Mixed Effect Modeling of Dose and Linear Energy Transfer Correlations With Brain Image Changes After Intensity Modulated Proton Therapy for Skull Base Head and Neck Cancer

Contrast-enhancing Lesions Induced by Central Nervous System-directed Intensity Modulated Proton Therapy: Distribution Patterns, Kinetics, Risk Factors, and Outcomes

PURPOSE

Patients treated with intensity modulated proton therapy (IMPT) may develop intracranial radiation-induced contrast enhancement (RICE). The incidence, distribution, kinetics, predisposing factors, linear energy of transfer (LET) associations, and clinical outcomes of RICE are inadequately defined.

METHODS AND MATERIALS

The incidence and characteristics of RICE were analyzed in brain tumor patients treated with at least 50 Gy IMPT, 1-year follow-up, and 3 posttreatment magnetic resonance imaging scans. RICE distribution was classified as overlapping with tumor/tumor bed (A), inside or marginal to high-dose region (≤5 mm from the 95% isodose line [IDL]) (B), or distant (>5 mm from 95% IDL) (C). Voxelized dose and LET were computed for each RICE lesion. Risk factors were assessed using binary logistic regression.

RESULTS

With a median follow-up of 3 years, 73 RICE lesions were observed in 36 of 137 patients (26%), appearing at a median of 11 months post-IMPT. Group-wise distribution demonstrated 10 (28%), 24 (67%), and 2 (5%) lesions in groups A, B, and C, respectively. Ten (7% overall) patients were symptomatic. After a median of 5 months, most lesions (78%) improved or resolved. Median dose and LET in RICE lesions were 50.4 Gy and 3.1 keV/µm. RICE risk increased with age as a continuous variable (0.4%/year), age ≥18 years (odds ratio [OR], 5.4), tumor volume >30 cc (OR, 2.8), and 95% IDL overlapping the ventricles (OR, 3.8).

CONCLUSIONS

RICE is a common radiographic finding after IMPT, primarily occurring in the periventricular and high-dose regions, but is infrequently symptomatic. Periventricular-sparing treatment may be considered to minimize the risk of RICE.

Systematic review of MRI alterations in the brain following proton and photon radiation therapy: Towards a uniform European Particle Therapy Network (EPTN) definition

Magnetic resonance imaging (MRI) often demonstrates alterations following cranial radiotherapy (RT), which may result in clinical symptoms and diagnostic uncertainty, and thus potentially impact treatment decisions. The potential differences in MRI alterations after proton and photon RT, has raised concerns regarding the relative biological effectiveness of proton therapy. To provide an overview of MRI alterations in the brain post-RT and to explore differences between photon and proton RT, a systematic review adhering to the PRISMA guidelines was conducted, focusing on the assessment methods and definitions across studies. A systematic search of three electronic databases was performed using the concepts 'normo-fractionated radiotherapy ', 'MRI alterations' and 'brain, skull base or head and neck tumours in adult and paediatric populations'. Data extraction and quality assessment was performed on articles meeting the predefined criteria by two independent reviewers. Out of 5887 screened studies, 94 met the inclusion criteria. These studies were categorized based on confinement of the MRI alterations to temporal lobe, brainstem, or across the entire brain. Additional subclassification was performed based on MRI sequences evaluated or by the nature of the alterations, with pseudoprogression generally reserved for glioma patients. While many papers exist on MRI alterations in the brain after RT, this review highlights significant inconsistencies in the terminology and definitions, limiting the comparability of findings across studies. Our results highlight the need for and facilitate the development of a standardized framework for describing MRI alterations after RT.

Mixed effect model confirms increased risk of image changes with increasing linear energy transfer in proton therapy of gliomas

BACKGROUND AND PURPOSE

Radiation induced image changes (IC) on MRI have been observed after proton therapy for brain tumours. This study aims to create predictive models, with and without taking into account patient variation, based on dose, linear energy transfer (LET) and periventricular zone (PVZ) in a national cohort of patients with glioma treated with pencil beam scanning (PBS).

MATERIALS AND METHODS

A cohort of 87 consecutive patients with oligodendroglioma or astrocytoma (WHO grade 2-4) treated with PBS from January 2019 to December 2021 was included. All patients were treated with three to four beams. Monte Carlo calculations of dose and LET were performed for all treatment plans. Lesion weighted as well as mixed effect logistic regression models were developed to predict IC in a voxel.

RESULTS

12 patients (14 %) developed ICs on the follow-up MR-scans. Mixed effect modelling accounting for interpatient variation was justified by the non-negligible inter class correlation coefficient (ICC = 0.33). The two approaches identified similar model features and marginal improvement in model performance was found, when increasing model parameters from two (AUC = 0.92/0.94) to three (AUC = 0.93/0.95) parameters. Univariate analysis showed that patients treated with narrow beam configurations had an increased incidence of IC (p = 0.01).

CONCLUSION

14% of patients developed IC following PT. Lesion-weighted and mixed effect models resulted in similar model performance confirming increased risk of IC with increasing LET. The beam arrangement seems to influence the risk of IC and needs further investigation.

Enabling clinical use of linear energy transfer in proton therapy for head and neck cancer - A review of implications for treatment planning and adverse events study

Proton therapy offers significant advantages due to its unique physical and biological properties, particularly the Bragg peak, enabling precise dose delivery to tumors while sparing healthy tissues. However, the clinical implementation is challenged by the oversimplification of the relative biological effectiveness (RBE) as a fixed value of 1.1, which does not account for the complex interplay between dose, linear energy transfer (LET), and biological endpoints. Lack of heterogeneity control or the understanding of the complex interplay may result in unexpected adverse events and suboptimal patient outcomes. On the other hand, expanding our knowledge of variable tumor RBE and LET optimization may provide a better management strategy for radioresistant tumors. This review examines recent advancements in LET calculation methods, including analytical models and Monte Carlo simulations. The integration of LET into plan evaluation is assessed to enhance plan quality control. LET-guided robust optimization demonstrates promise in minimizing high-LET exposure to organs at risk, thereby reducing the risk of adverse events. Dosimetric seed spot analysis is discussed to show its importance in revealing the true LET-related effect upon the adverse event initialization by finding the lesion origins and eliminating the confounding factors from the biological processes. Dose-LET volume histograms (DLVH) are discussed as effective tools for correlating physical dose and LET with clinical outcomes, enabling the derivation of clinically relevant dose-LET volume constraints without reliance on uncertain RBE models. Based on DLVH, the dose-LET volume constraints (DLVC)-guided robust optimization is introduced to upgrade conventional dose-volume constraints-based robust optimization, which optimizes the joint distribution of dose and LET simultaneously. In conclusion, translating the advances in LET-related research into clinical practice necessitates a better understanding of the LET-related biological mechanisms and the development of clinically relevant LET-related volume constraints directly derived from the clinical outcomes. Future research is needed to refine these models and conduct prospective trials to assess the clinical benefits of LET-guided optimization on patient outcomes.

The proton RBE and the distal edge effect for acute and late normal tissue damage in vivo

BACKGROUND AND PURPOSE

In proton therapy, a relative biological effectiveness (RBE) of 1.1 is used toreach an isoeffective biological response between photon and proton doses. However, the RBE varies with biological endpoints and linear energy transfer (LET), two key parameters in radiotherapy. Few in vivo studies have investigated the increasing RBE with increasing LET. This study aims to test the hypothesis that the RBE varies between endpoints and has a distal edge effect in vivo.

MATERIALS AND METHODS

Unanesthetized micewere restrainedin jigs where their right hind legs were irradiated with a single dose of protons at the center (LET, all = 5.3 keV/μm) and distal edge (LET, all = 7.6 keV/μm) of a spread-out Bragg peak (SOBP). 6 MV photons were used as reference. The acute damage and skin toxicity were scored daily until day 30, and the late damage was evaluated using a joint contracture assay for one year after treatment.

RESULTS

An acute damage RBE of 1.06 ± 0.02(1.02-1.10) and late damage RBE of 1.16 ± 0.08(1.00-1.32) were found, displaying an enhanced RBE for late damage in the center SOBP. The distal edge RBE for acute and late damage was 1.15 ± 0.02(1.10-1.19) and 1.26 ± 0.09(1.07-1.43), showing a similar center-to-distal edge RBE enhancement of 8 % and 9 % for acute and late damage.

CONCLUSION

The findings demonstrate an increased RBE for late damage than acute damage and the distal edge effect is evident with increased RBE at the distal end of the proton SOBP in vivo.

The LET enhancement of energy-specific collimation in pencil beam scanning proton therapy

PURPOSE

To computationally characterize the LET distribution during dynamic collimation in PBS and quantify its impact on the resultant dose distribution.

METHODS

Monte Carlo simulations using Geant4 were used to model the production of low-energy proton scatter produced in the collimating components of a novel PBS collimator. Custom spectral tallies were created to quantify the energy, track- and dose-averaged LET resulting from individual beamlet and composite fields simulated from a model of the IBA dedicated nozzle system. The composite dose distributions were optimized to achieve a uniform physical dose coverage of a cubical and pyramidal target, and the resulting dose-average LET distributions were calculated for uncollimated and collimated PBS deliveries and used to generate RBE-weighted dose distributions.

RESULTS

For collimated beamlets, the scattered proton energy fluence is strongly dependent on collimator position relative to the central axis of the beamlet. When delivering a uniform profile, the distribution of dose-average LET was nearly identical within the target and increased between 1 and2 keV / μ m $2 \,{\rm keV}/\mathrm{\umu }\mathrm{m}$ within 10 mm surrounding the target. Dynamic collimation resulted in larger dose-average LET changes: increasing the dose-average LET between 1 and3 keV / μ m $3 \,{\rm keV}/\mathrm{\umu }\mathrm{m}$ within 10 mm of a pyramidal target while reducing the dose-average LET outside this margin by as much as10 keV / μ m $10 \,{\rm keV}/\mathrm{\umu }\mathrm{m}$ . Biological dose distributions are improved with energy-specific collimation in reducing the lateral penumbra.

CONCLUSION

The presence of energy-specific collimation in PBS can lead to dose-average LET changes relative to an uncollimated delivery. In some clinical situations, the placement and application of energy-specific collimation may require additional planning considerations based on its reduction to the lateral penumbra and increase in high-dose conformity. Future applications may embody these unique dosimetric characteristics to redirect high-LET portions of a collimated proton beamlet from healthy tissues while enhancing the dose-average LET distribution within target.

Linear approximation of variable relative biological effectiveness models for proton therapy

The McNamara (MCN) and Wedenberg (WED) RBE weighted dose (DRBE), dose and dose-weighted average LET (LETd) were calculated in twenty brain cancer patients. A linear approximation was made for each RBE model to give best agreement to clinically relevant dosimetric parameters. Additional evaluations were done on twenty head and neck and twenty breast cancer patients.The R2 of the fits was ≥0.94 and ≥0.91 for MCN and WED respectively for α/β values ≥1.0 Gy. The graphs derived in this work can be used to convert RBE-LET slopes derived from clinical data to α/β values in the MCN or WED models.

Variable-RBE-induced NTCP predictions for various side-effects following proton therapy for brain tumors - Identification of high-risk patients and risk mitigation

BACKGROUND AND PURPOSE

Disregarding the increase of relative biological effectiveness (RBE) may raise the risk of acute and late adverse events after proton beam therapy (PBT). This study aims to explore the relationship between variable RBE (above 1.1)-induced normal tissue complication probabilities (NTCP) and patient-specific factors, identify patients at high risk of RBE-induced NTCP increase, and assess risk mitigation by incorporating RBE variability into treatment planning.

MATERIALS AND METHODS

We retrospectively analyzed 105 primary brain tumor patients treated with PBT (RBE = 1.1). We calculated differences in estimated NTCP (ΔNTCP) using a variable RBE-weighted dose (DRBE, Wedenberg model) and a constant RBE-weighted dose (DRBE=1.1), across 16 NTCP models. These differences were correlated with patient-specific characteristics. Based on ΔNTCP, patients were classified as high risk (32 %) or low risk (68 %) for adverse events due to RBE-induced NTCP. This classification was compared with alternative classifications based on (a) relevant patient-specific characteristics, (b) DRBE=1.1, and (c) the difference between DRBE and DRBE=1.1 (ΔD), assessing the balanced accuracy. The potential to reduce RBE-induced NTCP through track-end and linear energy transfer (LET) optimization was evaluated in six example patients.

RESULTS

Using a variable RBE instead of a constant one resulted in NTCP increases (up to 32 percentage points). Variable-RBE-induced NTCP increases were strongly negatively correlated with the distance between the clinical target volume (CTV) and the organ at risk (OAR) for most side-effects, and positively correlated with CTV volume for certain side-effects. High increases were associated with (a) specific patient factors, particularly the proximity of the CTV to OARs, (b) DRBE=1.1, and (c) ΔD, with a balanced accuracy of 0.88, 0.94, and 0.86, respectively. Optimization of track-ends and LET considerably reduced NTCP values, achieving a mean reduction of 31 % for optimized OARs.

CONCLUSION

The risk of variable-RBE-induced NTCP strongly depends on patient-specific factors and the considered side-effect. A small distance between the tumor and OARs notably increases the risk. Integrating biologically-guided objectives into treatment planning can effectively mitigate the risk.

Radiation Toxicity in MDA5+ and PL7-Positive Dermatomyositis: Heightened Risk in Autoimmune Subtypes

Purpose

To increase awareness of peri-radiation therapy (RT) intervention that may unduly heighten the risk of toxicity in lung cancer patients and encourage molecular testing and pretreatment consultation with rheumatology for patients with active autoimmune conditions.

Materials and Methods

A 42-year-old male with an autoimmune disease was diagnosed with non-small cell lung cancer. He received 4 cycles of pemetrexed/cisplatin with proton therapy (PT) delivered halfway through for a bronchial stump positive margin. After completing the first cycle of adjuvant chemotherapy, he was given 61.6 Gy in 28 fractionations of PT. Before restarting chemotherapy, he experienced a dry cough and later shortness of breath (SOB), which resolved with an aggressive steroid taper. After completing his third cycle of cisplatin/pemetrexed, his SOB and cough worsened. He was admitted for an urgent bronchoscopy with debridement of the distal trachea and proximal left main bronchus. He received high-dose steroids again and another bronchoscopy, revealing a tracheoesophageal fistula. Rheumatology identified an MDA5+ and PL7-positive dermatomyositis subtype at this time, known to be associated with rare ulcerative symptoms.

Results

A rare MDA5+ and PL7-positive dermatomyositis subtype, discovered post treatment, most likely contributed to SOB and cough following chemotherapy and PT, resulting in bronchoscopy of the irradiated field. A combination of these factors may have contributed to the tracheoesophageal fistula.

Conclusion

Patients with autoimmune disease should be carefully evaluated for rare underlying subtypes that could pose a danger to treatment. Oncologists should continue to be vigilant about underlying genetic predisposing factors that lead to exacerbated toxicity. Immunosuppressive agents given with RT may be considered for patients with autoimmune disease. Avoidance of biopsy, tissue manipulation, debridement, or any form of soft-tissue or hard-tissue violation needs to be discussed across the multidisciplinary spectrum to avoid nonhealing lesions shortly after RT.

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy

Objective.This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.Approach.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n= 151). The best-performing model was identified and externally validated on patients from a different center (n= 107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model.Main results.We found NNs based solely on the planned dose distribution, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24 keV µm-1, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points.Significance.The ability of NNs to predict LETdbased solely on planned dose distributions suggests a viable alternative to compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

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

BACKGROUND

Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1.

PURPOSE

This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses.

METHODS

The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives.

RESULTS

In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp).

CONCLUSIONS

The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.

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.

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.

Linear energy transfer-inclusive models of brainstem necrosis following proton therapy of paediatric ependymoma

Background and Purpose

Radiation-induced brainstem necrosis after proton therapy is a severe toxicity with potential association to uncertainties in the proton relative biological effectiveness (RBE). A constant RBE of 1.1 is assumed clinically, but the RBE is known to vary with linear energy transfer (LET). LET-inclusive predictive models of toxicity may therefore be beneficial during proton treatment planning. Hence, we aimed to construct models describing the association between brainstem necrosis and LET in the brainstem.

Materials and methods

A matched case-control cohort (n = 28, 1:3 case-control ratio) of symptomatic brainstem necrosis was selected from 954 paediatric ependymoma brain tumour patients treated with passively scattered proton therapy. Dose-averaged LET (LET_d) parameters in restricted volumes (L_50%, L_10% and L_0.1cm³, the cumulative LET_d) within high-dose thresholds were included in linear- and logistic regression normal tissue complication probability (NTCP) models.

Results

A 1 keV/µm increase in L_10% to the brainstem volume receiving dose over 54 Gy(RBE) led to an increased brainstem necrosis risk [95% confidence interval] of 2.5 [0.0, 7.8] percentage points. The corresponding logistic regression model had area under the receiver operating characteristic curve (AUC) of 0.76, increasing to 0.84 with the anterior pons substructure as a second parameter. 19 [7, 350] patients with toxicity were required to associate the L_10% (D > 54 Gy(RBE)) and brainstem necrosis with 80% statistical power.

Conclusion

The established models of brainstem necrosis illustrate a potential impact of high LET regions in patients receiving high doses to the brainstem, and thereby support LET mitigation during clinical treatment planning.

Linear Energy Transfer and Relative Biological Effectiveness Investigation of Various Structures for a Cohort of Proton Patients With Brain Tumors

Purpose

The current knowledge on biological effects associated with proton therapy is limited. Therefore, we investigated the distributions of dose, dose-averaged linear energy transfer (LETd), and the product between dose and LETd (DLETd) for a patient cohort treated with proton therapy. Different treatment planning system features and visualization tools were explored.

Methods and Materials

For a cohort of 24 patients with brain tumors, the LETd, DLETd, and dose was calculated for a fixed relative biological effectiveness value and 2 variable models: plan-based and phenomenological. Dose threshold levels of 0, 5, and 20 Gy were imposed for LETd visualization. The relationship between physical dose and LETd and the frequency of LETd hotspots were investigated.

Results

The phenomenological relative biological effectiveness model presented consistently higher dose values. For lower dose thresholds, the LETd distribution was steered toward higher values related to low treatment doses. Differences up to 26.0% were found according to the threshold. Maximum LETd values were identified in the brain, periventricular space, and ventricles. An inverse relationship between LETd and dose was observed. Frequency information to the domain of dose and LETd allowed for the identification of clusters, which steer the mean LETd values, and the identification of higher, but sparse, LETd values.

Conclusions

Identifying, quantifying, and recording LET distributions in a standardized fashion is necessary, because concern exists over a link between toxicity and LET hotspots. Visualizing DLETd or dose × LETd during treatment planning could allow for clinicians to make informed decisions.

Increased relative biological effectiveness and periventricular radiosensitivity in proton therapy of glioma patients

PURPOSE

Currently, there is an intense debate on variations in intra-cerebral radiosensitivity and relative biological effectiveness (RBE) in proton therapy of primary brain tumours. Here, both effects were retrospectively investigated using late radiation-induced brain injuries (RIBI) observed in follow-up after proton therapy of patients with diagnosed glioma.

METHODS

In total, 42 WHO grade 2-3 glioma patients out of a consecutive patient cohort having received (adjuvant) proton radio(chemo)therapy between 2014 and 2017 were eligible for analysis. RIBI lesions (symptomatic or clinically asymptomatic) were diagnosed and delineated on contrast-enhanced T1-weighted magnetic resonance imaging scans obtained in the first two years of follow-up. Correlation of RIBI location and occurrence with dose (D), proton dose-averaged linear energy transfer (LET) and variable RBE dose parameters were tested in voxel- and in patient-wise logistic regression analyses. Additionally, anatomical and clinical parameters were considered. Model performance was estimated through cross-validated area-under-the-curve (AUC) values.

RESULTS

In total, 64 RIBI lesions were diagnosed in 21 patients. The median time between start of proton radio(chemo)therapy and RIBI appearance was 10.2 months. Median distances of the RIBI volume centres to the cerebral ventricles and to the clinical target volume border were 2.1 mm and 1.3 mm, respectively. In voxel-wise regression, the multivariable model with D, D × LET and periventricular region (PVR) revealed the highest AUC of 0.90 (95 % confidence interval: 0.89-0.91) while the corresponding model without D × LET revealed a value of 0.84 (0.83-0.86). In patient-level analysis, the equivalent uniform dose (EUD₁₁, a = 11) in the PVR using a variable RBE was the most prominent predictor for RIBI with an AUC of 0.63 (0.32-0.90).

CONCLUSIONS

In this glioma cohort, an increased radiosensitivity within the PVR was observed as well as a spatial correlation of RIBI with an increased RBE. Both need to be considered when delivering radio(chemo)therapy using proton beams.

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.

Technical note: Investigation of dose and LETd effect to rectum and bladder by using non-straight laterals in prostate cancer receiving proton therapy

BACKGROUND

Parallel-opposed lateral beams are the conventional beam arrangements in proton therapy for prostate cancer. However, when considering linear energy transfer (LET) and RBE effects, alternative beam arrangements should be investigated.

PURPOSE

To investigate the dose and dose averaged LET (LET_d ) impact of using new beam arrangements rotating beams 5°-15° posteriorly to the laterals in prostate cancer treated with pencil-beam-scanning (PBS) proton therapy.

METHODS

Twenty patients with localized prostate cancer were included in this study. Four proton treatment plans for each patient were generated utilizing 0°, 5°, 10°, and 15° posterior oblique beam pairs relative to parallel-opposed lateral beams. Dose-volume histograms (DVHs) from posterior oblique beams were analyzed. Dose-LET_d -volume histogram (DLVH) was employed to study the difference in dose and LET_d with each beam arrangement. DLVH indices, V ( d , l ) $V( {d,l} )$ , defined as the cumulative absolute volume that has a dose of at least d (Gy[RBE]) and a LET_d of at least l (keV/µm), were calculated for both the rectum and bladder to the whole group of patients and two-sub groups with and without hydrogel spacer. These metrics were tested using Wilcoxon signed-rank test.

RESULTS

Rotating beam angles from laterals to slightly posterior by 5°-15° reduced high LET_d volumes while it increased the dose volume in the rectum and increased LET_d in bladders. Beam angles rotated five degrees posteriorly from laterals (i.e., gantry in 95° and 265°) are proposed since they achieved the optimal balance of better LET_d sparing and minimal dose increase in the rectum. A reduction of V(50 Gy[RBE], 2.6 keV/µm) from 7.41 to 3.96 cc (p < 0.01), and a slight increase of V(50 Gy[RBE], 0 keV/µm) from 20.1 to 21.6 cc (p < 0.01) were observed for the group without hydrogel spacer. The LET_d sparing was less effective for the group with hydrogel spacer, which achieved the reduction of V(50 Gy[RBE], 2.6 keV/µm) from 4.28 to 2.10 cc (p < 0.01).

CONCLUSIONS

Posterior oblique angle plans improved LET_d sparing of the rectum while sacrificing LET_d sparing in the bladder in the treatment of prostate cancer with PBS. Beam angle modification from laterals to slightly posterior may be a strategy to redistribute LET_d and perhaps reduce rectal toxicity risks in prostate cancer patients treated with PBS. However, the effect is reduced for patients with hydrogel spacer.

Comparing biological effectiveness guided plan optimization strategies for cranial proton therapy: potential and challenges

BACKGROUND

To introduce and compare multiple biological effectiveness guided (BG) proton plan optimization strategies minimizing variable relative biological effectiveness (RBE) induced dose burden in organs at risk (OAR) while maintaining plan quality with a constant RBE.

METHODS

Dose-optimized (DOSEopt) proton pencil beam scanning reference treatment plans were generated for ten cranial patients with prescription doses ≥ 54 Gy(RBE) and ≥ 1 OAR close to the clinical target volume (CTV). For each patient, four additional BG plans were created. BG objectives minimized either proton track-ends, dose-averaged linear energy transfer (LET_d), energy depositions from high-LET protons or variable RBE-weighted dose (D_RBE) in adjacent serially structured OARs. Plan quality (RBE = 1.1) was assessed by CTV dose coverage and robustness (2 mm setup, 3.5% density), dose homogeneity and conformity in the planning target volumes and adherence to OAR tolerance doses. LET_d, D_RBE (Wedenberg model, α/β_CTV = 10 Gy, α/β_OAR = 2 Gy) and resulting normal tissue complication probabilities (NTCPs) for blindness and brainstem necrosis were derived. Differences between DOSEopt and BG optimized plans were assessed and statistically tested (Wilcoxon signed rank, α = 0.05).

RESULTS

All plans were clinically acceptable. DOSEopt and BG optimized plans were comparable in target volume coverage, homogeneity and conformity. For recalculated D_RBE in all patients, all BG plans significantly reduced near-maximum D_RBE to critical OARs with differences up to 8.2 Gy(RBE) (p < 0.05). Direct D_RBE optimization primarily reduced absorbed dose in OARs (average ΔD_mean = 2.0 Gy; average ΔLET_d,mean = 0.1 keV/µm), while the other strategies reduced LET_d (average ΔD_mean < 0.3 Gy; average ΔLET_d,mean = 0.5 keV/µm). LET-optimizing strategies were more robust against range and setup uncertaintes for high-dose CTVs than D_RBE optimization. All BG strategies reduced NTCP for brainstem necrosis and blindness on average by 47% with average and maximum reductions of 5.4 and 18.4 percentage points, respectively.

CONCLUSIONS

All BG strategies reduced variable RBE-induced NTCPs to OARs. Reducing LET_d in high-dose voxels may be favourable due to its adherence to current dose reporting and maintenance of clinical plan quality and the availability of reported LET_d and dose levels from clinical toxicity reports after cranial proton therapy. These optimization strategies beyond dose may be a first step towards safely translating variable RBE optimization in the clinics.

Roadmap: helium ion therapy

Helium ion beam therapy for the treatment of cancer was one of several developed and studied particle treatments in the 1950s, leading to clinical trials beginning in 1975 at the Lawrence Berkeley National Laboratory. The trial shutdown was followed by decades of research and clinical silence on the topic while proton and carbon ion therapy made debuts at research facilities and academic hospitals worldwide. The lack of progression in understanding the principle facets of helium ion beam therapy in terms of physics, biological and clinical findings persists today, mainly attributable to its highly limited availability. Despite this major setback, there is an increasing focus on evaluating and establishing clinical and research programs using helium ion beams, with both therapy and imaging initiatives to supplement the clinical palette of radiotherapy in the treatment of aggressive disease and sensitive clinical cases. Moreover, due its intermediate physical and radio-biological properties between proton and carbon ion beams, helium ions may provide a streamlined economic steppingstone towards an era of widespread use of different particle species in light and heavy ion therapy. With respect to the clinical proton beams, helium ions exhibit superior physical properties such as reduced lateral scattering and range straggling with higher relative biological effectiveness (RBE) and dose-weighted linear energy transfer (LET_d) ranging from ∼4 keVμm^-1to ∼40 keVμm^-1. In the frame of heavy ion therapy using carbon, oxygen or neon ions, where LET_dincreases beyond 100 keVμm^-1, helium ions exhibit similar physical attributes such as a sharp lateral penumbra, however, with reduced radio-biological uncertainties and without potentially spoiling dose distributions due to excess fragmentation of heavier ion beams, particularly for higher penetration depths. This roadmap presents an overview of the current state-of-the-art and future directions of helium ion therapy: understanding physics and improving modeling, understanding biology and improving modeling, imaging techniques using helium ions and refining and establishing clinical approaches and aims from learned experience with protons. These topics are organized and presented into three main sections, outlining current and future tasks in establishing clinical and research programs using helium ion beams-A. Physics B. Biological and C. Clinical Perspectives.

A case-control study of linear energy transfer and relative biological effectiveness related to symptomatic brainstem toxicity following pediatric proton therapy

BACKGROUND AND PURPOSE

A fixed relative biological effectiveness (RBE) of 1.1 (RBE_1.1) is used clinically in proton therapy even though the RBE varies with properties such as dose level and linear energy transfer (LET). We therefore investigated if symptomatic brainstem toxicity in pediatric brain tumor patients treated with proton therapy could be associated with a variable LET and RBE.

MATERIALS AND METHODS

36 patients treated with passive scattering proton therapy were selected for a case-control study from a cohort of 954 pediatric brain tumor patients. Nine children with symptomatic brainstem toxicity were each matched to three controls based on age, diagnosis, adjuvant therapy, and brainstem RBE_1.1 dose characteristics. Differences across cases and controls related to the dose-averaged LET (LET_d) and variable RBE-weighted dose from two RBE models were analyzed in the high-dose region.

RESULTS

LET_d metrics were marginally higher for cases vs. controls for the majority of dose levels and brainstem substructures. Considering areas with doses above 54 Gy(RBE_1.1), we found a moderate trend of 13% higher median LET_d in the brainstem for cases compared to controls (P = .08), while the difference in the median variable RBE-weighted dose for the same structure was only 2% (P = .6).

CONCLUSION

Trends towards higher LET_d for cases compared to controls were noticeable across structures and LET_d metrics for this patient cohort. While case-control differences were minor, an association with the observed symptomatic brainstem toxicity cannot be ruled out.

Exploratory study of seed spots analysis to characterize dose and linear energy transfer effect in adverse event initialization of pencil beam scanning proton therapy

BACKGROUND

Both dose and linear-energy-transfer (LET) could play a substantial role in adverse event (AE) initialization of cancer patients treated with pencil-beam-scanning proton therapy (PBS). However, not all the voxels within the AE regions are directly induced from the dose and LET effect. It is important to study the synergistic effect of dose and LET in AE initialization by only including a subset of voxels that are dosimetrically important.

PURPOSE

To perform exploratory investigation of the dose and LET effects upon AE initialization in PBS using seed spots analysis.

METHODS

113 head and neck (H&N) cancer patients receiving curative PBS were included. Among them, 20 patients experienced unanticipated CTCAEv4.0 grade≥3 AEs (AE group) and 93 patients did not (control group). Within the AE group, 13 AE patients were included in the seed spot analysis to derive the descriptive features of AE initialization and the remaining 7 mandible osteoradionecrosis patients and 93 control patients were used to derive the feature-based volume constraint of mandible osteoradionecrosis. The AE regions were contoured and the corresponding dose-LET volume histograms (DLVHs) of AE regions were generated for all patients in the AE group. We selected high LET voxels (the highest 5% of each dose bin) with a range of moderate to high dose (≥∼40 Gy[RBE]) as critical voxels. Critical voxels which were contiguous with each other were grouped into clusters. Each cluster was considered as a potential independent seed spot for AE initialization. Seed spots were displayed in a 2D dose-LET plane based on their mean dose and LET to derive the descriptive features of AE initialization. A volume constraint of mandible osteoradionecrosis was then established based on the extracted features using a receiver operating characteristic curve.

RESULTS

The product of dose and LET (xBD) was found to be a descriptive feature of seed spots leading to AE initialization in this preliminary study. The derived xBD volume constraint for mandible osteoradionecrosis showed good performance with an area-under-curve of 0.87 (sensitivity of 0.714 and specificity of 0.807 in the leave-one-out cross validation) for the very limited patient data included in this study.

CONCLUSION

Our exploratory study showed that both dose and LET were observed to be important in AE initializations. The derived xBD volume constraint could predict mandible osteoradionecrosis reasonably well in the very limited H&N cancer patient data treated with PBS included in this study. This article is protected by copyright. All rights reserved.

An ion-independent phenomenological relative biological effectiveness (RBE) model for proton therapy

BACKGROUND

A relative biological effectiveness (RBE) of 1.1 is used for proton therapy though clinical evidence of varying RBE was raised. Clinical studies on RBE variability have been conducted for decades for carbon radiation, which could advance the understanding of the clinical proton RBE given an ion-independent RBE model. In this work, such a model, linear and simple, using the beam quantity Q = Z²/E (Z = ion charge, E = kinetic energy per nucleon) was tested and compared to the commonly used, proton-specific and linear energy transfer (LET) based Wedenberg RBE model.

MATERIAL AND METHODS

The Wedenberg and Q models, both predicting RBE_max and RBE_min (i.e., RBE at vanishing and very high dose, respectively), are compared in terms of ion-dependence and prediction power. An experimental in-vitro data ensemble covering 115 publications for various ions was used as dataset.

RESULTS

The model parameter of the Q model was observed to be similar for different ions (in contrast to LET). The Q model was trained without any prior knowledge of proton data. For proton RBE, the differences between experimental data and corresponding predictions of the Wedenberg or the Q model were highly comparable.

CONCLUSIONS

A simple linear RBE model using Q instead of LET was proposed and tested to be able to predict proton RBE using model parameter trained based on only RBE data of other particles in a clinical proton energy range for a large in-vitro dataset. Adding (pre)clinical knowledge from carbon ion therapy may, therefore, reduce the dominating biological uncertainty in proton RBE modelling. This would translate in reduced RBE related uncertainty in proton therapy treatment planning.

Clinical use and future requirements of relative biological effectiveness: survey among all european proton therapy centres

BACKGROUND AND PURPOSE

The relative biological effectiveness (RBE) varies along the treatment field. However, in clinical practice, a constant RBE of 1.1 is assumed, which can result in undesirable side effects. This study provides an accurate overview of current clinical practice for considering proton RBE in Europe.

MATERIALS AND METHODS

A survey was devised and sent to all proton therapy centres in Europe that treat patients. The online questionnaire consisted of 39 questions addressing various aspects of RBE consideration in clinical practice, including treatment planning, patient follow-up and future demands.

RESULTS

All 25 proton therapy centres responded. All centres prescribed a constant RBE of 1.1, but also applied measures (except for one eye treatment centre) to counteract variable RBE effects such as avoiding beams stopping inside or in front of an organ at risk and putting restrictions on the minimum number and opening angle of incident beams for certain treatment sites. For the future, most centres (16) asked for more retrospective or prospective outcome studies investigating the potential effect of the effect of a variable RBE. To perform such studies, 18 centres asked for LET and RBE calculation and visualisation tools developed by treatment planning system vendors.

CONCLUSION

All European proton centres are aware of RBE variability but comply with current guidelines of prescribing a constant RBE. However, they actively mitigate uncertainty and risk of side effects resulting from increased RBE by applying measures and restrictions during treatment planning. To change RBE-related clinical guidelines in the future more clinical data on RBE are explicitly demanded.

Models for Translational Proton Radiobiology-From Bench to Bedside and Back

The number of proton therapy centers worldwide are increasing steadily, with more than two million cancer patients treated so far. Despite this development, pending questions on proton radiobiology still call for basic and translational preclinical research. Open issues are the on-going discussion on an energy-dependent varying proton RBE (relative biological effectiveness), a better characterization of normal tissue side effects and combination treatments with drugs originally developed for photon therapy. At the same time, novel possibilities arise, such as radioimmunotherapy, and new proton therapy schemata, such as FLASH irradiation and proton mini-beams. The study of those aspects demands for radiobiological models at different stages along the translational chain, allowing the investigation of mechanisms from the molecular level to whole organisms. Focusing on the challenges and specifics of proton research, this review summarizes the different available models, ranging from in vitro systems to animal studies of increasing complexity as well as complementing in silico approaches.