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

Towards a European prospective data registry for particle therapy

The evidence for the value of particle therapy (PT) is still sparse. While randomized trials remain a cornerstone for robust comparisons with photon-based radiotherapy, data registries collecting real-world data can play a crucial role in building evidence for new developments. This Perspective describes how the European Particle Therapy Network (EPTN) is actively working on establishing a prospective data registry encompassing all patients undergoing PT in European centers. Several obstacles and hurdles are discussed, for instance harmonization of nomenclature and structure of technical and dosimetric data and data protection issues. A preferred approach is the adoption of a federated data registry model with transparent and agile governance to meet European requirements for data protection, transfer, and processing. Funding of the registry, especially for operation after the initial setup process, remains a major challenge.

Linear Energy Transfer Measurements and Estimation of Relative Biological Effectiveness in Proton and Helium Ion Beams Using Fluorescent Nuclear Track Detectors

PURPOSE

Our objective was to develop a methodology for assessing the linear energy transfer (LET) and relative biological effectiveness (RBE) in clinical proton and helium ion beams using fluorescent nuclear track detectors (FNTDs).

METHODS AND MATERIALS

FNTDs were exposed behind solid water to proton and helium (4He) ion spread-out Bragg peaks. Detectors were imaged with a confocal microscope, and the LET spectra were derived from the fluorescence intensity. The track- and dose-averaged LET (LETF and LETD, respectively) were calculated from the LET spectra. LET measurements were used as input on RBE models to estimate the RBE. Human alveolar adenocarcinoma cells (A549) were exposed at the same positions as the FNTDs. The RBE was calculated from the resulting survival curves. All measurements were compared with Monte Carlo simulations.

RESULTS

For protons, average relative differences between measurements and simulations were 6% and 19% for LETF and LETD, respectively. For helium ions, the same differences were 11% for both quantities. The position of the experimental LET spectra primary peaks agreed with the simulations within 9% and 14% for protons and helium ions, respectively. For the RBE models using LETD as input, FNTD-based RBE values ranged from 1.02 ± 0.01 to 1.25 ± 0.04 and from 1.08 ± 0.09 to 2.68 ± 1.26 for protons and helium ions, respectively. The average relative differences between these values and simulations were 2% and 4%. For A549 cells, the RBE ranged from 1.05 ± 0.07 to 1.47 ± 0.09 and from 0.89 ± 0.06 to 3.28 ± 0.20 for protons and helium ions, respectively. Regarding the RBE-weighted dose (2.0 Gy at the spread-out Bragg peak), the differences between simulations and measurements were below 0.10 Gy.

CONCLUSIONS

This study demonstrates for the first time that FNTDs can be used to perform direct LET measurements and to estimate the RBE in clinical proton and helium ion beams.

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.

Shoot-through proton FLASH irradiation lowers linear energy transfer in organs at risk for neurological tumors and is robust against density variations

Objective. The goal of the study was to test the hypothesis that shoot-through FLASH proton beams would lead to lower dose-averaged LET (LETD) values in critical organs, while providing at least equal normal tissue sparing as clinical proton therapy plans.Approach. For five neurological tumor patients, pencil beam scanning (PBS) shoot-through plans were made, using the maximum energy of 227 MeV and assuming a hypothetical FLASH protective factor (FPF) of 1.5. The effect of different FPF ranging from 1.2 to 1.8 on the clinical goals were also considered. LETDwas calculated for the clinical plan and the shoot-through plan, applying a 2 Gy total dose threshold (RayStation 8 A/9B and 9A-IonRPG). Robust evaluation was performed considering density uncertainty (±3% throughout entire volume).Main results.Clinical plans showed large LETDvariations compared to shoot-through plans and the maximum LETDin OAR is 1.2-8 times lower for the latter. Although less conformal, shoot-through plans met the same clinical goals as the clinical plans, for FLASH protection factors above 1.4. The FLASH shoot-through plans were more robust to density uncertainties with a maximum OAR D2%increase of 0.6 Gy versus 5.7 Gy in the clinical plans.Significance.Shoot-through proton FLASH beams avoid uncertainties in LETDdistributions and proton range, provide adequate target coverage, meet planning constraints and are robust to density variations.

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.

Proposing a Clinical Model for RBE Based on Proton Track-End Counts

PURPOSE

In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts.

METHODS AND MATERIALS

We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE.

RESULTS

Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track end model identified the same biological hotspots as predicted by LETd-based radiobiological models of proton RBE.

CONCLUSIONS

These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LETd-based models in terms of information provided while also offering superior statistical properties.

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.

Double scattering and pencil beam scanning Monte Carlo workflows for proton therapy retrospective studies on radiation-induced toxicities

PURPOSE

Monte Carlo (MC) simulations can be used to accurately simulate dose and linear energy transfers (LET) distributions, thereby allowing for the calculation of the relative biological effectiveness (RBE) of protons. We present hereby the validation and implementation of a workflow for the Monte Carlo modelling of the double scattered and pencil beam scanning proton beamlines at our institution.

METHODS

The TOPAS/Geant4 MC model of the clinical nozzle has been comprehensively validated against measurements. The validation also included a comparison between simulated clinical treatment plans for four representative patients and the clinical treatment planning system (TPS). Moreover, an in-house tool implemented in Python was tested to assess the variable RBE-weighted dose in proton plans, which was illustrated for a patient case with a developing radiation-induced toxicity.

RESULTS

The simulated range and modulation width closely matches the measurements. Gamma-indexes (3%/3mm 3D), which compare the TPS and MC computations, showed a passing rate superior to 98%. The calculated RBE-weighted dose presented a slight increase at the necrosis location, within the PTV margins. This indicates the need for reporting on the physical and biological effects of irradiation in high dose regions, especially at the healthy tissues and increased LET distributions location.

CONCLUSION

The results demonstrate that the Monte Carlo method can be used to independently validate a TPS calculation, and to estimate LET distributions. The features of the in-house tool can be used to correlate LET and RBE-weighted dose distributions with the incidence of radiation-induced toxicities following proton therapy treatments.

State-of-the-art and potential of experimental microdosimetry in ion-beam therapy

In radiotherapy, radiation-quality should be an expression of the biological and physical characteristics of ionizing radiation such as spatial distribution of ionization or energy deposition. Linear energy transfer (LET) and lineal energy (y) are two descriptors used to quantify the radiation quality. These two quantities are connected and exhibit similar features. In ion-beam therapy (IBT), lineal energy can be measured with microdosimeters, which are specifically designed to cope with the high fluence of particles in clinical beams, while the quantification of LET is generally based on calculations. In pre-clinical studies, microdosimetric spectra are used for the indirect determination of relative biological effectiveness (RBE), e.g., using the microdosimetric kinetic model (MKM) or biophysical response functions. In this context it is important to consider saturation effects, which occur when the highest values of y become less biologically relevant compared to the relative contribution they make to the physical dose. Recent clinical data suggests that local tumor control and normal tissue effects can be linked to macroscopic and microscopic dosimetry parameters. In particular, positive clinical outcomes have been correlated to the highest LET values in the density distribution, and there is no evident link to the saturation discussed above. A systematic collection of microdosimetric information in combination with clinical data in retrospective studies may clarify the role of radiation quality at the highest LET. In the clinical setting, microdosimetry is not widely used yet, despite its potential to be linked with LET by experimentally-determined y values. Through this connection, both play an important role in complex therapy techniques such as intensity modulated particle therapy (IMPT), LET-painting and multi-ion optimization. This review summarizes the current state of microdosimetry for IBT and its potential, as well as research and development needed to make experimental microdosimetry a mature procedure in a clinical context.

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.

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.

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.

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.

A Monte Carlo study of different LET definitions and calculation parameters for proton beam therapy

The strongin vitroevidence that proton Relative Biological Effectiveness (RBE) varies with Linear Energy Transfer (LET) has led to an interest in applying LET within treatment planning. However, there is a lack of consensus on LET definition, Monte Carlo (MC) parameters or clinical methodology. This work aims to investigate how common variations of LET definition may affect potential clinical applications. MC simulations (GATE/GEANT4) were used to calculate absorbed dose and different types of LET for a simple Spread Out Bragg Peak (SOBP) and for four clinical PBT plans covering a range of tumour sites. Variations in the following LET calculation methods were considered: (i) averaging (dose-averaged LET (LET_d) & track-averaged LET); (ii) scoring (LET_dto water, to medium and to mass density); (iii) particle inclusion (LET_dto all protons, to primary protons and to particles); (iv) MC settings (hit type and Maximum Step Size (MSS)). LET distributions were compared using: qualitative comparison, LET Volume Histograms (LVHs), single value criteria (maximum and mean values) and optimised LET-weighted dose models. Substantial differences were found between LET values in averaging, scoring and particle type. These differences depended on the methodology, but for one patient a difference of ∼100% was observed between the maximum LET_dfor all particles and maximum LET_dfor all protons within the brainstem in the high isodose region (4 keVμm^-1and 8 keVμm^-1respectively). An RBE model using LET_dincluding heavier ions was found to predict substantially different LET-weighted dose compared to those using other LET definitions. In conclusion, the selection of LET definition may affect the results of clinical metrics considered in treatment planning and the results of an RBE model. The authors' advocate for the scoring of dose-averaged LET to water for primary and secondary protons using a random hit type and automated MSS.