Range uncertainty in proton therapy due to variable biological effectiveness

On the Way to Accounting for Lung Modulation Effects in Particle Therapy of Lung Cancer Patients-A Review

Particle therapy presents a promising alternative to conventional photon therapy for treating non-small cell lung cancer (NSCLC). However, the heterogeneous structure of lung tissue leads to the degradation of the Bragg peak and thereby to the degradation of the dose distribution. This review offers a comprehensive overview of the models developed to account for these modulation effects. It summarizes studies focused on determining modulation power as a predictor of this so-called lung modulation. In addition, the review covers early investigations on dose uncertainties caused by lung modulation in CT-based lung phantoms and patient anatomies and discusses future challenges in integrating these solutions into clinical treatment planning routines.

Interpreting the biological effects of protons as a function of physical quantity: linear energy transfer or microdosimetric lineal energy spectrum?

The choice of appropriate physical quantities to characterize the biological effects of ionizing radiation has evolved over time coupled with advances in scientific understanding. The basic hypothesis in radiation dosimetry is that the energy deposited by ionizing radiation initiates all the consequences of exposure in a biological sample (e.g., DNA damage, reproductive cell death). Physical quantities defined to characterize energy deposition have included dose, a measure of the mean energy imparted per unit mass of the target, and linear energy transfer (LET), a measure of the mean energy deposition per unit distance that charged particles traverse in a medium. The primary advantage of using the "dose and LET" physical system is its relative simplicity, especially for presenting and recording results. Inclusion of additional information such as the energy spectrum of charged particles renders this approach adequate to describe the biological effects of large dose levels from homogeneous sources. The primary disadvantage of this system is that it does not provide a unique description of the stochastic nature of radiation interactions. We and others have used dose-averaged LET (LETd) as a correlative physical quantity to the relative biological effectiveness (RBE) of proton beams. This approach is based on established experimental findings that proton RBE increases with LETd. However, this approach might not be applicable to intensity-modulated proton therapy or other applications in which the proton energy spectrum is highly heterogeneous. In the current study, we irradiated cancer cells with scanning proton beams with identical LETd (3.4 keV/µm) but arising from two different proton energy/LET spectra (a narrow spectrum in group 1 and a widespread heterogeneous spectrum in group 2). Clonogenic survival after irradiation revealed significant differences in RBE at any cell surviving fraction: e.g., at a surviving fraction of 0.1, the RBE was 0.97 ± 0.03 in group 1 and 1.16 ± 0.04 in group 2 (p≤0.01), validating our hypothesis that LETd alone may not adequately indicate proton RBE. Further analysis showed that microdosimetric spectrum (the probability density function of the stochastic physical quantity lineal energy y) was helpful for interpreting observed differences in biological effects. However, more accurate use of microdosimetric spectrum to quantify RBE requires a cell line-specific mechanistic model.

Novel radiation quality metrics accounting for proton energy spectra for RBE proton models

BACKGROUND

For proton therapy, a relative biological effectiveness (RBE) of 1.1 is widely applied clinically. However, due to abundant evidence of variable RBE in vitro, and as suggested in studies of patient outcomes, RBE might increase by the end of the proton tracks, as described by several proposed variable RBE models. Typically, the dose averaged linear energy transfer (LET d $\text{LET}_d$ ) has been used as a radiation quality metric (RQM) for these models. However, the optimal choice of RQM has not been fully explored.

PURPOSE

This study aims to propose novel RQMs that effectively weight protons of different energies, and assess their predictive power for variable RBE in proton therapy. The overall objective is to identify an RQM that better describes the contribution of individual particles to the RBE of proton beams.

METHODS

High-throughput experimental set-ups of in vitro cell survival studies for proton RBE determination are simulated utilizing the SHIELD-HIT12A Monte Carlo particle transport code. For every data point, the proton energy spectra are simulated, allowing the calculation of novel RQMs by applying different power levels to the spectra of LET or effective Q $Q$ (Q eff $Q_\mathrm{eff}$ ) values. A phenomenological linear-quadratic-based RBE model is then applied to the in vitro data, using various RQMs as input variables, and the model performance is evaluated by root-mean-square-error (RMSE) for the logarithm of cell surviving fractions of each data point.

RESULTS

Increasing the power level, that is, putting an even higher weight on higher LET particles when constructing the RQM is generally associated with an increased model performance, with dose averagedLET 3 $\text{LET}^3$ (i.e., dose averaged cubed LET,cLET d $\mathrm{cLET}_d$ ) resulting in a RMSE value 0.31, compared to 0.45 for a model based on (linearly weighted)LET d $\text{LET}_d$ , with similar trends also observed for track averaged andQ eff $Q_\mathrm{eff}$ -based RQMs.

CONCLUSIONS

The results indicate that improved proton variable RBE models can be constructed assuming a non-linear RBE(LET) relationship for individual protons. If similar trends hold also for an in vitro-environment, variable RBE effects are likely better described bycLET d $\mathrm{cLET}_d$ or tracked averaged cubed LET (cLET t $\mathrm{cLET}_t$ ), or correspondingQ eff $Q_\mathrm{eff}$ -based RQM, rather than linearly weightedLET d $\text{LET}_d$ orLET t $\text{LET}_t$ which is conventionally applied today.

Research Trends in the Study of the Relative Biological Effectiveness: A Bibliometric Study

The relative biological effectiveness is a mathematical quantity first defined in the 1950s. This has resulted in more than 4,000 scientific papers published to date. Yet defining the correct value of the RBE to use in clinical practice remains a challenge. A scientific analysis in the radiation research literature can provide an understanding of how this mathematical quantity has evolved. The purpose of this study is to investigate documents published since 1950 using bibliometric indicators and network visualization. This analysis seeks to provide an assessment of global research activities, key themes, and RBE research within the radiation-related field. It strives to highlight top-performing authors, organizations, and nations that have made major contributions to this research domain, as well as their interactions. The Scopus Collection was searched for articles and reviews pertaining to RBE in radiation research from 1950 through 2023. Scopus and Bibiometrix analytic tools were used to investigate the most productive countries, researchers, collaboration networks, journals, along with the citation analysis of references and keywords. A total of 4,632 documents were retrieved produced by authors originating from 71 countries. Publication trends could be separated in 20-year groupings beginning with slow accrual from 1950 to 1970, an early rise from 1970-1990, followed by a sharp increase in the years 1990s-2010s that matches the development of charged particle therapy in clinics worldwide and opened discussion on the true value of the RBE in proton beam therapy. Since the 2010s, a steady 200 papers, on average, have been published per year. The United States produced the most publications overall (N = 1,378) and Radiation Research was the most likely journal to have published articles related to the RBE (606 publications during this period). J. Debus was the most prolific author (112 contributions, with 2,900 citations). The RBE has captured the research interest of over 7,000 authors in the past decade alone. This study supports that notion that the growth of the body of evidence surrounding the RBE, which started 75 years ago, is far from reaching its end. Applications to medicine have continuously dominated the field, with physics competing with Biochemistry, Genetics and Molecular Biology for second place over the decades. Future research can be predicted to continue.

An updated variable RBE model for proton therapy

Objective.While a constant relative biological effectiveness (RBE) of 1.1 forms the basis for clinical proton therapy, variable RBE models are increasingly being used in plan evaluation. However, there is substantial variation across RBE models, and several newin vitrodatasets have not yet been included in the existing models. In this study, an updatedin vitroproton RBE database was collected and used to examine current RBE model assumptions, and to propose an up-to-date RBE model as a tool for evaluating RBE effects in clinical settings.Approach.A proton database (471 data points) was collected from the literature, almost twice the size of the previously largest model database. Each data point included linear-quadratic model parameters and linear energy transfer (LET). Statistical analyses were performed to test the validity of commonly applied assumptions of phenomenological RBE models, and new model functions were proposed forRBEmaxandRBEmin(RBE at the lower and upper dose limits). Previously published models were refitted to the database and compared to the new model in terms of model performance and RBE estimates.Main results.The statistical analysis indicated that the intercept of theRBEmaxfunction should be a free fitting parameter and RBE estimates were clearly higher for models with free intercept.RBEminincreased with increasing LET, while a dependency ofRBEminon the reference radiation fractionation sensitivity (α/βx) did not significantly improve model performance. Evaluating the models, the new model gave overall lowest RMSE and highest R2 score. RBE estimates in the distal part of a spread-out-Bragg-peak in water (α/βx= 2.1 Gy) were 1.24-1.51 for original models, 1.25-1.49 for refits and 1.42 for the new model.Significance.An updated RBE model based on the currently largest database among published phenomenological models was proposed. Overall, the new model showed better performance compared to refitted published RBE models.

Dosimetric and NTCP advantages of robust proton therapy over robust VMAT for Stage III NSCLC in the immunotherapy era

AIMS

To assess the robustness and to define the dosimetric and NTCP advantages of pencil-beam-scanning proton therapy (PBSPT) compared with VMAT for unresectable Stage III non-small lung cancer (NSCLC) in the immunotherapy era.

MATERIAL AND METHODS

10 patients were re-planned with VMAT and PBSPT using: 1) ITV-based robust optimization with 0.5 cm setup uncertainties and (for PBSPT) 3.5 % range uncertainties on free-breathing CT 2) CTV-based RO including all 4DCTs anatomies. Target coverage (TC), organs at risk dose and TC robustness (TCR), set at V95%, were compared. The NTCP risk for radiation pneumonitis (RP), 24-month mortality (24MM), G2 + acute esophageal toxicity (ET), the dose to the immune system (EDIC) and the left anterior descending (LAD) coronary artery V15 < 10 % were registered. Wilcoxon test was used.

RESULTS

Both PBSPT methods improved TC and TCR (p < 0.01). The mean lung dose and lung V20 were lower with PBSPT (p < 0.01). Median mean heart dose reduction with PBSPT was 8 Gy (p < 0.001). PT lowered median LAD V15 (p = 0.004). ΔNTCP > 5 % with PBSPT was observed for two patients for RP and for five patients for 24 MM. ΔNTCP for ≥ G2 ET was not in favor of PBSPT for all patients. PBSPT halved median EDIC (4.9/5.1 Gy for ITV/CTV-based VMAT vs 2.3 Gy for both ITV/CTV-based PBSPT, p < 0.01).

CONCLUSIONS

PBSPT is a robust approach with significant dosimetric and NTCP advantages over VMAT; the EDIC reduction could allow for a better integration with immunotherapy. A clinical benefit for a subset of NSCLC patients is expected.

A linear energy transfer distributions computation method for inhomogeneous medium by using the water equivalent ratio approximation

Dose-averaged linear energy transfer (LET), LETd is widely used in proton therapy. Compared with analytical models, Monte Carlo (MC) simulations are more accurate in obtaining LETd distributions, but they are time-consuming. This study used the 3D LETd distributions of proton beam spots in water by MC simulations as a benchmark data set. Subsequently, by combining the water equivalent ratio of various human tissues, the 3D LETd distributions of clinical cases could be quickly obtained. Our method was applied to a single spot of 160 MeV proton beam in a water-bone phantom and a pelvic case. We also computed the 3D LETd distributions for multiple proton beam spots in the pelvic case and a lung case. The results of our method were compared with the results of MC simulations, demonstrating that our method can rapidly provide 3D LETd distributions of clinical cases with acceptable differences from MC simulations.

An Analysis of Positron Emission Tomography Maximum Standard Uptake Value Among Patients With Head and Neck Cancer Receiving Photon and Proton Radiation

PURPOSE

One main advantage of proton therapy versus photon therapy is its precise radiation delivery to targets without exit dose, resulting in lower dose to surrounding healthy tissues. This is critical, given the proximity of head and neck tumors to normal structures. However, proton planning requires careful consideration of factors, including air-tissue interface, anatomic uncertainties, surgical artifacts, weight fluctuations, rapid tumor response, and daily variations in setup and anatomy, as these heterogeneities can lead to inaccuracies in targeting and creating unwarranted hotspots to a greater extent than photon radiation. In addition, the elevated relative biological effectiveness at the Bragg peak's distal end can also increase hot spots within and outside the target area.

METHODS AND MATERIALS

The purpose of this study was to evaluate for a difference in positron emission tomography (PET) standard uptake value (SUV) after definitive treatment, between intensity modulated proton therapy (IMPT) and intensity modulated photon therapy (IMRT). In addition, we compared the biologic dose between PET areas of high and low uptake within the clinical target volume-primary of patients treated with IMPT. This work is assuming that the greater SUV may potentially result in greater toxicities. For the purposes of this short communication, we are strictly focusing on the SUV and do not have correlation with toxicity outcomes. To accomplish this, we compared the 3- and 6-month posttreatment fluorodeoxyglucose PET scans for 100 matched patients with oropharyngeal cancer treated definitively without surgery using either IMPT (n = 50) or IMRT (n = 50).

RESULTS

Our study found a significant difference in biologic dose between the high- and low-uptake regions on 3-month posttreatment scans of IMPT. However, this difference did not translate to a significant difference in PET uptake in the clinical target volume-primary at 3 and 6 months' follow-up between patients who received IMPT versus IMRT.

CONCLUSIONS

Studies have proposed that proton's greater relative biological effectiveness at the Bragg peak could lead to tissue inflammation. Our study did not corroborate these findings. This study's conclusion underscores the need for further investigations with ultimate correlation with clinical toxicity outcomes.

Calculation of biological effectiveness of SOBP proton beams: a TOPAS Monte Carlo study

Objective.This study aims to investigate the biological effectiveness of Spread-Out Bragg-Peak (SOBP) proton beams with initial kinetic energies 50-250 MeV at different depths in water using TOPAS Monte Carlo code.Approach.The study modelled SOBP proton beams using TOPAS time feature. Various LET-based models and Repair-Misrepair-Fixation model were employed to calculate Relative Biological Effectiveness (RBE) for V79 cell lines at different on-axis depths based on TOPAS. Microdosimetric Kinetic Model and biological weighting function-based models, which utilize microdosimetric distributions, were also used to estimate the RBE. A phase-space-based method was adopted for calculating microdosimetric distributions.Main results.The trend of variation of RBE with depth is similar in all the RBE models, but the absolute RBE values vary based on the calculation models. RBE sharply increases at the distal edge of SOBP proton beams. In the entrance region of all the proton beams, RBE values at 4 Gy i.e. RBE(4 Gy) resulting from different models are in the range of 1.04-1.07, comparable to clinically used generic RBE of 1.1. Moving from the proximal to distal end of the SOBP, RBE(4 Gy) is in the range of 1.15-1.33, 1.13-1.21, 1.11-1.17, 1.13-1.18 and 1.17-1.21, respectively for 50, 100, 150, 200 and 250 MeV SOBP beams, whereas at the distal dose fall-off region, these values are 1.68, 1.53, 1.44, 1.42 and 1.40, respectively.Significance.The study emphasises application of depth-, dose- and energy- dependent RBE values in clinical application of proton beams.

Proton dosimetry in a magnetic field: Measurement and calculation of magnetic field correction factors for a plane-parallel ionization chamber

BACKGROUND

The combination of magnetic resonance imaging and proton therapy offers the potential to improve cancer treatment. The magnetic field (MF)-dependent change in the dosage of ionization chambers in magnetic resonance imaging-integrated proton therapy (MRiPT) is considered by the correction factork B ⃗ , M , Q $k_{\vec{B},M,Q}$ , which needs to be determined experimentally or computed via Monte Carlo (MC) simulations.

PURPOSE

In this study,k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was both measured and simulated with high accuracy for a plane-parallel ionization chamber at different clinical relevant proton energies and MF strengths.

MATERIAL AND METHODS

The dose-response of the Advanced Markus chamber (TM34045, PTW, Freiburg, Germany) irradiated with homogeneous 10 × $\times$ 10 cm2 $^2$ quasi mono-energetic fields, using 103.3, 128.4, 153.1, 223.1, and 252.7 MeV proton beams was measured in a water phantom placed in the MF of an electromagnet with MF strengths of 0.32, 0.5, and 1 T. The detector was positioned at a depth of 2 g/cm2 $^2$ in water, with chamber electrodes parallel to the MF lines and perpendicular to the proton beam incidence direction. The measurements were compared with TOPAS MC simulations utilizing COMSOL-calculated 0.32, 0.5, and 1 T MF maps of the electromagnet.k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was calculated for the measurements for all energies and MF strengths based on the equation:k B ⃗ , M , Q = M Q M Q B ⃗ $k_{\vec{B},M,Q}=\frac{M_\mathrm{Q}}{M_\mathrm{Q}^{\vec{B}}}$ , whereM Q B ⃗ $M_\mathrm{Q}^{\vec{B}}$ andM Q $M_\mathrm{Q}$ were the temperature and air-pressure corrected detector readings with and without the MF, respectively. MC-based correction factors were determined ask B ⃗ , M , Q = D det D det B ⃗ $k_{\vec{B},M,Q}=\frac{D_\mathrm{det}}{D_\mathrm{det}^{\vec{B}}}$ , whereD det B ⃗ $D_\mathrm{det}^{\vec{B}}$ andD det $D_\mathrm{det}$ were the doses deposited in the air cavity of the ionization chamber model with and without the MF, respectively. Furthermore, MF effects on the chamber dosimetry are studied using MC simulations, examining the impact on the absorbed dose-to-water (D W $D_{W}$ ) and the shift in depth of the Bragg peak.

RESULTS

The detector showed a reduced dose-response for all measured energies and MF strengths, resulting in experimentally determinedk B ⃗ , M , Q $k_{\vec{B},M,Q}$ values larger than unity. For all energies and MF strengths examined,k B ⃗ , M , Q $k_{\vec{B},M,Q}$ ranged between 1.0065 and 1.0205. The dependence on the energy and the MF strength was found to be non-linear with a maximum at 1 T and 252.7 MeV. The MC simulatedk B ⃗ , M , Q $k_{\vec{B},M,Q}$ values agreed with the experimentally determined correction factors within their standard deviations with a maximum difference of 0.6%. The MC calculated impact onD W $D_{W}$ was smaller 0.2 %.

CONCLUSION

For the first time, measurements and simulations were compared for proton dosimetry within MFs using an Advanced Markus chamber. Good agreement ofk B ⃗ , M , Q $k_{\vec{B},M,Q}$ was found between experimentally determined and MC calculated values. The performed benchmarking of the MC code allows for calculatingk B ⃗ , M , Q $k_{\vec{B},M,Q}$ for various ionization chamber models, MF strengths and proton energies to generate the data needed for a proton dosimetry protocol within MFs and is, therefore, a step towards MRiPT.

Variable RBE in proton radiotherapy: a comparative study with the predictive Mayo Clinic Florida microdosimetric kinetic model and phenomenological models of cell survival

Objectives. (1) To examine to what extent the cell- and exposure- specific information neglected in the phenomenological proton relative biological effectiveness (RBE) models could influence the computed RBE in proton therapy. (2) To explore similarities and differences in the formalism and the results between the linear energy transfer (LET)-based phenomenological proton RBE models and the microdosimetry-based Mayo Clinic Florida microdosimetric kinetic model (MCF MKM). (3) To investigate how the relationship between the RBE and the dose-mean proton LET is affected by the proton energy spectrum and the secondary fragments.Approach. We systematically compared six selected phenomenological proton RBE models with the MCF MKM in track-segment simulations, monoenergetic proton beams in a water phantom, and two spread-out Bragg peaks. A representative comparison within vitrodata for human glioblastoma cells (U87 cell line) is also included.Main results. Marked differences were observed between the results of the phenomenological proton RBE models, as reported in previous studies. The dispersion of these models' results was found to be comparable to the spread in the MCF MKM results obtained by varying the cell-specific parameters neglected in the phenomenological models. Furthermore, while single cell-specific correlation between RBE and the dose-mean proton LET seems reasonable above 2 keVμm-1, caution is necessary at lower LET values due to the relevant contribution of secondary fragments. The comparison within vitrodata demonstrates comparable agreement between the MCF MKM predictions and the results of the phenomenological models.Significance. The study highlights the importance of considering cell-specific characteristics and detailed radiation quality information for accurate RBE calculations in proton therapy. Furthermore, these results provide confidence in the use of the MCF MKM for clonogenic survival RBE calculations in proton therapy, offering a more mechanistic approach compared to phenomenological models.

Postmastectomy Intensity Modulated Proton Therapy: 5-Year Oncologic and Patient-Reported Outcomes

PURPOSE

To report oncologic, physician-assessed, and patient-reported outcomes (PROs) for a group of women homogeneously treated with modern, skin-sparing multifield optimized pencil-beam scanning proton (intensity modulated proton therapy [IMPT]) postmastectomy radiation therapy (PMRT).

METHODS AND MATERIALS

We reviewed consecutive patients who received unilateral, curative-intent, conventionally fractionated IMPT PMRT between 2015 and 2019. Strict constraints were applied to limit the dose to the skin and other organs at risk. Five-year oncologic outcomes were analyzed. Patient-reported outcomes were evaluated as part of a prospective registry at baseline, completion of PMRT, and 3 and 12 months after PMRT.

RESULTS

A total of 127 patients were included. One hundred nine (86%) received chemotherapy, among whom 82 (65%) received neoadjuvant chemotherapy. The median follow-up was 4.1 years. Five-year locoregional control was 98.4% (95% CI, 93.6-99.6), and overall survival was 87.9% (95% CI, 78.7-96.5). Acute grade 2 and 3 dermatitis was seen in 45% and 4% of patients, respectively. Three patients (2%) experienced acute grade 3 infection, all of whom had breast reconstruction. Three late grade 3 adverse events occurred: morphea (n = 1), infection (n = 1), and seroma (n = 1). There were no cardiac or pulmonary adverse events. Among the 73 patients at risk for PMRT-associated reconstruction complications, 7 (10%) experienced reconstruction failure. Ninety-five patients (75%) enrolled in the prospective PRO registry. The only metrics to increase by >1 point were skin color (mean change: 5) and itchiness (2) at treatment completion and tightness/pulling/stretching (2) and skin color (2) at 12 months. There was no significant change in the following PROs: bleeding/leaking fluid, blistering, telangiectasia, lifting, arm extension, or bending/straightening the arm.

CONCLUSIONS

With strict dose constraints to skin and organs at risk, postmastectomy IMPT was associated with excellent oncologic outcomes and PROs. Rates of skin, chest wall, and reconstruction complications compared favorably to previous proton and photon series. Postmastectomy IMPT warrants further investigation in a multi-institutional setting with careful attention to planning techniques.

Monte Carlo simulations of cell survival in proton SOBP

Objective. The objective of this study is to develop a multi-scale modeling approach that accurately predicts radiation-induced DNA damage and survival fraction in specific cell lines.Approach. A Monte Carlo based simulation framework was employed to make the predictions. The FLUKA Monte Carlo code was utilized to estimate absorbed doses and fluence energy spectra, which were then used in the Monte Carlo Damage Simulation code to compute DNA damage yields in Chinese hamster V79 cell lines. The outputs were converted into cell survival fractions using a previously published theoretical model. To reduce the uncertainties of the predictions, new values for the parameters of the theoretical model were computed, expanding the database of experimental points considered in the previous estimation. Simulated results were validated against experimental data, confirming the applicability of the framework for proton beams up to 230 MeV. Additionally, the impact of secondary particles on cell survival was estimated.Main results. The simulated survival fraction versus depth in a glycerol phantom is reported for eighteen different configurations. Two proton spread out Bragg peaks at several doses were simulated and compared with experimental data. In all cases, the simulations follow the experimental trends, demonstrating the accuracy of the predictions up to 230 MeV.Significance. This study holds significant importance as it contributes to the advancement of models for predicting biological responses to radiation, ultimately contributing to more effective cancer treatment in proton therapy.

Influence of beam pruning techniques on LET and RBE in proton arc therapy

Introduction

Proton arc therapy (PAT) is an emerging treatment modality that holds promise to improve target volume coverage and reduce linear energy transfer (LET) in organs at risk. We aimed to investigate if pruning the highest energy layers in each beam direction could increase the LET in the target and reduce LET in tissue and organs at risk (OAR) surrounding the target volume, thus reducing the relative biological effectiveness (RBE)-weighted dose and sparing healthy tissue.

Methods

PAT plans for a germinoma, an ependymoma and a rhabdomyosarcoma patient were created in the Eclipse treatment planning system with a prescribed dose of 54 Gy(RBE) using a constant RBE of 1.1 (RBE1.1). The PAT plans was pruned for high energy spots, creating several PAT plans with different amounts of pruning while maintaining tumor coverage, denoted PX-PAT plans, where X represents the amount of pruning. All plans were recalculated in the FLUKA Monte Carlo software, and the LET, physical dose, and variable RBE-weighted dose from the phenomenological Rørvik (ROR) model and an LET weighted dose (LWD) model were evaluated.

Results and discussion

For the germinoma case, all plans but the P6-PAT reduced the mean RBE-weighted dose to the surrounding healthy tissue compared to the PAT plan. The LET was increasingly higher within the PTV for each pruning iteration, where the mean LET from the P6-PAT plan was 1.5 keV / μm higher than for the PAT plan, while the P4- and P5-PAT plans provided an increase of 0.4 and 0.7 keV / μm , respectively. The other plans increased the LET by a smaller margin compared to the PAT plan. Likewise, the LET values to the healthy tissue were reduced for each degree of pruning. Similar results were found for the ependymoma and the rhabdomyosarcoma case. We demonstrated a PAT pruning technique that can increase both LET and RBE in the target volume and at the same time decreased values in healthy tissue, without affecting the target volume dose coverage.

An Overview of Head and Neck Tumor Reirradiation: What Has Been Achieved So Far?

The recurrence rate of head and neck cancers (HNCs) after initial treatment may reach 70%, and poor prognosis is reported in most cases. Curative options for recurrent HNCs mainly depend on the treatment history and the recurrent tumor localization. Reirradiation for HNCs is effective and has been included in most guidelines. However, the option remains clinically challenging due to high incidence of severe toxicity, especially in cases of quick infield recurrence. Recent technical advances in radiation therapy (RT) provide the means for upgrade in reirradiation protocols. While the majority of hospitals stay focused on conventional and widely accessible modulated RTs, the particle therapy options emerge as tolerable and providing further treatment opportunities for recurrent HNCs. Still, the progress is impeded by high heterogeneity of the data and the lack of large-scale prospective studies. This review aimed to summarize the outcomes of reirradiation for HNCs in the clinical perspective.

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?

PURPOSE

To 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 MATERIAL

Our 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.

RESULTS

Domain 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.

CONCLUSIONS

Large 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.

Proton Beam Therapy in the Oligometastatic/Oligorecurrent Setting: Is There a Role? A Literature Review

BACKGROUND

Stereotactic ablative radiotherapy (SABR) and stereotactic radiosurgery (SRS) with conventional photon radiotherapy (XRT) are well-established treatment options for selected patients with oligometastatic/oligorecurrent disease. The use of PBT for SABR-SRS is attractive given the property of a lack of exit dose. The aim of this review is to evaluate the role and current utilisation of PBT in the oligometastatic/oligorecurrent setting.

METHODS

Using Medline and Embase, a comprehensive literature review was conducted following the PICO (Patients, Intervention, Comparison, and Outcomes) criteria, which returned 83 records. After screening, 16 records were deemed to be relevant and included in the review.

RESULTS

Six of the sixteen records analysed originated in Japan, six in the USA, and four in Europe. The focus was oligometastatic disease in 12, oligorecurrence in 3, and both in 1. Most of the studies analysed (12/16) were retrospective cohorts or case reports, two were phase II clinical trials, one was a literature review, and one study discussed the pros and cons of PBT in these settings. The studies presented in this review included a total of 925 patients. The metastatic sites analysed in these articles were the liver (4/16), lungs (3/16), thoracic lymph nodes (2/16), bone (2/16), brain (1/16), pelvis (1/16), and various sites in 2/16.

CONCLUSIONS

PBT could represent an option for the treatment of oligometastatic/oligorecurrent disease in patients with a low metastatic burden. Nevertheless, due to its limited availability, PBT has traditionally been funded for selected tumour indications that are defined as curable. The availability of new systemic therapies has widened this definition. This, together with the exponential growth of PBT capacity worldwide, will potentially redefine its commissioning to include selected patients with oligometastatic/oligorecurrent disease. To date, PBT has been used with encouraging results for the treatment of liver metastases. However, PBT could be an option in those cases in which the reduced radiation exposure to normal tissues leads to a clinically significant reduction in treatment-related toxicities.

Modeling RBE with other quantities than LET significantly improves prediction of in vitro cell survival for proton therapy

BACKGROUND

For proton therapy, a relative biological effectiveness (RBE) of 1.1 has broadly been applied clinically. However, as unexpected toxicities have been observed by the end of the proton tracks, variable RBE models have been proposed. Typically, the dose-averaged linear energy transfer (LET_d ) has been used as an input variable for these models but the way the LET_d was defined, calculated, or determined was not always consistent, potentially impacting the corresponding RBE value.

PURPOSE

This study compares consistently calculated LET_d with other quantities as input variables for a phenomenological RBE model and attempts to determine which quantity that can best predicts proton RBE. The comparison was performed within the frame of introducing a new model for the proton RBE.

METHODS

High-throughput experimental setups of in vitro cell survival studies for proton RBE determination are simulated using the SHIELD-HIT12A Monte Carlo particle transport code. Together with LET, z ∗ 2 / β 2 $z^{*2}/\beta ^2$ , here called effective Q (Q_eff ), and Q are scored. Each quantity is calculated using the dose and track averaging methods, because the scoring includes all hadronic particles, all protons or only primaries. A phenomenological linear-quadratic-based RBE model is subsequently applied to the in vitro data with the various beam quality descriptors used as input variables and the goodness of fit is determined and compared using a bootstrapping approach. Both linear and nonlinear fit functions were tested.

RESULTS

Versions of Q_eff and Q outperform LET with a statistically significant margin, with the best nonlinear and linear fit having a relative root mean square error (RMSE) for RBE_2Gy ± one standard error of 1.55 ± 0.04 (Q_{eff, t, primary} ) and 2.84 ± 0.07 (Q_{eff, d, primary} ), respectively. For comparison, the corresponding best nonlinear and linear fits for LET_{d, all protons} had a relative RMSE of 2.07 ± 0.06 and 3.39 ± 0.08, respectively. Applying Welch's t-test for comparing the calculated RMSE of RBE_2Gy resulted in two-tailed p-values of <0.002 for all Q and Q_eff quantities compared to LET_{d, all protons} .

CONCLUSIONS

The study shows that Q or Q_eff could be better RBE descriptors that dose averaged LET.

Introduce a rotational robust optimization framework for spot-scanning proton arc (SPArc) therapy

Objective. Proton dosimetric uncertainties resulting from the patient's daily setup errors in rotational directions exist even with advanced image-guided radiotherapy techniques. Thus, we developed a new rotational robust optimization SPArc algorithm (SPArc_rot) to mitigate the dosimetric impact of the rotational setup error in Raystation ver. 6.02 (RaySearch Laboratory AB, Stockholm, Sweden).Approach.The initial planning CT was rotated ±5° simulating the worst-case setup error in the roll direction. The SPArc_rotuses a multi-CT robust optimization framework by taking into account of such rotational setup errors. Five cases representing different disease sites were evaluated. Both SPArc_originaland SPArc_rotplans were generated using the same translational robust optimized parameters. To quantitatively investigate the mitigation effect from the rotational setup errors, all plans were recalculated using a series of pseudo-CT with rotational setup error (±1°/±2°/±3°/±5°). Dosimetric metrics such as D98% of CTV, and 3D gamma analysis were used to assess the dose distribution changes in the target and OARs.Main results.The magnitudes of dosimetric changes in the targets due to rotational setup error were significantly reduced by the SPArc_rotcompared to SPArc in all cases. The uncertainties of the max dose to the OARs, such as brainstem, spinal cord and esophagus were significantly reduced using SPArc_rot. The uncertainties of the mean dose to the OARs such as liver and oral cavity, parotid were comparable between the two planning techniques. The gamma passing rate (3%/3 mm) was significantly improved for CTV of all tumor sites through SPArc_rot.Significance.Rotational setup error is one of the major issues which could lead to significant dose perturbations. SPArc_rotplanning approach can consider such rotational error from patient setup or gantry rotation error by effectively mitigating the dose uncertainties to the target and in the adjunct series OARs.

Hyperfractionated intensity-modulated proton therapy for pharyngeal cancer with variable relative biological effectiveness: A simulation study

BACKGROUND

The relative biological effectiveness (RBE) of proton is considered to be dependent on biological parameters and fractional dose. While hyperfractionated photon therapy was effective in the treatment of patients with head and neck cancers, its effect in intensity-modulated proton therapy (IMPT) under the variable RBE has not been investigated in detail.

PURPOSE

To study the effect of variable RBE on hyperfractionated IMPT for the treatment of pharyngeal cancer. We investigated the biologically effective dose (BED) to determine the theoretical effective hyperfractionated schedule.

METHODS

The treatment plans of three pharyngeal cancer patients were used to define the ΔBED for the clinical target volume (CTV) and soft tissue (acute and late reaction) as the difference between the BED for the altered schedule with variable RBE and conventional schedule with constant RBE. The ΔBED with several combinations of parameters (treatment days, number of fractions, and prescribed dose) was comprehensively calculated. Of the candidate schedules, the one that commonly gave a higher ΔBED for CTV was selected as the resultant schedule. The BED volume histogram was used to compare the influence of variable RBE and fractionation.

RESULTS

In the conventional schedule, compared with the constant RBE, the variable RBE resulted in a mean 2.6 and 2.7 Gy reduction of BED_mean for the CTV and soft tissue (acute reaction) of the three plans, respectively. Moreover, the BED_mean for soft tissue (late reaction) increased by 7.4 Gy, indicating a potential risk of increased RBE. Comprehensive calculation of the ΔBED resulted in the hyperfractionated schedule of 80.52 Gy (RBE = 1.1)/66 fractions in 6.5 weeks. When variable RBE was used, compared with the conventional schedule, the hyperfractionated schedule increased the BED_mean for CTV by 7.6 Gy; however, this was associated with a 7.8 Gy increase for soft tissue (acute reaction). The BED_mean for soft tissue (late reaction) decreased by 2.4 Gy.

CONCLUSION

The results indicated a potential effect of the variable RBE on IMPT for pharyngeal cancer but with the possibility that hyperfractionation could outweigh this effect. Although biological uncertainties require conservative use of the resultant schedule, hyperfractionation is expected to be an effective strategy in IMPT for pharyngeal cancer.

Validation of pencil beam scanning proton therapy with multi-leaf collimator calculated by a commercial Monte Carlo dose engine

This study aimed to evaluate the clinical beam commissioning results and lateral penumbra characteristics of our new pencil beam scanning (PBS) proton therapy using a multi-leaf collimator (MLC) calculated by use of a commercial Monte Carlo dose engine. Eighteen collimated uniform dose plans for cubic targets were optimized by the RayStation 9A treatment planning system (TPS), varying scan area, modulation widths, measurement depths, and collimator angles. To test the patient-specific measurements, we also created and verified five clinically realistic PBS plans with the MLC, such as the liver, prostate, base-of-skull, C-shape, and head-and-neck. The verification measurements consist of the depth dose (DD), lateral profile (LP), and absolute dose (AD). We compared the LPs and ADs between the calculation and measurements. For the cubic plans, the gamma index pass rates (γ-passing) were on average 96.5% ± 4.0% at 3%/3 mm for the DD and 95.2% ± 7.6% at 2%/2 mm for the LP. In several LP measurements less than 75 mm depths, the γ-passing deteriorated (increased the measured doses) by less than 90% with the scattering such as the MLC edge and range shifter. The deteriorated γ-passing was satisfied by more than 90% at 2%/2 mm using uncollimated beams instead of collimated beams except for three planes. The AD differences and the lateral penumbra width (80%-20% distance) were within ±1.9% and ± 1.1 mm, respectively. For the clinical plan measurements, the γ-passing of LP at 2%/2 mm and the AD differences were 97.7% ± 4.2% on average and within ±1.8%, respectively. The measurements were in good agreement with the calculations of both the cubic and clinical plans inserted in the MLC except for LPs less than 75 mm regions of some cubic and clinical plans. The calculation errors in collimated beams can be mitigated by substituting uncollimated beams.

Hypoxia adapted relative biological effectiveness models for proton therapy: a simulation study

In proton therapy, a constant relative biological effectiveness (RBE) factor of 1.1 is applied although the RBE has been shown to depend on factors including the Linear Energy Transfer (LET). The biological effectiveness of radiotherapy has also been shown to depend on the level of oxygenation, quantified by the oxygen enhancement ratio (OER). To estimate the biological effectiveness across different levels of oxygenation the RBE-OER-weighted dose (ROWD) can be used. To investigate the consistency between different approaches to estimate ROWD, we implemented and compared OER models in a Monte Carlo (MC) simulation tool. Five OER models were explored: Wenzl and Wilkens 2011 (WEN), Tinganelliet al2015 (TIN), Strigariet al2018 (STR), Dahleet al2020 (DAH) and Meinet al2021 (MEI). OER calculations were combined with a proton RBE model and the microdosimetric kinetic model for ROWD calculations. ROWD and OER were studied for a water phantom scenario and a head and neck cancer case using hypoxia PET data for the OER calculation. The OER and ROWD estimates from the WEN, MEI and DAH showed good agreement while STR and TIN gave higher OER values and lower ROWD. The WEN, STR and DAH showed some degree of OER-LET dependency while this was negligible for the MEI and TIN models. The ROWD for all implemented models is reduced in hypoxic regions with an OER of 1.0-2.1 in the target volume. While some variations between the models were observed, all models display a large difference in the estimated dose from hypoxic and normoxic regions. This shows the potential to increase the dose or LET in hypoxic regions or reduce the dose to normoxic regions which again could lead to normal tissue sparing. With reliable hypoxia imaging, RBE-OER weighting could become a useful tool for proton therapy plan optimization.

Assessing the DNA Damaging Effectiveness of Ionizing Radiation Using Plasmid DNA

Plasmid DNA is useful for investigating the DNA damaging effects of ionizing radiation. In this study, we have explored the feasibility of plasmid DNA-based detectors to assess the DNA damaging effectiveness of two radiotherapy X-ray beam qualities after undergoing return shipment of ~8000 km between two institutions. The detectors consisted of 18 μL of pBR322 DNA enclosed with an aluminum seal in nine cylindrical cavities drilled into polycarbonate blocks. We shipped them to Toronto, Canada for irradiation with either 100 kVp or 6 MV X-ray beams to doses of 10, 20, and 30 Gy in triplicate before being shipped back to San Diego, USA. The Toronto return shipment also included non-irradiated controls and we kept a separate set of controls in San Diego. In San Diego, we quantified DNA single strand breaks (SSBs), double strand breaks (DSBs), and applied Nth and Fpg enzymes to quantify oxidized base damage. The rate of DSBs/Gy/plasmid was 2.8±0.7 greater for the 100 kVp than the 6 MV irradiation. The 100 kVp irradiation also resulted in 5±2 times more DSBs/SSB than the 6 MV beam, demonstrating that the detector is sensitive enough to quantify relative DNA damage effectiveness, even after shipment over thousands of kilometers.

CONVERSION OF DOSE DISTRIBUTION TO CELL SURVIVAL FRACTION THROUGH DNA DAMAGE: A MONTE CARLO STUDY

Ionizing radiation plays an important role in cancer treatment. Radiation is able to damage the genetic material of cells, blocking their ability to divide and proliferate further. Since radiation affects both healthy and malignant tissues, for all radiation treatments, the design of an accurate treatment plan is fundamental. Usually, weight factors, such as the relative biological effectiveness, are applied to estimate the impact of the kind of radiation and the irradiated medium on the dose deposition. However, these factors can only provide a partial estimation of the real effect on tissues. In this work, a flexible system that is able to predict cell survival fractions according to the planned dose distribution is presented. Dose deposition and subsequent DNA damage were simulated with a multi-scale modeling approach by first applying the FLUKA Monte Carlo (MC) code to estimate the absorbed doses and fluence energy spectra and then using the MC Damage Simulation code to compute the DNA damage yields. Lastly, the results are converted into cell survival fraction using a theoretical model. The comparisons between the simulated survival fractions with experimental data are reported for a proton spread out Bragg peak at several doses. The presented approach helps to elucidate radiobiological responses along the Bragg curve and has the flexibility to be extended to a wide range of situations of clinical interest.

Range uncertainty reductions in proton therapy may lead to the feasibility of novel beam arrangements which improve organ-at-risk sparing

PURPOSE

In proton therapy, dose distributions are currently often conformed to organs at risk (OARs) using the less sharp dose fall-off at the lateral beam edge to reduce the effects of uncertainties in the in vivo proton range. However, range uncertainty reductions may make greater use of the sharper dose fall-off at the distal beam edge feasible, potentially improving OAR sparing. We quantified the benefits of such novel beam arrangements.

METHODS

For each of 10 brain or skull base cases, five treatment plans robust to 2 mm setup and 0%-4% range uncertainty were created for the traditional clinical beam arrangement and a novel beam arrangement making greater use of the distal beam edge to conform the dose distribution to the brainstem. Metrics including the brainstem normal tissue complication probability (NTCP) with the endpoint of necrosis were determined for all plans and all setup and range uncertainty scenarios.

RESULTS

For the traditional beam arrangement, reducing the range uncertainty from the current level of approximately 4% to a potentially achievable level of 1% reduced the brainstem NTCP by up to 0.9 percentage points in the nominal and up to 1.5 percentage points in the worst-case scenario. Switching to the novel beam arrangement at 1% range uncertainty improved these values by a factor of 2, that is, to 1.8 percentage points and 3.2 percentage points, respectively. The novel beam arrangement achieved a lower brainstem NTCP in all cases starting at a range uncertainty of 2%.

CONCLUSION

The benefits of novel beam arrangements may be of the same magnitude or even exceed the direct benefits of range uncertainty reductions. Indirect effects may therefore contribute markedly to the benefits of reducing proton range uncertainties.

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

BACKGROUND

Variable 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 MATERIALS

The 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.

RESULTS

The 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.

DISCUSSION

Our 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.

CONCLUSIONS

Adopting 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.

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

PURPOSE

Relative 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.

METHODS

Fifteen 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( α β ) 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.

RESULTS

The 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.

CONCLUSIONS

Calculations of the RBE-weighted dose uncertainties based on 6 RBE models and 2 different( α β ) 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.

Dictionary-based software for proton dose reconstruction and submilimetric range verification

Objective. This paper presents a new method for fast reconstruction (compatible with in-beam use) of deposited dose during proton therapy using data acquired from a PET scanner. The most innovative feature of this novel method is the production of noiseless reconstructed dose distributions from which proton range can be derived with high precision. Approach. A new MLEM & simulated annealing (MSA) algorithm, developed especially in this work, reconstructs the deposited dose distribution from a realistic pre-calculated activity-dose dictionary. This dictionary contains the contribution of each beam in the plan to the 3D activity and dose maps, as calculated by a Monte Carlo simulation. The MSA algorithm, using a priori information of the treatment plan, seeks for the linear combination of activities of the precomputed beams that best fits the observed PET data, obtaining at the same time the deposited dose. Main results. the method has been tested using simulated data to determine its performance under 4 different test cases: (1) dependency of range detection accuracy with delivered dose, (2) in-beam versus offline verification, (3) ability to detect anatomical changes and (4) reconstruction of a realistic spread-out Bragg peak. The results show the ability of the method to accurately reconstruct doses from PET data corresponding to 1 Gy irradiations, both in intra-fraction and inter-fraction verification scenarios. For this dose level (1 Gy) the method was able to spot range variations as small as 0.6 mm. Significance. out method is able to reconstruct dose maps with remarkable accuracy from clinically relevant dose levels down to 1 Gy. Furthermore, due to the noiseless nature of reconstructed dose maps, an accuracy better than one millimeter was obtained in proton range estimates. These features make of this method a realistic option for range verification in proton therapy.

Impact of RBE variations on risk estimates of temporal lobe necrosis in patients treated with intensity-modulated proton therapy for head and neck cancer

BACKGROUND

Temporal lobe necrosis (TLN) is a potential late effect after radiotherapy for skull base head and neck cancer (HNC). Several photon-derived dose constraints and normal tissue complication probability (NTCP) models have been proposed, however variation in relative biological effectiveness (RBE) may challenge the applicability of these dose constraints and models in proton therapy. The purpose of this study was therefore to investigate the influence of RBE variations on risk estimates of TLN after Intensity-Modulated Proton Therapy for HNC.

MATERIAL AND METHODS

Seventy-five temporal lobes from 45 previously treated patients were included in the analysis. Sixteen temporal lobes had radiation associated Magnetic Resonance image changes (TLIC) suspected to be early signs of TLN. Fixed (RWD_Fix) and variable RBE-weighed doses (RWD_Var) were calculated using RBE = 1.1 and two RBE models, respectively. RWD_Fix and RWD_Var for temporal lobes were compared using Friedman's test. Based on RWD_Fix, six NTCP models were fitted and internally validated through bootstrapping. Estimated probabilities from RWD_Fix and RWD_Var were compared using paired Wilcoxon test. Seven dose constraints were evaluated separately for RWD_Fix and RWD_Var by calculating the observed proportion of TLIC in temporal lobes meeting the specific dose constraints.

RESULTS

RWD_Var were significantly higher than RWD_Fix (p < 0.01). NTCP model performance was good (AUC:0.79-0.84). The median difference in estimated probability between RWD_Fix and RWD_Var ranged between 5.3% and 20.0% points (p < 0.01), with V_60GyRBE and D_Max at the smallest and largest differences, respectively. The proportion of TLIC was higher for RWD_Fix (4.0%-13.1%) versus RWD_Var (1.3%-5.3%). For V_65GyRBE ≤ 0.03 cc the proportion of TLIC was less than 5% for both RWD_Fix and RWD_Var.

CONCLUSION

NTCP estimates were significantly influenced by RBE variations. D_max as model predictor resulted in the largest deviations in risk estimates between RWD_Fix and RWD_Var. V_65GyRBE ≤ 0.03 cc was the most consistent dose constraint for RWD_Fix and RWD_Var.

Microdosimetric characterization of a clinical proton therapy beam: comparison between simulated lineal energy distributions in spherical water targets and experimental measurements with a silicon detector

Objective Treatment planning based on computer simulations were proposed to account for the increase in the relative biological effectiveness (RBE) of proton radiotherapy beams near to the edges of the irradiated volume. Since silicon detectors could be used to validate the results of these simulations, it is important to explore the limitations of this comparison. Approach Microdosimetric measurements with a MicroPlus Bridge V2 silicon detector (thickness = 10 µm) were performed along the Bragg peak of a clinical proton beam. The lineal energy distributions, the dose mean values, and the RBE calculated with a biological weighting function were compared with simulations with PHITS (microdosimetric target = 1 µm water sphere), and published clonogenic survival in vitro RBE data for the V79 cell line. The effect of the silicon-to-water conversion was also investigated by comparing three different methodologies (conversion based on a single value, novel bin-to-bin conversions based on SRIM and PSTAR). Main results Mainly due to differences in the microdosimetric targets, the experimental dose-mean lineal energy and RBE values at the distal edge were respectively up to 53% and 28% lower than the simulated ones. Furthermore, the methodology chosen for the silicon-to-water conversion was proven to affect the dose mean lineal energy and the RBE10 up to 32% and 11% respectively. The best methodology to compensate for this underestimation was the bin-to-bin silicon-to-water conversion based on PSTAR. Significance This work represents the first comparison between PHITS-simulated lineal energy distributions in water targets and corresponding experimental spectra measured with silicon detectors. Furthermore, the effect of the silicon-to-water conversion on the RBE was explored for the first time. The proposed methodology based on the PSTAR bin-to-bin conversion appears to provide superior results with respect to commonly used single scaling factors and is recommended for future studies.

Impact of a spatially dependent dose delivery time structure on the biological effectiveness of scanning proton therapy

PURPOSE

In the scanning beam delivery of protons, different portions of the target are irradiated with different linear energy transfer protons with various time intervals and irradiation times. This research aimed to evaluate the spatially dependent biological effectiveness of protracted irradiation in scanning proton therapy.

METHODS

One and two parallel opposed fields plans were created in water phantom with the prescribed dose of 2 Gy. Three scenarios (instantaneous, continuous, and layered scans) were used with the corresponding beam delivery models. The biological dose (physical dose × relative biological effectiveness) was calculated using the linear quadratic model and the theory of dual radiation action to quantitatively evaluate the dose delivery time effect. In addition, simulations using clinical plans (postoperative seminoma and prostate tumor cases) were conducted to assess the impact of the effects on the dose volume histogram parameters and homogeneity coefficient (HC) in targets.

RESULTS

In a single-field plan of water phantom, when the treatment time was 19 min, the layered-scan scenario showed a decrease of <0.2% (almost 3.3%) in the biological dose from the plan on the distal (proximal) side because of the high (low) dose rate. This is in contrast to the continuous scenario, where the biological dose was almost uniformly decreased over the target by approximately 3.3%. The simulation with clinical geometry showed that the decrease rates in D_99% were 0.9% and 1.5% for every 10 min of treatment time prolongation for postoperative seminoma and prostate tumor cases, respectively, whereas the increase rates in HC were 0.7% and 0.2%.

CONCLUSIONS

In protracted irradiation in scanning proton therapy, the spatially dependent dose delivery time structure in scanning beam delivery can be an important factor for accurate evaluation of biological effectiveness.

The Organ Sparing Potential of Different Biological Optimization Strategies in Proton Therapy

Purpose

Variable relative biological effectiveness (RBE) models allow for differences in linear energy transfer (LET), physical dose, and tissue type to be accounted for when quantifying and optimizing the biological damage of protons. These models are complex and fraught with uncertainties, and therefore, simpler RBE optimization strategies have also been suggested. Our aim was to compare several biological optimization strategies for proton therapy by evaluating their performance in different clinical cases.

Methods and Materials

Two different optimization strategies were compared: full variable RBE optimization and differential RBE optimization, which involve applying fixed RBE for the planning target volume (PTV) and variable RBE in organs at risk (OARs). The optimization strategies were coupled to 2 variable RBE models and 1 LET-weighted dose model, with performance demonstrated on 3 different clinical cases: brain, head and neck, and prostate tumors.

Results

In cases with low (α/β)x in the tumor, the full RBE optimization strategies had a large effect, with up to 10% reduction in RBE-weighted dose to the PTV and OARs compared with the reference plan, whereas smaller variations (<5%) were obtained with differential optimization. For tumors with high (α/β)x, the differential RBE optimization strategy showed a greater reduction in RBE-weighted dose to the OARs compared with the reference plan and the full RBE optimization strategy.

Conclusions

Differences between the optimization strategies varied across the studied cases, influenced by both biological and physical parameters. Whereas full RBE optimization showed greater OAR sparing, awareness of underdosage to the target must be carefully considered.

Handling of beam spectra in training and application of proton RBE models

Published data from cell survival experiments are frequently used as training data for models of proton relative biological effectiveness (RBE). The publications rarely provide full information about the primary particle spectrum of the used beam, or its content of heavy secondary particles. The purpose of this paper is to assess to what extent heavy secondary particles may have been present in published cell survival experiments, and to investigate the impact of non-primary protons for RBE calculations in treatment planning. We used the Monte Carlo code Geant4 to calculate the occurrence of non-primary protons and heavier secondary particles for clinical protons beams in water for four incident energies in the [100, 250] MeV interval. We used the resulting spectra together with a conservative RBE parameterization and an RBE model to map both the rise of RBE at the beam entry surface due to heavy secondary particle buildup, and the difference in estimated RBE if non-primary protons are included or not in the beam quality metric. If included, non-primary protons cause a difference of 2% of the RBE in the plateau region of an spread out Bragg peak and 1% in the Bragg peak. Including non-primary protons specifically for RBE calculations will consequently have a negligible impact and can be ignored. A buildup distance in water of one millimeter was sufficient to reach an equilibrium state of RBE for the four incident energies selected. For the investigated experimental data, 83 out of the 86 data points were found to have been determined with at least that amount of buildup material. Hence, RBE model training data should be interpreted to include the contribution of heavy secondaries.

Study of relationship between dose, LET and the risk of brain necrosis after proton therapy for skull base tumors

PURPOSE

We investigated the relationship between RBE-weighted dose (DRBE) calculated with constant (cRBE) and variable RBE (vRBE), dose-averaged linear energy transfer (LETd) and the risk of radiographic changes in skull base patients treated with protons.

METHODS

Clinical treatment plans of 45 patients were recalculated with Monte Carlo tool FRED. Radiographic changes (i.e. edema and/or necrosis) were identified by MRI. Dosimetric parameters for cRBE and vRBE were computed. Biological margin extension and voxel-based analysis were employed looking for association of DRBE(vRBE) and LETd with brain edema and/or necrosis.

RESULTS

When using vRBE, Dmax in the brain was above the highest dose limits for 38% of patients, while such limit was never exceeded assuming cRBE. Similar values of Dmax were observed in necrotic regions, brain and temporal lobes. Most of the brain necrosis was in proximity to the PTV. The voxel-based analysis did not show evidence of an association with high LETd values.

CONCLUSIONS

When looking at standard dosimetric parameters, the higher dose associated with vRBE seems to be responsible for an enhanced risk of radiographic changes. However, as revealed by a voxel-based analysis, the large inter-patient variability hinders the identification of a clear effect for high LETd.

Dosimetric Assessment of a High Precision System for Mouse Proton Irradiation to Assess Spinal Cord Toxicity

The uncertainty associated with the relative biological effectiveness (RBE) in proton therapy, particularly near the Bragg peak (BP), has led to the shift towards biological-based treatment planning. Proton RBE uncertainty has recently been reported as a possible cause for brainstem necrosis in pediatric patients treated with proton therapy. Despite this, in vivo studies have been limited due to the complexity of accurate delivery and absolute dosimetry. The purpose of this investigation was to create a precise and efficient method of treating the mouse spinal cord with various portions of the proton Bragg curve and to quantify associated uncertainties for the characterization of proton RBE. Mice were restrained in 3D printed acrylic boxes, shaped to their external contour, with a silicone insert extending down to mold around the mouse. Brass collimators were designed for parallel opposed beams to treat the spinal cord while shielding the brain and upper extremities of the animal. Up to six animals may be accommodated for simultaneous treatment within the restraint system. Two plans were generated targeting the cervical spinal cord, with either the entrance (ENT) or the BP portion of the beam. Dosimetric uncertainty was measured using EBT3 radiochromic film with a dose-averaged linear energy transfer (LETd) correction. Positional uncertainty was assessed by collecting a library of live mouse scans (n = 6 mice, two independent scans per mouse) and comparing the following dosimetric statistics from the mouse cervical spinal cord: Volume receiving 90% of the prescription dose (V90); mean dose to the spinal cord; and LETd. Film analysis results showed the dosimetric uncertainty to be ±1.2% and ±5.4% for the ENT and BP plans, respectively. Preliminary results from the mouse library showed the V90 to be 96.3 ± 4.8% for the BP plan. Positional uncertainty of the ENT plan was not measured due to the inherent robustness of that treatment plan. The proposed high-throughput mouse proton irradiation setup resulted in accurate dose delivery to mouse spinal cords positioned along the ENT and BP. Future directions include adapting the setup to account for weight fluctuations in mice undergoing fractionated irradiation.

Exploratory Investigation of Dose-Linear Energy Transfer (LET) Volume Histogram (DLVH) for Adverse Events Study in Intensity Modulated Proton Therapy (IMPT)

PURPOSE

We proposed a novel tool-a dose linear energy transfer (LET)-volume histogram (DLVH)-and performed an exploratory study to investigate rectal bleeding in prostate cancer treated with intensity modulated proton therapy.

METHODS AND MATERIALS

The DLVH was constructed with dose and LET as 2 axes, and the normalized volume of the structure was contoured in the dose-LET plane as isovolume lines. We defined the DLVH index, DLv%(d,l) (ie, v% of the structure) to have a dose of ≥d Gy and an LET of ≥l keV/μm, similar to the dose-volume histogram index Dv%. Nine patients with prostate cancer with rectal bleeding (Common Terminology Criteria for Adverse Events grade ≥2) were included as the adverse event group, and 48 patients with no complications were considered the control group. A P value map was constructed by comparison of the DLVH indices of all patients between the 2 groups using the Mann-Whitney U test. Dose-LET volume constraints (DLVCs) were derived based on the P value map with a manual selection procedure facilitated by Spearman's correlation tests. The obtained DLVCs were further cross-validated using a multivariate support vector machine (SVM)-based normal tissue complication probability (NTCP) model with an independent testing data set composed of 8 adverse event and 13 control patients.

RESULTS

We extracted 2 DLVC constraints. One DLVC was obtained, Vdose/LETboundary:2.5keVμmat 75 Gy to 3.2keVμmat8.65Gy <1.27% (DLVC1), revealing a high LET volume effect. The second DLVC, V(72.2Gy,0keVμm) < 2.23% (DVLC2), revealed a high dose volume effect. The SVM-based NTCP model with 2 DLVCs provided slightly superior performance than using dose only, with an area under the curve of 0.798 versus 0.779 for the testing data set.

CONCLUSIONS

Our results demonstrated the importance of rectal "hot spots" in both high LET (DLVC1) and high dose (DLVC2) in inducing rectal bleeding. The SVM-based NTCP model confirmed the derived DLVCs as good predictors for rectal bleeding when intensity modulated proton therapy is used to treat prostate cancer.

A Critical Review of LET-Based Intensity-Modulated Proton Therapy Plan Evaluation and Optimization for Head and Neck Cancer Management

In this review article, we review the 3 important aspects of linear-energy-transfer (LET) in intensity-modulated proton therapy (IMPT) for head and neck (H&N) cancer management. Accurate LET calculation methods are essential for LET-guided plan evaluation and optimization, which can be calculated either by analytical methods or by Monte Carlo (MC) simulations. Recently, some new 3D analytical approaches to calculate LET accurately and efficiently have been proposed. On the other hand, several fast MC codes have also been developed to speed up the MC simulation by simplifying nonessential physics models and/or using the graphics processor unit (GPU)–acceleration approach. Some concepts related to LET are also briefly summarized including (1) dose-weighted versus fluence-weighted LET; (2) restricted versus unrestricted LET; and (3) microdosimetry versus macrodosimetry. LET-guided plan evaluation has been clinically done in some proton centers. Recently, more and more studies using patient outcomes as the biological endpoint have shown a positive correlation between high LET and adverse events sites, indicating the importance of LET-guided plan evaluation in proton clinics. Various LET-guided plan optimization methods have been proposed to generate proton plans to achieve biologically optimized IMPT plans. Different optimization frameworks were used, including 2-step optimization, 1-step optimization, and worst-case robust optimization. They either indirectly or directly optimize the LET distribution in patients while trying to maintain the same dose distribution and plan robustness. It is important to consider the impact of uncertainties in LET-guided optimization (ie, LET-guided robust optimization) in IMPT, since IMPT is sensitive to uncertainties including both the dose and LET distributions. We believe that the advancement of the LET-guided plan evaluation and optimization will help us exploit the unique biological characteristics of proton beams to improve the therapeutic ratio of IMPT to treat H&N and other cancers.

MR-guided proton therapy: Impact of magnetic fields on the detector response

PURPOSE

To investigate the response of detectors for proton dosimetry in the presence of magnetic fields.

MATERIAL AND METHODS

Four ionization chambers (ICs), two thimble-type and two plane-parallel-type, and a diamond detector were investigated. All detectors were irradiated with homogeneous single-energy-layer fields, using 252.7 MeV proton beams. A Farmer IC was additionally irradiated in the same geometrical configuration, but with a lower nominal energy of 97.4 MeV. The beams were subjected to magnetic field strengths of 0, 0.25, 0.5, 0.75, and 1 T produced by a research dipole magnet placed at the room's isocenter. Detectors were positioned at 2 cm water equivalent depth, with their stem perpendicular to both the magnetic field lines and the proton beam's central axis, in the direction of the Lorentz force. Normality and two sample statistical Student's t tests were performed to assess the influence of the magnetic field on the detectors' responses.

RESULTS

For all detectors, a small but significant magnetic field-dependent change of their response was found. Observed differences compared to the no magnetic field case ranged from +0.5% to -0.7%. The magnetic field dependence was found to be nonlinear and highest between 0.25 and 0.5 T for 252.7 MeV proton beams. A different variation of the Farmer chamber response with magnetic field strength was observed for irradiations using lower energy (97.4 MeV) protons. The largest magnetic field effects were observed for plane-parallel ionization chambers.

CONCLUSION

Small magnetic field-dependent changes in the detector response were identified, which should be corrected for dosimetric applications.

A systematic review on the usage of averaged LET in radiation biology for particle therapy

Linear Energy Transfer (LET) is widely used to express the radiation quality of ion beams, when characterizing the biological effectiveness. However, averaged LET may be defined in multiple ways, and the chosen definition may impact the resulting reported value. We review averaged LET definitions found in the literature, and quantify which impact using these various definitions have for different reference setups. We recorded the averaged LET definitions used in 354 publications quantifying the relative biological effectiveness (RBE) of hadronic beams, and investigated how these various definitions impact the reported averaged LET using a Monte Carlo particle transport code. We find that the kind of averaged LET being applied is, generally, poorly defined. Some definitions of averaged LET may influence the reported averaged LET values up to an order of magnitude. For publications involving protons, most applied dose averaged LET when reporting RBE. The absence of what target medium is used and what secondary particles are included further contributes to an ill-defined averaged LET. We also found evidence of inconsistent usage of averaged LET definitions when deriving LET-based RBE models. To conclude, due to commonly ill-defined averaged LET and to the inherent problems of LET-based RBE models, averaged LET may only be used as a coarse indicator of radiation quality. We propose a more rigorous way of reporting LET values, and suggest that ideally the entire particle fluence spectra should be recorded and provided for future RBE studies, from which any type of averaged LET (or other quantities) may be inferred.

Dosimetric impact of range uncertainty in passive scattering proton therapy

Purpose

The objective of this study was to investigate the dosimetric impact of range uncertainty in a large cohort of patients receiving passive scatter proton therapy.

Methods

A cohort of 120 patients were reviewed in this study retrospectively, of which 61 were brain, 39 lung, and 20 prostate patients. Range uncertainties of ±3.5% (overshooting and undershooting by 3.5%, respectively) were added and recalculated on the original plans, which had been planned according to our clinical planning protocol while keeping beamlines, apertures, compensators, and dose grids intact. Changes in the coverage on CTV and DVH for critical organs were compared and analyzed. Correlation between dose change and minimal distance between CTV and critical organs were also investigated.

Results

Although CTV coverages and maximum dose to critical organs were largely maintained for most brain patients, large variations over 5% were still observed sporadically. Critical organs, such as brainstem and chiasm, could still be affected by range uncertainty at 4 cm away from CTV. Coverage and OARs in lung and prostate patients were less likely to be affected by range uncertainty with very few exceptions.

Conclusion

The margin recipe in modern TPS leads to clinically acceptable OAR doses in the presence of range uncertainties. However, range uncertainties still pose a noticeable challenge for small but critical serial organs near tumors, and occasionally for large parallel organs that are located distal to incident proton beams.

Dual-storage phosphor proton therapy dosimetry: Simultaneous quantification of dose and linear energy transfer

PURPOSE

To investigate the feasibility of using the high Z_eff storage phosphor material BaFBrI:Eu²⁺ in conjunction with the low Z_eff storage phosphor material KCl:Eu²⁺ for simultaneous proton dose and linear energy transfer (LET) measurements by (a) measuring the fundamental optical and dosimetric properties of BaFBrI:Eu²⁺ , (b) evaluating its compatibility in being readout simultaneously with KCl:Eu²⁺ dosimeters, and (c) modeling and validating its LET dependence under elevated proton LET irradiation.

METHODS

A commercial BaFBrI:Eu²⁺ storage phosphor detector (Model ST-VI, Fujifilm) was characterized with energy dispersive x-ray spectroscopy (EDS) analysis to obtain its elemental composition. The dosimeters were irradiated using both a Mevion S250 proton therapy unit (at the center of a spread-out Bragg peak, SOBP) and a Varian Clinac iX linear accelerator with the latter being a low LET irradiation. The photostimulated luminescence (PSL) emission spectra, excitation spectra, and luminescent lifetimes of the detector were measured after proton and photon irradiations. Dosimetric properties including dose linearity, dose rate dependence, radiation hardness, temporal, and readout stabilities were studied using a laboratory optical reader after proton irradiations. In addition, its proton energy dependence was analytically modeled and experimentally validated by irradiating the detectors at various depths within the SOBP (Range: 15.0 g/cm² , Modulation: 10.0 g/cm² ).

RESULTS

The active detector composition for the high Z_eff storage phosphor detector was found to be BaFBr_0.85 I_0.15 :Eu²⁺ . The BaFBr_0.85 I_0.15 :Eu²⁺ material's excitation and emission spectra were in agreement under proton and photon irradiations, with peaks of 586 ± 1 nm and 400 ± 1 nm, respectively, with a full width at half maximum (FWHM) of 119 ± 3 nm and 30 ± 2 nm, respectively. As dosimeter response under photon irradiation is generally believed to be free from LET effect, these results suggest LET independence of charge storage center types resulted from ionizing radiations. There is sufficient spectral overlaps with KCl:Eu²⁺ dosimeters allowing both dosimeters to be readout under equivalent readout conditions, that is, 594 nm stimulation and 420 nm detection wavelengths. Its PSL characteristic lifetime was found to be less than 5 microseconds which would make it suitable for fast 2D readout post irradiation. Its 420 nm emission band intensity was found to be linear up to 10 Gy absolute proton dose under the same irradiation conditions, dose rate independent, stable in time and under multiple readouts, and with high radiation hardness under cumulative proton dose histories up to 200 Gy as tested in this study. BaFBr_0.85 I_0.15 :Eu²⁺ showed significant proton energy-dependent dose under-response in regions of high LET which could be modeled by stopping power ratio calculations with an accuracy of 3% in low LET regions and a distance-to-agreement (DTA) of 1 mm in high LET regions (>5 keV/μm).

CONCLUSION

We have proven the feasibility of dual-storage phosphor proton dosimetry for simultaneous proton dose and LET measurements. BaFBr_0.85 I_0.15 :Eu²⁺ has shown equally excellent dosimetry performance as its low Z_eff complement KCl:Eu²⁺ with distinctive LET dependence merely as a result of its higher Z_eff . These promising results pave the way for future studies involving simultaneous proton dose and LET measurements using this novel approach.

Variation in relative biological effectiveness for cognitive structures in proton therapy of pediatric brain tumors

BACKGROUND

Clinically, a constant value of 1.1 is used for the relative biological effectiveness (RBE) of protons, whereas in vitro the RBE has been shown to vary depending on physical dose, tissue type, and linear energy transfer (LET). As the LET increases at the distal end of the proton beam, concerns exist for an elevated RBE in normal tissues. The aim of this study was therefore to investigate the heterogeneity of RBE to brain structures associated with cognition (BSCs) in pediatric suprasellar tumors.

MATERIAL AND METHODS

Intensity-modulated proton therapy (IMPT) plans for 10 pediatric craniopharyngioma patients were re-calculated using 11 phenomenological and two plan-based variable RBE models. Based on LET, tissue dependence and number of data points used to fit the models, the three RBE models considered the most relevant for the studied endpoint were selected. Thirty BSCs were investigated in terms of RBE and dose/volume parameters.

RESULTS

For a representative patient, the median (range) dose-weighted mean RBE (RBE_d) across all BSCs from the plan-based models was among the lowest (1.09 (1.02-1.52) vs. the phenomenological models at 1.21 (0.78-2.24)). Omitting tissue dependency resulted in RBE_d at 1.21 (1.04-2.24). Across all patients, the narrower RBE model selection gave median RBE_d values from 1.22 to 1.30.

CONCLUSION

For all BSCs, there was a systematic model-dependent variation in RBE_d, mirroring the uncertainty in biological effects of protons. According to a refined selection of in vitro models, the RBE variation across BSCs was in effect underestimated when using a fixed RBE of 1.1.

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.

The impact of variable relative biological effectiveness in proton therapy for left-sided breast cancer when estimating normal tissue complications in the heart and lung

The aim of this study was to evaluate the clinical impact of relative biological effectiveness (RBE) variations in proton beam scanning treatment (PBS) for left-sided breast cancer versus the assumption of a fixed RBE of 1.1, particularly in the context of comparisons with photon-based three-dimensional conformal radiotherapy (3DCRT) and volumetric modulated arc therapy (VMAT). Ten patients receiving radiation treatment to the whole breast/chest wall and regional lymph nodes were selected for each modality. For PBS, the dose distributions were re-calculated with both a fixed RBE and a variable RBE using an empirical RBE model. Dosimetric indices based on dose-volume histogram analysis were calculated for the entire heart wall, left anterior descending artery (LAD) and left lung. Furthermore, normal tissue toxicity probabilities for different endpoints were evaluated. The results show that applying a variable RBE significantly increases the RBE-weighted dose and consequently the calculated dosimetric indices increases for all organs compared to a fixed RBE. The mean dose to the heart and the maximum dose to the LAD and the left lung are significantly lower for PBS assuming a fixed RBE compared to 3DCRT. However, no statistically significant difference is seen when a variable RBE is applied. For a fixed RBE, lung toxicities are significantly lower compared to 3DCRT but when applying a variable RBE, no statistically significant differences are noted. A disadvantage is seen for VMAT over both PBS and 3DCRT. One-to-one plan comparison on 8 patients between PBS and 3DCRT shows similar results. We conclude that dosimetric analysis for all organs and toxicity estimation for the left lung might be underestimated when applying a fixed RBE for protons. Potential RBE variations should therefore be considered as uncertainty bands in outcome analysis.

Spatial Agreement of Brainstem Dose Distributions Depending on Biological Model in Proton Therapy for Pediatric Brain Tumors

Purpose

During radiation therapy for pediatric brain tumors, the brainstem is a critical organ at risk, possibly with different radio-sensitivity across its substructures. In proton therapy, treatment planning is currently performed using a constant relative biological effectiveness (RBE) of 1.1 (RBE_1.1), whereas preclinical studies point toward spatial variability of this factor. To shed light on this biological uncertainty, we investigated the spatial agreement between isodose maps produced by different RBE models, with emphasis on (smaller) substructures of the brainstem.

Methods and Materials

Proton plans were recalculated using Monte Carlo simulations in 3 anonymized pediatric patients with brain tumors (a craniopharyngioma, a low-grade glioma, and a posterior fossa ependymoma) to obtain dose and linear energy transfer distributions. Doses and volume metrics for the brainstem and its substructures were calculated using a constant RBE_1.1, 4 phenomenological RBE models with varying (α/β)_x parameters, and with a simpler linear energy transfer-dependent model. The spatial agreement between the dose distributions of constant RBE_1.1 versus the variable RBE models was compared using the Dice similarity coefficient.

Results

The spatial agreement between the variable RBE dose distributions and RBE_1.1 decreased with increasing isodose levels in all patient cases. The patient with ependymoma showed the greatest variation in dose and dose volumes, where V_50Gy(RBE) in the brainstem increased from 32% (RBE_1.1) to 35% to 49% depending on the applied model, corresponding to a spatial agreement (Dice similarity coefficient) between 0.79 and 0.95. The remaining patients showed similar trends, however, with lower absolute values due to lower brainstem doses.

Conclusions

All phenomenological RBE models fully enclosed the isodose volumes of the constant RBE_1.1, and the volumes based on variable RBE spatially agreed. The spatial agreement was dependent on the isodose level, where higher isodose levels showed larger expansions and less agreement between the variable RBE models and RBE_1.1.

Proton Radiotherapy to Preserve Fertility and Endocrine Function: A Translational Investigation

PURPOSE

Photon radiation therapy (x-ray radiation therapy [XRT] and gamma-ray radiation therapy [GRT]) of tumors close to ovaries causes reproductive and endocrine sequelae due to ovarian primordial follicle depletion. Given its finite range, proton radiation therapy (PRT) can preserve ovarian function when ovaries are positioned distal to the spread-out Bragg peak (SOBP) in tumors of the abdominopelvic region. This study compared anti-Müllerian hormone (AMH) levels (a biomarker of ovarian function) and primordial follicle survival after in vivo mouse pelvic GRT versus PRT.

METHODS AND MATERIALS

One hundred twenty-four female prepubertal mice received sham, GRT, or PRT with ovaries positioned at various depth with respect to the proton SOBP, with single doses of 1.8 or 0.2 Gy. AMH was measured at baseline, 1, 3, and 8 weeks after treatment, and the total number of surviving primordial follicles was counted. Multivariable linear mixed-effects modeling was used to assess the relationship between radiation therapy modality and dose on AMH and primordial follicle survival.

RESULTS

For ovaries beyond the SOBP, ovarian function (P = .5) and ovarian primordial follicle (OPF; P = 1.0) were spared relative to sham controls. For ovaries in the SOBP plateau, ovarian function and primordial follicle reserve 8 weeks after treatment were reduced for all groups: 1.8 Gy GRT (β_AMH = -4.9 ng/mL; β_OPF = -728.2/animal), 1.8 Gy (relative biological effectiveness [RBE] = 1.1) PRT (β_AMH = -5.1 ng/mL; β_OPF = -728.2/animal), 0.2 Gy GRT (β_AMH = -2.5 ng/mL; β_OPF = -595.1/animal), and 0.2 Gy (RBE = 1.1) PRT (β_AMH = -3.0 ng/mL; β_OPF = -555.4/animal) relative to sham controls (all differences P < .001).

CONCLUSIONS

This study uses an animal model to demonstrate the safety of proton therapy in sparing fertility. Ovaries positioned beyond the SOBP during PRT maintain ovarian reserve, suggesting that a proton beam has no energy and exit dose beyond SOBP. This study proposes that proton therapy is much safer than photon radiation therapy to protect ovarian follicles with the same dose, and it supports further testing of proton therapy for abdominopelvic tumors in young women.

FLUKA simulation of target fragmentation in proton therapy

In proton therapy, secondary fragments are created in nuclear interactions of the beam with the target nuclei. The secondary fragments have low kinetic energies and high atomic numbers as compared to primary protons. Fragments have a high LET and deposit all their energy close to the generation point. For their characteristics, secondary fragments can alter the dose distribution and lead to an increase of RBE for the same delivered physical dose. Moreover, the radiobiological impact of target fragmentation is significant mostly in the region before the Bragg peak, where generally healthy tissues are present, and immediately after Bragg peak. Considering the high biological impact of those particles, especially in the case of healthy tissues or organs at risk, the inclusion of target fragmentation processes in the dose calculation of a treatment planning system can be relevant to improve the treatment accuracy and for this reason it is one of the major tasks of the MoVe IT project. In this study, Monte Carlo simulations were employed to fully characterize the mixed radiation field generated by target fragmentation in proton therapy. The dose averaged LET has been evaluated in case of a Spread Out Bragg Peak (SOBP). Starting from LET distribution, RBE has been evaluated with two different phenomenological models. In order to characterize the mixed radiation field, the production cross section has been evaluated by means of the FLUKA code. The future development of present work is to generate a MC database of fragments fluence to be included in TPS.

Clinical implications of variable relative biological effectiveness in proton therapy for prostate cancer

PURPOSE

To study the potential consequences of differences in the evaluation of variable versus uniform relative biological effectiveness calculations in proton radiotherapy for prostate cancer.

METHODS AND MATERIAL

Experimental data with proton beams suggest that relative biological effectiveness increases with linear energy transfer. This relation also depends on the α / β ratio, characteristic of a tissue and a considered endpoint. Three phenomenological models (Carabe et al., Wedenberg et al. and McNamara et al.) are compared to a mechanistic model based on microdosimetry (microdosimetric kinetic model) and to the current assumption of uniform relative biological effectiveness equal to 1.1 in a prostate case.

RESULTS AND CONCLUSIONS

Phenomenological models clearly predict higher relative biological effectiveness values compared to microdosimetric kinetic model, that seems to approach to the constant value of 1.1 adopted in the clinics, at least for low linear energy transfer values achieved in typical prostate proton plans. All models predict a higher increase of the relative biological effectiveness-weighted dose for the prostate tumor than for the rest of structures involved due to its lower α / β ratio, even when linear energy transfer is, in general, lower in the tumor than on the surroundings tissues. Prostate cancer is, therefore, a good candidate to take advantage of variable relative biological effectiveness, especially if linear energy transfer is enhanced within the tumor. However, the discrepancies among models hinder the clinical implementation of variable relative biological effectiveness.