Dual-energy CT-based stopping power prediction for dental materials in particle therapy.

Radiotherapy with protons or light ions can offer accurate and precise treatment delivery. Accurate knowledge of the stopping power ratio (SPR) distribution of the tissues in the patient is crucial for improving dose prediction in patients during planning. However, materials of uncertain stoichiometric composition such as dental implant and restoration materials can substantially impair particle therapy treatment planning due to related SPR prediction uncertainties. This study investigated the impact of using dual-energy computed tomography (DECT) imaging for characterizing and compensating for commonly used dental implant and restoration materials during particle therapy treatment planning. Radiological material parameters of ten common dental materials were determined using two different DECT techniques: sequential acquisition CT (SACT) and dual-layer spectral CT (DLCT). DECT-based direct SPR predictions of dental materials via spectral image data were compared to conventional single-energy CT (SECT)-based SPR predictions obtained via indirect CT-number-to-SPR conversion. DECT techniques were found overall to reduce uncertainty in SPR predictions in dental implant and restoration materials compared to SECT, although DECT methods showed limitations for materials containing elements of a high atomic number. To assess the influence on treatment planning, an anthropomorphic head phantom with a removable tooth containing lithium disilicate as a dental material was used. The results indicated that both DECT techniques predicted similar ranges for beams unobstructed by dental material in the head phantom. When ion beams passed through the lithium disilicate restoration, DLCT-based SPR predictions using a projection-based method showed better agreement with measured reference SPR values (range deviation: 0.2 mm) compared to SECT-based predictions. DECT-based SPR prediction may improve the management of certain non-tissue dental implant and restoration materials and subsequently increase dose prediction accuracy.

Combined RBE and OER optimization in proton therapy with FLUKA based on EF5-PET.

INTRODUCTION: Tumor hypoxia is associated with poor treatment outcome. Hypoxic regions are more radioresistant than well-oxygenated regions, as quantified by the oxygen enhancement ratio (OER). In optimization of proton therapy, including OER in addition to the relative biological effectiveness (RBE) could therefore be used to adapt to patient-specific radioresistance governed by intrinsic radiosensitivity and hypoxia. METHODS: A combined RBE and OER weighted dose (ROWD) calculation method was implemented in a FLUKA Monte Carlo (MC) based treatment planning tool. The method is based on the linear quadratic model, with α and ß parameters as a function of the OER, and therefore a function of the linear energy transfer (LET) and partial oxygen pressure (pO2 ). Proton therapy plans for two head and neck cancer (HNC) patients were optimized with pO2 estimated from [18 F]-EF5 positron emission tomography (PET) images. For the ROWD calculations, an RBE of 1.1 (RBE1.1,OER ) and two variable RBE models, Rørvik (ROR) and McNamara (MCN), were used, alongside a reference plan without incorporation of OER (RBE1.1 ). RESULTS: For the HNC patients, treatment plans in line with the prescription dose and with acceptable target ROWD could be generated with the established tool. The physical dose was the main factor modulated in the ROWD. The impact of incorporating OER during optimization of HNC patients was demonstrated by the substantial difference found between ROWD and physical dose in the hypoxic tumor region. The largest physical dose differences between the ROWD optimized plans and the reference plan was 12.2 Gy. CONCLUSION: The FLUKA MC based tool was able to optimize proton treatment plans taking the tumor pO2 distribution from hypoxia PET images into account. Independent of RBE-model, both elevated LET and physical dose were found in the hypoxic regions, which shows the potential to increase the tumor control compared to a conventional optimization approach.

Do We Preserve Tumor Control Probability (TCP) in FLASH Radiotherapy? A Model-Based Analysis.

Reports of concurrent sparing of normal tissue and iso-effective treatment of tumors at ultra-high dose-rates (uHDR) have fueled the growing field of FLASH radiotherapy. However, iso-effectiveness in tumors is often deduced from the absence of a significant difference in their growth kinetics. In a model-based analysis, we investigate the meaningfulness of these indications for the clinical treatment outcome. The predictions of a previously benchmarked model of uHDR sparing in the "UNIfied and VERSatile bio response Engine" (UNIVERSE) are combined with existing models of tumor volume kinetics as well as tumor control probability (TCP) and compared to experimental data. The potential TCP of FLASH radiotherapy is investigated by varying the assumed dose-rate, fractionation schemes and oxygen concentration in the target. The developed framework describes the reported tumor growth kinetics appropriately, indicating that sparing effects could be present in the tumor but might be too small to be detected with the number of animals used. The TCP predictions show the possibility of substantial loss of treatment efficacy for FLASH radiotherapy depending on several variables, including the fractionation scheme, oxygen level, and DNA repair kinetics. The possible loss of TCP should be seriously considered when assessing the clinical viability of FLASH treatments.

Dual-layer spectral CT for proton, helium, and carbon ion beam therapy planning of brain tumors.

Pretreatment computed tomography (CT) imaging is an essential component of the particle therapy treatment planning chain. Treatment planning and optimization with charged particles require accurate and precise estimations of ion beam range in tissues, characterized by the stopping power ratio (SPR). Reduction of range uncertainties arising from conventional CT-number-to-SPR conversion based on single-energy CT (SECT) imaging is of importance for improving clinical practice. Here, the application of a novel imaging and computational methodology using dual-layer spectral CT (DLCT) was performed toward refining patient-specific SPR estimates. A workflow for DLCT-based treatment planning was devised to evaluate SPR prediction for proton, helium, and carbon ion beam therapy planning in the brain. DLCT- and SECT-based SPR predictions were compared in homogeneous and heterogeneous anatomical regions. This study included eight patients scanned for diagnostic purposes with a DLCT scanner. For each patient, four different treatment plans were created, simulating tumors in different parts of the brain. For homogeneous anatomical regions, mean SPR differences of about 1% between the DLCT- and SECT-based approaches were found. In plans of heterogeneous anatomies, relative (absolute) proton range shifts of 0.6% (0.4 mm) in the mean and up to 4.4% (2.1 mm) at the distal fall-off were observed. In the investigated cohort, 12% of the evaluated organs-at-risk (OARs) presented differences in mean or maximum dose of more than 0.5 Gy (RBE) and up to 6.8 Gy (RBE) over the entire treatment. Range shifts and dose differences in OARs between DLCT and SECT in helium and carbon ion treatment plans were similar to protons. In the majority of investigated cases (75th percentile), SECT- and DLCT-based range estimations were within 0.6 mm. Nonetheless, the magnitude of patient-specific range deviations between SECT and DLCT was clinically relevant in heterogeneous anatomical sites, suggesting further study in larger, more diverse cohorts. Results indicate that patients with brain tumors may benefit from DLCT-based treatment planning.

Impact of DNA Repair Kinetics and Dose Rate on RBE Predictions in the UNIVERSE.

Accurate knowledge of the relative biological effectiveness (RBE) and its dependencies is crucial to support modern ion beam therapy and its further development. However, the influence of different dose rates of the reference radiation and ion beam are rarely considered. The ion beam RBE-model within our "UNIfied and VERSatile bio response Engine" (UNIVERSE) is extended by including DNA damage repair kinetics to investigate the impact of dose-rate effects on the predicted RBE. It was found that dose-rate effects increase with dose and biological effects saturate at high dose-rates, which is consistent with data- and model-based studies in the literature. In a comparison with RBE measurements from a high dose in-vivo study, the predictions of the presented modification were found to be improved in comparison to the previous version of UNIVERSE and existing clinical approaches that disregard dose-rate effects. Consequently, DNA repair kinetics and the different dose rates applied by the reference and ion beams might need to be considered in biophysical models to accurately predict the RBE. Additionally, this study marks an important step in the further development of UNIVERSE, extending its capabilities in giving theoretical guidance to support progress in ion beam therapy.

The Impact of Sub-Millisecond Damage Fixation Kinetics on the In Vitro Sparing Effect at Ultra-High Dose Rate in UNIVERSE.

The impact of the exact temporal pulse structure on the potential cell and tissue sparing of ultra-high dose-rate irradiation applied in FLASH studies has gained increasing attention. A previous version of our biophysical mechanistic model (UNIVERSE: UNIfied and VERSatile bio response Engine), based on the oxygen depletion hypothesis, has been extended in this work by considering oxygen-dependent damage fixation dynamics on the sub-milliseconds scale and introducing an explicit implementation of the temporal pulse structure. The model successfully reproduces in vitro experimental data on the fast kinetics of the oxygen effect in irradiated mammalian cells. The implemented changes result in a reduction in the assumed amount of oxygen depletion. Furthermore, its increase towards conventional dose-rates is parameterized based on experimental data from the literature. A recalculation of previous benchmarks shows that the model retains its predictive power, while the assumed amount of depleted oxygen approaches measured values. The updated UNIVERSE could be used to investigate the impact of different combinations of pulse structure parameters (e.g., dose per pulse, pulse frequency, number of pulses, etc.), thereby aiding the optimization of potential clinical application and the development of suitable accelerators.

Modeling Direct and Indirect Action on Cell Survival After Photon Irradiation under Normoxia and Hypoxia.

The demand for personalized medicine in radiotherapy has been met by a surge of mechanistic models offering predictions of the biological effect of ionizing radiation under consideration of a growing number of parameters. We present an extension of our existing model of cell survival after photon irradiation to explicitly differentiate between the damage inflicted by the direct and indirect (radicals-mediated) action of ionizing radiation. Within our approach, we assume that the oxygenation status affects the indirect action. The effect of different concentrations of dimethyl sulfoxide (DMSO), an effective radical scavenger, has been simulated at different dose levels in normoxic and hypoxic conditions for various cell lines. Our model is found to accurately predict experimental data available in literature, validating the assumptions made in our approach. The presented extension adds further flexibility to our model and could act as basis for further developments of our model.

In Vivo Validation of the BIANCA Biophysical Model: Benchmarking against Rat Spinal Cord RBE Data.

(1) Background: Cancer ion therapy is constantly growing thanks to its increased precision and, for heavy ions, its increased biological effectiveness (RBE) with respect to conventional photon therapy. The complex dependence of RBE on many factors demands biophysical modeling. Up to now, only the Local Effect Model (LEM), the Microdosimetric Kinetic Model (MKM), and the "mixed-beam" model are used in clinics. (2) Methods: In this work, the BIANCA biophysical model, after extensive benchmarking in vitro, was applied to develop a database predicting cell survival for different ions, energies, and doses. Following interface with the FLUKA Monte Carlo transport code, for the first time, BIANCA was benchmarked against in vivo data obtained by C-ion or proton irradiation of the rat spinal cord. The latter is a well-established model for CNS (central nervous system) late effects, which, in turn, are the main dose-limiting factors for head-and-neck tumors. Furthermore, these data have been considered to validate the LEM version applied in clinics. (3) Results: Although further benchmarking is desirable, the agreement between simulations and data suggests that BIANCA can predict RBE for C-ion or proton treatment of head-and-neck tumors. In particular, the agreement with proton data may be relevant if the current assumption of a constant proton RBE of 1.1 is revised. (4) Conclusions: This work provides the basis for future benchmarking against patient data, as well as the development of other databases for specific tumor types and/or normal tissues.

Modeling the Effect of Hypoxia and DNA Repair Inhibition on Cell Survival After Photon Irradiation.

Mechanistic approaches to modeling the effects of ionizing radiation on cells are on the rise, promising a better understanding of predictions and higher flexibility concerning conditions to be accounted for. In this work we modified and extended a previously published mechanistic model of cell survival after photon irradiation under hypoxia to account for radiosensitization caused by deficiency or inhibition of DNA damage repair enzymes. The model is shown to be capable of describing the survival data of cells with DNA damage repair deficiency, both under norm- and hypoxia. We find that our parameterization of radiosensitization is invariant under change of oxygen status, indicating that the relevant parameters for both mechanisms can be obtained independently and introduced freely to the model to predict their combined effect.

Monte Carlo simulations of a low energy proton beamline for radiobiological experiments.

BACKGROUND: In order to determine the relative biological effectiveness (RBE) of protons with high accuracy, radiobiological experiments with detailed knowledge of the linear energy transfer (LET) are needed. Cell survival data from high LET protons are sparse and experiments with low energy protons to achieve high LET values are therefore required. The aim of this study was to quantify LET distributions from a low energy proton beam by using Monte Carlo (MC) simulations, and to further compare to a proton beam representing a typical minimum energy available at clinical facilities. MATERIALS AND METHODS: A Markus ionization chamber and Gafchromic films were employed in dose measurements in the proton beam at Oslo Cyclotron Laboratory. Dose profiles were also calculated using the FLUKA MC code, with the MC beam parameters optimized based on comparisons with the measurements. LET spectra and dose-averaged LET (LETd) were then estimated in FLUKA, and compared with LET calculated from an 80 MeV proton beam. RESULTS: The initial proton energy was determined to be 15.5 MeV, with a Gaussian energy distribution of 0.2% full width at half maximum (FWHM) and a Gaussian lateral spread of 2 mm FWHM. The LETd increased with depth, from approximately 5 keV/µm in the entrance to approximately 40 keV/µm in the distal dose fall-off. The LETd values were considerably higher and the LET spectra were much narrower than the corresponding spectra from the 80 MeV beam. CONCLUSIONS: MC simulations accurately modeled the dose distribution from the proton beam and could be used to estimate the LET at any position in the setup. The setup can be used to study the RBE for protons at high LETd, which is not achievable in clinical proton therapy facilities.

Linear energy transfer distributions in the brainstem depending on tumour location in intensity-modulated proton therapy of paediatric cancer.

BACKGROUND: For tumours near organs at risk, there is concern about unintended increase in biological dose from elevated linear energy transfer (LET) at the distal end of treatment fields. The objective of this study was therefore to investigate how different paediatric posterior fossa tumour locations impact LET and biological dose to the brainstem during intensity-modulated proton therapy (IMPT). MATERIAL AND METHODS: Multiple IMPT plans were generated for four different simulated tumour locations relative to the brainstem for a five-year-old male patient. A prescribed dose of 59.4 Gy(RBE) was applied to the planning target volumes (PTVs). Plans with two lateral and one posterior non-coplanar fields were created, along with plans with modified field arrangements. The dose-averaged LET (LETd) and the physical dose × RBELET (D × RBELET), where RBELET=1+c × LETd, were calculated using the FLUKA Monte Carlo code. A scaling parameter c was applied to make the RBELET represent variations in the biological effect due to LET. RESULTS: High LETd values surrounded parts of the PTV and encompassed portions of the brainstem. Mean LETd values in the brainstem were 3.2-6.6 keV/µm. The highest absolute brainstem LETd values were seen with the tumour located most distant from the brainstem, whereas lower and more homogeneous LETd values were seen when the tumour invaded the brainstem. In contrast, the highest mean D × RBELET values were found in the latter case (54.0 Gy(RBE)), while the case with largest distance between tumour and brainstem had a mean D × RBELET of 1.8 Gy(RBE). CONCLUSIONS: Using IMPT to treat posterior fossa tumours may result in high LETd values within the brainstem, particularly if the tumour volume is separated from the brainstem. However, the D × RBELET was greater for tumours that approached or invaded the brainstem. Changing field angles showed a reduction of LETd and D × RBELET in the brainstem.

Proton beam radiotherapy: report of the first ten patients treated at the "Centro Nazionale di Adroterapia Oncologica (CNAO)" for skull base and spine tumours.

PURPOSE: The Italian National Centre for Oncological Hadrontherapy (Centro Nazionale di Adroterapia Oncologica, CNAO), equipped with a proton and ion synchrotron, started clinical activity in September 2011. The clinical and technical characteristics of the first ten proton beam radiotherapy treatments are reported. MATERIALS AND METHODS: Ten patients, six males and four females (age range 27-73 years, median 55.5), were treated with proton beam radiotherapy. After one to two surgical procedures, seven patients received a histological diagnosis of chordoma (of the skull base in three cases, the cervical spine in one case and the sacrum in three cases) and three of low-grade chondrosarcoma (skull base). Prescribed doses were 74 GyE for chordoma and 70 GyE for chondrosarcoma at 2 GyE/fraction delivered 5 days per week. RESULTS: Treatment was well tolerated without toxicity-related interruptions. The maximal acute toxicity was grade 2, with oropharyngeal mucositis, nausea and vomiting for the skull base tumours, and grade 2 dermatitis for the sacral tumours. After 6-12 months of follow-up, no patient developed tumour progression. CONCLUSIONS: The analysis of the first ten patients treated with proton therapy at CNAO showed that this treatment was feasible and safe. Currently, patient accrual into these as well as other approved protocols is continuing, and a longer follow-up period is needed to assess tumour control and late toxicity.

Comment on 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation'.

We comment on the recently published study 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation' by Shiraishiet al. While the general approach of the study may be appropriate, we wish to comment on its limitations and point out issues concerning their choice of the benchmarking and fitting data. The approach by the authors could become viable in an extended form once more comprehensive data is available.

Diamond detectors for dose and instantaneous dose-rate measurements for ultra-high dose-rate scanned helium ion beams.

BACKGROUND: The possible emergence of the FLASH effect-the sparing of normal tissue while maintaining tumor control-after irradiations at dose-rates exceeding several tens of Gy per second, has recently spurred a surge of studies attempting to characterize and rationalize the phenomenon. Investigating and reporting the dose and instantaneous dose-rate of ultra-high dose-rate (UHDR) particle radiotherapy beams is crucial for understanding and assessing the FLASH effect, towards pre-clinical application and quality assurance programs. PURPOSE: The purpose of the present work is to investigate a novel diamond-based detector system for dose and instantaneous dose-rate measurements in UHDR particle beams. METHODS: Two types of diamond detectors, a microDiamond (PTW 60019) and a diamond detector prototype specifically designed for operation in UHDR beams (flashDiamond), and two different readout electronic chains, were investigated for absorbed dose and instantaneous dose-rate measurements. The detectors were irradiated with a helium beam of 145.7 MeV/u under conventional and UHDR delivery. Dose-rate delivery records by the monitoring ionization chamber and diamond detectors were studied for single spot irradiations. Dose linearity at 5 cm depth and in-depth dose response from 2 to 16 cm were investigated for both measurement chains and both detectors in a water tank. Measurements with cylindrical and plane-parallel ionization chambers as well as Monte-Carlo simulations were performed for comparisons. RESULTS: Diamond detectors allowed for recording the temporal structure of the beam, in good agreement with the one obtained by the monitoring ionization chamber. A better time resolution of the order of few µs was observed as compared to the approximately 50 µs of the monitoring ionization chamber. Both diamonds detectors show an excellent linearity response in both delivery modalities. Dose values derived by integrating the measured instantaneous dose-rates are in very good agreement with the ones obtained by the standard electrometer readings. Bragg peak curves confirmed the consistency of the charge measurements by the two systems. CONCLUSIONS: The proposed novel dosimetric system allows for a detailed investigation of the temporal evolution of UHDR beams. As a result, reliable and accurate determinations of dose and instantaneous dose-rate are possible, both required for a comprehensive characterization of UHDR beams and relevant for FLASH effect assessment in clinical treatments.

Development and validation of MonteRay, a fast Monte Carlo dose engine for carbon ion beam radiotherapy.

BACKGROUND: Monte Carlo (MC) simulations are considered the gold-standard for accuracy in radiotherapy dose calculation; so far however, no commercial treatment planning system (TPS) provides a fast MC for supporting clinical practice in carbon ion therapy. PURPOSE: To extend and validate the in-house developed fast MC dose engine MonteRay for carbon ion therapy, including physical and biological dose calculation. METHODS: MonteRay is a CPU MC dose calculation engine written in C++ that is capable of simulating therapeutic proton, helium and carbon ion beams. In this work, development steps taken to include carbon ions in MonteRay are presented. Dose distributions computed with MonteRay are evaluated using a comprehensive validation dataset, including various measurements (pristine Bragg peaks, spread out Bragg peaks in water and behind an anthropomorphic phantom) and simulations of a patient plan. The latter includes both physical and biological dose comparisons. Runtimes of MonteRay were evaluated against those of FLUKA MC on a standard benchmark problem. RESULTS: Dosimetric comparisons between MonteRay and measurements demonstrated good agreement. In terms of pristine Bragg peaks, mean errors between simulated and measured integral depth dose distributions were between -2.3% and +2.7%. Comparing SOBPs at 5, 12.5 and 20 cm depth, mean absolute relative dose differences were 0.9%, 0.7% and 1.6% respectively. Comparison against measurements behind an anthropomorphic head phantom revealed mean absolute dose differences of 1.2 % ± 1.1 % $1.2\% \pm 1.1\;\%$ with global 3%/3 mm 3D-γ passing rates of 99.3%, comparable to those previously reached with FLUKA (98.9%). Comparisons against dose predictions computed with the clinical treatment planning tool RayStation 11B for a meningioma patient plan revealed excellent local 1%/1 mm 3D-γ passing rates of 98% for physical and 94% for biological dose. In terms of runtime, MonteRay achieved speedups against reference FLUKA simulations ranging from 14× to 72×, depending on the beam's energy and the step size chosen. CONCLUSIONS: Validations against clinical dosimetric measurements in homogeneous and heterogeneous scenarios and clinical TPS calculations have proven the validity of the physical models implemented in MonteRay. To conclude, MonteRay is viable as a fast secondary MC engine for supporting clinical practice in proton, helium and carbon ion radiotherapy.

Development and verification of an electron Monte Carlo engine for applications in intraoperative radiation therapy.

BACKGROUND: In preparation of future clinical trials employing the Mobetron electron linear accelerator to deliver FLASH Intraoperative Radiation Therapy (IORT), the development of a Monte Carlo (MC)-based framework for dose calculation was required. PURPOSE: To extend and validate the in-house developed fast MC dose engine MonteRay (MR) for future clinical applications in IORT. METHODS: MR is a CPU MC dose calculation engine written in C++ that is capable of simulating therapeutic proton, helium, and carbon ion beams. In this work, development steps are taken to include electrons and photons in MR are presented. To assess MRs accuracy, MR generated simulation results were compared against FLUKA predictions in water, in presence of heterogeneities as well as in an anthropomorphic phantom. Additionally, dosimetric data has been acquired to evaluate MRs accuracy in predicting dose-distributions generated by the Mobetron accelerator. Runtimes of MR were evaluated against those of the general-purpose MC code FLUKA on standard benchmark problems. RESULTS: MR generated dose distributions for electron beams incident on a water phantom match corresponding FLUKA calculated distributions within 2.3% with range values matching within 0.01 mm. In terms of dosimetric validation, differences between MR calculated and measured dose values were below 3% for almost all investigated positions within the water phantom. Gamma passing rate (1%/1 mm) for the scenarios with inhomogeneities and gamma passing rate (3%/2 mm) with the anthropomorphic phantom, were > 99.8% and 99.4%, respectively. The average dose differences between MR (FLUKA) and the measurements was 1.26% (1.09%). Deviations between MR and FLUKA were well within 1.5% for all investigated depths and 0.6% on average. In terms of runtime, MR achieved a speedup against reference FLUKA simulations of about 13 for 10 MeV electrons. CONCLUSIONS: Validations against general purpose MC code FLUKA predictions and experimental dosimetric data have proven the validity of the physical models implemented in MR for IORT applications. Extending the work presented here, MR will be interfaced with external biophysical models to allow accurate FLASH biological dose predictions in IORT.

Development and benchmarking of a dose rate engine for raster-scanned FLASH helium ions.

BACKGROUND: Radiotherapy with charged particles at high dose and ultra-high dose rate (uHDR) is a promising technique to further increase the therapeutic index of patient treatments. Dose rate is a key quantity to predict the so-called FLASH effect at uHDR settings. However, recent works introduced varying calculation models to report dose rate, which is susceptible to the delivery method, scanning path (in active beam delivery) and beam intensity. PURPOSE: This work introduces an analytical dose rate calculation engine for raster scanned charged particle beams that is able to predict dose rate from the irradiation plan and recorded beam intensity. The importance of standardized dose rate calculation methods is explored here. METHODS: Dose is obtained with an analytical pencil beam algorithm, using pre-calculated databases for integrated depth dose distributions and lateral penumbra. Dose rate is then calculated by combining dose information with the respective particle fluence (i.e., time information) using three dose-rate-calculation models (mean, instantaneous, and threshold-based). Dose rate predictions for all three models are compared to uHDR helium ion beam (145.7 MeV/u, range in water of approximatively 14.6 cm) measurements performed at the Heidelberg Ion Beam Therapy Center (HIT) with a diamond-detector prototype. Three scanning patterns (scanned or snake-like) and four field sizes are used to investigate the dose rate differences. RESULTS: Dose rate measurements were in good agreement with in-silico generated distributions using the here introduced engine. Relative differences in dose rate were below 10% for varying depths in water, from 2.3 to 14.8 cm, as well as laterally in a near Bragg peak area. In the entrance channel of the helium ion beam, dose rates were predicted within 7% on average for varying irradiated field sizes and scanning patterns. Large differences in absolute dose rate values were observed for varying calculation methods. For raster-scanned irradiations, the deviation between mean and threshold-based dose rate at the investigated point was found to increase with the field size up to 63% for a 10 mm × 10 mm field, while no significant differences were observed for snake-like scanning paths. CONCLUSIONS: This work introduces the first dose rate calculation engine benchmarked to instantaneous dose rate, enabling dose rate predictions for physical and biophysical experiments. Dose rate is greatly affected by varying particle fluence, scanning path, and calculation method, highlighting the need for a consensus among the FLASH community on how to calculate and report dose rate in the future. The here introduced engine could help provide the necessary details for the analysis of the sparing effect and uHDR conditions.

Ultra-High Dose Rate Helium Ion Beams: First In Vivo Evidence for Neuroprotective FLASH Effect.

Purpose: To investigate ultra-high-dose rate helium ion irradiation and its potential FLASH sparing effect with the endpoint acute brain injury in preclinical in vivo settings. Material and methods: Raster-scanned helium ion beams were administered to explore and compare the impact of dose rate variations between standard dose rate (SDR at 0.2 Gy/s) and FLASH (at 141 Gy/s) radiotherapy (RT). Irradiation-induced brain injury was investigated in healthy C57BL/6 mice via DNA damage response kinetic studies using nuclear γH2AX as a surrogate for double-strand breaks (DSB). The integrity of the neurovascular and immune compartments was assessed via CD31+ microvascular density and microglia/macrophages activation. Iba1+ ramified and CD68+ phagocytic microglia/macrophages were quantified, together with the expression of inducible nitric oxide synthetase (iNOS). Results: Helium FLASH RT significantly prevented acute brain tissue injury compared with SDR. This was demonstrated by reduced levels of DSB and structural preservation of the neurovascular endothelium after FLASH RT. Moreover, FLASH RT exhibited reduced activation of neuroinflammatory signals compared with SDR, as detected by quantification of CD68+ iNOS+ microglia/macrophages. Conclusion: To our knowledge, this is the first report on the FLASH-sparing neuroprotective effect of raster scanning helium ion radiotherapy in vivo.

Understanding Relative Biological Effectiveness and Clinical Outcome of Prostate Cancer Therapy Using Particle Irradiation: Analysis of Tumor Control Probability With the Modified Microdosimetric Kinetic Model.

PURPOSE: Recent experimental studies and clinical trial results might indicate that-at least for some indications-continued use of the mechanistic model for relative biological effectiveness (RBE) applied at carbon ion therapy facilities in Europe for several decades (LEM-I) may be unwarranted. We present a novel clinical framework for prostate cancer treatment planning and tumor control probability (TCP) prediction based on the modified microdosimetric kinetic model (mMKM) for particle therapy. METHODS AND MATERIALS: Treatment plans of 91 patients with prostate tumors (proton: 46, carbon ions: 45) applying 66 GyRBE [RBE = 1.1 for protons and LEM-I, (α/ß)x = 2.0 Gy, for carbon ions] in 20 fractions were recalculated using mMKM [(α/ß)x = 3.1 Gy]). Based solely on the response data of photon-irradiated patient groups stratified according to risk and usage of androgen deprivation therapy, we derived parameters for an mMKM-based Poisson-TCP model. Subsequently, new carbon and helium ion plans, adhering to prescribed biological dose criteria, were generated. These were systematically compared with the clinical experience of Japanese centers employing an analogous fractionation scheme and existing proton plans. RESULTS: mMKM predictions suggested significant biological dose deviation between the proton and carbon ion arms. Patients irradiated with protons received (3.25 ± 0.08) GyRBEmMKM/Fx, whereas patients treated with carbon ions received(2.51 ± 0.05) GyRBEmMKM/Fx. TCP predictions were (86 ± 3)% for protons and (52 ± 4)% for carbon ions, matching the clinical outcome of 85% and 50%. Newly optimized carbon ion plans, guided by the mMKM/TCP model, effectively replicated clinical data from Japanese centers. Using mMKM, helium ions exhibited similar target coverage as proton and carbon ions and improved rectum and bladder sparing compared with proton. CONCLUSIONS: Our mMKM-based model for prostate cancer treatment planning and TCP prediction was validated against clinical data for proton and carbon ion therapy, and its application was extended to helium ion therapy. Based on the data presented in this work, mMKM seems to be a good candidate for clinical biological calculations in carbon ion therapy for prostate cancer.

Towards precise LET measurements based on energy deposition of therapeutic ions in Timepix3 detectors.

Objective.There is an increasing interest in calculating and measuring linear energy transfer (LET) spectra in particle therapy in order to assess their impact in biological terms. As such, the accuracy of the particle fluence energy spectra becomes paramount. This study focuses on quantifying energy depositions of distinct proton, helium, carbon, and oxygen ion beams using a silicon pixel detector developed at CERN to determine LET spectra in silicon.Approach.While detection systems have been investigated in this pursuit, the scarcity of detectors capable of providing per-ion data with high spatial and temporal resolution remains an issue. This gap is where silicon pixel detector technology steps in, enabling online tracking of single-ion energy deposition. The used detector consisted of a 300µm thick silicon sensor operated in partial depletion.Main results.During post-processing, artifacts in the acquired signals were identified and methods for their corrections were developed. Subsequently, a correlation between measured and Monte Carlo-based simulated energy deposition distributions was performed, relying on a two-step recalibration approach based on linear and saturating exponential models. Despite the observed saturation effects, deviations were confined below 7% across the entire investigated range of track-averaged LET values in silicon from 0.77 keVµm-1to 93.16 keVµm-1.Significance.Simulated and measured mean energy depositions were found to be aligned within 7%, after applying artifact corrections. This extends the range of accessible LET spectra in silicon to clinically relevant values and validates the accuracy and reliability of the measurements. These findings pave the way towards LET-based dosimetry through an approach to translate these measurements to LET spectra in water. This will be addressed in a future study, extending functionality of treatment planning systems into clinical routine, with the potential of providing ion-beam therapy of utmost precision to cancer patients.