Analytical calculation of the dose to a spherical target by an ion at almost all impact parameters, and calculation of the energy deposition spectra.

Objective. Clinical proton therapy assumes a constant relative biological effectiveness (RBE) of 1.1, although proton RBE varies with linear energy transfer (LET). High-energy transmission beams (TBs) deposit dose entirely within the low-LET entrance plateau, suggesting a potentially distinct radiobiological behavior compared with conventional spread-out Bragg peaks (SOBP).Approach.We performedin vitroclonogenic survival experiments with four cell lines (A431, CRL2189, V79, A253) irradiated with TB, SOBP, mixed fields (SOBP + TB), and reference photons. Early post-irradiation metabolic viability was also assessed using the MTT assay.Main results. TB irradiation produced RBE values close to unity at 2 Gy (median 1.04-1.07), comparable to photons, whereas SOBP beams showed higher RBE values (≈1.10-1.35). In the tested 40% TB/60% SOBP configuration, the mixed-field response remained biologically indistinguishable from conventional SOBP and was well described by the prediction of the theory of dual radiation action (TDRA) derived from the independently measured TB and SOBP survival parameters. MTT viability measurements showed the same overall hierarchy, with TB responses close to photons and stronger effects observed for SOBP and SOBP + TB.Significance. High-energy proton TBs operate in a near-photon radiobiological regime. A mixed field containing 40% TB remained biologically indistinguishable from conventional SOBP and was well described by the TDRA. Complementary viability measurements showed the same modality-dependent pattern.

225Ac]Ac-Macropa-PEG4-FPA150 enables targeted alpha therapy of B7-H4-Expressing tumors.

Objective. Proton therapy (PT) doses are commonly prescribed assuming a constant relative biological effectiveness (RBE) of 1.1, despite extensive evidence that RBE varies with radiation quality, dose, and tissue type. Here, we introduce the photon isoeffective dose (PHID) model, a cell line-specific formalism for computing photon isoeffective (IsoE) doses in PT. The model is based on the linear-quadratic framework and accounts for mixed charged-particle fields, linear energy transfer (LET)-dependent radiobiological parameters, sublethal damage repair, and synergistic effects among field components.Approach. PHID was developed for head-and-neck squamous cell carcinoma (HNSCC), human skin fibroblasts, and Chinese hamster fibroblasts (V79 cell lines, using ion-specific, LET-dependentαandβparameters derived from the BIANCA biophysical model. PHID was evaluated for monoenergetic and modulated proton beams by analyzing the impact of secondary particles, cell line, reference radiation, and LET on dose calculations. Results were compared with those obtained using fixed-RBE approach and with several phenomenological RBE models. A tumor control probability (TCP) model explored clinical implications in a proof-of-concept scenario.Main results. PHID predicts depth- and dose-dependent IsoE doses that can substantially deviate from RBE-weighted doses, particularly in high-LET regions near the distal edge of the Bragg peak. The model reproduces the increase of RBE with increasing LET and decreasing dose per fraction, and reveals a strong dependence on cell line and reference radiation. Alpha particles were the dominant high-LET contributors beyond protons. Compared with phenomenological RBE models, PHID yields intermediate RBE ranges consistent with its cell-specific construction and provides a mechanistic interpretation of observed trends. TCP calculations showed measurable differences relative to the fixed-RBE approach.Significance. PHID provides a biophysically grounded alternative to fixed-RBE prescriptions in PT. This framework can be extended to other particle-based radiotherapy modalities, including carbon-ion and alpha-particle therapy, where high-LET components play a central role.

Objective.Biological effect of charged particles characterized by cell surviving fraction (SF) depends on physical factors such as particle type, dose, beam quality descriptors, e.g. linear energy transfer or lineal energy. Driven by the crucial role of DNA double-strand breaks (DSBs) as indicators of cellular responses to ionizing radiation, this study aims to develop a cell-specific SF model based on the initial DSBs of varying complexities applicable to photon, proton, and carbon-ion irradiations across the investigated beam qualities.Approach.Microscopic Monte Carlo simulations were used to calculate DSBs for experiments measuring SF of H460 and H1437 lung cancer cells irradiated by proton (dose-mean lineal energyy¯d2.0-20.0 keVµm-1), carbon ions (y¯d18.6-87.9 keVµm-1) and reference137Cs photon beam. We modeled SF as a third-order polynomial function of DSBs of various complexities with two, three, and more strand breaks. The function was determined by a data fitting process.Main Results.For each cell line, a single model was able to accurately describe SF in experiments under all 19 irradiation conditions with different particle types andy¯dvalues. Root mean square errors were 0.218 for H460 cells and 0.170 for H1437 cells. When applying the model to a proton spread-out-Bragg-peak case, calculated relative biological effectiveness at SF = 0.1 were 1.01-1.42 for the H460 cells and 1.03-1.65 for the H1437 cells depending on the depth.Significance.We successfully developed an SF model using DSBs of various complexities as input variables. The model provides a unified description of photon, proton, and carbon-ion irradiations across investigated beam qualities.

Objective.Real-time imaging of alpha-particle tracks in scintillators is promising for microdosimetric studies of alpha-emitting radionuclides in targeted radionuclide therapy. However, when inorganic scintillators such as Gd3Al2Ga3O12(GAGG) are used, the observed track characteristics differ from those in biological tissues. This study aimed to validate the GATE (geant4 application for tomographic emission) simulation framework using experimentally obtained alpha-particle track images and to compare track characteristics in GAGG and biological tissue-equivalent media. Such analysis is essential for quantitatively interpreting track images obtained with scintillator-based imaging systems in microdosimetry.Approach.Alpha-particle track images were obtained using a real-time high-resolution imaging system based on a GAGG scintillator and an Am-241 source. Simulated track ranges were compared with experimental images. The finalRange parameter in GATE was optimized because it affects the Bragg peak shape of alpha particles. Furthermore, simulated track characteristics in biological tissue-equivalent media were quantitatively compared with those in GAGG.Main Results.A bright endpoint artifact was identified in simulated alpha-particle tracks, originating from the particle transport mechanism implemented in Geant4/GATE and depending on the finalRange value. The simulated and experimental ranges of alpha particles in GAGG were 8.20μm and 8.05μm, respectively, demonstrating good agreement. Linear energy transfer (LET) values in GAGG were 2.8 and 1.8 times higher than those in adipose and bone, respectively.Significance.Recognizing this artifact is important for correct interpretation of LET distributions in microdosimetric evaluations. Our results demonstrated that GATE can accurately reproduce alpha-particle track characteristics and provides a useful framework for interpreting track structures observed in inorganic scintillators in terms of energy deposition in biological tissues. Nevertheless, optimization of the finalRange parameter is required for reliable microdosimetric evaluation.

Dual-function of proton irradiation enhances photodynamic therapy and fluorescence imaging via localized secondary electron generation at the Bragg peak: A Hypothesis.

Multi-organ acute and delayed effects following exposure to neutron radiation

Sustained human operations on the lunar surface require robust radiation protection, as the Moon lacks both a substantial atmosphere and a global magnetosphere, leaving crews exposed to galactic cosmic rays (GCR) and solar energetic particle (SEP) events. The surface radiation field is also influenced by albedo secondaries, particularly neutrons and gamma rays produced when primary particles interact with lunar regolith. These secondaries can contribute substantially to biological dose. This review synthesizes lunar and orbital measurements, radiation transport modeling, and experimental beam and neutron transmission studies to evaluate lunar regolith as an in situ resource utilization shielding material for surface habitats. Across published simulations, the first few tens of grams per square centimeter of regolith often reduce dose equivalent by fragmenting high linear energy transfer ions and lowering the average quality factor. At greater thicknesses, additional shielding can yield diminishing returns as secondary neutron production increases. Hybrid shielding strategies that place a hydrogen-rich material as an interior liner generally outperform shielding strategies with only regolith. Experimental results broadly support these trends and show that benchmarked Monte Carlo configurations can reproduce measured effects.

Development and dosimetric characterization of an in vitro benchtop Am-241 alpha irradiator platform.

Inverse treatment planning is central to intensity-modulated proton therapy (IMPT), where high-quality dose distributions must be achieved under machine, biological, delivery-efficiency, and robustness constraints. The alternating direction method of multipliers (ADMM) is a flexible operator-splitting framework that is well suited to such structured optimization problems because it separates smooth dose-fidelity terms from nonsmooth constraints or regularizers. This tutorial review summarizes representative ADMM formulations for proton therapy treatment planning, including minimum monitor unit (MMU) optimization, linear energy transfer (LET) optimization, energy-layer sparsity, robust optimization, and spot sparsity for proton arc therapy. We also place these formulations in the broader context of radiation therapy optimization, compare them with alternative methods, report illustrative computation times from five matRad examples, and discuss practical limitations, including parameter sensitivity, nonconvex convergence issues, and barriers to clinical translation.

To determine proton relative biological effectiveness (RBE) across the spread-out Bragg peak (SOBP) in rat lung using a histological endpoint, with emphasis on changes associated with increasing linear energy transfer (LET). Histological alterations in alveolar epithelial cells (ATI and ATII) and inflammatory responses involving [Formula: see text] and mast cells were also evaluated. The rat lung was irradiated with single-dose proton irradiation delivered to four different regions (dose-mean LET 1.89-3.68keV/μm) along a 9cm SOBP or with 6MV photon irradiation as a reference. Lung tissues were harvested 4weeks after irradiation and subjected to histological analysis. Lung injury was scored using the American Thoracic Society-recommended system (endpoint [Formula: see text]), from which [Formula: see text] (effective dose for 50% response) and RBE values were derived. Cellular and inflammatory responses were evaluated at dose levels of 16 and 20Gy using immunohistochemical staining for AQP5 (ATI), SFTPC (ATII), and [Formula: see text] as an inflammatory marker, while mast cells were identified by toluidine blue staining. Along the SOBP, the RBE values increased from [Formula: see text] to [Formula: see text] as [Formula: see text] values decreased from [Formula: see text]Gy to [Formula: see text]Gy, respectively. All irradiated groups showed altered ATI-positive cell proportion, [Formula: see text] expression, and mast cell number compared with controls. In the low-LET regions (proximal and central SOBP), these changes were comparable to those in the photon group, whereas the distal high-LET SOBP region exhibited more pronounced alterations, including reduced ATI-positive cell proportion and increased [Formula: see text] expression and mast cell accumulation. Although ATII-positive cell proportion was reduced in all irradiated groups, no regional differences were observed along the SOBP; however, morphological alterations were evident in the distal region. CONCLUSIONS: Tissue-level RBE calculations revealed an increase toward the distal region of the proton SOBP. Proton-induced lung injury was spatially heterogeneous along the SOBP, with distal high-LET regions showing the most severe epithelial damage and inflammation. These findings suggest that the use of a constant generic RBE may underestimate biological effects, highlighting the need for LET-informed proton therapy planning.

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are biologically and clinically heterogeneous tumors, most of which overexpress somatostatin receptors (SSTRs). The presence of SSTRs enables staging and allows patient selection for treatment with radiolabeled somatostatin analogs (SSAs), such as DOTATATE. [225Ac]Ac-DOTATATE is an α-emitting radiopharmaceutical in development for the treatment of patients with SSTR2-expressing solid tumors. α particles have a shorter path length and higher linear energy transfer than do β particles, leading to largely irreparable double-strand DNA breaks and cytotoxicity. ACTION-1 (NCT05477576) is a 2-part, randomized, controlled, open-label, phase 1b/3 trial of [225Ac]Ac-DOTATATE in patients with SSTR-expressing GEP-NETs whose disease progressed after 177Lu-labeled SSA therapy. ACTION-1 included a dosimetry substudy to determine the feasibility of obtaining imaging data with 225Ac. The objectives of the substudy were to estimate radiation absorbed doses of [225Ac]Ac-DOTATATE in critical organs and tumors. Methods: [225Ac]Ac-DOTATATE was administered intravenously every 8 wk for 1-4 cycles to adults with grade 1 or 2, well-differentiated, inoperable SSTR2-expressing GEP-NETs that progressed after 2-4 cycles of 177Lu-lableled SSA. Dosimetry was assessed after cycles 1 and 4 of [225Ac]Ac-DOTATATE via SPECT/CT of 221Fr (4.8-min half-life), the first daughter and surrogate for 225Ac and 213Bi (46.6-min half-life, surrogate for later daughters). Absorbed doses and absorbed dose coefficients adjusted for a relative biological effectiveness factor of 5 (ADCRBE=5) to target tissues and tumors were calculated; tumor doses were estimated by MIRD S-value methodology. Results: Dosimetry data were obtained from 9 of 17 patients in phase 1b, each completing 4 cycles. 213Bi mostly remained with DOTATATE in the tumors; a minor fraction went to the kidneys. The estimated absorbed doses to kidneys and red bone marrow were 22.3 and 1.1 Gy, respectively. The ADCRBE=5 to selected tumors ranged from 488 to 8775 mGy/MBq across both treatment cycles. The ADCRBE=5 for most tumors was lower in cycle 4 than in cycle 1; many tumors defined in cycle 1 were unidentifiable in cycle 4. Conclusion: Dosimetry data from ACTION-1 demonstrated the feasibility of image-based dosimetry of 225Ac through SPECT/CT imaging of 221Fr and 213Bi. The 213Bi daughter mostly remained with DOTATATE in tumors, decaying at the same location as 221Fr. The favorable tumor-to-normal tissue absorbed dose ratio of [225Ac]Ac-DOTATATE supports its use in patients with SSTR-expressing GEP-NETs.

Recently, ultra-high dose rate (uHDR) irradiation has received attention for FLASH effect, a phenomenon in vivo that reduces normal-tissue damage without compromising antitumor efficacy compared to normal dose rate (NDR) irradiation. Such protective responses observed in vitro are referred to as cell-sparing effect. In previous studies, the cell-sparing effect was demonstrated using a carbon-ion beam scanning system. This study aimed to reproduce comparable irradiation conditions using a different machine at another facility and evaluate the cell-sparing effect. Comparable beam settings were adopted: physical dose 7Gy, average dose rates (ADR) 100Gy/s for uHDR and 1Gy/s for NDR, dose-averaged linear energy transfer (LETd) 16.3 and 50keV/μm, and identical scanning patterns. The same cell lines, Human salivary gland cell line (HSGc-C5), human dermal fibroblast (HDF), and human lung bronchial epithelial cell line (Nuli-1), were irradiated under normoxia. Colony formation assay and immunofluorescence staining of γH2AX were performed to assess cell survival and DNA damage. Comparable physical dose, ADR, and field flatness were verified by measurements. HDF and Nuli-1 showed the cell-sparing effects with increased surviving fractions and less DNA damage, which were enhanced at higher LET. In contrast, HSGc-C5 exhibited the smaller cell-sparing effect, being absent at low LET. These results were largely consistent with previous studies. To the best of current knowledge, this study is the first to indicate that the cell-sparing effect depends not on irradiation devices but on beam parameters, contributing to accelerating further FLASH research and clinical implementation of carbon-ion uHDR irradiation.

Abstract This paper introduces the latest generation of airborne ionising radiation monitors, developed at the Surrey Space Centre (SSC) as part of the United Kingdom's (UK's) Space Weather Instrumentation, Measurement, Modeling and Risk (SWIMMR) program. These Smart Active Ionising Radiation at Altitude (SAIRA) instruments are deployed on commercial aircraft and weather balloons to measure atmospheric radiation during both quiet and enhanced space weather conditions, such as Ground Level Enhancements (GLEs). The instruments use silicon photodiodes to record linear energy transfer across 16 channels, enabling accurate determination of absorbed dose, with conversion processes for ambient dose equivalent and particle fluxes. Two configurations have been developed: a portable aircraft unit and a balloon unit compatible with Vaisala RS41 radiosondes. Calibration and validation have been performed using laboratory sources, neutron facilities, and in‐flight measurements. Initial operational data from UK airlines demonstrate reliable performance and coverage, with further deployments planned. The SAIRA instruments provide critical data for validating radiation models with future developments aimed at expanding capabilities and wider availability.

Alpha-emitting radionuclides enable precise cancer therapy through high linear energy transfer and limited tissue penetration, damaging tumor cells while sparing healthy tissue. Diffusing Alpha-emitters Radiation Therapy (Alpha DaRT) features Ra-224 sources that are implanted directly into the tumor and emit alpha particles during radioactive decay. Alpha DaRT has demonstrated efficacy and safety in preclinical and early clinical trials across multiple tumor types, including skin, head and neck, and pancreatic cancers. Reliable and efficient methods for verifying Alpha DaRT source activity prior to treatment can help support accurate and consistent radiation delivery. The direct measurement of alpha particles from sources within an Alpha DaRT applicator is impractical due to their short range; however, gamma emissions from the Ra-224 sources can be used to infer radioactivity. This study established a protocol for verifying the source activity within Ra-224 Alpha DaRT applicators using a reentrant well-type ionization chamber, providing users with a practical method for detecting errors in source manufacturing or certificate paperwork without compromising applicator sterility. Ra-224 Alpha DaRT sources in sterile packaging (Flex and Needle applicators with 1-4 sources) were assessed. Source energy spectra and activities were verified using a high-purity germanium (HPGe) radiation detector. Calibration factors (kBq/pA) were established using an IVB1000 well-type ionization chamber with measurements conducted by placing single applicator sterile packages into the chamber with sources centered in the chamber's sweet spot and corrected for temperature, pressure, and leakage current. Quality assurance was performed on 26 Flex applicators using the established calibrations before the first clinical procedure. HPGe measurements agreed with vendor-stated activities. The average calibration coefficient using the IVB1000 chamber was 233±3 kBq/pA for Flex and 597±7 kBq/pA for Needle applicators. Calibration coefficients were consistent across two IVB1000 chambers. Source number dependence was observed, with calibration factors increasing by 1.7%±0.7% per source (Needle) and 2.7%±0.6% per source (Flex). Measurement repeatability was 3.3%. Applying the calibration to 26 Flex applicators before the first patient treatment yielded a 1.1±5.8% (range: -7.5% to 11.4%) difference relative to the vendor's stated activity. A reentrant well-type ionization chamber is suitable for pre-treatment quality assurance of Ra-224 Alpha DaRT applicators, enabling verification of the vendor-stated activity while maintaining sterility within sealed packaging.

The increasing sophistication of Monte Carlo (MC)-based simulations, such as TOPAS-nBio for radiation track structure and DNA damage, and MEDRAS-MC for subsequent DNA repair and cell survival, has ushered in an era ofin-silicosingle-cell radiobiology. However, these simulations remain computationally prohibitive. In this study, we introduce a novel method that significantly accelerates the integrated simulation process forin-silicosingle-cell radiobiology. Our approach centers on pre-calculating and constructing a single-particle-track (SPT) standard DNA damage (SDD) data library using TOPAS-nBio. Each SPT-SDD data entry in this library records the positions of various DNA damage types (e.g. base damage, single-strand breaks, and double-strand breaks) produced by a single particle track. The comprehensive library contains a large number of SPT-SDD data entries, covering a broad range of particle energies. This data library functions as a look-up table, allowing for rapid assembly of DNA damage data for any desired dose level. This is achieved by randomly fetching and superimposing many SPT-SDD data entries from the pre-calculated library. The resulting 'composite' SDD data file then serves as input for MEDRAS-MC to simulate and compute DNA damage outcomes, including chromosome aberrations and cell lethality for each individual cell. Furthermore, 'timestamps' can be added to the superimposed data to account for dose rate effects. This work presents the first integrated MC framework that bridges track-structure simulation (TOPAS-nBio) with mechanistic repair-misrepair modeling (MEDRAS-MC) to predict chromosome aberrations and cell lethality on a cell-by-cell basis. In this paper, we first describe this novel methodology and then apply it to compute radiation-induced outcomes for three previously reportedin vitroexperiments. These applications involve 280 kVpx-rays, protons, and alpha particles, covering a broad spectrum of linear energy transfer. Finally, we compare ourin silicoresults with experimental data and provide a detailed discussion of any observed discrepancies.

Advanced nanoscale devices are core components in modern aerospace systems. The on-orbit reliability of the devices faces challenges from Single Event Effects (SEEs) induced by high-energy particles in space. The ground-based irradiation testing is a critical method for predicting on-orbit performance. However, the ground test is an accelerated testing method. The influence of ion strike time intervals (i.e. ion flux) on the SEE sensitivity of advanced nanoscale devices is not yet fully understood. This problem can lead to inaccurate reliability assessment. In this work, the impact of ion strike time intervals on the Single Event Upset (SEU) has been investigated systematically in a 28 nm Static Random Access Memory based (SRAM-based) Field Programmable Gate Array (FPGA). The ground-based irradiation experiments were conducted using various heavy ions under well controlled ion flux levels. The experimental results definitively demonstrate that the device's SEU cross section increases significantly as the ion strike time interval decreases. It shows when the flux exceeds 1000 ions/(cm2·s), the cross section exhibits changes, while it remains unchanged at the flux below 1000 ions/(cm2·s). Moreover, the flux of 1000 ions/(cm2·s) is significantly lower than the typical flux used in SEE testing. This phenomenon was more pronounced at lower core voltages and higher Linear Energy Transfer (LET) values. The analysis reveals that the voltage drop induced by transient pulses from heavy ions is the primary physical mechanism that is responsible for the flux dependence. Furthermore, the physical mechanism of the experimental phenomena has been elucidated through Technology Computer-Aided Design (TCAD) and circuit-level simulations. Moreover, the mechanism is equally applicable to other advanced nanoscale devices. This finding provides an essential reference for accurate prediction of on-orbit failure rates of the advanced nanoscale devices.

The biological effectiveness of ionizing radiation depends not only on absorbed dose but also on radiation quality and microenvironmental factors, particularly linear energy transfer (LET) and oxygenation. Although Monte Carlo track-structure simulations can describe radiation-matter interactions in detail, such complexity often obscures the individual roles played by governing parameters. We present here a closed-form, analytical reaction-kinetics model for the indirect chemical stage of radiation action. The model introduces an LET-dependent source term for hydroxyl radical production based on experimentally and computationally established G-value trends and combines it with a balance equation derived from a directional Boltzmann-P1 approximation under spatial averaging. Macroscopic reaction rates incorporate the presence of oxygen and background scavengers, leading to an explicit, steady-state expression for hydroxyl radical density independent of biological response functions. The model systematically replicates suppression of indirect chemical activity with increasing LET and predicts the natural emergence of smoothly varying radiochemical regimes corresponding to production-limited, scavenging-limited, and track-structure-dominated behavior. These regimes emerge naturally from the model structure and the interplay between production, scavenging, and track‑density effects. The framework is not designed to predict biological damage or clinical outcomes but provides a physically transparent and analytically tractable description of the chemical stage of radiation action, one suitable for incorporation into multiscale models of heterogeneous irradiation.

While a constant relative biological effectiveness (RBE) of 1.1 is applied in clinical proton therapy, longstanding clinical concern and in vitro evidence demonstrate a variable proton RBE. Several RBE models for protons have been developed based on general assumptions of RBE dependencies together with fitting to in vitro data, for which some modelling authors have included greater diversity of cell types than others. In this study we use neural networks (NNs) to model the proton RBE without any predefined dependencies, investigate the effect of using different biological inputs and combinations of input parameters in the modelling, and compare the results to previous approaches. A comprehensive in vitro RBE database of 431 data points was used, including parameter values for the proton linear energy transfer (LET), the (α/β)x value of the linear quadratic model parameters of the reference photon radiation, and survival fraction (SF)-specific photon doses (Dx(SF)). NNs were used to model RBEs at specific SFs (RBESF) as a function of (1) LET, (2) LET and (α/β)x and (3) LET, (α/β)x and Dx(SF). Models with inputs LET, (α/β)x and Dx(SF) showed overall best performance, particularly inputs with Dx(0.1) and Dx(0.2), indicating that an appropriate standardized input parameter for Dx(SF) could be established by choosing an SF between 0.1 and 0.2. The presented approach to assumption-free NN-based modelling of proton RBE showed similar RBE dependencies as previously published models with similar predictive power. Further, it was demonstrated that adding the photon dose sensitivity as an input parameter to modelling could increase the quality of RBE models.