Dose-averaged linear energy transfer (LETd) is conventionally evaluated from the relative biological effectiveness (RBE)-LETd fitted function used in the treatment planning system. In this study, we calculated the physical doses and their linear energy transfer (LET) distributions for patterns of typical CIRT beams using Monte Carlo (MC) simulation. The LETd was then deduced from the MC simulation and compared with that obtained from the conventional method. The two types of LETd agreed well with each other, except around the distal end of the spread-out Bragg peak. Furthermore, an MC simulation was conducted with the material composition of water and realistic materials. The profiles of physical dose and LETd were in good agreement for both techniques. These results indicate that the previous studies to analyze the minimum LETd in CIRT cases are valid for practical situations, and the material composition conversion to water little affects the dose distribution in the irradiation field.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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 ∼ 3.5 or ∼ 1.7, respectively.
UNASSIGNED: 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.

This study aimed to investigate the effect of diabetes on radiation attenuation parameters of the femur and tibia of rats using Monte Carlo Simulations. First, control and diabetic rats were identified and tibias and femurs were removed. Then, the elemental ratios of the bones obtained were calculated using EDS (Energy Dissipative X-ray Spectroscopy). Therefore, radiation permeability properties of control and diabetic bones were simulated by using the content ratios in the bones in MCNP6 (Monte Carlo N-Particle) and PHITS (Particle and Heavy Ion Transport code System) 3.22 and Stopping and Range of Ions in Matter (SRIM) simulation codes. Attenuation coefficient results were compared with the NIST database via XCOM. Although differences in absorption coefficients are observed at low energies, these differences disappear as the energy increases.

The reference dose for clinical proton beam therapy is based on ionization chamber dosimetry. However, data on uncertainties in proton dosimetry are lacking, and multifaceted studies are required. Monte Carlo simulations are useful tools for calculating ionization chamber dosimetry in radiation fields and are sensitive to the transport algorithm parameters when particles are transported in a heterogeneous region. We aimed to evaluate the proton transport algorithm of the Particle and Heavy Ion Transport Code System (PHITS) using the Fano test. The response of the ionization chamber f Q and beam quality correction factors k Q were calculated using the same parameters as those in the Fano test and compared with those of other Monte Carlo codes for verification. The geometry of the Fano test consisted of a cylindrical gas-filled cavity sandwiched between two cylindrical walls. f Q was calculated as the ratio of the absorbed dose in water to the dose in the cavity in the chamber. We compared the f Q calculated using PHITS with that of a previous study, which was calculated using other Monte Carlo codes (Geant4, FULKA, and PENH) under similar conditions. The flight mesh, a parameter for charged particle transport, passed the Fano test within 0.15%. This was shown to be sufficiently accurate compared with that observed in previous studies. The f Q calculated using PHITS were 1.116 ± 0.002 and 1.124 ± 0.003 for NACP-02 and PTW-30013, respectively, and the k Q were 0.981 ± 0.008 and 1.027 ± 0.008, respectively, at 150 MeV. Our results indicate that PHITS can calculate the f Q and k Q with high precision.

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.

The response functions (RFs) of a Bonner Sphere Spectrometer (BSS) with a 6LiI thermal neutron detector were calculated using the Monte Carlo codes PHITS (version 3.26) and MCNPX (version 2.7.0), with their own default nuclear data libraries, and physics models. RFs were compared with other published data, obtained for the same spectrometer using the MCNP6.1 code with its own physics models. A discussion on the influence of using different nuclear data libraries and physics models using these codes/versions is analyzed.

Objective. Estimation of the probability density of the microdosimetric quantities in macroscopic matter is indispensable for applying the concept of microdosimetry to medical physics and radiological protection. The Particle and Heavy Ion Transport code System (PHITS) enables estimating the microdosimetric probability densities due to its unique hybrid modality between the Monte Carlo and analytical approaches called the microdosimetric function. It can convert the deposition energies calculated by the macroscopic Monte Carlo radiation transport simulation to microdosimetric probability densities in water using an analytical function based on the track-structure simulations.Approach. In this study, we improved this function using the latest track-structure simulation codes implemented in PHITS. The improved function is capable of calculating the probability densities of not only the conventional microdosimetric quantities such as lineal energy but also the number of ionization events occurring in a target site, the so-called ionization cluster size distribution, for arbitrary site diameters from 3 nm to 1μm.Main results. The accuracy of the improved function was well verified by comparing the microdosimetric probability densities measured by tissue-equivalent proportional counters with the corresponding data calculated in this study. Test calculations for clonogenic cell survival using the improved function coupled with the modified microdosimetric kinetic model suggested a slight increase of its relative biological effectiveness compared with our previous estimations. As a new application of the improved function, we calculated the relative biological effectiveness of the single-strand break and double-strand break yields for proton irradiations using the updated PHITS coupled with the simplified DNA damage estimation model, and confirmed its equivalence in accuracy and its superiority in computational time compared to our previously proposed method based on the track-structure simulation.Significance. From these features, we concluded that the improved function could expand the application fields of PHITS by bridging the gap between microdosimetry and macrodosimetry.

In a brachytherapy room irradiated with an Iridium-192 (192Ir) source, the spatial distributions of photon dose rates were measured and calculated for the dose distribution both inside and outside the room. The spatial distributions were measured using a thermoluminescent dosimeter (LiF-100) on the surfaces of the concrete walls and barriers of the irradiation room. The calculations were performed using the particle and heavy ion transport code system (PHITS) by considering the detailed model of the brachytherapy room and the radiation source used in the measurements. The measured and calculated doses exhibited a similar distribution pattern within and outside the brachytherapy room. To reduce the edge effect at the entrance door, the addition of a 3-mm thick lead layer on the surface of the concrete wall on the left doorstop is recommended. For the 60Co source, with the existing walls and lead door thickness, the dose at the control console and in front of the entrance maze increased by a factor of approximately 60.

Hadron radiation therapy is of great interest worldwide. Heavy-ion beams provide ideal therapeutic conditions for deep-seated local tumours. At the Heidelberg Ion Beam Therapy Center (HIT, Germany), protons and carbon ions are already integrated into the clinical routine, while16O ions are still used for research only. To ensure the protection of the technical staff and members of the public, it is required to estimate the neutron dose distribution for optimal working conditions and at different locations. The Particle and Heavy Ion Transport Code System (PHITS) is used in this work to evaluate the dose rate distribution of secondary neutrons in a treatment room at HIT where16O ions are used: an equivalent target in soft tissue is considered in the shielding assessment to simulate the interaction of the beam with patients. The angular dependence of neutron fluences and energy spectra around the considered phantom were calculated. Alongside the spatial distribution of the neutron and photon fluence, a map of the effective dose rate was estimated using the ICRP fluence-to-effective dose conversion coefficients, exploiting the PHITS code\'s built-in capabilities. The capability of the actual shielding design of the studied HIT treatment room was approved.

Detector efficiency is a measure of the detectors\' ability to detect radiation. It is known that the efficiency values, which are important and affect the activity calculation in germanium detectors, decrease rapidly at low energies. This study focuses on the reasons for this handicap in the low energy region of the efficiency curve. The Monte Carlo simulation was carried out with four setups: germanium only, germanium with a dead layer, germanium with aluminum holders, and finally germanium with a dead layer and aluminum holders. The effect of each setup on the efficiency curve was observed. As a result, it was seen that the main cause of the handicap was the dead layer. For this reason, it was concluded that the current value of the dead layer, which is known to change over time, should be taken into account in detector calibrations or characterizations.