Tuning spatially fractionated radiotherapy dose profiles using the moiré effect.

Spatially Fractionated Radiotherapy (SFRT) has demonstrated promising potential in cancer treatment, combining the advantages of reduced post-radiation effects and enhanced local control rates. Within this paradigm, proton minibeam radiotherapy (pMBRT) was suggested as a new treatment modality, possibly producing superior normal tissue sparing to conventional proton therapy, leading to improvements in patient outcomes. However, an effective and convenient beam generation method for pMBRT, capable of implementing various optimum dose profiles, is essential for its real-world application. Our study investigates the potential of utilizing the moiré effect in a dual collimator system (DCS) to generate pMBRT dose profiles with the flexibility to modify the center-to-center distance (CTC) of the dose distribution in a technically simple way.We employ the Geant4 Monte Carlo simulations tool to demonstrate that the angle between the two collimators of a DCS can significantly impact the dose profile. Varying the DCS angle from 10 ∘ to 50 ∘ we could cover CTC ranging from 11.8 mm to 2.4 mm, respectively. Further investigations reveal the substantial influence of the multi-slit collimator's (MSC) physical parameters on the spatially fractionated dose profile, such as period (CTC), throughput, and spacing between MSCs. These findings highlight opportunities for precision dose profile adjustments tailored to specific clinical scenarios.The DCS capacity for rapid angle adjustments during the energy transition stages of a spot scanning system can facilitate dynamic alterations in the irradiation profile, enhancing dose contrast in normal tissues. Furthermore, its unique attribute of spatially fractionated doses in both lateral directions could potentially improve normal tissue sparing by minimizing irradiated volume. Beyond the realm of pMBRT, the dual MSC system exhibits remarkable versatility, showing compatibility with different types of beams (X-rays and electrons) and applicability across various SFRT modalities.Our study illuminates the dual MSC system's potential as an efficient and adaptable tool in the refinement of pMBRT techniques. By enabling meticulous control over irradiation profiles, this system may expedite advancements in clinical and experimental applications, thereby contributing to the evolution of SFRT strategies.

Investigation on the physical dose filtered by linear energy transfer for treatment plan evaluation in carbon ion therapy.

BACKGROUND: Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT. PURPOSE: Purpose of this study was to investigate on a novel dosimetric quantity, namely high-LET-dose ( D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumor volume. METHODS: Ten cTPs with a planning target volume, PTV ≥ 500 cm 3 $\mathrm{PTV}\ge {500}\,{{\rm cm}^{3}}$ (large) and nine with a PTV < 500 cm 3 $\mathrm{PTV}<{500}\,{{\rm cm}^{3}}$ (small) were selected for this study. To find a reasonable LET threshold ( L thr $\textrm {L}_{\textrm {thr}}$ ) that results in a significant difference in terms of D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the voxel based normalized high-LET-dose ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ distributions within the target of all 19 cTPs at the before determined L thr $\textrm {L}_{\textrm {thr}}$ . Statistical significance of the difference between the two groups in terms of mean D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ volume histogram parameters was evaluated by means of (two-sided) t-test or Mann-Whitney-U-test. In addition, the minimum target coverage at the above determined L thr $\textrm {L}_{\textrm {thr}}$ was compared and validated against three other thresholds to verify its potential in differentiation between small and large volume tumors. RESULTS: An L thr $\textrm {L}_{\textrm {thr}}$ of approximately 30 keV / µ m ${30}\,{\rm keV/}\umu {\rm m}$ was found to be a reasonable threshold to classify the two groups. At this threshold, the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ were significantly larger ( p < 0.05 $p<0.05$ ) in small CTVs. For the small tumor group, the near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) in the CTV were in average 9.3 ± 1.5 Gy $9.3\pm {1.5}\,{\rm Gy}$ (0.31 ± 0.08) and 13.6 ± 1.6 Gy $13.6\pm {1.6}\,{\rm Gy}$ (0.46 ± 0.06), respectively. For the large tumors, these parameters were 6.6 ± 0.2 Gy $6.6\pm {0.2}\,{\rm Gy}$ (0.20 ± 0.01) and 8.6 ± 0.4 Gy $8.6\pm {0.4}\,{\rm Gy}$ (0.28 ± 0.02). The difference between the two groups in terms of mean near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) was 2.7 Gy (11%) and 5.0 Gy (18%), respectively. CONCLUSIONS: The feasibility of high-LET-dose based evaluation was shown in this study where a lower D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high-LET-dose based studies.

Treatment planning of scanned proton beams in RayStation.

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

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/ß 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.

Plan robustness and RBE influence for proton dose painting by numbers for head and neck cancers.

PURPOSE: To investigate the feasibility of dose painting by numbers (DPBN) with respect to robustness for proton therapy for head and neck cancers (HNC), and to study the influence of variable RBE on the TCP and OAR dose burden. METHODS AND MATERIALS: Data for 19 patients who have been scanned pretreatment with PET-FDG and subsequently treated with photon therapy were used in the study. A dose response model developed for photon therapy was implemented in a TPS, allowing DPBN plans to be created. Conventional homogeneous dose and DPBN plans were created for each patient, optimized with either fixed RBE = 1.1 or a variable RBE model. Robust optimization was used to create clinically acceptable plans. To estimate the maximum potential loss in TCP due to actual SUV variations from the pre-treatment imaging, we applied a test case with randomized SUV distribution. RESULTS: Regardless of the use of variable RBE for optimization or evaluation, a statistically significant increase (p < 0.001) in TCP was found for DPBN plans as compared to homogeneous dose plans. Randomizing the SUV distribution decreased the TCP for all plans. A correlation between TCP increase and variance of the SUV distribution and target volume was also found. CONCLUSION: DPBN for protons and HNC is feasible and could lead to a TCP gain. Risks associated with the temporal variation of SUV distributions could be mitigated by imposing minimum doses to targets. The correlation found between TCP increase and SUV variance and target volume may be used for patient selection.

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.

3D-conformal very-high energy electron therapy as candidate modality for FLASH-RT: A treatment planning study for glioblastoma and lung cancer.

BACKGROUND: Pre-clinical ultra-high dose rate (UHDR) electron irradiations on time scales of 100 ms have demonstrated a remarkable sparing of brain and lung tissues while retaining tumor efficacy when compared to conventional dose rate irradiations. While clinically-used gantries and intensity modulation techniques are too slow to match such time scales, novel very-high energy electron (VHEE, 50-250 MeV) radiotherapy (RT) devices using 3D-conformed broad VHEE beams are designed to deliver UHDR treatments that fulfill these timing requirements. PURPOSE: To assess the dosimetric plan quality obtained using VHEE-based 3D-conformal RT (3D-CRT) for treatments of glioblastoma and lung cancer patients and compare the resulting treatment plans to those delivered by standard-of-care intensity modulated photon RT (IMRT) techniques. METHODS: Seven glioblastoma patients and seven lung cancer patients were planned with VHEE-based 3D-CRT using 3 to 16 coplanar beams with equidistant angular spacing and energies of 100 and 200 MeV using a forward planning approach. Dose distributions, dose-volume histograms, coverage (V95% ) and homogeneity (HI98% ) for the planning target volume (PTV), as well as near-maximum doses (D2% ) and mean doses (Dmean ) for organs-at-risk (OAR) were evaluated and compared to clinical IMRT plans. RESULTS: Mean differences of V95% and HI98% of all VHEE plans were within 2% or better of the IMRT reference plans. Glioblastoma plan dose metrics obtained with VHEE configurations of 200 MeV and 3-16 beams were either not significantly different or were significantly improved compared to the clinical IMRT reference plans. All OAR plan dose metrics evaluated for VHEE plans created using 5 beams of 100 MeV were either not significantly different or within 3% on average, except for Dmean for the body, Dmean for the brain, D2% for the brain stem, and D2% for the chiasm, which were significantly increased by 1, 2, 6, and 8 Gy, respectively (however below clinical constraints). Similarly, the dose metrics for lung cancer patients were also either not significantly different or were significantly improved compared to the reference plans for VHEE configurations with 200 MeV and 5 to 16 beams with the exception of D2% and Dmean to the spinal canal (however below clinical constraints). For the lung cancer cases, the VHEE configurations using 100 MeV or only 3 beams resulted in significantly worse dose metrics for some OAR. Differences in dose metrics were, however, strongly patient-specific and similar for some patient cases. CONCLUSIONS: VHEE-based 3D-CRT may deliver conformal treatments to simple, mostly convex target shapes in the brain and the thorax with a limited number of critical adjacent OAR using a limited number of beams (as low as 3 to 7). Using such treatment techniques, a dosimetric plan quality comparable to that of standard-of-care IMRT can be achieved. Hence, from a treatment planning perspective, 3D-conformal UHDR VHEE treatments delivered on time scales of 100 ms represent a promising candidate technique for the clinical transfer of the FLASH effect.

Detectability of Anatomical Changes With Prompt-Gamma Imaging: First Systematic Evaluation of Clinical Application During Prostate-Cancer Proton Therapy.

PURPOSE: The development of online-adaptive proton therapy (PT) is essential to overcome limitations encountered by day-to-day variations of the patient's anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present the results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system. METHODS AND MATERIALS: For 15 patients with prostate cancer, PGI measurements were performed during 105 fractions (201 fields) with in-room control computed tomography (CT)acquisitions. Field-wise doses on control CT scans were manually classified as whether showing relevant or non-relevant anatomical changes. This manual classification of the treatment fields was then used to establish an automatic field-wise ground truth based on spot-wise dosimetric range shifts, which were retrieved from integrated depth-dose (IDD) profiles. To determine the detection capability of anatomical changes with PGI, spot-wise PGI-based range shifts were initially compared with corresponding dosimetric IDD range shifts. As final endpoint, the agreement of a developed field-wise PGI classification model with the field-wise ground truth was determined. Therefore, the PGI model was optimized and tested for a subcohort of 131 and 70 treatment fields, respectively. RESULTS: The correlation between PGI and IDD range shifts was high, ρpearson = 0.67 (p < 0.01). Field-wise binary PGI classification resulted in an area under the curve of 0.72 and 0.80 for training and test cohorts, respectively. The model detected relevant anatomical changes in the independent test cohort, with a sensitivity and specificity of 74% and 79%, respectively. CONCLUSIONS: For the first time, evidence of the detection capability of anatomical changes in prostate-cancer PT from clinically acquired PGI data is shown. This emphasizes the benefit of PGI-based range verification and demonstrates its potential for online-adaptive PT.

Modelling tissue specific RBE for different radiation qualities based on a multiscale characterization of energy deposition.

PURPOSE: We present the nanoCluE model, which uses nano- and microdosimetric quantities to model RBE for protons and carbon ions. Under the hypothesis that nano- and microdosimetric quantities correlates with the generation of complex DNA double strand breakes, we wish to investigate whether an improved accuracy in predicting LQ parameters may be achieved, compared to some of the published RBE models. METHODS: The model is based on experimental LQ data for protons and carbon ions. We generated a database of track structure data for a number of proton and carbon ion kinetic energies with the Geant4-DNA Monte Carlo code. These data were used to obtain both a nanodosimetric quantity and a set of microdosimetric quantities. The latter were tested with different parameterizations versus experimental LQ-data to select the variable and parametrization that yielded the best fit. RESULTS: For protons, the nanoCluE model yielded, for the ratio of the linear LQ term versus the test data, a root mean square error (RMSE) of 1.57 compared to 1.31 and 1.30 for two earlier other published proton models. For carbon ions the RMSE was 2.26 compared to 3.24 and 5.24 for earlier published carbon ion models. CONCLUSION: These results demonstrate the feasibility of the nanoCluE RBE model for carbon ions and protons. The increased accuracy for carbon ions as compared to two other considered models warrants further investigation.

Technical note: In silico benchmarking of the linear energy transfer-based functionalities for carbon ion beams in a commercial treatment planning system.

BACKGROUND: The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS. PURPOSE: This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LETd ) scoring and (2) physical dose filtration based on LET for future LET-based treatment plan evaluation and optimization studies. METHODS: The LETd scoring and LET-based dose filtering (in which the deposited dose can be separated into the dose below and above the user specified LET threshold) functionalities for carbon ions in the research version RayStation (RS) 9A-IonPG TPS (RaySearch Laboratories, Sweden) were benchmarked against GATE/Geant4 simulations. Pristine Bragg peaks (BPs) and cuboid targets, positioned at different depths in a homogeneous water phantom and a setup with heterogeneity were used for this study. RESULTS: For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LETd difference was less than 1 keV/ µ $\umu$ m (3.5%) in the plateau and target and less than 2 keV/ µ $\umu$ m (8.3%) in the fragmentation tail. The maximum local differences were 4 and 6 keV/ µ $\umu$ m, respectively. The mean absolute (and relative) physical dose differences for both low- and high-LET doses were less than 1 cGy (1.5%) in the plateau, target and tail with a maximum absolute difference of 2 cGy. CONCLUSIONS: No computation error was found in the tested functionalities except for LETd in lateral direction outside the target, showing the limitation of the implemented monochrome model in the tested TPS version.

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 (LETd), energy depositions from high-LET protons or variable RBE-weighted dose (DRBE) 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. LETd, DRBE (Wedenberg model, α/ßCTV = 10 Gy, α/ßOAR = 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 DRBE in all patients, all BG plans significantly reduced near-maximum DRBE to critical OARs with differences up to 8.2 Gy(RBE) (p < 0.05). Direct DRBE optimization primarily reduced absorbed dose in OARs (average ΔDmean = 2.0 Gy; average ΔLETd,mean = 0.1 keV/µm), while the other strategies reduced LETd (average ΔDmean < 0.3 Gy; average ΔLETd,mean = 0.5 keV/µm). LET-optimizing strategies were more robust against range and setup uncertaintes for high-dose CTVs than DRBE 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 LETd 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 LETd 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.

Treatment planning considerations for the development of FLASH proton therapy.

With increasing focus on the translation of the observed FLASH effect into clinical practice, this paper presents treatment planning considerations for its development using proton therapy. Potential requirements to induce a FLASH effect are discussed along with the properties of existing proton therapy delivery systems and the changes in planning and delivery approaches required to satisfy these prerequisites. For the exploration of treatment planning approaches for FLASH, developments in treatment planning systems are needed. Flexibility in adapting to new information will be important in such an evolving area. Variations in definitions, threshold values and assumptions can make it difficult to compare different published studies and to interpret previous studies in the context of new information. Together with the fact that much is left to be understood about the underlying mechanism behind the FLASH effect, a systematic and comprehensive approach to information storage is encouraged. Collecting and retaining more detailed information on planned and realised dose delivery as well as reporting the assumptions made in planning studies creates the potential for research to be revisited and re-evaluated in the light of future improvements in understanding. Forward thinking at the time of study development can help facilitate retrospective analysis. This, we hope, will increase the available evidence and accelerate the translation of the FLASH effect into clinical benefit.

Measurement-based validation of a commercial Monte Carlo dose calculation algorithm for electron beams.

PURPOSE: This work presents the clinical validation of RayStation's electron Monte Carlo code by the use of diodes and plane parallel radiation detectors in homogenous and heterogeneous tissues. Results are evaluated against internationally accepted criteria. METHODS: The Monte Carlo-based electron beam dose calculation code was validated using diodes, air- and liquid-filled parallel radiation detectors on an Elekta linac with beam energies of 4, 6, 8, 10, and 12 MeV. Treatment setups with varying source-to-skin distances, different applicators, various cutouts, and oblique beam incidences were addressed, together with dose prediction behind lung-, air-, and bone-equivalent inserts. According to NCS (Netherlands Commission for Radiation Dosimetry) report 15 for nonstandard treatment setups, a dose agreement of 3% in the δ1 region (high-dose region around Zref ), a distance-to-agreement (DTA) of 3 mm or a dose agreement of 10% in the δ2 region (regions with high-dose gradients), and 4% in the δ4 region (photon tail/low-dose region) were applied. During validation, clinical routine settings of 2 × 2 × 2-mm3 dose voxels and a statistically dose uncertainty of 0.6% (250 000 histories/cm2 ) were used. RESULTS: RayStation's electron Monte Carlo code dose prediction was able to achieve the tolerances of NCS report 15. Output predictions as a function of the SSD improve with energy and applicator size. Cutout data revealed no field size or energy dependence on the accuracy of the dose prediction. Excellent agreement for the oblique incidence data was achieved and a maximum of one voxel difference was obtained for the DTA behind heterogeneous inserts. CONCLUSIONS: The accuracy of RayStation's Monte Carlo-based electron beam dose prediction for Elekta accelerators is confirmed for clinical treatment planning that is not only performed within an acceptable timeframe in terms of the number of histories but also addresses for homogenous and heterogeneous media.

Treatment planning for Flash radiotherapy: General aspects and applications to proton beams.

The increased radioresistence of healthy tissues when irradiated at very high dose rates (known as the Flash effect) is a radiobiological mechanism that is currently investigated to increase the therapeutic ratio of radiotherapy treatments. To maximize the benefits of the clinical application of Flash, a patient-specific balance between different properties of the dose distribution should be found, that is, Flash needs to be one of the variables considered in treatment planning. We investigated the Flash potential of three proton therapy planning and beam delivery techniques, each on a different anatomical region. Based on a set of beam delivery parameters, on hypotheses on the dose and dose rate thresholds needed for the Flash effect to occur, and on two definitions of Flash dose rate, we generated exemplary illustrations of the capabilities of current proton therapy equipment to generate Flash dose distributions. All techniques investigated could both produce dose distributions comparable with a conventional proton plan and reach the Flash regime, to an extent that was strongly dependent on the dose per fraction and the Flash dose threshold. The beam current, Flash dose rate threshold, and dose rate definition typically had a more moderate effect on the amount of Flash dose in normal tissue. A systematic estimation of the impact of Flash on different patient anatomies and treatment protocols is possible only if Flash-specific treatment planning features become readily available. Planning evaluation tools such as a voxel-based dose delivery time structure, and the inclusion in the optimization cost function of parameters directly associated with Flash (e.g., beam current, spot delivery sequence, and scanning speed), are needed to generate treatment plans that are taking full advantage of the potential benefits of the Flash effect.

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

PURPOSE: The primary objective of our study was to perform a quantitative robustness analysis of the dose-averaged linear energy transfer (LETd ) and related RBE-weighted dose in robustly optimized (in terms of the range and set up uncertainties) pencil beam scanning (PBS) proton lung cancer plans. METHODS: In this study, we utilized the 4DCT dataset of six anonymized lung patients. PBS lung plans were generated using a robust optimization technique (range uncertainty: ±3.5% and setup errors: ±5 mm) on the CTV for a total dose of 5000 cGy (RBE) in five fractions using the RBE of 1.1. For each patient, the LETd distributions were calculated for the nominal plan and three groups. Group 1: two plan robustness scenarios for range uncertainties of ±3.5%; Group 2: twelve plan robustness scenarios (range uncertainty (±3.5%) in conjunction with setup errors (±5 mm)); and Group 3: ten different breathing phases of the 4DCT dataset. The RBE-weighted dose to the OARs was evaluated for all robustness scenarios and breathing phases. The variation (∆) in the mean LETd and mean RBE-weighted dose from each group was recorded. RESULTS: The mean LETd in the CTV of nominal PBS lung plans among six patients ranged from 2.2 to 2.6 keV/µm. On average, for the combined range and setup uncertainties, the ∆ in the mean LETd among 12 scenarios of all six patients was 0.6 keV/µm, which is slightly higher than when only the range uncertainties were considered (0.4 keV/µm). The ∆ in the mean LETd in a patient was ≤1.7 keV/µm in the heart and ≤1.2 keV/µm in the esophagus and total lung. The ∆ in the mean RBE-weighted dose in a patient was up to 79 cGy for the total lung, 165 cGy for the heart, and 258 cGy for the esophagus. For ten breathing phases, the ∆ in the mean LETd in a patient was ≤0.3 keV/µm in the CTV, ≤0.5 keV/µm in the heart, ≤0.4 keV/µm in the esophagus, and ≤0.7 keV/µm in the total lung. CONCLUSION: The addition of setup errors to the range uncertainties resulted in slightly less homogeneous LETd distributions. The variations in the mean LETd among the ten breathing phases were slightly larger in the total lung than in the heart and esophagus. The combination of setup and range uncertainties had a greater impact than the effect of breathing phases on the variations in the mean RBE-weighted dose to the OARs. Overall, the LETd distributions in the CTV were less sensitive than those in the OARs to setup errors, range uncertainties, and breathing phases for robustly optimized (in terms of range and setup uncertainities) PBS proton lung cancer plans.

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

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

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

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

Characteristics of very high-energy electron beams for the irradiation of deep-seated targets.

PURPOSE: Driven by advances in accelerator technology and the potential of exploiting the FLASH effect for the treatment of deep-seated targets (>5 cm), there is an active interest in the construction of devices to deliver very high-energy electron (VHEE) beams for radiation therapy. The application of novel VHEE devices, however, requires an assessment of the tradeoffs between the different beam parameter choices including beam energies, beam divergences, and maximal field sizes. This study systematically examines the dosimetric beam properties of VHEE beams, determining their clinical usefulness while marking their limits of applications for different beam configurations. METHODS: We performed Monte Carlo simulations of the dose distributions of electron beams for different energies (25-250 MeV), source-to-surface distances (SSD) (50 cm, 100 cm, parallel), and field sizes (2 cm2  × 2 cm2 to 15 cm2  × 15 cm2 ) in water using a research version of the RayStation treatment planning system (RaySearch Labs 9A IONPG). The beam was simulated using a monoenergetic point source and perfect collimation. Central axis percentage depth dose (PDD) and transverse dose profiles at multiple depths were evaluated and compared to those of MV photon beams. Profile characteristics including therapeutic range (TR) at 90%, proximal fall-off (PFO) at 90%, lateral penumbra (LP) at 90%-10%, and field width (FW) at 90% were obtained. RESULTS: Very high-energy electrons beams with SSD 100 cm and parallel beams (infinite SSD) exhibit a linear to near-linear increase of TR as a function of energy in the simulated energy range and reach values well beyond the typical depths of lesions encountered in clinics (<20 cm). Their TR show a marked field size dependence only for field sizes <10 cm2  × 10 cm2 . For VHEE beams with SSD 50 cm, TR are largely reduced (4-8 cm). For beam energies >150 MeV with large SSD (>100 cm), for many configurations, there is no substantial difference in PDD when adding an opposed beam. This may potentially reduce the number of VHEE beams needed for treatment by a factor of two compared to a treatment using lower energies and lower SSD. In order to cover deep-seated targets homogeneously, VHEE devices with a parallel beam must provide a maximum field size up to several centimeters larger than the tumor size. For the investigated diverging beams, there is not such a significant field width reduction with depth for larger fields as it is compensated by divergence. Penumbrae of VHEE beams are smaller than those of clinical MV photon beams for lower depths (<5 cm) but increase quickly for larger depths. There is only a relatively small dependence of penumbra on the SSD of the beam. CONCLUSIONS: The findings presented in this study assess the performance of VHEE beams and offer a first estimate of treatment indications and tradeoffs for a given design of a VHEE device. SSD >100 cm results in clinically more favorable PDD. Beam energies of 100 MeV and above are needed to cover common tumors (5-15 cm in-depth) conformally. Higher energies provide an additional benefit specifically for small and deep-seated lesions due to their reduced lateral penumbrae.

Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mappings - what is the potential to increase the tumor control probability?

BACKGROUND AND PURPOSE: The aim of this study was to evaluate the potential to increase the tumor control probability (TCP) with 'dose painting by numbers' (DPBN) plans optimized in a treatment planning system (TPS) compared to uniform dose plans. The DPBN optimization was based on our earlier published formalism for prostate cancer that is driven by dose-responses of Gleason scores mapped from apparent diffusion coefficients (ADC). MATERIAL AND METHODS: For 17 included patients, a set of DPBN plans were optimized in a TPS by maximizing the TCP for an equal average dose to the prostate volume (CTVT) as for a conventional uniform dose treatment. For the plan optimizations we applied different photon energies, different precisions for the ADC-to-Gleason mappings, and different CTVT positioning uncertainties. The TCP increasing potential was evaluated by the DPBN efficiency, defined as the ratio of TCP increases for DPBN plans by TCP increases for ideal DPBN prescriptions (optimized without considering radiation transport phenomena, uncertainties of the CTVT positioning, and uncertainties of the ADC-to-Gleason mapping). RESULTS: The median DPBN efficiency for the most conservative planning scenario optimized with a low precision ADC-to-Gleason mapping, and a positioning uncertainty of 0.6 cm was 10%, meaning that more than half of the patients had a TCP gain of at least 10% of the TCP for an ideal DPBN prescription. By increasing the precision of the ADC-to-Gleason mapping, and decreasing the positioning uncertainty the median DPBN efficiency increased by up to 40%. CONCLUSIONS: TCP increases with DPBN plans optimized in a TPS were found more likely with a high precision mapping of image data into dose-responses and a high certainty of the tumor positioning. These findings motivate further development to ensure precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor positioning when implementing DPBN clinically.