RBE Model Research Articles

728: Comparing RBE models based on LET vs. a track structure quantity in pediatric brain proton therapy

728: Comparing RBE models based on LET vs. a track structure quantity in pediatric brain proton therapy

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.

Potential Therapeutic Improvements in Prostate Cancer Treatment Using Pencil Beam Scanning Proton Therapy with LETd Optimization and Disease-Specific RBE Models.

To demonstrate the feasibility of improving prostate cancer patient outcomes with PBS proton LETd optimization. SFO, IPT-SIB, and LET-optimized plans were created for 12 patients, and generalized-tissue and disease-specific LET-dependent RBE models were applied. The mean LETd in several structures was determined and used to calculate mean RBEs. LETd- and dose-volume histograms (LVHs/DVHs) are shown. TODRs were defined based on clinical dose goals and compared between plans. The impact of robust perturbations on LETd, TODRs, and DVH spread was evaluated. LETd optimization achieved statistically significant increased target volume LETd of ~4 keV/µm compared to SFO and IPT-SIB LETd of ~2 keV/µm while mitigating OAR LETd increases. A disease-specific RBE model predicted target volume RBEs > 1.5 for LET-optimized plans, up to 18% higher than for SFO plans. LET-optimized target LVHs/DVHs showed a large increase not present in OARs. All RBE models showed a statistically significant increase in TODRs from SFO to IPT-SIB to LET-optimized plans. RBE = 1.1 does not accurately represent TODRs when using LETd optimization. Robust evaluations demonstrated a trade-off between increased mean target LETd and decreased DVH spread. The demonstration of improved TODRs provided via LETd optimization shows potential for improved patient outcomes.

Plan robustness and RBE influence for proton dose painting by numbers for head and neck cancers

PurposeTo investigate the feasibility of dose painting by numbers (DPBN) with respect to robustness for proton therapy for head and neck cancers (HNC), and to study the influence of variable RBE on the TCP and OAR dose burden. Methods and materialsData for 19 patients who have been scanned pretreatment with PET-FDG and subsequently treated with photon therapy were used in the study. A dose response model developed for photon therapy was implemented in a TPS, allowing DPBN plans to be created. Conventional homogeneous dose and DPBN plans were created for each patient, optimized with either fixed RBE = 1.1 or a variable RBE model. Robust optimization was used to create clinically acceptable plans. To estimate the maximum potential loss in TCP due to actual SUV variations from the pre-treatment imaging, we applied a test case with randomized SUV distribution. ResultsRegardless of the use of variable RBE for optimization or evaluation, a statistically significant increase (p < 0.001) in TCP was found for DPBN plans as compared to homogeneous dose plans. Randomizing the SUV distribution decreased the TCP for all plans. A correlation between TCP increase and variance of the SUV distribution and target volume was also found. ConclusionDPBN for protons and HNC is feasible and could lead to a TCP gain. Risks associated with the temporal variation of SUV distributions could be mitigated by imposing minimum doses to targets. The correlation found between TCP increase and SUV variance and target volume may be used for patient selection.

A systematic analysis of the particle irradiation data ensemble in the key of the microdosimetric kinetic model: Should clonogenic data be used for clinical relative biological effectiveness?

PurposeTo perform a systematic analysis of the Particle Irradiation Data Ensemble (PIDE) database for clonogenic survival assays in the context of the Microdosimetric Kinetic Model (MKM). Methods and materialOur study used data from the PIDE database containing data on various cell lines and radiation types. Two main parameters of the MKM were determined experiment-wise: the domain radius, which accounts for the increase of the linear parameter as a function of LET or lineal energy, and the nucleus radius, which accounts for the overkilling effect at LET high enough. We used experiments with LET less and more than 75 keV/μm to determine domain and nucleus radius, respectively. Experiments with cells in asynchronous phase of the cell cycle and monoenergetic beams were considered, and data from 294 out of 461 available experiments with protons, alpha, and carbon beams were used. ResultsDomain and nucleus radii were determined for 32 cell lines as the median among cell-specific experiments after filtering experiments using protons, α-particles, and carbon ions, including 28 human cells and 12 rodent cells. The median values found for domain radii were 380 nm for normal human cells, 390 nm for tumor human cells, 295 nm for normal rodent cells, and 525 nm for tumor rodent cells (only one experiment with rodent tumor cells) with large variability across cell lines and across experiments on each cell line. ConclusionsLarge inter-experiment variabilities were found for the same cell lines, based on enormous experimental uncertainties and different experimental conditions. Our analysis raises questions about how convenient is to use clonogenic data to feed RBE models to be utilized in the clinical practice in particle therapy.

Modelling tissue specific RBE for different radiation qualities based on a multiscale characterization of energy deposition

PurposeWe present the nanoCluE model, which uses nano- and microdosimetric quantities to model RBE for protons and carbon ions. Under the hypothesis that nano- and microdosimetric quantities correlates with the generation of complex DNA double strand breakes, we wish to investigate whether an improved accuracy in predicting LQ parameters may be achieved, compared to some of the published RBE models. MethodsThe model is based on experimental LQ data for protons and carbon ions. We generated a database of track structure data for a number of proton and carbon ion kinetic energies with the Geant4-DNA Monte Carlo code. These data were used to obtain both a nanodosimetric quantity and a set of microdosimetric quantities. The latter were tested with different parameterizations versus experimental LQ-data to select the variable and parametrization that yielded the best fit. ResultsFor protons, the nanoCluE model yielded, for the ratio of the linear LQ term versus the test data, a root mean square error (RMSE) of 1.57 compared to 1.31 and 1.30 for two earlier other published proton models. For carbon ions the RMSE was 2.26 compared to 3.24 and 5.24 for earlier published carbon ion models. ConclusionThese results demonstrate the feasibility of the nanoCluE RBE model for carbon ions and protons. The increased accuracy for carbon ions as compared to two other considered models warrants further investigation.

OC-0455 RBE models of brainstem toxicity from proton therapy of paediatric ependymoma

OC-0455 RBE models of brainstem toxicity from proton therapy of paediatric ependymoma

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.

Proceedings to the 7th Annual Conference of the Particle Therapy Cooperative Group North America (PTCOG-NA)

Proceedings to the 7th Annual Conference of the Particle Therapy Cooperative Group North America (PTCOG-NA)

Quantifying Systematic RBE-Weighted Dose Uncertainty Arising from Multiple Variable RBE Models in Organ at Risk

PurposeRelative biological effectiveness (RBE) uncertainties have been a concern for treatment planning in proton therapy, particularly for treatment sites that are near organs at risk (OARs). In such a clinical situation, the utilization of variable RBE models is preferred over constant RBE model of 1.1. The problem, however, lies in the exact choice of RBE model, especially when current RBE models are plagued with a host of uncertainties. This paper aims to determine the influence of RBE models on treatment planning, specifically to improve the understanding of the influence of the RBE models with regard to the passing and failing of treatment plans. This can be achieved by studying the RBE-weighted dose uncertainties across RBE models for OARs in cases where the target volume overlaps the OARs. Multi-field optimization (MFO) and single-field optimization (SFO) plans were compared in order to recommend which technique was more effective in eliminating the variations between RBE models. MethodsFifteen brain tumor patients were selected based on their profile where their target volume overlaps with both the brain stem and the optic chiasm. In this study, 6 RBE models were analyzed to determine the RBE-weighted dose uncertainties. Both MFO and SFO planning techniques were adopted for the treatment planning of each patient. RBE-weighted dose uncertainties in the OARs are calculated assuming (αβ)x of 3 Gy and 8 Gy. Statistical analysis was used to ascertain the differences in RBE-weighted dose uncertainties between MFO and SFO planning. Additionally, further investigation of the linear energy transfer (LET) distribution was conducted to determine the relationship between LET distribution and RBE-weighted dose uncertainties. ResultsThe results showed no strong indication on which planning technique would be the best for achieving treatment planning constraints. MFO and SFO showed significant differences (P <.05) in the RBE-weighted dose uncertainties in the OAR. In both clinical target volume (CTV)-brain stem and CTV-chiasm overlap region, 10 of 15 patients showed a lower median RBE-weighted dose uncertainty in MFO planning compared with SFO planning. In the LET analysis, 8 patients (optic chiasm) and 13 patients (brain stem) showed a lower mean LET in MFO planning compared with SFO planning. It was also observed that lesser RBE-weighted dose uncertainties were present with MFO planning compared with SFO planning technique. ConclusionsCalculations of the RBE-weighted dose uncertainties based on 6 RBE models and 2 different (αβ)x revealed that MFO planning is a better option as opposed to SFO planning for cases of overlapping brain tumor with OARs in eliminating RBE-weighted dose uncertainties. Incorporation of RBE models failed to dictate the passing or failing of a treatment plan. To eliminate RBE-weighted dose uncertainties in OARs, the MFO planning technique is recommended for brain tumor when CTV and OARs overlap.

Fast neutron energy based modelling of biological effectiveness with implications for proton and ion beams

A practical neutron energy dependent RBE model has been developed, based on the relationship between a mono-energetic neutron energy and its likely recoil proton energy. Essentially, the linear energy transfer (LET) values of the most appropriate recoil proton energies are then used to modify the linear quadratic model radiosensitivities (α and β) from their reference LET radiation values to provide the RBE estimates. Experimental neutron studies published by Hall (including some mono-energetic beams ranging from 0.2 to 15 MeV), Broerse, Berry, and data from the Clatterbridge and Detroit clinical neutron beams, which all contain some data from a spectrum of neutron energies, are used to derive single effective neutron energies (NEeff) for each spectral beam. These energies yield a recoil proton spectrum, but with an effective mean proton energy (being around 50% of NEeff). The fractional increase in LET is given by the recoil proton LET divided by the proton (LETU) value which provides the highest RBE. This ratio is then used to determine the change in the linear-quadratic model α and β parameters, from those of the reference radiation, to estimate the RBE. The predicted proton recoil RBE is then reasonably close to the experimental neutron RBE values found when taking into account the variation inherent in biological experiments. The work has some important consequences. The data of Hall et al (1975 Radiat. Res. 64 245–55) shows that the highest RBE values are found with neutron energies around 0.3–0.4 MeV, but this energy cannot possibly generate recoil proton energies which are higher, as necessary for a 0.68 MeV proton with a 30.5 keV μm−1 LETU (the LET value which provides the maximum obtainable RBE for a specified ion). For 0.4 MeV neutrons with proton recoil energies of around 0.2 MeV, the latter have a LET of around 62.88 keV μm−1. This could have an impact on proton beam RBE modelling. However, this is compensated by finding that the maximum radiosensitivity for mono-energetic neutrons was around 1.7 times larger than previously suggested from experimental ion beam studies, probably due to the necessary spreading out of Bragg peaks for ion beam experimental purposes, sampling errors and particle range considerations. This semi-empirical model can be used with minimal computer support and could have applications in ionic beams and in radioprotection.

Incorporation of the LETd-weighted biological dose in the evaluation of breast intensity-modulated proton therapy plans

Purpose To evaluate the LETd-weighted biological dose to OARs in proton therapy for breast cancer and to study the relationship of the LETd-weighted biological dose relative to the standard dose (RBE = 1.1) and thereby to provide estimations of the biological dose uncertainties with the standard dose calculations (RBE = 1.1) commonly used in clinical practice. Method This study included 20 patients who received IMPT treatment to the whole breast/chest wall and regional lymph nodes. The LETd distributions were calculated along with the physical dose using an open-source Monte Carlo simulation package, MCsquare. Using the McMahon linear model, the LETd-weighted biological dose was computed from the physical dose and LETd. OAR doses were compared between the Dose (RBE = 1.1) and the LETd-weighted biological dose, on brachial plexus, rib, heart, esophagus, and Ipsilateral lung. Results On average, the LETd-weighted biological dose compared to the Dose (RBE = 1.1) was higher by 8% for the brachial plexus D0.1 cc, 13% for the ribs D0.5 cc, 24% for mean heart dose, and 10% for the esophagus D0.1 cc, respectively. The LETd-weighted doses to the Ipsilateral lung V5, V10, and V20 were comparable to the Dose (RBE = 1.1). No statistically significant difference in biological dose enhancement to OARs was observed between the intact breast group and the CW group, with the exception of the ribs: the CW group experienced slightly greater biological dose enhancement (13% vs. 12%, p = 0.04) to the ribs than the intact breast group. Conclusion Enhanced biological dose was observed compared to standard dose with assumed RBE of 1.1 for the heart, ribs, esophagus, and brachial plexus in breast/CW and regional nodal IMPT plans. Variable RBE models should be considered in the evaluation of the IMPT breast plans, especially for OARs located near the end of range of a proton beam. Clinical outcome studies are needed to validate model predictions for clinical toxicities.

On the concepts of dose-mean lineal energy, unrestricted and restricted dose-averaged LET in proton therapy

To calculate 3D distributions of microdosimetric-based restricted dose-averaged LET (LETd) and dose-mean lineal energy () in order to explore their similarities and differences between each other and with the traditional unrestricted LETd. Additionally, a new expression for optimum restricted LETd calculation is derived, allowing for disregarding straggling-associated functions in the classical microdosimetric theory.Restricted LETd and for polyenergetic beams can be obtained by integrating previously developed energy-dependent microdosimetric functions over the energetic spectrum of these beams. This calculation is extended to the entire calculation volume using an algorithm to determine spectral fluence. Equivalently, unrestricted LETd can be obtained integrating the stopping power curve on the spectrum. A new expression to calculate restricted LETd is also derived. Results for traditional and new formulas are compared for a clinical 100 MeV proton beam. Distributions of unrestricted LETd, restricted LETd and are analyzed for a prostate case, for microscopic spherical sites of 1 µm and 10 µm in diameter.Traditional and new expressions for restricted LETd remarkably agree, being the mean differences 0.05 ± 0.04 keV µm−1 for the 1 µm site and 0.05 ± 0.02 keV µm−1 for the 10 µm site. In the prostate case, the ratio between the maximum and the central value for central axis (CAX) profiles is around 2 for all the quantities, being the highest for restricted LETd for 1 µm (2.17) and the lowest for for 1 µm (1.78).Unrestricted LETd, restricted LETd and can be analytically computed and compared for clinical plans. Two important consequences of the calculation of are: (1) its distribution can be verified by directly measuring it in clinical beams; and (2), optimization of proton treatments based on these quantities is enabled as well as future developments of RBE models based on them.

Uncertainty of RBE Model in Proton Radiotherapy Based on $\frac {\alpha }{\beta }$ Ratio and Linear Energy Transfer

Uncertainty of RBE Model in Proton Radiotherapy Based on $\frac {\alpha }{\beta }$ Ratio and Linear Energy Transfer

OC-0589 RBE-weighted dose in carbon ion therapy: impact of the RBE model translation on clinical outcomes

OC-0589 RBE-weighted dose in carbon ion therapy: impact of the RBE model translation on clinical outcomes

SP-0262 Limitations of current RBE models and their implication for clinical trial design

SP-0262 Limitations of current RBE models and their implication for clinical trial design

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.

SP-0440: The state of affairs with ion RBE models

SP-0440: The state of affairs with ion RBE models

SU‐F‐J‐187: The Statistical NTCP and TCP Models in the Proton Therapy

Purpose:The statistical models (SM) are typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known. The normal tissue complications and tumor control are frequently stochastic effects in the Radiotherapy (RT). Based on probabilistic treatments, it recently has been formulated new NTCP and TCP models for the RT. Investigating the particular requirements for their clinical use in the proton therapy (PT) is the goal of this work.Methods:The SM can be used as phenomenological or mechanistic models. The former way allows fitting real data and getting theirparameters. In the latter one, we should do efforts for determining the parameters through the acceptable estimations, measurements, and/or simulation experiments. Experimental methodologies for determination of the parameters have been developed from the fraction cells surviving the proton irradiation curves in tumor and OAR, and precise RBE models are used for calculating the variable of effective dose. As the executions of these methodologies have a high costs, so we have developed computer tools enable to perform simulation experiments as complement to limitations of the real ones.Results:The requirements for the use of the SM in the PT, such as validation and improvement of the elaborated and existent methodologies for determining the SM parameters and effective dose respectively, were determined.Conclusion:The SM realistically simulates the main processes in the PT, and for this reason these can be implemented in this therapy, which are simples, computable and they have other advantages over some current models. It has been determined some negative aspects for some currently used probabilistic models in the RT, like the LKB NTCP and others derived from logistic functions; which can be improved with the proposed methods in this study.

MO-FG-CAMPUS-TeP3-02: Benchmarks of a Proton Relative Biological Effectiveness (RBE) Model for DNA Double Strand Break (DSB) Induction in the FLUKA, MCNP, TOPAS, and RayStation™ Treatment Planning System

Purpose: Validate implementation of a published RBE model for DSB induction (RBEDSB) in several general purpose Monte Carlo (MC) code systems and the RayStation™ treatment planning system (TPS). For protons and other light ions, DSB induction is a critical initiating molecular event that correlates well with the RBE for cell survival. Methods: An efficient algorithm to incorporate information on proton and light ion RBEDSB from the independently tested Monte Carlo Damage Simulation (MCDS) has now been integrated into MCNP (Stewart et al. PMB 60, 8249–8274, 2015), FLUKA, TOPAS and a research build of the RayStation™ TPS. To cross-validate the RBEDSB model implementation LET distributions, depth-dose and lateral (dose and RBEDSB) profiles for monodirectional monoenergetic (100 to 200 MeV) protons incident on a water phantom are compared. The effects of recoil and secondary ion production (2H+, 3H+, 3He2+, 4He2+), spot size (3 and 10 mm), and transport physics on beam profiles and RBEDSB are examined. Results: Depth-dose and RBEDSB profiles among all of the MC models are in excellent agreement using a 1 mm distance criterion (width of a voxel). For a 100 MeV proton beam (10 mm spot), RBEDSB = 1.2 ± 0.03 (− 2–3%) at the tip of the Bragg peak and increases to 1.59 ± 0.3 two mm distal to the Bragg peak. RBEDSB tends to decrease as the kinetic energy of the incident proton increases. Conclusion: The model for proton RBEDSB has been accurately implemented into FLUKA, MCNP, TOPAS and the RayStation™TPS. The transport of secondary light ions (Z > 1) has a significant impact on RBEDSB, especially distal to the Bragg peak, although light ions have a small effect on (dosexRBEDSB) profiles. The ability to incorporate spatial variations in proton RBE within a TPS creates new opportunities to individualize treatment plans and increase the therapeutic ratio. Dr. Erik Traneus is employed full-time as a Research Scientist at RaySearch Laboratories. The research build of the RayStation used in the study was made available to the University of Washington free of charge. RaySearch Laboratories did not provide any monetary support for the reported studies.