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

LET-based approximation of the microdosimetric kinetic model for proton radiotherapy

BACKGROUND

Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges.

PURPOSE

This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy.

METHODS

At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons.

RESULTS

A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed.

CONCLUSIONS

The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

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.

Unique brain injury patterns after proton vs photon radiotherapy for WHO grade 2-3 gliomas

BACKGROUND

Central nervous system (CNS) injury following brain-directed radiotherapy remains a major challenge. Proton radiotherapy (PRT) minimizes radiation to healthy brain, potentially limiting sequelae. We characterized CNS radiotoxicity, including radiation-induced leukoencephalopathy (RIL), brain tissue necrosis (TN), and cerebral microbleeds (CMB), in glioma patients treated with PRT or photons (XRT).

PATIENTS AND METHODS

Thirty-four patients (19 male; median age 39.6 years) with WHO grade 2-3 gliomas treated with partial cranial radiotherapy (XRT [n = 17] vs PRT[n = 17]) were identified and matched by demographic/clinical criteria. Radiotoxicity was assessed longitudinally for 3 years post-radiotherapy via serial analysis of T2/FLAIR- (for RIL), contrast-enhanced T1- (for TN), and susceptibility (for CMB)-weighted MRI sequences. RIL was rated at whole-brain and hemispheric levels using a novel Fazekas scale-informed scoring system.

RESULTS

The scoring system proved reliable (ICC > 0.85). Both groups developed moderate-to-severe RIL (62%[XRT]; 71%[PRT]) within 3 years; however, XRT was associated with persistent RIL increases in the contralesional hemisphere, whereas contralesional hemispheric RIL plateaued with PRT at 1-year post-radiotherapy (t = 2.180; P = .037). TN rates were greater with PRT (6%[XRT] vs 18%[PRT]; P = ns). CMB prevalence (76%[XRT]; 71%[PRT]) and burden (mean #CMB: 4.0[XRT]; 4.2[PRT]) were similar; however, XRT correlated with greater contralesional hemispheric CMB burden (27%[XRT]; 17%[PRT]; X2 = 4.986; P = .026), whereas PRT-specific CMB clustered at the radiation field margin (X2 = 14.7; P = .002).

CONCLUSIONS

CNS radiotoxicity is common and progressive in glioma patients. Injury patterns suggest radiation modality-specificity as RIL, TN, and CMB exhibit unique spatiotemporal differences following XRT vs PRT, likely reflecting underlying dosimetric and radiobiological differences. Familiarity with such injury patterns is essential to improve patient management. Prospective studies are needed to validate these findings and assess their impacts on neurocognitive function.

Modelling of RBE differences in selected points within similar spread-out Bragg-peaks (SOBP) placed at superficial and deep water phantom locations in passively scattered beams but not in scanned pencil beams: A hypothesis

PURPOSE

To model relative biological effectiveness (RBE) differences found in two studies which used spread-out Bragg-peaks (SOBP) placed at (a) superficial depth and (b) at the maximum range depth. For pencil beam scanning (PBS), RBE at similar points within the SOBP did not change between the two extreme SOBP placement depths; in passively scattered beams (PSB), high RBE values (typically 1.2-1.3) were found within superficially- placed SOBP but reduced to lower values (1-1.07) at similar points within the extreme-depth positioned SOBP. The dose, LET (linear energy transfer) distributions along each SOBP were closely comparable regardless of placement depth, but significant changes in dose rate occurred with depth in the PSB beam.

METHODS

The equations used allow α and β changes with falling dose rate (the converse to FLASH studies) in PSB, resulting in reduced α/β ratios, compatible with a reduction in micro-volumetric energy transfer (the product of Fluence and LET), with commensurate reductions in RBE. The experimental depth-distances, positions within SOBP, observed dose-rates and radiosensitivity ratios were used to estimate the changes in RBE.

RESULTS

RBE values within a 5 % tolerance limit of the experimental results for PSB were found at the deepest SOBP placement. No RBE changes were predicted for PBS beams, as in the published results.

CONCLUSIONS

Enhanced proton therapy toxicity might occur with PBS when compared with PSB for deeply positioned SOBP due to the maintenance of higher RBE. Scanned pencil beam users need to be vigilant about RBE and further research is indicated.

An updated variable RBE model for proton therapy

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

Possible association of dose rate and the development of late visual toxicity for patients with intracranial tumours treated with pencil beam scanned proton therapy

BACKGROUND AND PURPOSE

Rare but severe toxicities of the optic apparatus have been observed after treatment of intracranial tumours with proton therapy. Some adverse events have occurred at unusually low dose levels and are thus difficult to understand considering dose metrics only. When transitioning from double scattering to pencil beam scanning, little consideration was given to increased dose rates observed with the latter delivery paradigm. We explored if dose rate related metrics could provide additional predicting factors for the development of late visual toxicities.

MATERIALS AND METHODS

Radiation-induced intracranial visual pathway lesions were delineated on MRI for all index cases. Voxel-wise maximum dose rate (MDR) was calculated for 2 patients with observed optic nerve toxicities (CTCAE grade 3 and 4), and 6 similar control cases. Additionally, linear energy transfer (LET) related dose enhancing metrics were investigated.

RESULTS

For the index cases, which developed toxicities at low dose levels (mean, 50 GyRBE), some dose was delivered at higher instantaneous dose rates. While optic structures of non-toxicity cases were exposed to dose rates of up to 1 to 3.2 GyRBE/s, the pre-chiasmatic optic nerves of the 2 toxicity cases were exposed to dose rates above 3.7 GyRBE/s. LET-related metrics were not substantially different between the index and non-toxicity cases.

CONCLUSIONS

Our observations reveal large variations in instantaneous dose rates experienced by different volumes within our patient cohort, even when considering the same indications and beam arrangement. High dose rate regions are spatially overlapping with the radiation induced toxicity areas in the follow up images. At this point, it is not feasible to establish causality between exposure to high dose rates and the development of late optic apparatus toxicities due to the low incidence of injury.

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.

Proton therapy induces a local microglial neuroimmune response

BACKGROUND AND PURPOSE

Although proton therapy is increasingly being used in the treatment of paediatric and adult brain tumours, there are still uncertainties surrounding the biological effect of protons on the normal brain. Microglia, the brain-resident macrophages, have been shown to play a role in the development of radiation-induced neurotoxicity. However, their molecular and hence functional response to proton irradiation remains unknown. This study investigates the effect of protons on microglia by comparing the effect of photons and protons as well as the influence of age and different irradiated volumes.

MATERIALS AND METHODS

Rats were irradiated with 14 Gy to the whole brain with photons (X-rays), plateau protons, spread-out Bragg peak (SOBP) protons or to 50 % anterior, or 50 % posterior brain sub-volumes with plateau protons. RNA sequencing, validation of microglial priming gene expression using qPCR and high-content imaging analysis of microglial morphology were performed in the cortex at 12 weeks post irradiation.

RESULTS

Photons and plateau protons induced a shared transcriptomic response associated with neuroinflammation. This response was associated with a similar microglial priming gene expression signature and distribution of microglial morphologies. Expression of the priming gene signature was less pronounced in juvenile rats compared to adults and slightly increased in rats irradiated with SOBP protons. High-precision partial brain irradiation with protons induced a local microglial priming response and morphological changes.

CONCLUSION

Overall, our data indicate that the brain responds in a similar manner to photons and plateau protons with a shared local upregulation of microglial priming-associated genes, potentially enhancing the immune response to subsequent inflammatory challenges.

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.

Robustness and dosimetric verification of hippocampal-sparing craniospinal pencil beam scanning proton plans for pediatric medulloblastoma

Background and Purpose

Hippocampal-sparing (HS) is a method that can potentially reduce late cognitive complications for pediatric medulloblastoma (MB) patients treated with craniospinal proton therapy (PT). The aim of this study was to investigate robustness and dosimetric plan verification of pencil beam scanning HS PT.

Materials and Methods

HS and non-HS PT plans for the whole brain part of craniospinal treatment were created for 15 pediatric MB patients. A robust evaluation of the plans was performed. Plans were recalculated in a water phantom and measured field-by-field using an ion chamber detector at depths corresponding to the central part of hippocampi. All HS and non-HS fields were measured with the standard resolution of the detector and in addition 16 HS fields were measured with high resolution. Measured and planned dose distributions were compared using gamma evaluation.

Results

The median mean hippocampus dose was reduced from 22.9 Gy (RBE) to 8.9 Gy (RBE), while keeping CTV V95% above 95 % for all nominal HS plans. HS plans were relatively robust regarding hippocampus mean dose, however, less robust regarding target coverage and maximum dose compared to non-HS plans. For standard resolution measurements, median pass rates were 99.7 % for HS and 99.5 % for non-HS plans (p < 0.001). For high-resolution measurements, median pass rates were 100 % in the hippocampus region and 98.2 % in the surrounding region.

Conclusions

A substantial reduction of dose in the hippocampus region appeared feasible. Dosimetric accuracy of HS plans was comparable to non-HS plans and agreed well with planned dose distribution in the hippocampus region.

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

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

Aberrant choroid plexus formation in human cerebral organoids exposed to radiation

Brain tumor patients are commonly treated with radiotherapy, but the efficacy of the treatment is limited by its toxicity, particularly the risk of radionecrosis. We used human cerebral organoids to investigate the mechanisms and nature of postirradiation brain image changes commonly linked to necrosis. Irradiation of cerebral organoids lead to increased formation of ZO1+/AQP1+/CLN3+-choroid plexus (CP) structures. Increased CP formation was triggered by radiation via the NOTCH/WNT signaling pathways and associated with delayed growth and neural stem cell differentiation, but not necrosis. The effect was more pronounced in immature than in mature organoids, reflecting the clinically-observed increased radiosensitivity of the pediatric brain. Protons were more effective than X-rays at the same dose, as also observed in clinical treatments. We conclude that radiation-induced brain image-changes can be attributed to aberrant CP formation, providing a new cellular mechanism and strategy for possible countermeasures.

Clinical benefit of range uncertainty reduction in proton treatment planning based on dual-energy CT for neuro-oncological patients

OBJECTIVE

Several studies have shown that dual-energy CT (DECT) can lead to improved accuracy for proton range estimation. This study investigated the clinical benefit of reduced range uncertainty, enabled by DECT, in robust optimisation for neuro-oncological patients.

METHODS

DECT scans for 27 neuro-oncological patients were included. Commercial software was applied to create stopping-power ratio (SPR) maps based on the DECT scan. Two plans were robustly optimised on the SPR map, keeping the beam and plan settings identical to the clinical plan. One plan was robustly optimised and evaluated with a range uncertainty of 3% (as used clinically; denoted 3%-plan); the second plan applied a range uncertainty of 2% (2%-plan). Both plans were clinical acceptable and optimal. The dose-volume histogram parameters were compared between the two plans. Two experienced neuro-radiation oncologists determined the relevant dose difference for each organ-at-risk (OAR). Moreover, the OAR toxicity levels were assessed.

RESULTS

For 24 patients, a dose reduction >0.5/1 Gy (relevant dose difference depending on the OAR) was seen in one or more OARs for the 2%-plan; e.g. for brainstem D0.03cc in 10 patients, and hippocampus D40% in 6 patients. Furthermore, 12 patients had a reduction in toxicity level for one or two OARs, showing a clear benefit for the patient.

CONCLUSION

Robust optimisation with reduced range uncertainty allows for reduction of OAR toxicity, providing a rationale for clinical implementation. Based on these results, we have clinically introduced DECT-based proton treatment planning for neuro-oncological patients, accompanied with a reduced range uncertainty of 2%.

ADVANCES IN KNOWLEDGE

This study shows the clinical benefit of range uncertainty reduction from 3% to 2% in robustly optimised proton plans. A dose reduction to one or more OARs was seen for 89% of the patients, and 44% of the patients had an expected toxicity level decrease.

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.

Does variable RBE affect toxicity risks for mediastinal lymphoma patients? NTCP-based evaluation after proton therapy treatment

INTRODUCTION

Mediastinal lymphoma (ML) is a solid malignancy affecting young patients. Modern combined treatments allow obtaining good survival probability, together with a long life expectancy, and therefore with the need to minimize treatment-related toxicities. We quantified the expected toxicity risk for different organs and endpoints in ML patients treated with intensity-modulated proton therapy (IMPT) at our centre, accounting also for uncertainties related to variable RBE.

METHODS

Treatment plans for ten ML patients were recalculated with a TOPAS-based Monte Carlo code, thus retrieving information on LET and allowing the estimation of variable RBE. Published NTCP models were adopted to calculate the toxicity risk for hypothyroidism, heart valve defects, coronary heart disease and lung fibrosis. NTCP was calculated assuming both constant (i.e. 1.1) and variable RBE. The uncertainty associated with individual radiosensitivity was estimated by random sampling α/β values before RBE evaluation.

RESULTS

Variable RBE had a minor impact on hypothyroidism risk for 7 patients, while it led to significant increase for the remaining three (+24% risk maximum increase). Lung fibrosis was slightly affected by variable RBE, with a maximum increase of ≅ 1%. This was similar for heart valve dysfunction, with the exception of one patient showing an about 10% risk increase, which could be explained by means of large heart volume and D₁ increase.

DISCUSSION

The use of NTCP models allows for identifying those patients associated with a higher toxicity risk. For those patients, it might be worth including variable RBE in plan evaluation.

Slice2Volume: Fusion of multimodal medical imaging and light microscopy data of irradiation-injured brain tissue in 3D

Comprehending cellular changes of radiation-induced brain injury is crucial to prevent and treat the pathology. We provide a unique open dataset of proton-irradiated mouse brains consisting of medical imaging, radiation dose simulations, and large-scale microscopy images, all registered into a common coordinate system. This allows dose-dependent analyses on single-cell level.

Unchanged perfusion in normal-appearing white and grey matter of glioma patients nine months after proton beam irradiation

Purpose: Radio(chemo)therapy is used as a standard treatment for glioma patients. The surrounding normal tissue is inevitably affected by the irradiation. The aim of this longitudinal study was to investigate perfusion alterations in the normal-appearing tissue after proton irradiation and assess the dose sensitivity of the normal tissue perfusion.Methods: In 14 glioma patients, a sub-cohort of a prospective clinical trial (NCT02824731), perfusion changes in normal-appearing white matter (WM), grey matter (GM) and subcortical GM structures, i.e. caudate nucleus, hippocampus, amygdala, putamen, pallidum and thalamus, were evaluated before treatment and at three-monthly intervals after proton beam irradiation. The relative cerebral blood volume (rCBV) was assessed with dynamic susceptibility contrast MRI and analysed as the percentage ratio between follow-up and baseline image (ΔrCBV). Radiation-induced alterations were evaluated using Wilcoxon signed rank test. Dose and time correlations were investigated with univariate and multivariate linear regression models.Results: No significant ΔrCBV changes were found in any normal-appearing WM and GM region after proton beam irradiation. A positive correlation with radiation dose was observed in the multivariate regression model applied to the combined ΔrCBV values of low (1-20 Gy), intermediate (21-40 Gy) and high (41-60 Gy) dose regions of GM (p < 0.001), while no time dependency was detected in any normal-appearing area.Conclusion: The perfusion in normal-appearing brain tissue remained unaltered after proton beam therapy. In further studies, a direct comparison with changes after photon therapy is recommended to confirm the different effect of proton therapy on the normal-appearing tissue.