Inclusion of a variable RBE into proton and photon plan comparison for various fractionation schedules in prostate radiation therapy

Robustness evaluation of pencil beam scanning proton therapy treatment planning: A systematic review

Compared to conventional radiotherapy using X-rays, proton therapy, in principle, allows better conformity of the dose distribution to target volumes, at the cost of greater sensitivity to physical, anatomical, and positioning uncertainties. Robust planning, both in terms of plan optimization and evaluation, has gained high visibility in publications on the subject and is part of clinical practice in many centers. However, there is currently no consensus on the methods and parameters to be used for robust optimization or robustness evaluation. We propose to overcome this deficiency by following the modified Delphi consensus method. This method first requires a systematic review of the literature. We performed this review using the PubMed and Web Of Science databases, via two different experts. Potential conflicts were resolved by a third expert. We then explored the different methods before focusing on clinical studies that evaluate robustness on a significant number of patients. Many robustness assessment methods are proposed in the literature. Some are more successful than others and their implementation varies between centers. Moreover, they are not all statistically or mathematically equivalent. The most sophisticated and rigorous methods have seen more limited application due to the difficulty of their implementation and their lack of widespread availability.

Biological optimization for hybrid proton-photon radiotherapy

Objective.Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose.Approach.The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method.Main results.Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies.Significance.This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

A perspective on tumor radiation resistance following high-LET radiation treatment

High-linear energy transfer (LET) radiation is a promising alternative to conventional low-LET radiation for therapeutic gain against cancer owing to its ability to induce complex and clustered DNA lesions. However, the development of radiation resistance poses a significant barrier. The potential molecular mechanisms that could confer resistance development are translesion synthesis (TLS), replication gap suppression (RGS) mechanisms, autophagy, epithelial-mesenchymal transition (EMT) activation, release of exosomes, and epigenetic changes. This article will discuss various types of complex clustered DNA damage, their repair mechanisms, mutagenic potential, and the development of radiation resistance strategies. Furthermore, it highlights the importance of careful consideration and patient selection when employing high-LET radiotherapy in clinical settings.

Benchmarking proton RBE models

Objective.To biologically optimise proton therapy, models which can accurately predict variations in proton relative biological effectiveness (RBE) are essential. Current phenomenological models show large disagreements in RBE predictions, due to different model assumptions and differences in the data to which they were fit. In this work, thirteen RBE models were benchmarked against a comprehensive proton RBE dataset to evaluate predictions when all models are fit using the same data and fitting techniques, and to assess the statistical robustness of the models.Approach.Model performance was initially evaluated by fitting to the full dataset, and then a cross-validation approach was applied to assess model generalisability and robustness. The impact of weighting the fit and the choice of biological endpoint (either single or multiple survival levels) was also evaluated.Main results.Fitting the models to a common dataset reduced differences between their predictions, however significant disagreements remained due to different underlying assumptions. All models performed poorly under cross-validation in the weighted fits, suggesting that some uncertainties on the experimental data were significantly underestimated, resulting in over-fitting and poor performance on unseen data. The simplest model, which depends linearly on the LET but has no tissue or dose dependence, performed best for a single survival level. However, when fitting to multiple survival levels simultaneously, more complex models with tissue dependence performed better. All models had significant residual uncertainty in their predictions compared to experimental data.Significance.This analysis highlights that poor quality of error estimation on the dose response parameters introduces substantial uncertainty in model fitting. The significant residual error present in all approaches illustrates the challenges inherent in fitting to large, heterogeneous datasets and the importance of robust statistical validation of RBE models.

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.

Variation of the relative biological effectiveness with fractionation in proton therapy: Analysis of prostate cancer response

BACKGROUND

In treatment planning for proton therapy a constant Relative Biological Effectiveness (RBE) of 1.1 is used, disregarding variations with linear energy transfer, clinical endpoint, or fractionation.

PURPOSE

To present a methodology to analyze the variation of RBE with fractionation from clinical data of tumor control probability (TCP) and to apply it to study the response of prostate cancer to proton therapy.

METHODS AND MATERIALS

We analyzed the dependence of the RBE on the dose per fraction by using the LQ model and the Poisson TCP formalism. Clinical tumor control probabilities for prostate cancer (low and intermediate risk) treated with photon and proton therapy for conventional fractionation (2 Gy(RBE)×37 fractions), moderate hypofractionation (3 Gy(RBE)×20 fractions) and hypofractionation (7.25 Gy(RBE)×5 fractions) were obtained from the literature and analyzed aiming at obtaining the RBE and its dependence on the dose per fraction.

RESULTS

The theoretical analysis of the dependence of the RBE on the dose per fraction showed three distinct regions with RBE monotonically decreasing, increasing or staying constant with the dose per fraction, depending on the change of (α, β) values between photon and proton irradiation (the equilibrium point being at (αp /βp ) = (αX /βX )(αX /αp )). An analysis of the clinical data showed RBE values that decline with increasing dose per fraction: for low risk RBE≈1.124, 1.119, and 1.102 for 1.82 Gy, 2.73 Gy and 6.59 Gy per fraction (physical proton doses), respectively; for intermediate risk RBE≈1.119 and 1.102 for 1.82 Gy and 6.59 Gy per fraction (physical proton doses), respectively. These values are nonetheless very close to the nominal 1.1 value.

CONCLUSIONS

In this study, we have presented a methodology to analyze the RBE for different fractionations, and we used it to study clinical data for prostate cancer and evaluate the RBE versus dose per fraction. The analysis shows a monotonically decreasing RBE with increasing dose per fraction, which is expected from the LQ formalism and the changes in (α, β) values between photon and proton irradiation. However, the calculations in this study have to be considered with care as they may be biased by limitations in the modeling assumptions and/or by the clinical data set used for the analysis.

A Systematic Review of LET-Guided Treatment Plan Optimisation in Proton Therapy: Identifying the Current State and Future Needs

The well-known clinical benefits of proton therapy are achieved through higher target-conformality and normal tissue sparing than conventional radiotherapy. However, there is an increased sensitivity to uncertainties in patient motion/setup, proton range and radiobiological effect. Although recent efforts have mitigated some uncertainties, radiobiological effect remains unresolved due to a lack of clinical data for relevant endpoints. Therefore, RBE optimisations may be currently unsuitable for clinical treatment planning. LET optimisation is a novel method that substitutes RBE with LET, shifting LET hotspots outside critical structures. This review outlines the current status of LET optimisation in proton therapy, highlighting knowledge gaps and possible future research. Following the PRISMA 2020 guidelines, a search of the MEDLINE® and Scopus databases was performed in July 2023, identifying 70 relevant articles. Generally, LET optimisation methods achieved their treatment objectives; however, clinical benefit is patient-dependent. Inconsistencies in the reported data suggest further testing is required to identify therapeutically favourable methods. We discuss the methods which are suitable for near-future clinical deployment, with fast computation times and compatibility with existing treatment protocols. Although there is some clinical evidence of a correlation between high LET and adverse effects, further developments are needed to inform future patient selection protocols for widespread application of LET optimisation in proton therapy.

An iterative convex relaxation method for proton LET optimization

Objective:A constant relative biological effectiveness of 1.1 in current clinical practice of proton radiotherapy (RT) is a crude approximation and may severely underestimate the biological dose from proton RT to normal tissues, especially near the treatment target at the end of Bragg peaks that exhibits high linear energy transfer (LET). LET optimization can account for biological effectiveness of protons during treatment planning, for minimizing biological proton dose and hot spots to normal tissues. However, the LET optimization is usually nonlinear and nonconvex to solve, for which this work will develop an effective optimization method based on iterative convex relaxation (ICR).Approach: In contrast to the generic nonlinear optimization method, such as Quasi-Newton (QN) method, that does not account for specific characteristics of LET optimization, ICR is tailored to LET modeling and optimization in order to effectively and efficiently solve the LET problem. Specifically, nonlinear dose-averaged LET term is iteratively linearized and becomes convex during ICR, while nonconvex dose-volume constraint and minimum-monitor-unit constraint are also handled by ICR, so that the solution for LET optimization is obtained by solving a sequence of convex and linearized convex subproblems. Since the high LET mostly occurs near the target, a 1 cm normal-tissue expansion of clinical target volume (CTV) (excluding CTV), i.e. CTV1cm, is defined to as an auxiliary structure during treatment planning, where LET is minimized.Main results: ICR was validated in comparison with QN for abdomen, lung, and head-and-neck cases. ICR was effective for LET optimization, as ICR substantially reduced the LET and biological dose in CTV1cm the ring, with preserved dose conformality to CTV. Compared to QN, ICR had smaller LET, physical and biological dose in CTV1cm, and higher conformity index values; ICR was also computationally more efficient, which was about 3 times faster than QN.Significance: A LET-specific optimization method based on ICR has been developed for solving proton LET optimization, which has been shown to be more computationally efficient than generic nonlinear optimizer via QN, with better plan quality in terms of LET, biological and physical dose conformality.

Determination of the proton LET using thin film solar cells coated with scintillating powder

PURPOSE

The amount of luminescent light detected in a scintillator is reduced with increased proton linear energy transfer (LET) despite receiving the same proton dose, through a phenomenon called quenching. This study evaluated the ability of a solar cell coated with scintillating powder (SC-SP) to measure therapeutic proton LET by measuring the quenching effect of the scintillating powder using a solar cell while simultaneously measuring the dose of the proton beam.

METHODS

SC-SP was composed of a flexible thin film solar cell and scintillating powder. The LET and dose of the pristine Bragg peak in the 14 cm range were calculated using a validated Monte Carlo model of a double scattering proton beam nozzle. The SC-SP was evaluated by measuring the proton beam under the same conditions at specific depths using SC-SP and Markus chamber. Finally, the 10 and 20 cm range pristine Bragg peaks and 5 cm spread-out Bragg peak (SOBP) in the 14 cm range were measured using the SC-SP and the Markus chamber. LETs measured using the SC-SP were compared with those calculated using Monte Carlo simulations.

RESULTS

The quenching factors of the SC-SP and solar cell alone, which were slopes of linear fit obtained from quenching correction factors according to LET, were 0.027 and 0.070 µm/keV (R² : 0.974 and 0.975). For pristine Bragg peaks in the 10 and 20 cm ranges, the maximum differences between LETs measured using the SC-SP and calculated using Monte Carlo simulations were 0.5 keV/µm (15.7%) and 1.2 keV/µm (12.0%), respectively. For a 5 cm SOBP proton beam, the LET measured using the SC-SP and calculated using Monte Carlo simulations differed by up to 1.9 keV/µm (18.7%).

CONCLUSIONS

Comparisons of LETs for pristine Bragg peaks and SOBP between measured using the SC-SP and calculated using Monte Carlo simulations indicated that the solar cell-based system could simultaneously measure both LET and dose in real-time and is cost-effective.

Quantitative analysis of dose-averaged linear energy transfer (LETd ) robustness in pencil beam scanning proton lung plans

PURPOSE

The primary objective of our study was to perform a quantitative robustness analysis of the dose-averaged linear energy transfer (LET_d ) and related RBE-weighted dose in robustly optimized (in terms of the range and set up uncertainties) pencil beam scanning (PBS) proton lung cancer plans.

METHODS

In this study, we utilized the 4DCT data set of six anonymized lung patients. PBS lung plans were generated using a robust optimization technique (range uncertainty: ±3.5% and setup errors: ±5 mm) on the CTV for a total dose of 5000 cGy(RBE) in 5 fractions using RBE of 1.1. For each patient, the LET_d distributions were calculated for the nominal plan and three groups. Group 1: two plan robustness scenarios for range uncertainties of ±3.5%; Group 2: twelve plan robustness scenarios (range uncertainty (±3.5%) in conjunction with setup errors (±5 mm)); and Group 3: ten different breathing phases of the 4DCT data set. RBE-weighted dose to the OARs was evaluated for all robustness scenarios and breathing phases. The variation (∆) in the mean LET_d and mean RBE-weighted dose from each group was recorded.

RESULTS

The mean LET_d in the CTV of nominal PBS lung plans among six patients ranged from 2.2 to 2.6 keV/μm. On average, for the combined range and setup uncertainties, the ∆ in the mean LET_d among 12 scenarios of all six patients was 0.6 keV/μm, which is slightly higher than when only the range uncertainties were considered (0.4 keV/μm). The ∆ in the mean LET_d in a patient was ≤1.7 keV/μm in the heart and ≤1.2 keV/μm in the esophagus and total lung. The ∆ in the mean RBE-weighted dose in a patient was up to 79 cGy for the total lung, 165 cGy for the heart, and 258 cGy for the esophagus. For ten breathing phases, the ∆ in the mean LET_d in a patient was ≤0.3 keV/μm in the CTV, ≤0.5 keV/μm in the heart, ≤0.4 keV/μm in the esophagus, and ≤0.7 keV/μm in the total lung.

CONCLUSION

The addition of setup errors to the range uncertainties resulted in slightly less homogeneous LET_d distributions. The variations in the mean LET_d among ten breathing phases were slightly larger in the total lung than in the heart and esophagus. The combination of setup and range uncertainties had a greater impact than the effect of breathing phases on the variations in the mean RBE-weighted dose to the OARs. Overall, the LET_d distributions in the CTV were less sensitive than those in the OARs to setup errors, range uncertainties, and breathing phases for robustly optimized PBS proton lung cancer plans. This article is protected by copyright. All rights reserved.

Towards harmonizing clinical linear energy transfer (LET) reporting in proton radiotherapy: a European multi-centric study

BACKGROUND

Clinical data suggest that the relative biological effectiveness (RBE) in proton therapy (PT) varies with linear energy transfer (LET). However, LET calculations are neither standardized nor available in clinical routine. Here, the status of LET calculations among European PT institutions and their comparability are assessed.

MATERIALS AND METHODS

Eight European PT institutions used suitable treatment planning systems with their center-specific beam model to create treatment plans in a water phantom covering different field arrangements and fulfilling commonly agreed dose objectives. They employed their locally established LET simulation environments and procedures to determine the corresponding LET distributions. Dose distributions D1.1 and DRBE assuming constant and variable RBE, respectively, and LET were compared among the institutions. Inter-center variability was assessed based on dose- and LET-volume-histogram parameters.

RESULTS

Treatment plans from six institutions fulfilled all clinical goals and were eligible for common analysis. D1.1 distributions in the target volume were comparable among PT institutions. However, corresponding LET values varied substantially between institutions for all field arrangements, primarily due to differences in LET averaging technique and considered secondary particle spectra. Consequently, DRBE using non-harmonized LET calculations increased inter-center dose variations substantially compared to D1.1 and significantly in mean dose to the target volume of perpendicular and opposing field arrangements (p < 0.05). Harmonizing LET reporting (dose-averaging, all protons, LET to water or to unit density tissue) reduced the inter-center variability in LET to the order of 10-15% within and outside the target volume for all beam arrangements. Consequentially, inter-institutional variability in DRBE decreased to that observed for D1.1.

CONCLUSION

Harmonizing the reported LET among PT centers is feasible and allows for consistent multi-centric analysis and reporting of tumor control and toxicity in view of a variable RBE. It may serve as basis for harmonized variable RBE dose prescription in PT.

Acute toxicity and patient-reported symptom score after conventional versus moderately hypofractionated proton therapy for prostate cancer

INTRODUCTION

To confirm the feasibility of hypofractionated proton beam therapy (PBT), we compared the acute adverse event rates and International Prostate Symptom Score (IPSS) in prostate cancer patients treated with hypofractionated versus conventionally fractionated (2.0 Gy relative biological effectiveness (RBE)/fraction) PBT.

METHODS

We reviewed 289 patients with prostate cancer, of whom 73, 100, and 116 patients were treated with 2.0, 2.5, and 3.0 Gy (RBE)/fraction, respectively. The endpoints were acute genitourinary and gastrointestinal toxicities and the IPSS, evaluated up to 6 months after PBT initiation.

RESULTS

No significant differences were found in acute toxicity rates or the IPSS among the fractionation schedules. Diabetes mellitus, age, and androgen deprivation therapy were not identified as factors associated with the IPSS.

CONCLUSION

There were no significant differences in adverse events or quality of life among the three fractionation schedules early after PBT.

Biological Impact of Target Fragments on Proton Treatment Plans: An Analysis Based on the Current Cross-Section Data and a Full Mixed Field Approach

Simple Summary

Proton therapy is now an established external radiotherapy modality for cancer treatment. Clinical routine currently neglects the radiobiological impact of nuclear target fragments even if experimental evidences show a significant enhancement in cell-killing effect due to secondary particles. This paper quantifies the contribution of proton target fragments of different charge in different irradiation scenarios and compares the computationally predicted corrections to the overall biological dose with experimental data.

Abstract

Clinical routine in proton therapy currently neglects the radiobiological impact of nuclear target fragments generated by proton beams. This is partially due to the difficult characterization of the irradiation field. The detection of low energetic fragments, secondary protons and fragments, is in fact challenging due to their very short range. However, considering their low residual energy and therefore high LET, the possible contribution of such heavy particles to the overall biological effect could be not negligible. In this context, we performed a systematic analysis aimed at an explicit assessment of the RBE (relative biological effectiveness, i.e., the ratio of photon to proton physical dose needed to achieve the same biological effect) contribution of target fragments in the biological dose calculations of proton fields. The TOPAS Monte Carlo code has been used to characterize the radiation field, i.e., for the scoring of primary protons and fragments in an exemplary water target. TRiP98, in combination with LEM IV RBE tables, was then employed to evaluate the RBE with a mixed field approach accounting for fragments’ contributions. The results were compared with that obtained by considering only primary protons for the pristine beam and spread out Bragg peak (SOBP) irradiations, in order to estimate the relative weight of target fragments to the overall RBE. A sensitivity analysis of the secondary particles production cross-sections to the biological dose has been also carried out in this study. Finally, our modeling approach was applied to the analysis of a selection of cell survival and RBE data extracted from published in vitro studies. Our results indicate that, for high energy proton beams, the main contribution to the biological effect due to the secondary particles can be attributed to secondary protons, while the contribution of heavier fragments is mainly due to helium. The impact of target fragments on the biological dose is maximized in the entrance channels and for small α/β values. When applied to the description of survival data, model predictions including all fragments allowed better agreement to experimental data at high energies, while a minor effect was observed in the peak region. An improved description was also obtained when including the fragments’ contribution to describe RBE data. Overall, this analysis indicates that a minor contribution can be expected to the overall RBE resulting from target fragments. However, considering the fragmentation effects can improve the agreement with experimental data for high energy proton beams.

Normal Tissue Injury Induced by Photon and Proton Therapies: Gaps and Opportunities

Despite technological advances in radiation therapy (RT) and cancer treatment, patients still experience adverse effects. Proton therapy (PT) has emerged as a valuable RT modality that can improve treatment outcomes. Normal tissue injury is an important determinant of the outcome; therefore, for this review, we analyzed 2 databases: (1) clinical trials registered with ClinicalTrials.gov and (2) the literature on PT in PubMed, which shows a steady increase in the number of publications. Most studies in PT registered with ClinicalTrials.gov with results available are nonrandomized early phase studies with a relatively small number of patients enrolled. From the larger database of nonrandomized trials, we listed adverse events in specific organs/sites among patients with cancer who are treated with photons and protons to identify critical issues. The present data demonstrate dosimetric advantages of PT with favorable toxicity profiles and form the basis for comparative randomized prospective trials. A comparative analysis of 3 recently completed randomized trials for normal tissue toxicities suggests that for early stage non-small cell lung cancer, no meaningful comparison could be made between stereotactic body RT and stereotactic body PT due to low accrual (NCT01511081). In addition, for locally advanced non-small cell lung cancer, a comparison of intensity modulated RTwith passive scattering PT (now largely replaced by spot-scanned intensity modulated PT), PT did not provide any benefit in normal tissue toxicity or locoregional failure over photon therapy. Finally, for locally advanced esophageal cancer, proton beam therapy provided a lower total toxicity burden but did not improve progression-free survival and quality of life (NCT01512589). The purpose of this review is to inform the limitations of current trials looking at protons and photons, considering that advances in technology, physics, and biology are a continuum, and to advocate for future trials geared toward accurate precision RT that need to be viewed as an iterative process in a defined path toward delivering optimal radiation treatment. A foundational understanding of the radiobiologic differences between protons and photons in tumor and normal tissue responses is fundamental to, and necessary for, determining the suitability of a given type of biologically optimized RT to a patient or cohort.

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.

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.

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.

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.

Impact of range uncertainty on clinical distributions of linear energy transfer and biological effectiveness in proton therapy

PURPOSE

Increased radiation response after proton irradiation, such as late radiation-induced toxicity, is determined by high dose and elevated linear energy transfer (LET). Steep dose-averaged LET (LET_d ) gradients and elevated LET_d occur at the end of proton range and might be particularly sensitive to uncertainties in range prediction. Therefore, this study quantified LET_d distributions and the impact of range uncertainty in robust dose-optimized proton treatment plans and assessed the biological effect in normal tissues and tumors of patients.

METHODS

For each of six cancer patients (two brain, head-and-neck, and prostate), two nominal treatment plans were robustly dose optimized using single- and multi-field optimization, respectively. For each plan, two additional scenarios with ±3.5% range deviation relative to the nominal plan were derived by global rescaling of stopping-power ratios. Dose and LET_d distributions were calculated for each scenario using the beam parameters of the corresponding nominal plan. The variability in relative biological effectiveness (RBE) and probability of late radiation-induced brain toxicity (P_IC ) was assessed.

RESULTS

The optimization technique (single- vs multi-field) had a negligible impact on the LET_d distributions in the clinical target volume (CTV) and in most organs at risk (OARs). LET_d distributions in the CTV were rather homogeneous with arithmetic mean of LET_d below 3.2 keV/µm and robust against range deviations. The RBE variability within the CTV induced by range uncertainty was small (≤0.05, 95% confidence interval). In OARs, LET_d hotspots (>7 keV/µm) occurred and LET_d distributions were inhomogeneous and sensitive to range deviations. LET_d hotspots and the impact of range deviations were most prominent in OARs of brain tumor patients which translated in RBE values exceeding 1.1 in all brain OARs. The near-maximum predicted P_IC in healthy brain tissue of brain tumor patients was smaller than 5% and occurred adjacent to the CTV. Range deviations induced absolute differences in P_IC up to 1.2%.

CONCLUSIONS

Robust dose optimization generates LET_d distributions in the target volume robust against range deviations. The current findings support using a constant RBE within the CTV. The impact of range deviations on the considered probability of late radiation-induced toxicity in brain tissue was limited for robust dose-optimized treatment plans. Incorporation of LET_d in robust optimization frameworks may further reduce uncertainty related to the RBE-weighted dose estimation in normal tissues.

RBE for proton radiation therapy - a Nordic view in the international perspective

BACKGROUND

This paper presents an insight into the critical discussions and the current strategies of the Nordic countries for handling the variable proton relative biological effectiveness (RBE) as presented at The Nordic Collaborative Workshop for Particle Therapy that took place at the Skandion Clinic on 14th and 15th of November 2019.

MATERIAL AND METHODS

In the current clinical practice at the two proton centres in operation at the date, Skandion Clinic, and the Danish Centre for Particle Therapy, a constant proton RBE of 1.1 is applied. The potentially increased effectiveness at the end of the particle range is however considered at the stage of treatment planning at both places based on empirical observations and knowledge. More elaborated strategies to evaluate the plans and mitigate the problem are intensely investigated internationally as well at the two centres. They involve the calculation of the dose-averaged linear energy transfer (LET_d) values and the assessment of their distributions corroborated with the distribution of the dose and the location of the critical clinical structures.

RESULTS

Methods and tools for LET_d calculations are under different stages of development as well as models to account for the variation of the RBE with LET_d, dose per fraction, and type of tissue. The way they are currently used for evaluation and optimisation of the plans and their robustness are summarised. A critical but not exhaustive discussion of their potential future implementation in the clinical practice is also presented.

CONCLUSIONS

The need for collaboration between the clinical proton centres in establishing common platforms and perspectives for treatment planning evaluation and optimisation is highlighted as well as the need of close interaction with the research academic groups that could offer a complementary perspective and actively help developing methods and tools for clinical implementation of the more complex metrics for considering the variable effectiveness of the proton beams.

RBE variation in prostate carcinoma cells in active scanning proton beams: In-vitro measurements in comparison with phenomenological models

PURPOSE

In-vitro radiobiological studies are essential for modelling the relative biological effectiveness (RBE) in proton therapy. The purpose of this study was to experimentally determine the RBE values in proton beams along the beam path for human prostate carcinoma cells (Du-145). RBE-dose and RBE-LET_d (dose-averaged linear energy transfer) dependencies were investigated and three phenomenological RBE models, i.e. McNamara, Rørvik and Wilkens were benchmarked for this cell line.

METHODS

Cells were placed at multiple positions along the beam path, employing an in-house developed solid phantom. The experimental setup reflected the clinical prostate treatment scenario in terms of field size, depth, and required proton energies (127.2-180.1 MeV) and the physical doses from 0.5 to 6 Gy were delivered. The reference irradiation was performed with 200 kV X-ray beams. Respective (α/β) values were determined using the linear quadratic model and LET_d was derived from the treatment planning system at the exact location of cells.

RESULTS AND CONCLUSION

Independent of the cell survival level, all experimental RBE values were consistently higher in the target than the generic clinical RBE value of 1.1; with the lowest RBE value of 1.28 obtained at the beginning of the SOBP. A systematic RBE decrease with increasing dose was observed for the investigated dose range. The RBE values from all three applied models were considerably smaller than the experimental values. A clear increase of experimental RBE values with LET_d parameter suggests that proton LET must be taken into consideration for this low (α/β) tissue.

Cancer risk after breast proton therapy considering physiological and radiobiological uncertainties

BACKGROUND

The reduced normal tissue dose burden from protons can reduce the risk of second cancer for breast cancer patients. Breathing motion and the impact of variable relative biological effectiveness (RBE) are however concerns for proton dose distributions. This study aimed to quantify the impact of these factors on risk predictions from proton and photon therapy.

MATERIALS AND METHODS

Twelve patients were planned in free breathing with protons and photons to deliver 50 Gy (RBE) in 25 fractions (assuming RBE = 1.1 for protons) to the left breast. Second cancer risk was evaluated with several models for the lungs, contralateral breast, heart and esophagus as organs at risk (OARs). Plans were recalculated on CT-datasets acquired in extreme phases to account for breathing motion. Proton plans were also recalculated assuming variable RBE for a range of radiobiological parameters.

RESULTS

The OARs received substantially lower doses from protons compared to photons. The highest risks were for the lungs (average second cancer risks of 0.31% and 0.12% from photon and proton plans, respectively). The reduced risk with protons was maintained, even when breathing and/or RBE variation were taken into account. Furthermore, while the total risks from the photon plans were seen to increase with the integral dose, no such correlation was observed for the proton plans.

CONCLUSIONS

Protons have an advantage over the photons with respect to the induction of cancer. Uncertainties in physiological movements and radiobiological parameters affected the absolute risk estimates, but not the general trend of lower risk associated with proton therapy.

Technical Note: Integrating an open source Monte Carlo code "MCsquare" for clinical use in intensity-modulated proton therapy

PURPOSE

To commission an open source Monte Carlo (MC) dose engine, "MCsquare" for a synchrotron-based proton machine, integrate it into our in-house C++-based I/O user interface and our web-based software platform, expand its functionalities, and improve calculation efficiency for intensity-modulated proton therapy (IMPT).

METHODS

We commissioned MCsquare using a double Gaussian beam model based on in-air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread-out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++-based dose calculation code and web-based second check platform "DOSeCHECK." We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well-benchmarked GPU-accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)-related model-dependent biological dose calculation.

RESULTS

Differences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients' geometries using an inexpensive CPU workstation (Intel Xeon E5-2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min.

CONCLUSIONS

MCsquare was successfully commissioned for a synchrotron-based proton beam therapy delivery system and integrated into our web-based second check platform. After adopting CT resampling and implementing LET model-dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo-based and LET-guided robust optimization in IMPT, which will be done in the future studies.

Hybrid 3D analytical linear energy transfer calculation algorithm based on precalculated data from Monte Carlo simulations

PURPOSE

The dose-averaged linear energy transfer (LET_d ) for intensity-modulated proton therapy (IMPT) calculated by one-dimensional (1D) analytical models deviates from more accurate but time-consuming Monte Carlo (MC) simulations. We developed a fast hybrid three-dimensional (3D) analytical LET_d calculation that is more accurate than 1D analytical model.

METHODS

We used the Geant4 MC code to generate 3D LET_d distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LET_d lateral profiles at various depths to the MC simulation. The 3D LET_d calculation kernel was a lookup table of these fitted coefficients, and LET_d was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LET_d distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank-sum test.

RESULTS

The passing rate of 3D Gamma analysis comparing LET_d distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LET_d simultaneously using an Intel Xeon E5-2680 2.50 GHz workstation was approximately 2.5 min.

CONCLUSIONS

Our new method significantly improved the LET_d calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU-based fast MC code.

The impact of proton LET/RBE modeling and robustness analysis on base-of-skull and pediatric craniopharyngioma proton plans relative to VMAT

Purpose: Pediatric craniopharyngioma, adult base-of-skull sarcoma and chordoma cases are all regarded as priority candidates for proton therapy. In this study, a dosimetric comparison between volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) was first performed. We then investigated the impact of physical and biological uncertainties. We assessed whether IMPT plans remained dosimetrically superior when such uncertainty estimates were considered, especially with regards to sparing organs at risk (OARs).Methodology: We studied 10 cases: four chondrosarcoma, two chordoma and four pediatric craniopharyngioma. VMAT and IMPT plans were created according to modality-specific protocols. For IMPT, we considered (i) variable RBE modeling using the McNamara model for different values of (α/β)x, and (ii) robustness analysis with ±3 mm set-up and 3.5% range uncertainties.Results: When comparing the VMAT and IMPT plans, the dosimetric advantages of IMPT were clear: IMPT led to reduced integral dose and, typically, improved CTV coverage given our OAR constraints. When physical robustness analysis was performed for IMPT, some uncertainty scenarios worsened the CTV coverage but not usually beyond that achieved by VMAT. Certain scenarios caused OAR constraints to be exceeded, particularly for the brainstem and optical chiasm. However, variable RBE modeling predicted even more substantial hotspots, especially for low values of (α/β)x. Variable RBE modeling often prompted dose constraints to be exceeded for critical structures.Conclusion: For base-of-skull and pediatric craniopharyngioma cases, both physical and biological robustness analyses should be considered for IMPT: these analyses can substantially affect the sparing of OARs and comparisons against VMAT. All proton RBE modeling is subject to high levels of uncertainty, but the clinical community should remain cognizant possible RBE effects. Careful clinical and imaging follow-up, plus further research on end-of-range RBE mitigation strategies such as LET optimization, should be prioritized for these cohorts of proton patients.

Phantom design and dosimetric characterization for multiple simultaneous cell irradiations with active pencil beam scanning

A new phantom was designed for in vitro studies on cell lines in horizontal particle beams. The phantom enables simultaneous irradiation at multiple positions along the beam path. The main purpose of this study was the detailed dosimetric characterization of the phantom which consists of various heterogeneous structures. The dosimetric measurements described here were performed under non-reference conditions. The experiment involved a CT scan of the phantom, dose calculations performed with the treatment planning system (TPS) RayStation employing both the Pencil Beam (PB) and Monte Carlo (MC) algorithms, and proton beam delivery. Two treatment plans reflecting the typical target location for head and neck cancer and prostate cancer treatment were created. Absorbed dose to water and dose homogeneity were experimentally assessed within the phantom along the Bragg curve with ionization chambers (ICs) and EBT3 films. LET_d distributions were obtained from the TPS. Measured depth dose distributions were in good agreement with the Monte Carlo-based TPS data. Absorbed dose calculated with the PB algorithm was 4% higher than the absorbed dose measured with ICs at the deepest measurement point along the spread-out Bragg peak. Results of experiments using melanoma (SKMel) cell line are also presented. The study suggested a pronounced correlation between the relative biological effectiveness (RBE) and LET_d, where higher LET_d leads to elevated cell death and cell inactivation. Obtained RBE values ranged from 1.4 to 1.8 at the survival level of 10% (RBE₁₀). It is concluded that dosimetric characterization of a phantom before its use for RBE experiments is essential, since a high dosimetric accuracy contributes to reliable RBE data and allows for a clearer differentiation between physical and biological uncertainties.

Stereotactic body radiation therapy with optional focal lesion ablative microboost in prostate cancer: Topical review and multicenter consensus

Stereotactic body radiotherapy (SBRT) for prostate cancer (PCa) is gaining interest by the recent publication of the first phase III trials on prostate SBRT and the promising results of many other phase II trials. Before long term results became available, the major concern for implementing SBRT in PCa in daily clinical practice was the potential risk of late genitourinary (GU) and gastrointestinal (GI) toxicity. A number of recently published trials, including late outcome and toxicity data, contributed to the growing evidence for implementation of SBRT for PCa in daily clinical practice. However, there exists substantial variability in delivering SBRT for PCa. The aim of this topical review is to present a number of prospective trials and retrospective analyses of SBRT in the treatment of PCa. We focus on the treatment strategies and techniques used in these trials. In addition, recent literature on a simultaneous integrated boost to the tumor lesion, which could create an additional value in the SBRT treatment of PCa, was described. Furthermore, we discuss the multicenter consensus of the FLAME consortium on SBRT for PCa with a focal boost to the macroscopic intraprostatic tumor nodule(s).

Fixed- versus Variable-RBE Computations for Intensity Modulated Proton Therapy

Purpose

To evaluate how using models of proton therapy that incorporate variable relative biological effectiveness (RBE) versus the current practice of using a fixed RBE of 1.1 affects dosimetric indices on treatment plans for large cohorts of patients treated with intensity modulated proton therapy (IMPT).

Methods and Materials

Treatment plans for 4 groups of patients who received IMPT for brain, head-and-neck, thoracic, or prostate cancer were selected. Dose distributions were recalculated in 4 ways: 1 with a fast-dose Monte Carlo calculator with fixed RBE and 3 with RBE calculated to 3 different models—McNamara, Wedenberg, and repair-misrepair-fixation. Differences among dosimetric indices (D02, D50, D98, and mean dose) for target volumes and organs at risk (OARs) on each plan were compared between the fixed-RBE and variable-RBE calculations.

Results

In analyses of all target volumes, for which the main concern is underprediction or RBE less than 1.1, none of the models predicted an RBE less than 1.05 for any of the cohorts. For OARs, the 2 models based on linear energy transfer, McNamara and Wedenberg, systematically predicted RBE >1.1 for most structures. For the mean dose of 25% of the plans for 2 OARs, they predict RBE equal to or larger than 1.4, 1.3, 1.3, and 1.2 for brain, head-and-neck, thorax, and prostate, respectively. Systematically lower increases in RBE are predicted by repair-misrepair-fixation, with a few cases (eg, femur) in which the RBE is less than 1.1 for all plans.

Conclusions

The variable-RBE models predict increased doses to various OARs, suggesting that strategies to reduce high-dose linear energy transfer in critical structures should be developed to minimize possible toxicity associated with IMPT.

Advanced Treatment Planning

Treatment planning for protons and heavier ions is adapting technologies originally developed for photon dose optimization, but also has to meet its particular challenges. Since the quality of the applied dose is more sensitive to geometric uncertainties, treatment plan robust optimization has a much more prominent role in particle therapy. This has led to specific planning tools, approaches, and research into new formulations of the robust optimization problems. Tools for solution space navigation and automatic planning are also being adapted to particle therapy. These challenges become even greater when detailed models of relative biological effectiveness (RBE) are included into dose optimization, as is required for heavier ions.

Introducing Proton Track-End Objectives in Intensity Modulated Proton Therapy Optimization to Reduce Linear Energy Transfer and Relative Biological Effectiveness in Critical Structures

PURPOSE

We propose the use of proton track-end objectives in intensity modulated proton therapy (IMPT) optimization to reduce the linear energy transfer (LET) and the relative biological effectiveness (RBE) in critical structures.

METHODS AND MATERIALS

IMPT plans were generated for 3 intracranial patient cases (1.8 Gy (RBE) in 30 fractions) and 3 head-and-neck patient cases (2 Gy (RBE) in 35 fractions), assuming a constant RBE of 1.1. Two plans were generated for each patient: (1) physical dose objectives only (DOSEopt) and (2) same dose objectives as the DOSEopt plan, with additional proton track-end objectives (TEopt). The track-end objectives penalized protons stopping in the risk volume of choice. Dose evaluations were made using a RBE of 1.1 and the LET-dependent Wedenberg RBE model, together with estimates of normal tissue complication probabilities (NTCPs). In addition, the distributions of proton track-ends and dose-average LET (LET_d) were analyzed.

RESULTS

The TEopt plans reduced the mean LET_d in the critical structures studied by an average of 37% and increased the mean LET_d in the primary clinical target volume (CTV) by an average of 23%. This was achieved through a redistribution of the proton track-ends, concurrently keeping the physical dose distribution virtually unchanged compared to the DOSEopt plans. This resulted in substantial RBE-weighted dose (D_RBE) reductions, allowing the TEopt plans to meet all clinical goals for both RBE models and reduce the NTCPs by 0 to 19 percentage points compared to the DOSEopt plans, assuming the Wedenberg RBE model. The DOSEopt plans met all clinical goals assuming a RBE of 1.1 but failed 10 of 19 normal tissue goals assuming the Wedenberg RBE model.

CONCLUSIONS

Proton track-end objectives allow for LET_d reductions in critical structures without compromising the physical target dose. This approach permits the lowering of D_RBE and NTCP in critical structures, independent of the variable RBE model used, and it could be introduced in clinical practice without changing current protocols based on the constant RBE of 1.1.

Impact of potentially variable RBE in liver proton therapy

Currently, the relative biological effectiveness (RBE) is assumed to be constant with a value of 1.1 in proton therapy. Although trends of RBE variations are well known, absolute values in patients are associated with considerable uncertainties. This study aims to evaluate the impact of a variable proton RBE in proton therapy liver trials using different fractionation schemes. Sixteen liver cancer cases were evaluated assuming two clinical schedules of 40 Gy/5 fractions and 58.05 Gy/15 fractions. The linear energy transfer (LET) and physical dose distribution in patients were simulated using Monte Carlo. The variable RBE distribution was calculated using a phenomenological model, considering the influence of the LET, fraction size and α/β value. Further, models to predict normal tissue complication probability (NTCP) and tumor control probability (TCP) were used to investigate potential RBE effects on outcome predictions. Applying the variable RBE model to the 5 and 15 fractions schedules results in an increase in mean fraction-size equivalent dose (FED) to the normal liver of 5.0% and 9.6% respectively. For patients with a mean FED to the normal liver larger than 29.8 Gy, this results in a non-negligible increase in the predicted NTCP of the normal liver averaging 11.6%, ranging from 2.7% to 25.6%. On the other hand, decrease in TCP was less than 5% for both fractionation regimens for all patients when assuming a variable RBE instead of constant. Consequently, the difference in TCP between the two fractionation schedules did not change significantly assuming a variable RBE while the impact on the NTCP difference was highly case specific. In addition, both the NTCP and TCP decrease with increasing α/β value for both fractionation schemes, with the decreases being more pronounced when using a variable RBE compared to using RBE  =  1.1. Assuming a constant RBE of 1.1 most likely overestimates the therapeutic ratio in proton therapy for liver cancer, predominantly due to underestimation of the RBE-weighted dose to the normal liver. The impact of applying a variable RBE (as compared to RBE  =  1.1) on the NTCP difference of the two fractionation regimens is case dependent. A variable RBE results in a slight increase in TCP difference. Variations in patient radiosensitivity increase when using a variable RBE.

Proton Relative Biological Effectiveness - Uncertainties and Opportunities

Proton therapy treatments are prescribed using a biological effectiveness relative to photon therapy of 1.1, that is, proton beams are considered to be 10% more biologically effective. Debate is ongoing as to whether this practice needs to be revised. This short review summarizes current knowledge on relative biological effectiveness variations and uncertainties in vitro and in vivo. Clinical relevance is discussed and strategies toward biologically guided treatment planning are presented.

Exploration and application of phenomenological RBE models for proton therapy

The relative biological effectiveness (RBE) of protons varies with multiple physical and biological factors. Phenomenological RBE models have been developed to include such factors in the estimation of a variable RBE, in contrast to the clinically applied constant RBE of 1.1. In this study, eleven published phenomenological RBE models and two plan-based models were explored and applied to simulated patient cases. All models were analysed with respect to the distribution and range of linear energy transfer (LET) and reference radiation fractionation sensitivity ((α/β) _x ) of their respective experimental databases. Proton therapy plans for a spread-out Bragg peak in water and three patient cases (prostate adenocarcinoma, pituitary adenoma and thoracic sarcoma) were optimised using an RBE of 1.1 in the Eclipse^™ treatment planning system prior to recalculation and modelling in the FLUKA Monte Carlo code. Model estimated dose-volume parameters for the planning target volumes (PTVs) and organs at risk (OAR) were compared. The experimental in vitro databases for the various models differed greatly in the range of (α/β) _x values and dose-averaged LET (LET_d). There were significant variations between the model estimations, which arose from fundamental differences in the database definitions and model assumptions. The greatest variations appeared in organs with low (α/β) _x and high LET_d, e.g. biological doses given to late responding OARs located distal to the target in the treatment field. In general, the variation in maximum dose (D_2%) was larger than the variation in mean dose and other dose metrics, with D_2% of the left optic nerve ((α/β) _x   =  2.1 Gy) in the pituitary adenoma case showing the greatest discrepancies between models: 28-52 Gy(RBE), while D_2% for RBE_1.1 was 30 Gy(RBE). For all patient cases, the estimated mean RBE to the PTV was in the range 1.09-1.29 ((α/β) _x   =  1.5/3.1/10.6 Gy). There were considerable variations between the estimations of RBE and RBE-weighted doses from the different models. These variations were a consequence of fundamental differences in experimental databases, model assumptions and regression techniques. The results from the implementation of RBE models in dose planning studies should be evaluated in light of these deviations.

Gene expression profiling of breast cancer cell lines treated with proton and electron radiations

OBJECTIVE

Technological advances in radiation therapy are evolving with the use of hadrons, such as protons, indicated for tumors where conventional radiotherapy does not give significant advantages or for tumors located in sensitive regions, which need the maximum of dose-saving of the surrounding healthy tissues. The genomic response to conventional and non-conventional linear energy transfer exposure is a poor investigated topic and became an issue of radiobiological interest. The aim of this work was to analyze and compare molecular responses in term of gene expression profiles, induced by electron and proton irradiation in breast cancer cell lines.

METHODS

We studied the gene expression profiling differences by cDNA microarray activated in response to electron and proton irradiation with different linear energy transfer values, among three breast cell lines (the tumorigenic MCF7 and MDA-MB-231 and the non-tumorigenic MCF10A), exposed to the same sublethal dose of 9 Gy.

RESULTS

Gene expression profiling pathway analyses showed the activation of different signaling and molecular networks in a cell line and radiation type-dependent manner. MCF10A and MDA-MB-231 cell lines were found to induce factors and pathways involved in the immunological process control.

CONCLUSION

Here, we describe in a detailed way the gene expression profiling and pathways activated after electron and proton irradiation in breast cancer cells. Summarizing, although specific pathways are activated in a radiation type-dependent manner, each cell line activates overall similar molecular networks in response to both these two types of ionizing radiation. Advances in knowledge: In the era of personalized medicine and breast cancer target-directed intervention, we trust that this study could drive radiation therapy towards personalized treatments, evaluating possible combined treatments, based on the molecular characterization.

Comparing photon and proton-based hypofractioned SBRT for prostate cancer accounting for robustness and realistic treatment deliverability

OBJECTIVE

To investigate whether photon or proton-based stereotactic body radiation therapy (SBRT is the preferred modality for high dose hypofractionation prostate cancer treatment. Achievable dose distributions were compared when uncertainties in target positioning and range uncertainties were appropriately accounted for.

METHODS

10 patients with prostate cancer previously treated at our institution (Montefiore Medical Center) with photon SBRT using volumetric modulated arc therapy (VMAT) were identified. MRI images fused to the treatment planning CT allowed for accurate target and organ at risk (OAR) delineation. The clinical target volume was defined as the prostate gland plus the proximal seminal vesicles. Critical OARs include the bladder wall, bowel, femoral heads, neurovascular bundle, penile bulb, rectal wall, urethra and urogenital diaphragm. Photon plan robustness was evaluated by simulating 2 mm isotropic setup variations. Comparative proton SBRT plans employing intensity modulated proton therapy (IMPT) were generated using robust optimization. Plan robustness was evaluated by simulating 2 mm setup variations and 3% or 1% Hounsfield unit (HU) calibration uncertainties.

RESULTS

Comparable maximum OAR doses are achievable between photon and proton SBRT, however, robust optimization results in higher maximum doses for proton SBRT. Rectal maximum doses are significantly higher for Robust proton SBRT with 1% HU uncertainty compared to photon SBRT (p = 0.03), whereas maximum doses were comparable for bladder wall (p = 0.43), urethra (p = 0.82) and urogenital diaphragm (p = 0.50). Mean doses to bladder and rectal wall are lower for proton SBRT, but higher for neurovascular bundle, urethra and urogenital diaphragm due to increased lateral scatter. Similar target conformality is achieved, albeit with slightly larger treated volume ratios for proton SBRT, >1.4 compared to 1.2 for photon SBRT.

CONCLUSION

Similar treatment plans can be generated with IMPT compared to VMAT in terms of target coverage, target conformality, and OAR sparing when range and HU uncertainties are neglected. However, when accounting for these uncertainties during robust optimization, VMAT outperforms IMPT in terms of achievable target conformity and OAR sparing. Advances in knowledge: Comparison between achievable dose distributions using modern, robust optimization of IMPT for high dose per fraction SBRT regimens for the prostate has not been previously investigated.

RBE and related modeling in carbon-ion therapy

Carbon ion therapy is a promising evolving modality in radiotherapy to treat tumors that are radioresistant against photon treatments. As carbon ions are more effective in normal and tumor tissue, the relative biological effectiveness (RBE) has to be calculated by bio-mathematical models and has to be considered in the dose prescription. This review (i) introduces the concept of the RBE and its most important determinants, (ii) describes the physical and biological causes of the increased RBE for carbon ions, (iii) summarizes available RBE measurements in vitro and in vivo, and (iv) describes the concepts of the clinically applied RBE models (mixed beam model, local effect model, and microdosimetric-kinetic model), and (v) the way they are introduced into clinical application as well as (vi) their status of experimental and clinical validation, and finally (vii) summarizes the current status of the use of the RBE concept in carbon ion therapy and points out clinically relevant conclusions as well as open questions. The RBE concept has proven to be a valuable concept for dose prescription in carbon ion radiotherapy, however, different centers use different RBE models and therefore care has to be taken when transferring results from one center to another. Experimental studies significantly improve the understanding of the dependencies and limitations of RBE models in clinical application. For the future, further studies investigating quantitatively the differential effects between normal tissues and tumors are needed accompanied by clinical studies on effectiveness and toxicity.

The influence of breathing motion and a variable relative biological effectiveness in proton therapy of left-sided breast cancer

BACKGROUND

Proton breast radiotherapy has been suggested to improve target coverage as well as reduce cardiopulmonary and integral dose compared with photon therapy. This study aims to assess this potential when accounting for breathing motion and a variable relative biological effectiveness (RBE).

METHODS

Photon and robustly optimized proton plans were generated to deliver 50 Gy (RBE) in 25 fractions (RBE = 1.1) to the CTV (whole left breast) for 12 patients. The plan evaluation was performed using the constant RBE and a variable RBE model. Robustness against breathing motion, setup, range and RBE uncertainties was analyzed using CT data obtained at free-breathing, breath-hold-at-inhalation and breath-hold-at-exhalation.

RESULTS

All photon and proton plans (RBE = 1.1) met the clinical goals. The variable RBE model predicted an average RBE of 1.18 for the CTVs (range 1.14-1.21) and even higher RBEs in organs at risk (OARs). However, the dosimetric impact of this latter aspect was minor due to low OAR doses. The normal tissue complication probability (NTCP) for the lungs was low for all patients (<1%), and similar for photons and protons. The proton plans were generally considered robust for all patients. However, in the most extreme scenarios, the lowest dose received by 98% of the CTV dropped from 96 to 99% of the prescribed dose to around 92-94% for both protons and photons. Including RBE uncertainties in the robustness analysis resulted in substantially higher worst-case OAR doses.

CONCLUSIONS

Breathing motion seems to have a minor effect on the plan quality for breast cancer. The variable RBE might impact the potential benefit of protons, but could probably be neglected in most cases where the physical OAR doses are low. However, to be able to identify outlier cases at risk for high OAR doses, the biological evaluation of proton plans taking into account the variable RBE is recommended.

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

BACKGROUND

The increased linear energy transfer (LET) at the end of the Bragg peak causes concern for an elevated and spatially varying relative biological effectiveness (RBE) of proton therapy (PT), often in or close to dose-limiting normal tissues. In this study, we investigated dose-averaged LET (LET_d) distributions for spot scanning PT of prostate cancer patients using different beam angle configurations. In addition, we derived RBE-weighted (RBE_w) dose distributions and related normal tissue complication probabilities (NTCPs) for the rectum and bladder.

MATERIAL AND METHODS

A total of 21 spot scanning proton plans were created for each of six patients using a prescription dose of 78 Gy(RBE_1.1), with each plan using two 'mirrored' beams with gantry angles from 110°/250° to 70°/290°, in steps of 2°. Physical dose and LET_d distributions were calculated as well as RBE_w dose distributions using either RBE = 1.1 or three different variable RBE models. The resulting biological dose distributions were used as input to NTCP models for the rectum and bladder.

RESULTS

For anterior oblique (AO) configurations, the rectum LET_d volume and RBE_w dose increased with increasing angles off the lateral opposing axis, with the RBE_w rectum dose being higher than for all posterior oblique (PO) configurations. For PO configurations, the corresponding trend was seen for the bladder. Using variable RBE models, the rectum NTCPs were highest for the AO configurations with up to 3% for the 80°/280° configuration while the bladder NTCPs were highest for the PO configurations with up to 32% for the 100°/260°. The rectum D_1cm³ constraint was fulfilled for most patients/configurations when using uniform RBE but not for any patient/configuration with variable RBE models.

CONCLUSIONS

Compared to using constant RBE, the variable RBE models predicted increased biological doses to the rectum, bladder and prostate, which in turn lead to substantially higher estimated rectum and bladder NTCPs.

Robust intensity-modulated proton therapy to reduce high linear energy transfer in organs at risk

PURPOSE

We propose a robust treatment planning model that simultaneously considers proton range and patient setup uncertainties and reduces high linear energy transfer (LET) exposure in organs at risk (OARs) to minimize the relative biological effectiveness (RBE) dose in OARs for intensity-modulated proton therapy (IMPT). Our method could potentially reduce the unwanted damage to OARs.

METHODS

We retrospectively generated plans for 10 patients including two prostate, four head and neck, and four lung cancer patients. The "worst-case robust optimization" model was applied. One additional term as a "biological surrogate (BS)" of OARs due to the high LET-related biological effects was added in the objective function. The biological surrogate was defined as the sum of the physical dose and extra biological effects caused by the dose-averaged LET. We generated nine uncertainty scenarios that considered proton range and patient setup uncertainty. Corresponding to each uncertainty scenario, LET was obtained by a fast LET calculation method developed in-house and based on Monte Carlo simulations. In each optimization iteration, the model used the worst-case BS among all scenarios and then penalized overly high BS to organs. The model was solved by an efficient algorithm (limited-memory Broyden-Fletcher-Goldfarb-Shanno) in a parallel computing environment. Our new model was benchmarked with the conventional robust planning model without considering BS. Dose-volume histograms (DVHs) of the dose assuming a fixed RBE of 1.1 and BS for tumor and organs under nominal and uncertainty scenarios were compared to assess the plan quality between the two methods.

RESULTS

For the 10 cases, our model outperformed the conventional robust model in avoidance of high LET in OARs. At the same time, our method could achieve dose distributions and plan robustness of tumors assuming a fixed RBE of 1.1 almost the same as those of the conventional robust model.

CONCLUSIONS

Explicitly considering LET in IMPT robust treatment planning can reduce the high LET to OARs and minimize the possible toxicity of high RBE dose to OARs without sacrificing plan quality. We believe this will allow one to design and deliver safer proton therapy.