Calculation of alpha particle single-event spectra using a neural network.

Introduction: A neural network was trained to accurately predict the entire single-event specific energy spectra for use in alpha-particle microdosimetry calculations. Methods: The network consisted of 4 inputs and 21 outputs and was trained on data calculated using Monte Carlo simulation where input parameters originated both from previously published data as well as randomly generated parameters that fell within a target range. The 4 inputs consisted of the source-target configuration (consisting of both cells in suspension and in tissue-like geometries), alpha particle energy (3.97-8.78 MeV), nuclei radius (2-10 µm), and cell radius (2.5-20 µm). The 21 output values consisted of the maximum specific energy (zmax), and 20 values of the single-event spectra, which were expressed as fractional values of zmax. The neural network consisted of two hidden layers with 10 and 26 nodes, respectively, with the loss function characterized as the mean square error (MSE) between the actual and predicted values for zmax and the spectral outputs. Results: For the final network, the root mean square error (RMSE) values of zmax for training, validation and testing were 1.57 x10-2, 1.51 x 10-2 and 1.35 x 10-2, respectively. Similarly, the RMSE values of the spectral outputs were 0.201, 0.175 and 0.199, respectively. The correlation coefficient, R2, was > 0.98 between actual and predicted values from the neural network. Discussion: In summary, the network was able to accurately reproduce alpha-particle single-event spectra for a wide range of source-target geometries.

Microdosimetric Simulation of Gold-Nanoparticle-Enhanced Radiotherapy.

Conventional X-ray therapy (XRT) is commonly applied to suppress cancerous tumors; however, it often inflicts collateral damage to nearby healthy tissue. In order to provide a better conformity of the dose distribution in the irradiated tumor, proton therapy (PT) is increasingly being used to treat solid tumors. Furthermore, radiosensitization with gold nanoparticles (GNPs) has been extensively studied to increase the therapeutic ratio. The mechanism of radiosensitization is assumed to be connected to an enhancement of the absorbed dose due to huge photoelectric cross-sections with gold. Nevertheless, numerous theoretical studies, mostly based on Monte Carlo (MC) simulations, did not provide a consistent and thorough picture of dose enhancement and, therefore, the radiosensitization effect. Radiosensitization by nanoparticles in PT is even less studied than in XRT. Therefore, we investigate the physics picture of GNP-enhanced RT using an MC simulation with Geant4 equipped with the most recent physics models, taking into account a wide range of physics processes relevant for realistic PT and XRT. Namely, we measured dose enhancement factors in the vicinity of GNP, with diameters ranging from 10 nm to 80 nm. The dose enhancement in the vicinity of GNP reaches high values for XRT, while it is very modest for PT. The macroscopic dose enhancement factors for realistic therapeutic GNP concentrations are rather low for all RT scenarios; therefore, other physico-chemical and biological mechanisms should be additionally invoked for an explanation of the radiosensitization effect observed in many experiments.

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

BACKGROUND: Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges. PURPOSE: This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy. METHODS: At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons. RESULTS: A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed. CONCLUSIONS: The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

3D small-scale dosimetry and tumor control of 225Ac radiopharmaceuticals for prostate cancer.

Radiopharmaceutical therapy using α -emitting 225 Ac is an emerging treatment for patients with advanced metastatic cancers. Measurement of the spatial dose distribution in organs and tumors is needed to inform treatment dose prescription and reduce off-target toxicity, at not only organ but also sub-organ scales. Digital autoradiography with α -sensitive detection devices can measure radioactivity distributions at 20-40 µ m resolution, but anatomical characterization is typically limited to 2D. We collected digital autoradiographs across whole tissues to generate 3D dose volumes and used them to evaluate the simultaneous tumor control and regional kidney dosimetry of a novel therapeutic radiopharmaceutical for prostate cancer, [225Ac]Ac-Macropa-PEG4-YS5, in mice. 22Rv1 xenograft-bearing mice treated with 18.5 kBq of [225Ac]Ac-Macropa-PEG4-YS5 were sacrificed at 24 h and 168 h post-injection for quantitative α -particle digital autoradiography and hematoxylin and eosin staining. Gamma-ray spectroscopy of biodistribution data was used to determine temporal dynamics and 213 Bi redistribution. Tumor control probability and sub-kidney dosimetry were assessed. Heterogeneous 225 Ac spatial distribution was observed in both tumors and kidneys. Tumor control was maintained despite heterogeneity if cold spots coincided with necrotic regions. 225 Ac dose-rate was highest in the cortex and renal vasculature. Extrapolation of tumor control suggested that kidney absorbed dose could be reduced by 41% while maintaining 90% TCP. The 3D dosimetry methods described allow for whole tumor and organ dose measurements following 225 Ac radiopharmaceutical therapy, which correlate to tumor control and toxicity outcomes.

Monte Carlo simulations of microdosimetry and radiolytic species production at long time post proton irradiation using GATE and Geant4-DNA.

BACKGROUND: Radiobiological effectiveness of radiation in cancer treatment can be studied at different scales (molecular till organ scale) and different time post irradiation. The production of free radicals and reactive oxygen species during water radiolysis is particularly relevant to understand the fundamental mechanisms playing a role in observed biological outcomes. The development and validation of Monte Carlo tools integrating the simulation of physical, physico-chemical and chemical stages after radiation is very important to maintain with experiments. PURPOSE: Therefore, in this study, we propose to validate a new Geant4-DNA chemistry module through the simulation of water radiolysis and Fricke dosimetry experiments on a proton preclinical beam line. MATERIAL AND METHODS: In this study, we used the GATE Monte Carlo simulation platform (version 9.3) to simulate a 67.5 MeV proton beam produced with the ARRONAX isochronous cyclotron (IBA Cyclone 70XP) at conventional dose rate (0.2 Gy/s) to simulate the irradiation of ultra-pure liquid water samples and Fricke dosimeter. We compared the depth dose profile with measurements performed with a plane parallel Advanced PTW 34045 Markus ionization chamber. Then, a new Geant4-DNA chemistry application proposed from Geant4 version 11.2 has been used to assess the evolution of HO • ${\mathrm{HO}}^ \bullet $ , e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , H 3 O + ${{\mathrm{H}}}_3{{\mathrm{O}}}^ + $ , H 2 O 2 ${{\mathrm{H}}}_2{{\mathrm{O}}}_2$ , H 2 ${{\mathrm{H}}}_2$ , HO 2 • ${\mathrm{HO}}_2^ \bullet $ , HO 2 - , O 2 • - ${\mathrm{HO}}_2^ - ,{\mathrm{\ O}}_2^{ \bullet - }$ and HO - ${\mathrm{HO}}^ - $ reactive species along time until 1-h post-irradiation. In particular, the effect of oxygen and pH has been investigated through comparisons with experimental measurements of radiolytic yields for H 2 O 2 ${{\mathrm{H}}}_2{{\mathrm{O}}}_2$ and Fe3+. RESULTS: GATE simulations reproduced, within 4%, the depth dose profile in liquid water. With Geant4-DNA, we were able to reproduce experimental H 2 O 2 ${{\mathrm{H}}}_2{{\mathrm{O}}}_2$ radiolytic yields 1-h post-irradiation in aerated and deaerated conditions, showing the impact of small changes in oxygen concentrations on species evolution along time. For the Fricke dosimeter, simulated G(Fe3+) is 15.97 ± 0.2 molecules/100 eV which is 11% higher than the measured value (14.4 ± 04 molecules/100 eV). CONCLUSIONS: These results aim to be consolidated by new comparisons involving other radiolytic species, such as e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ or , O 2 • - $,{\mathrm{\ O}}_2^{ \bullet - }$ to further study the mechanisms underlying the FLASH effect observed at ultra-high dose rates (UHDR).

Evaluation of relative biological effectiveness for diseases of the circulatory system based on microdosimetry.

In the next decade, the International Commission on Radiological Protection (ICRP) will issue the next set of general recommendations, for which evaluation of relative biological effectiveness (RBE) for various types of tissue reactions would be needed. ICRP has recently classified diseases of the circulatory system (DCS) as a tissue reaction, but has not recommended RBE for DCS. We therefore evaluated the mean and uncertainty of RBE for DCS by applying a microdosimetric kinetic model specialized for RBE estimation of tissue reactions. For this purpose, we analyzed several RBE data for DCS determined by past animal experiments and evaluated the radius of the subnuclear domain best fit to each experiment as a single free parameter included in the model. Our analysis suggested that RBE for DCS tends to be lower than that for skin reactions, and their difference was borderline significant due to large variances of the evaluated parameters. We also found that RBE for DCS following mono-energetic neutron irradiation of the human body is much lower than that for skin reactions, particularly at the thermal energy and around 1 MeV. This tendency is considered attributable not only to the intrinsic difference of neutron RBE between skin reactions and DCS but also to the difference in the contributions of secondary γ-rays to the total absorbed doses between their target organs. These findings will help determine RBE by ICRP for preventing tissue reactions.

A comparative study on the dose-effect of low-dose radiation based on microdosimetric analysis and single-cell sequencing technology.

The biological mechanisms triggered by low-dose exposure still need to be explored in depth. In this study, the potential mechanisms of low-dose radiation when irradiating the BEAS-2B cell lines with a Cs-137 gamma-ray source were investigated through simulations and experiments. Monolayer cell population models were constructed for simulating and analyzing distributions of nucleus-specific energy within cell populations combined with the Monte Carlo method and microdosimetric analysis. Furthermore, the 10 × Genomics single-cell sequencing technology was employed to capture the heterogeneity of individual cell responses to low-dose radiation in the same irradiated sample. The numerical uncertainties can be found both in the specific energy distribution in microdosimetry and in differential gene expressions in radiation cytogenetics. Subsequently, the distribution of nucleus-specific energy was compared with the distribution of differential gene expressions to guide the selection of differential genes bioinformatics analysis. Dose inhomogeneity is pronounced at low doses, where an increase in dose corresponds to a decrease in the dispersion of cellular-specific energy distribution. Multiple screening of differential genes by microdosimetric features and statistical analysis indicate a number of potential pathways induced by low-dose exposure. It also provides a novel perspective on the selection of sensitive biomarkers that respond to low-dose radiation.

A microdosimetry analysis of reversible electroporation in scattered, overlapping, and cancerous cervical cells.

We present a numerical method for studying reversible electroporation on normal and cancerous cervical cells. This microdosimetry analysis builds on a unique approach for extracting contours of free and overlapping cervical cells in the cluster from the Extended Depth of Field (EDF) images. The algorithm used for extracting the contours is a joint optimization of multiple-level set function along with the Gaussian mixture model and Maximally Stable Extremal Regions. These contours are then exported to a multi-physics domain solver, where a variable frequency pulsed electric field is applied. The trans-Membrane voltage (TMV) developed across the cell membrane is computed using the Maxwell equation coupled with a statistical approach, employing the asymptotic Smoluchowski equation. The numerical model was validated by successful replication of existing experimental configurations that employed low-frequency uni-polar pulses on the overlapping cells to obtain reversible electroporation, wherein, several overlapping clumps of cervical cells were targeted. For high-frequency calculation, a combination of normal and cancerous cells is introduced to the computational domain. The cells are assumed to be dispersive and the Debye dispersion equation is used for further calculations. We also present the resulting strength-duration relationship for achieving the threshold value of electroporation between the normal and cancerous cervical cells due to their size and conductivity differences. The dye uptake modulation during the high-frequency electric field electroporation is further advocated by a mathematical model.

Variation of the relative biological effectiveness in the penumbra of ion therapy beams estimated using different microdosimetric approaches.

Background and Purpose: The effort to translate clinical findings across institutions employing different relative biological effectiveness (RBE) models of ion radiotherapy has rapidly grown in recent years. Nevertheless, even for a chosen RBE model, different implementations exist. These approaches might consider or disregard the dose-dependence of the RBE and the radial variation of the radiation quality around the beam axis. This study investigated the theoretical impact of disregarding these effects during the RBE calculations. Materials and Methods: Microdosimetric simulations were carried out using the Monte Carlo code PHITS along the spread out Bragg peaks of 1H, 4He, 12C, 16O, and 20Ne ions in a water phantom. The RBE was computed using different implementations of the Mayo Clinic Florida microdosimetric kinetic model (MCF MKM) and the modified MKM, considering or not the radial variation of the radiation quality in the penumbra of the ion beams and the dose-dependence of the RBE. Results: For an OAR located 5 mm laterally from the target volume, disregarding the radial variation of the radiation quality or the dose-dependence of the RBE could result in an overestimation of the RBE-weighted dose up to a factor of âˆ¼ 3.5 or âˆ¼ 1.7, respectively. Conclusions: The RBE-weighted dose to OARs close to the tumor volume was substantially impacted by the approach employed for the RBE calculations, even when using the same RBE model and cell line. Therefore, care should be taken in considering these differences while translating clinical findings between institutions with dissimilar approaches.

Calculation of biological effectiveness of SOBP proton beams: a TOPAS Monte Carlo study.

Objective.This study aims to investigate the biological effectiveness of Spread-Out Bragg-Peak (SOBP) proton beams with initial kinetic energies 50-250 MeV at different depths in water using TOPAS Monte Carlo code.Approach.The study modelled SOBP proton beams using TOPAS time feature. Various LET-based models and Repair-Misrepair-Fixation model were employed to calculate Relative Biological Effectiveness (RBE) for V79 cell lines at different on-axis depths based on TOPAS. Microdosimetric Kinetic Model and biological weighting function-based models, which utilize microdosimetric distributions, were also used to estimate the RBE. A phase-space-based method was adopted for calculating microdosimetric distributions.Main results.The trend of variation of RBE with depth is similar in all the RBE models, but the absolute RBE values vary based on the calculation models. RBE sharply increases at the distal edge of SOBP proton beams. In the entrance region of all the proton beams, RBE values at 4 Gy i.e. RBE(4 Gy) resulting from different models are in the range of 1.04-1.07, comparable to clinically used generic RBE of 1.1. Moving from the proximal to distal end of the SOBP, RBE(4 Gy) is in the range of 1.15-1.33, 1.13-1.21, 1.11-1.17, 1.13-1.18 and 1.17-1.21, respectively for 50, 100, 150, 200 and 250 MeV SOBP beams, whereas at the distal dose fall-off region, these values are 1.68, 1.53, 1.44, 1.42 and 1.40, respectively.Significance.The study emphasises application of depth-, dose- and energy- dependent RBE values in clinical application of proton beams.

Boron-Containing MOF Nanoparticles with Stable Metabolism in U87-MG Cells Combining Microdosimetry To Evaluate Relative Biological Effectiveness of Boron Neutron Capture Therapy.

Accurate prediction of the relative biological effectiveness (RBE) of boron neutron capture therapy (BNCT) is challenging. The therapy is different from other radiotherapy; the dynamic distribution of boron-containing compounds in tumor cells affects the therapeutic outcome considerably and hampers accurate measurement of the neutron-absorbed dose. Herein, we used boron-containing metal-organic framework nanoparticles (BMOFs) with high boron content to target U87-MG cells and maintain the concentration of the 10B isotope in cells. The content of boron in the cells could maintain 90% (60 ppm) within 20 min compared with that at the beginning; therefore, the accurate RBE of BNCT can be acquired. The effects of BNCT upon cells after neutron irradiation were observed, and the neutron-absorbed dose was obtained by Monte Carlo simulations. The RBE of BMOFs was 6.78, which was 4.1-fold higher than that of a small-molecule boron-containing agent (boric acid). The energy spectrum of various particles was analyzed by Monte Carlo simulations, and the RBE was verified theoretically. Our results suggested that the use of nanoparticle-based boron carriers in BNCT may have many advantages and that maintaining a stable boron distribution within cells may significantly improve the efficiency of BNCT.

Integrating microdosimetricin vitroRBE models for particle therapy into TOPAS MC using the MicrOdosimetry-based modeliNg for RBE ASsessment (MONAS) tool.

Objective.In this paper, we present MONAS (MicrOdosimetry-based modelliNg for relative biological effectiveness (RBE) ASsessment) toolkit. MONAS is a TOPAS Monte Carlo extension, that combines simulations of microdosimetric distributions with radiobiological microdosimetry-based models for predicting cell survival curves and dose-dependent RBE.Approach.MONAS expands TOPAS microdosimetric extension, by including novel specific energy scorers to calculate the single- and multi-event specific energy microdosimetric distributions at different micrometer scales. These spectra are used as physical input to three different formulations of themicrodosimetric kinetic model, and to thegeneralized stochastic microdosimetric model(GSM2), to predict dose-dependent cell survival fraction and RBE. MONAS predictions are then validated against experimental microdosimetric spectra andin vitrosurvival fraction data. To show the MONAS features, we present two different applications of the code: (i) the depth-RBE curve calculation from a passively scattered proton SOBP and monoenergetic12C-ion beam by using experimentally validated spectra as physical input, and (ii) the calculation of the 3D RBE distribution on a real head and neck patient geometry treated with protons.Main results.MONAS can estimate dose-dependent RBE and cell survival curves from experimentally validated microdosimetric spectra with four clinically relevant radiobiological models. From the radiobiological characterization of a proton SOBP and12C fields, we observe the well-known trend of increasing RBE values at the distal edge of the radiation field. The 3D RBE map calculated confirmed the trend observed in the analysis of the SOBP, with the highest RBE values found in the distal edge of the target.Significance.MONAS extension offers a comprehensive microdosimetry-based framework for assessing the biological effects of particle radiation in both research and clinical environments, pushing closer the experimental physics-based description to the biological damage assessment, contributing to bridging the gap between a microdosimetric description of the radiation field and its application in proton therapy treatment with variable RBE.

Sensitivity of a mini-TEPC to radiation quality variations in clinical proton beams.

PURPOSE: This work aims at studying the sensitivity of a miniaturized Tissue-Equivalent Proportional Counter to variations of beam quality in clinical radiation fields, to further investigate its performances as radiation quality monitor. METHODS: Measurements were taken at the CATANA facility (INFN-LNS, Catania, Italy), in a monoenergetic and an energy-modulated proton beam with the same initial energy of 62 MeV. PMMA layers were placed in front of the detector to measure at different depths along the depth-dose profile. The frequency- and dose-mean lineal energy were compared to the track- and dose-averaged LET calculated by Monte Carlo simulations. A microdosimetric evaluation of the Relative Biological Effectiveness (RBE) was performed and compared with cell survival experiments. RESULTS: Microdosimetric distributions measured at identical depths in the two beams show spectral differences reflecting their different radiation quality. Discrepancies are most evident at depths corresponding to the Spread-Out Bragg Peak, while spectra at the entrance and in the dose fall-off regions are similar. This can be explained by the different energy components that compose the pristine and spread-out peaks at each depth. The trend of microdosimetric mean values matches that of calculated LET averages along the entire penetration depth, and the microdosimetric estimation of RBE is consistent with radiobiological data not only at 2 Gy but also at lower dose levels, such as those absorbed by healthy tissues. CONCLUSIONS: The mini-TEPC is sensitive to differences in radiation quality resulting from different modulations of the proton beam, confirming its potential for beam quality monitoring in proton therapy.

Diamond based integrated detection system for dosimetric and microdosimetric characterization of radiotherapy ion beams.

BACKGROUND: Ion beam therapy allows for a substantial sparing of normal tissues and higher biological efficacy. Synthetic single crystal diamond is a very good material to produce high-spatial-resolution and highly radiation hard detectors for both dosimetry and microdosimetry in ion beam therapy. PURPOSE: The aim of this work is the design, fabrication and test of an integrated waterproof detector based on synthetic single crystal diamond able to simultaneously perform dosimetric and microdosimetric characterization of clinical ion beams. METHODS: The active elements of the integrated diamond device, that is, dosimeter and microdosimeter, were both realized in a Schottky diode configuration featured by different area, thickness, and shape by means of photolithography technologies for the selective growth of intrinsic and boron-doped CVD diamond. The cross-section of the sensitive volume of the dosimetric element is 4 mm2 and 1 µm-thick, while the microdosimetric one has an active cross-sectional area of 100 × 100 µm2 and a thickness of about 6.2 µm. The dosimetric and microdosimetric performance of the developed device was assessed at different depths in a water phantom at the MedAustron ion beam therapy facility using a monoenergetic uniformly scanned carbon ion beam of 284.7 MeV/u and proton beam of 148.7 MeV. The particle flux in the region of the microdosimeter was 6·107  cm2 /s for both irradiation fields. At each depth, dose and dose distributions in lineal energy were measured simultaneously and the dose mean lineal energy values were then calculated. Monte Carlo simulations were also carried out by using the GATE-Geant4 code to evaluate the relative dose, dose averaged linear energy transfer (LETd ), and microdosimetric spectra at various depths in water for the radiation fields used, by considering the contribution from the secondary particles generated in the ion interaction processes as well. RESULTS: Dosimetric and microdosimetric quantities were measured by the developed prototype with relatively low noise (∼2 keV/µm). A good agreement between the measured and simulated dose profiles was found, with discrepancies in the peak to plateau ratio of about 3% and 4% for proton and carbon ion beams respectively, showing a negligible LET dependence of the dosimetric element of the device. The microdosimetric spectra were validated with Monte Carlo simulations and a good agreement between the spectra shapes and positions was found. Dose mean lineal energy values were found to be in close agreement with those reported in the literature for clinical ion beams, showing a sharp increase along the Bragg curve, being also consistent with the calculated LETd for all depths within the experimental error of 10%. CONCLUSIONS: The experimental indicate that the proposed device can allow enhanced dosimetry in particle therapy centers, where the absorbed dose measurement is implemented by the microdosimetric characterization of the radiation field, thus providing complementary results. In addition, the proposed device allows for the reduction of the experimental uncertainties associated with detector positioning and could facilitate the partial overcoming of some drawbacks related to the low sensitivity of diamond microdosimeters to low LET radiation.

Multiscale Monte Carlo simulations for dosimetry in x-ray breast imaging: Part II - Microscopic scales.

BACKGROUND: Although the benefits of breast screening and early diagnosis are known for reducing breast cancer mortality rates, the effects and risks of low radiation doses to the cells in the breast are still ongoing topics of study. PURPOSE: To study specific energy distributions ( f ( z , D g ) $f(z,D_{g})$ ) in cytoplasm and nuclei of cells corresponding to glandular tissue for different x-ray breast imaging modalities. METHODS: A cubic lattice (500 µm length side) containing 4064 spherical cells was irradiated with photons loaded from phase space files with varying glandular voxel doses ( D g $D_{g}$ ). Specific energy distributions were scored for nucleus and cytoplasm compartments using the PENELOPE (v. 2018) + penEasy (v. 2020) Monte Carlo (MC) code. The phase space files, generated in part I of this work, were obtained from MC simulations in a voxelized anthropomorphic phantom corresponding to glandular voxels for different breast imaging modalities, including digital mammography (DM), digital breast tomosynthesis (DBT), contrast enhanced digital mammography (CEDM) and breast CT (BCT). RESULTS: In general, the average specific energy in nuclei is higher than the respective glandular dose scored in the same region, by up to 10%. The specific energy distributions for nucleus and cytoplasm are directly related to the magnitude of the glandular dose in the voxel ( D g $D_{g}$ ), with little dependence on the spatial location. For similar D g $D_{g}$ values, f ( z , D g ) $f(z,D_{g})$ for nuclei is different between DM/DBT and CEDM/BCT, indicating that distinct x-ray spectra play significant roles in f ( z , D g ) $f(z,D_{g})$ . In addition, this behavior is also present when the specific energy distribution ( F g ( z ) $F_{g}(z)$ ) is considered taking into account the GDD in the breast. CONCLUSIONS: Microdosimetry studies are complementary to the traditional macroscopic breast dosimetry based on the mean glandular dose (MGD). For the same MGD, the specific energy distribution in glandular tissue varies between breast imaging modalities, indicating that this effect could be considered for studying the risks of exposing the breast to ionizing radiation.

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

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

Microdosimetry-based investigation of biological effectiveness of252Cf brachytherapy source: TOPAS Monte Carlo study.

Objective.To investigate biological effectiveness of252Cf brachytherapy source using Monte Carlo-calculated microdosimetric distributions.Approach.252Cf source capsule was placed at the center of the spherical water phantom and phase-space data were scored as a function of radial distance in water (R= 1-5 cm) using TOPAS Monte Carlo code. The phase-space data were used to calculate microdosimetric distributions at 1µm site size. Using these distributions, Relative Biological Effectiveness (RBE), mean quality factor (Q̅) and Oxygen Enhancement Ratio (OER) were calculated as a function ofR.Main results.The overall shapes of the microdosimetric distributions are comparable at all the radial distances in water. However, slight variation in the bin-wise yield is observed withR. RBE,Q̅and OER are insensitive to R over the range 1-5 cm. Microdosimetric kinetic model based RBE values are about 2.3 and 2.8 for HSG tumour cells and V79 cells, respectively, whereas biological weighting function-based RBE is about 2.8. ICRP 60 and ICRU 40 recommendation-basedQ̅values are about 14.5 and 16, respectively. Theory of dual radiation action based RBE is 11.4. The calculated value of OER is 1.6.Significance.This study demonstrates the relative insensitivity of RBE,Q̅and OER radially away from the252Cf source along the distances of 1-5 cm in water.

Haralick texture analysis for microdosimetry: characterization of Monte Carlo generated 3D specific energy distributions.

Objective.Explore the application of Haralick textural analysis to 3D distributions of specific energy (energy imparted per unit mass) scored in cell-scale targets considering varying mean specific energy (absorbed dose), target volume, and incident spectrum.Approach.Monte Carlo simulations are used to generate specific energy distributions in cell-scale water voxels ((1µm)3-(15µm)3) irradiated by photon sources (mean energies: 0.02-2 MeV) to varying mean specific energies (10-400 mGy). Five Haralick features (homogeneity, contrast, entropy, correlation, local homogeneity) are calculated using an implementation of Haralick analysis designed to reduce sensitivity to grey level quantization and are interpreted using fundamental radiation physics.Main results.Haralick measures quantify differences in 3D specific energy distributions observed with varying voxel volume, absorbed dose magnitude, and source spectrum. For example, specific energy distributions in small (1-3µm) voxels with low magnitudes of absorbed dose (10 mGy) have relatively high measures of homogeneity and local homogeneity and relatively low measures of contrast and entropy (all relative to measures for larger voxels), reflecting the many voxels with zero specific energy in an otherwise sporadic distribution. With increasing target size, energy is shared across more target voxels, and trends in Haralick measures, such as decreasing homogeneity and increasing contrast and entropy, reflect characteristics of each 3D specific energy distribution. Specific energy distributions for sources of differing mean energy are characterized by Haralick measures, e.g. contrast generally decreases with increasing source energy, correlation and homogeneity are often (not always) higher for higher energy sources.Significance.Haralick texture analysis successfully quantifies spatial trends in 3D specific energy distributions characteristic of radiation source, target size, and absorbed dose magnitude, thus offering new avenues to quantify microdosimetric data beyond first order histogram features. Promising future directions include investigations of multiscale tissue models, targeted radiation therapy techniques, and biological response to radiation.

GPU-accelerated calculation of proton microdosimetric spectra as a function of target size, proton energy, and bounding volume size.

Objective.Shortcomings of dose-averaged linear energy transfer (LETD), the quantity which is most commonly used to quantify proton relative biological effectiveness, have long been recognized. Microdosimetric spectra may overcome the limitations of LETDbut are extremely computationally demanding to calculate. A systematic library of lineal energy spectra for monoenergetic protons could enable rapid determination of microdosimetric spectra in a clinical environment. The objective of this work was to calculate and validate such a library of lineal energy spectra.Approach. SuperTrack, a GPU-accelerated CUDA/C++ based application, was developed to superimpose tracks calculated using Geant4 onto targets of interest and to compute microdosimetric spectra. Lineal energy spectra of protons with energies from 0.1 to 100 MeV were determined in spherical targets of diameters from 1 nm to 10µm and in bounding voxels with side lengths of 5µm and 3 mm.Main results.Compared to an analogous Geant4-based application, SuperTrack is up to 3500 times more computationally efficient if each track is resampled 1000 times. Dose spectra of lineal energy and dose-mean lineal energy calculated with SuperTrack were consistent with values published in the literature and with comparison to a Geant4 simulation. Using SuperTrack, we developed the largest known library of proton microdosimetric spectra as a function of primary proton energy, target size, and bounding volume size.Significance. SuperTrack greatly increases the computational efficiency of the calculation of microdosimetric spectra. The elevated lineal energy observed in a 3 mm side length bounding volume suggests that lineal energy spectra determined experimentally or computed in small bounding volumes may not be representative of the lineal energy spectra in voxels of a dose calculation grid. The library of lineal energy spectra calculated in this work could be integrated with a treatment planning system for rapid determination of lineal energy spectra in patient geometries.