) to determine possible benefits of β-delayed multiple-particle emitters minibeam radiation therapy (β-MBRT). Monte Carlo simulations were performed using the GATE toolkit to assess the dose distributions of each ion. RBE-weighted dose distributions were calculated and used for the aforementioned comparison. No significant differences were found among carbon isotopes. In contrast, 8Li and 31Ar exhibited improved RBE-weighted dose distributions with an approximately 12–20% increase in the Bragg-peak-to-entrance dose ratio (BEDR) for both peaks and valleys, which favors tissue sparing. Additionally, 8Li and 31Ar exhibited a lower peak-to-valley dose ratio (PVDR) in normal tissues and higher PVDR in the tumor than 7Li and 40Ar. Biological experiments are needed to conclude whether the differences observed make β-delayed multiple-particle emitters advantageous for MBRT.

Double scattering and pencil beam scanning Monte Carlo workflows for proton therapy retrospective studies on radiation-induced toxicities

PurposeMonte Carlo (MC) simulations can be used to accurately simulate dose and linear energy transfers (LET) distributions, thereby allowing for the calculation of the relative biological effectiveness (RBE) of protons. We present hereby the validation and implementation of a workflow for the Monte Carlo modelling of the double scattered and pencil beam scanning proton beamlines at our institution. MethodsThe TOPAS/Geant4 MC model of the clinical nozzle has been comprehensively validated against measurements. The validation also included a comparison between simulated clinical treatment plans for four representative patients and the clinical treatment planning system (TPS). Moreover, an in-house tool implemented in Python was tested to assess the variable RBE-weighted dose in proton plans, which was illustrated for a patient case with a developing radiation-induced toxicity. ResultsThe simulated range and modulation width closely matches the measurements. Gamma-indexes (3%/3mm 3D), which compare the TPS and MC computations, showed a passing rate superior to 98%. The calculated RBE-weighted dose presented a slight increase at the necrosis location, within the PTV margins. This indicates the need for reporting on the physical and biological effects of irradiation in high dose regions, especially at the healthy tissues and increased LET distributions location. ConclusionThe results demonstrate that the Monte Carlo method can be used to independently validate a TPS calculation, and to estimate LET distributions. The features of the in-house tool can be used to correlate LET and RBE-weighted dose distributions with the incidence of radiation-induced toxicities following proton therapy treatments.

Quantification of biological range uncertainties in patients treated at the Krakow proton therapy centre

BackgroundVariable relative biological effectiveness (vRBE) in proton therapy might significantly modify the prediction of RBE-weighted dose delivered to a patient during proton therapy. In this study we will present a method to quantify the biological range extension of the proton beam, which results from the application of vRBE approach in RBE-weighted dose calculation.Methods and materialsThe treatment plans of 95 patients (brain and skull base patients) were used for RBE-weighted dose calculation with constant and the McNamara RBE model. For this purpose the Monte Carlo tool FRED was used. The RBE-weighted dose distributions were analysed using indices from dose-volume histograms. We used the volumes receiving at least 95% of the prescribed dose (V95) to estimate the biological range extension resulting from vRBE approach.ResultsThe vRBE model shows higher median value of relative deposited dose and D95 in the planning target volume by around 1% for brain patients and 4% for skull base patients. The maximum doses in organs at risk calculated with vRBE was up to 14 Gy above dose limit. The mean biological range extension was greater than 0.4 cm.DiscussionOur method of estimation of biological range extension is insensitive for dose inhomogeneities and can be easily used for different proton plans with intensity-modulated proton therapy (IMPT) optimization. Using volumes instead of dose profiles, which is the common method, is more universal. However it was tested only for IMPT plans on fields arranged around the tumor area.ConclusionsAdopting a vRBE model results in an increase in dose and an extension of the beam range, which is especially disadvantageous in cancers close to organs at risk. Our results support the need to re-optimization of proton treatment plans when considering vRBE.

Extension of RBE-weighted 4D particle dose calculation for non-periodic motion.

Highly conformal scanned Carbon Ion Radiotherapy (CIRT) might permit dose escalation and improved local control in advanced stage thoracic tumors, but is challenged by target motion. Dose calculation algorithms typically assume a periodically repeating, regular motion. To assess the effect of realistic, irregular motion, new algorithms of validated accuracy are needed. We extended an in-house treatment planning system to calculate RBE-weighted dose distributions in CIRT on non-periodic CT image sequences. Dosimetric accuracy was validated experimentally on a moving, time-resolved ionization chamber array. Log-file based dose reconstructions were compared by gamma analysis and correlation to measurements at every intermediate detector frame during delivery. The impact of irregular motion on treatment quality was simulated on a virtual 4DCT thorax phantom. Periodic motion was compared to motion with varying amplitude and period ± baseline drift. Rescanning as a mitigation strategy was assessed on all scenarios. In experimental validation, average gamma pass rates were 99.89+-0.30% for 3%/3mm and 88.2+-2.2% for 2%/2mm criteria. Average correlation for integral dose distributions was 0.990±0.002. Median correlation for single 200ms frames was 0.947±0.006. In the simulations, irregular motion deteriorated V95 target coverage to 81.2%, 76.6% and 79.0% for regular, irregular motion and irregular motion with base-line drift, respectively. Rescanning restored V95 to >98% for both scenarios without baseline drift, but not with additional baseline drift at 83.7%. The validated algorithm permits to study the effects of irregular motion and to develop and adapt appropriate motion mitigation techniques.

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.

Spatial correlation of linear energy transfer and relative biological effectiveness with suspected treatment-related toxicities following proton therapy for intracranial tumors.

The enhanced relative biological effectiveness (RBE) at the end of the proton range might increase the risk of radiation-induced toxicities. This is of special concern for intracranial treatments where several critical organs at risk (OARs) surround the tumor. In the light of this, a retrospective analysis of dose-averaged linear energy transfer (LETd ) and RBE-weighted dose (DRBE ) distributions was conducted for three clinical cases with suspected treatment-related toxicities following intracranial proton therapy. Alternative treatment strategies aiming to reduce toxicity risks are also presented. The clinical single-field optimized (SFO) plans were recalculated for 81 error scenarios with a Monte Carlo dose engine. The fractionation DRBE was 1.8Gy (RBE) in 28 or 30 fractions assuming a constant RBE of 1.1. Two LETd - and α/β-dependent variable RBE models were used for evaluation, including a sensitivity analysis of the α/β parameter. Resulting distributions of DRBE and LETd were analyzed together with normal tissue complication probabilities (NTCPs). Subsequently, four multi-field optimized (MFO) plans, with an additional beam and/or objectives penalizing protons stopping in OARs, were created to investigate the potential reduction of LETd , DRBE , and NTCP. The two variable RBE models agreed well and predicted average RBE values around 1.3 in the toxicity volumes, resulting in an increased near-maximum DRBE of 7-11Gy (RBE) compared to RBE=1.1 in the nominal scenario. The corresponding NTCP estimates increased from 0.8%, 0.0%, and 3.7% (RBE=1.1) to 15.5%, 1.8%, and 45.7% (Wedenberg RBE model) for the three patients, respectively. The MFO plans generally allowed for LETd , DRBE , and NTCP reductions in OARs, without compromising the target dose. Compared to the clinical SFO plans, the maximum reduction in the near-maximum LETd was 56%, 63%, and 72% in the OAR exhibiting the toxicity for the three patients, respectively. Although a direct causality between RBE and toxicity cannot be established here, high LETd and DRBE correlated spatially with the observed toxicities, whereas setup and range uncertainties had a minor impact. Individual factors, which might affect the patient-specific radiosensitivity, were however not included in these calculations. The MFO plans using both an additional beam and proton track-end objectives allowed the largest reductions in LETd , DRBE , and NTCP, and might be future tools for similar cases.

In Silico Models of DNA Damage and Repair in Proton Treatment Planning: A Proof of Concept

There is strong in vitro cell survival evidence that the relative biological effectiveness (RBE) of protons is variable, with dependence on factors such as linear energy transfer (LET) and dose. This is coupled with the growing in vivo evidence, from post-treatment image change analysis, of a variable RBE. Despite this, a constant RBE of 1.1 is still applied as a standard in proton therapy. However, there is a building clinical interest in incorporating a variable RBE. Recently, correlations summarising Monte Carlo-based mechanistic models of DNA damage and repair with absorbed dose and LET have been published as the Manchester mechanistic (MM) model. These correlations offer an alternative path to variable RBE compared to the more standard phenomenological models. In this proof of concept work, these correlations have been extended to acquire RBE-weighted dose distributions and calculated, along with other RBE models, on a treatment plan. The phenomenological and mechanistic models for RBE have been shown to produce comparable results with some differences in magnitude and relative distribution. The mechanistic model found a large RBE for misrepair, which phenomenological models are unable to do. The potential of the MM model to predict multiple endpoints presents a clear advantage over phenomenological models.

RBE-weighted doses in target volumes of chordoma and chondrosarcoma patients treated with carbon ion radiotherapy: Comparison of local effect models I and IV

Background and purposeTo compare the relative biological effectiveness (RBE)-weighted dose distributions in the target volume of chordoma and chondrosarcoma patients when using two different versions of the local effect model (LEM I vs. IV) under identical conditions. Materials and methodsThe patient collective included 59 patients treated with 20 fractions of carbon ion radiotherapy for chordoma and low-grade chondrosarcoma of the skull base at the Helmholtzzentrum für Schwerionenforschung (GSI) in 2002 and 2003. Prescribed doses to the planning target volume (PTV) were 60 (n = 49), 66 (n = 2) and 70 (n = 8) Gy (RBE). The original treatment plans that were initially biologically optimized with LEM I, were now recalculated using LEM IV based on the absorbed dose distributions. The resulting RBE-weighted dose distributions were quantitatively compared to assess the clinical impact of LEM IV relative to LEM I in the target volume. ResultsLEM IV predicts 20–30 Gy (RBE) increased maximum doses as compared to LEM I, while minimum doses are decreased by 2–5 Gy (RBE). Population-based mean and median doses deviated by less than 2 Gy (RBE) between both models. ConclusionsLEM I and LEM IV-based RBE-weighted doses in the target volume may be significantly different. Replacing the applied model in patient treatments may therefore lead to local over- or underdosages in the tumor. If LEM IV is to be tested clinically, comparisons of the RBE-weighted dose distributions of both models are required for the individual patients to assess whether the LEM IV-plan would also be acceptable and prescribed dose as well as clinical outcome data have to be carefully reassessed.

Simultaneous optimization of RBE-weighted dose and nanometric ionization distributions in treatment planning with carbon ions

Inverse treatment planning in intensity modulated particle therapy (IMPT) with scanned carbon–ion beams is currently based on the optimization of RBE-weighted dose to satisfy requirements of target coverage and limited toxicity to organs-at-risk (OARs) and healthy tissues. There are many feasible IMPT plans that meet these requirements, which allows the introduction of further criteria to narrow the selection of a biologically optimal treatment plan. We propose a novel treatment planning strategy based on the simultaneous optimization of RBE-weighted dose and nanometric ionization details (ID) as a new physical characteristic of the delivered plan beyond LET. In particular, we focus on the distribution of large ionization clusters (more than 3 ionizations) to enhance the biological effect across the target volume while minimizing biological effect in normal tissues. Carbon–ion treatment plans for different patient geometries and beam configurations generated with the simultaneous optimization strategy were compared against reference plans obtained with RBE-weighted dose optimization alone. Quality indicators, inhomogeneity index and planning volume histograms of RBE-weighted dose and large ionization clusters were used to evaluate the treatment plans. We show that with simultaneous optimization, ID distributions can be optimized in carbon–ion radiotherapy without compromising the RBE-weighted dose distributions. This strategy can potentially be used to account for optimization of endpoints closely related to radiation quality to achieve better tumor control and reduce risks of complications.

Interlaced proton grid therapy – Linear energy transfer and relative biological effectiveness distributions

PurposeInterlaced beams have previously been proposed for delivering proton grid therapy. This study aims to assess dose-averaged LET (LETd) and RBE-weighted dose (DRBE) distributions of such beam geometries, and compare them with conventional intensity modulated proton therapy (IMPT). MethodsIMPT plans and four different interlaced proton grid therapy plans were generated for five patient cases (esophagus, lung, liver, prostate, anus). The constant RBE = 1.1 was assumed for optimization. The LETd was subsequently Monte Carlo calculated for each plan and used as input for two LET-dependent variable RBE models. The fulfilment of clinical goals, along with DVH and spatial distribution evaluations, were then assessed and compared. ResultsAll plans fulfilled the clinical target goals assuming RBE = 1.1. The target coverage was slightly compromised for some grid plans when assuming the variable RBE models. All IMPT plans, and 18 of 20 grid plans, fulfilled all clinical goals for the organs at risk when assuming RBE = 1.1, whereas most plans failed at least one goal when assuming the variable RBE models. Compared with the IMPT plans, the grid plans demonstrated substantially different LETd distributions due to the fundamentally different beam geometries. However, DRBE distributions in the target were similar. ConclusionsDespite the unconventional beam geometries of interlaced proton grid plans, with resulting alternating dose and LETd patterns, the fulfillment of realistic clinical goals seems to be comparable to regular IMPT plans, both assuming RBE = 1.1 and variable RBE models. In addition, the alternating grid patterns do not seem to give rise to unexpected DRBE hot-spots.

Biological dose and complication probabilities for the rectum and bladder based on linear energy transfer distributions in spot scanning proton therapy of prostate cancer

Background: The increased linear energy transfer (LET) at the end of the Bragg peak causes concern for an elevated and spatially varying relative biological effectiveness (RBE) of proton therapy (PT), often in or close to dose-limiting normal tissues. In this study, we investigated dose-averaged LET (LETd) distributions for spot scanning PT of prostate cancer patients using different beam angle configurations. In addition, we derived RBE-weighted (RBEw) dose distributions and related normal tissue complication probabilities (NTCPs) for the rectum and bladder.Material and methods: A total of 21 spot scanning proton plans were created for each of six patients using a prescription dose of 78 Gy(RBE1.1), with each plan using two ‘mirrored’ beams with gantry angles from 110°/250° to 70°/290°, in steps of 2°. Physical dose and LETd distributions were calculated as well as RBEw dose distributions using either RBE = 1.1 or three different variable RBE models. The resulting biological dose distributions were used as input to NTCP models for the rectum and bladder.Results: For anterior oblique (AO) configurations, the rectum LETd volume and RBEw dose increased with increasing angles off the lateral opposing axis, with the RBEw rectum dose being higher than for all posterior oblique (PO) configurations. For PO configurations, the corresponding trend was seen for the bladder. Using variable RBE models, the rectum NTCPs were highest for the AO configurations with up to 3% for the 80°/280° configuration while the bladder NTCPs were highest for the PO configurations with up to 32% for the 100°/260°. The rectum D1cm3 constraint was fulfilled for most patients/configurations when using uniform RBE but not for any patient/configuration with variable RBE models.Conclusions: Compared to using constant RBE, the variable RBE models predicted increased biological doses to the rectum, bladder and prostate, which in turn lead to substantially higher estimated rectum and bladder NTCPs.

Impact of respiratory motion on variable relative biological effectiveness in 4D-dose distributions of proton therapy

Background: Organ motion during radiation therapy with scanned protons leads to deviations between the planned and the delivered physical dose. Using a constant relative biological effectiveness (RBE) of 1.1 linearly maps these deviations into RBE-weighted dose. However, a constant value cannot account for potential nonlinear variations in RBE suggested by variable RBE models. Here, we study the impact of motion on recalculations of RBE-weighted dose distributions using a phenomenological variable RBE model.Material and methods: 4D-dose calculation including variable RBE was implemented in the open source treatment planning toolkit matRad. Four scenarios were compared for one field and two field proton treatments for a liver cancer patient assuming (α∕β)x = 2 Gy and (α∕β)x = 10 Gy: (A) the optimized static dose distribution with constant RBE, (B) a static recalculation with variable RBE, (C) a 4D-dose recalculation with constant RBE and (D) a 4D-dose recalculation with variable RBE. For (B) and (D), the variable RBE was calculated by the model proposed by McNamara. For (C), the physical dose was accumulated with direct dose mapping; for (D), dose-weighted radio-sensitivity parameters of the linear quadratic model were accumulated to model synergistic irradiation effects on RBE.Results: Dose recalculation with variable RBE led to an elevated biological dose at the end of the proton field, while 4D-dose recalculation exhibited random deviations everywhere in the radiation field depending on the interplay of beam delivery and organ motion. For a single beam treatment assuming (α∕β)x = 2 Gy, D95% was 1.98 Gy (RBE) (A), 2.15 Gy (RBE) (B), 1.81 Gy (RBE) (C) and 1.98 Gy (RBE) (D). The homogeneity index was 1.04 (A), 1.08 (B), 1.23 (C) and 1.25 (D).Conclusion: For the studied liver case, intrafractional motion did not reduce the modulation of the RBE-weighted dose postulated by variable RBE models for proton treatments.

Proton Treatment Techniques for Posterior Fossa Tumors: Consequences for Linear Energy Transfer and Dose-Volume Parameters for the Brainstem and Organs at Risk

In proton therapy of posterior fossa tumors, at least partial inclusion of the brainstem in the target is necessary because of its proximity to the tumor and required margins. Additionally, the preferred beam geometry results in directing the field distal edge toward this critical structure, raising concerns for brainstem toxicity. Some treatment techniques place the beam's distal edge within the brainstem (dose-sparing techniques), and others avoid elevated linear energy transfer (LET) of the proton field by placing the distal edge beyond it (LET-sparing techniques). Hybrid approaches are also being used. We examine the dosimetric efficacy of these techniques, accounting for LET-dependent and dose-dependent variable relative biologic effectiveness (RBE) distributions. Six techniques were applied in ependymoma cases: (a) 3-field dose-sparing; (b) 3-field LET-sparing; (c) 2-field dose-sparing, wide angles; (d) 2-field LET-sparing, wide angles; (e) 2-field LET-sparing, steep angles; and (f) 2-field LET-sparing with feathered distal end. Monte Carlo calculated dose, LET, and RBE-weighted dose distributions were compared. Decreased LET values in the brainstem by LET-sparing techniques were accompanied by higher, not statistically significant, median dose: 53.6Gy(RBE), 53.4Gy(RBE), and 54.3Gy(RBE) for techniques (b), (d), and (e) versus 52.1Gy(RBE) for technique (a). Accounting for variable RBE distributions, the brainstem volume receiving at least 55Gy(RBE) increased from 72.5% for technique (a) to 80.3% for (b) (P<.01) and from 70.7% for technique (c) to 77.6% for (d) (P<.01). Less than 2%, but statistically significant, decrease in maximum variable RBE-weighted brainstem dose was observed for the LET-sparing techniques compared with the corresponding dose-sparing (P=.03 and .004). Extending the proton range beyond the brainstem to reduce LET results in clinically comparable maximum radiobiologic effective dose to this sensitive structure. However this method significantly increasing the brainstem volume receiving RBE-weighted dose higher than 55Gy(RBE) with possible consequences based on known dose-volume parameters for increased toxicity.

WE-FG-BRB-00: The Challenges of Predicting RBE Effects in Particle Therapy and Opportunities for Improving Cancer Therapy

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences between particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: 1.To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE 2.To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy 3.To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.

WE-FG-BRB-02: Spatial Mapping of the RBE of Scanned Particle Beams

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences between particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: 1.To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE 2.To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy 3.To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.

WE-FG-BRB-03: Challenges and Opportunities for Implementing Biological Optimization in Particle Therapy

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences between particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: 1. To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE 2. To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy 3. To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.

WE-FG-BRB-01: Clinical Significance of RBE Variations in Proton Therapy

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences between particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: 1.To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE 2.To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy 3.To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.

WE-FG-BRB-04: RBEs for Human Lung Cancer Cells Exposed to Protons and Heavier Ions: Implications for Clinical Use of Charged Particles in Cancer Therapy

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences between particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: 1.To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE 2.To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy 3.To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.

Impact of fractionation and number of fields on dose homogeneity for intra-fractionally moving lung tumors using scanned carbon ion treatment

Background and purposeScanned particle beam therapy may result in over and under dosages within the target volume. This study quantifies how CTV dose coverage improves with number of fractions and fields. Materials and methodsBased on 4DCTs of nine lung tumor patients, treatment plans were optimized separately for four different fields using an ITV approach. 4D RBE-weighted dose distributions were calculated for varying motion parameters and fraction numbers. The total RBE-weighted dose was determined for one and four-field application per fraction. DVHs were analyzed for the tumor and interpreted based on statistical modeling. ResultsDose homogeneity within the CTV increased with the fraction number, but depends significantly on the tumor motion amplitude. For single-field schedules and amplitudes >6mm, the dose coverage indices (V95min=90.7% and V107max=0.4%) differed to the stationary case even after 40 fractions. Target coverage for a four-field approach followed a proposed model and homogeneous dose distributions could be achieved 6-times faster than single-field treatments. ConclusionsFractionated delivery improves dose homogeneity in scanned ion beam therapy of moving targets. The achievable homogeneity depends mainly on tumor volume and motion amplitude. The outcome of multiple-field irradiations can be predicted based on single-field results and accelerates the achievement of homogeneous dose distributions.