Monte Carlo techniques in medical radiation physics

Dose, dose, dose, but where is the patient dose?

The article reviews the historical developments in radiation dose metrices in medical imaging. It identifies the good, the bad, and the ugly aspects of current-day metrices. The actions on shifting focus from International Commission on Radiological Protection (ICRP) Reference-Man-based population-average phantoms to patient-specific computational phantoms have been proposed and discussed. Technological developments in recent years involving AI-based automatic organ segmentation and 'near real-time' Monte Carlo dose calculations suggest the feasibility and advantage of obtaining patient-specific organ doses. It appears that the time for ICRP and other international organizations to embrace 'patient-specific' dose quantity representing risk may have finally come. While the existing dose metrices meet specific demands, emphasis needs to be also placed on making radiation units understandable to the medical community.

Monte Carlo calculated photon interaction coefficients for several body tissues

Absorption of energy in body tissues because of radiation interactions may induce harmful outcomes such as cancer and hereditary effects due to a variety of damages in the integrity and activity of the cells. This study presents Monte Carlo calculated $\boldsymbol{\mu} /\boldsymbol{\rho}$, ${\boldsymbol{\mu}}_{\boldsymbol{en}}/\boldsymbol{\rho}$ and ${\boldsymbol{\mu}}_{\boldsymbol{tr}}/\boldsymbol{\rho}$ values of some common tissues and organs found in the human body (namely, adipose tissue, blood, bone-cortical, brain-grey/white matter, breast tissue, eye lens, lung tissue, muscle-skeletal, ovary, soft tissue and testes) as well as water for comparison purposes. The simulation model involves a monoenergetic point source producing a pencil beam where, depending on the parameter under study, particle flux, energy flux or absorbed dose from photon interactions are scored in the range of 10 keV to 20 MeV energy. The simulations were performed using the Monte Carlo package MCNP6.1 and provided $\boldsymbol{\mu} /\boldsymbol{\rho}$, ${\boldsymbol{\mu}}_{\boldsymbol{en}}/\boldsymbol{\rho}$ and ${\boldsymbol{\mu}}_{\boldsymbol{tr}}/\boldsymbol{\rho}$ values. The data produced in this study were compared with theoretical photon attenuation data from the XMUDAT database and demonstrated good agreement. The results, which are based on a simple model geometry and pure elemental compositions, indicate that this approach can be applied to evaluate $\boldsymbol{\mu} /\boldsymbol{\rho}$, ${\boldsymbol{\mu}}_{\boldsymbol{en}}/\boldsymbol{\rho}$ and ${\boldsymbol{\mu}}_{\boldsymbol{tr}}/\boldsymbol{\rho}$ in a broad energy range for any element, compound or mixture.

Mechanistic model of radiotherapy-induced lung fibrosis using coupled 3D agent-based and Monte Carlo simulations

BACKGROUND

Mechanistic modelling of normal tissue toxicities is unfolding as an alternative to the phenomenological normal tissue complication probability models. The latter, currently used in the clinics, rely exclusively on limited patient data and neglect spatial dose distribution information. Among the various approaches, agent-based models are appealing as they provide the means to include patient-specific parameters and simulate long-term effects in complex systems. However, Monte Carlo tools remain the state-of-the-art for modelling radiation transport and provide measurements of the delivered dose with unmatched precision.

METHODS

In this work, we develop and characterize a coupled 3D agent-based - Monte Carlo model that mechanistically simulates the onset of the radiation-induced lung fibrosis in an alveolar segment. To the best of our knowledge, this is the first such model.

RESULTS

Our model replicates extracellular matrix patterns, radiation-induced lung fibrosis severity indexes and functional subunits survivals that show qualitative agreement with experimental studies and are consistent with our past results. Moreover, in accordance with experimental results, higher functional subunits survival and lower radiation-induced lung fibrosis severity indexes are achieved when a 5-fractions treatment is simulated. Finally, the model shows increased sensitivity to more uniform protons dose distributions with respect to more heterogeneous ones from photon irradiation.

CONCLUSIONS

This study lays thus the groundwork for further investigating the effects of different radiotherapeutic treatments on the onset of radiation-induced lung fibrosis via mechanistic modelling.

Performance Evaluation of Radiation-Shielding Materials and Process Technology for Manufacturing Skin Protection Cream

Personnel using X-ray devices, the main source of radiation in medical institutions, are primarily affected by scattered rays. When interventionists use radiation for examinations/treatments, their hands may enter the radiation-generating area. The shielding gloves used for protection against these rays restrict movement and cause discomfort. Here, a shielding cream that directly adheres to the skin was developed and examined as a personal protective device; further, its shielding performance was verified. Bismuth oxide and barium sulfate were selected as shielding materials and comparatively evaluated in terms of thickness, concentration, and energy. With increasing wt% of the shielding material, the protective cream became thicker, resulting in improved protection. Furthermore, the shielding performance improved with increasing mixing temperature. Because the shielding cream is applied to the skin and has a protective effect, it must be stable on the skin and easy to remove. During manufacturing, the bubbles were removed, and the dispersion improved by 5% with increasing stirring speed. During mixing, the temperature increased as the shielding performance increased by 5% in the low-energy region. In terms of the shielding performance, bismuth oxide was superior to barium sulfate by approximately 10%. This study is expected to facilitate the mass production of cream in the future.

The Software with a Graphical User Interface for GAMOS: Basic Training and an Educational Tool for Medical Physicists

Introduction: It is necessary to have special experience to perform the Monte Carlo calculation, commonly used in medical physics and accepted as the gold standard. In this study, we developed software to teach basic steps to medical physicists who were inexperienced in the medical linear accelerator Monte Carlo simulation.

Material and methods: For the design interface, a software called GamosLinacGUI was developed using Gnome Builder, Python, and GTK. The user, who wants to learn the basics of GAMOS and simulate a linear accelerator, can enter the values in the software, select some options and quickly create geometry and physics files.

Results: For proof that the software generates the correct inputs for GAMOS simulation in the same conditions for the measurements and calculations. Required files for GAMOS have been created and tested and run the simulation accordingly. This software was tested with Centos Linux.

Conclusions: GamosLinacGUI has been successfully developed, which creates the geometry and physics files required for the simulation with GAMOS as a training and learning tool.

Small field output factor measurement and verification for CyberKnife robotic radiotherapy and radiosurgery system using 3D polymer gel, ionization chamber, diode, diamond and scintillator detectors, Gafchromic film and Monte Carlo simulation

The dosimetry of small fields has become tremendously important with the advent of intensity-modulated radiation therapy (IMRT) and stereotactic radiosurgery, where small field segments or very small fields are used to treat tumors. With high dose gradients in the stereotactic radiosurgery or radiotherapy treatment, small field dosimetry becomes challenging due to the lack of lateral electronic equilibrium in the field, x-ray source occlusion, and detector volume averaging. Small volume and tissue-equivalent detectors are recommended to overcome the challenges. With the lack of a perfect radiation detector, studies on available detectors are ongoing with reasonable disagreement and uncertainties. The joint IAEA and AAPM international code of practice (CoP) for small field dosimetry, TRS 483 (Alfonso et al., 2017) provides guidelines and recommendations for the dosimetry of small static fields in external beam radiotherapy. The CoP provides a methodology for field output factor (FOF) measurements and use of field output correction factors for a series of small field detectors and strongly recommends additional measurements, data collection and verification for CyberKnife (CK) robotic stereotactic radiotherapy/radiosurgery system using the listed detectors and more new detectors so that the FOFs can be implemented clinically. The present investigation is focused on using 3D gel along with some other commercially available detectors for the measurement and verification of field output factors (FOFs) for the small fields available in the CK system. The FOF verification was performed through a comparison with published data and Monte Carlo simulation. The results of this study have proved the suitability of an in-house developed 3D polymer gel dosimeter, several commercially available detectors, and Gafchromic films as a part of small field dosimetric measurements for the CK system.

Dosimetric accuracy of Acuros® XB and AAA algorithms for stereotactic body radiotherapy (SBRT) lung treatments: evaluation with PRIMO Monte Carlo code

Purpose:

The study aimed to compare the dosimetric performance of Acuros® XB (AXB) and anisotropic analytical algorithm (AAA) for lung SBRT plans using Monte Carlo (MC) simulations.

Methods:

We compared the dose calculation algorithms AAA and either of the dose reporting modes of AXB (dose to medium (AXB-Dm) or dose to water (AXB-Dw)) algorithms implemented in Eclipse® (Varian Medical Systems, Palo Alto, CA) Treatment planning system (TPS) with MC. PRIMO code was used for the MC simulations. The TPS-calculated dose profiles obtained with a multi-slab heterogeneity phantom were compared to MC. A lung phantom with a tumour was used to validate TPS algorithms using different beam delivery techniques. 2D gamma values obtained from Gafchromic film measurements in the tumour isocentre plane were compared with TPS algorithms and MC. Ten VMAT SBRT plans generated in TPS with each algorithm were recalculated with a PRIMO MC system for identical beam parameters for the clinical plan validation. A dose–volume histogram (DVH) based plan comparison and a 3D global gamma analysis were performed.

Results:

AXB demonstrated better agreement with MC and film measurements in the lung phantom validation, with good agreement in PDD, profiles and gamma analysis. AAA showed an overestimated PDD, a significant difference in dose profiles and a lower gamma pass rate near the field borders. With AAA, there was a dose overestimation at the periphery of the tumour. For clinical plan validation, AXB demonstrated higher agreement with MC than AAA.

Conclusions:

AXB provided better agreement with MC than AAA in the phantom and clinical plan evaluations.

Tumor Response, Disease Control, and Progression-Free Survival as Surrogate Endpoints in Trials Evaluating Immune Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer: Study- and Patient-Level Analyses

Background: To assess the usefulness of tumor response and progression-free survival (PFS) as surrogates for overall survival (OS) in non-small cell lung cancer (NSCLC) trials with immune checkpoint inhibitors (ICI), which have not been confirmed. Methods: Patient- and trial-level analyses were performed. The Response Evaluation Criteria in Solid Tumors was preferred for image assessment. For trial-level analysis, surrogacy was assessed using the weighted rank correlation coefficient (r) following "reciprocal duplication." This method duplicates all plots as if the experimental and the reference arms were switched. Monte Carlo simulations were performed for evaluating this method. Results: A total of 3312 cases were included in the patient-level analysis. Patients without response (first line (1L): hazard ratio (HR) 1.95, 95% confidence interval (CI) 1.71-2.23; second or later line (2L-): HR 4.22, 95% CI 3.22-5.53), without disease control (1L: HR 4.34, 95% CI 3.82-4.94; 2L-: HR 3.36, 95% CI 2.96-3.81), or with progression during the first year (1L: HR 3.42, 95% CI 2.60-4.50; 2L-: HR 3.33, 95% CI 2.64-4.20), had a higher risk of death. Systematic searches identified 38 RCTs including 17,515 patients for the study-level analysis. Odds ratio in the objective response rate (N = 38 × 2, r = -0.87) and HR in PFS (N = 38 × 2, r = 0.85) showed an excellent association with HR in overall survival, while this effect was not observed in the disease control rate (N = 26 × 2, r = -0.03). Conclusions: Objective response rate and PFS are reasonable surrogates for OS in NSCLC trials with ICI.

Note on uncertainty in Monte Carlo dose calculations and its relation to microdosimetry

PURPOSE

The Type A standard uncertainty in Monte Carlo (MC) dose calculations is usually determined using the "history by history" method. Its applicability is based on the assumption that the central limit theorem (CLT) can be applied such that the dispersion of repeated calculations can be modeled by a Normal distribution. The justification for this assumption, however, is not obvious. The concept of stochastic quantities used in the field of microdosimetry offers an alternative approach to assess uncertainty. This leads to a new and simple expression.

METHODS

The value of the MC determined absorbed dose is considered a random variable which is comparable to the stochastic quantity specific energy, z. This quantity plays an important role in microdosimetry and in the definition of the quantity absorbed dose, D. One of the main features of z is that it is itself the product of two other random variables, specifically of the mean dose contribution in a 'single event' and of the mean number of such events. The term 'single event' signifies the sum of energies imparted by all correlated particles to the matter in a given volume. The similarity between the MC calculated absorbed dose and the specific energy is used to establish the 'event by event' method for the determination of the uncertainty. MC dose calculations were performed to test and compare both methods.

RESULTS

It is shown that the dispersion of values obtained by MC dose calculations indeed depend on the product of the mean absorbed dose per event, and the number of events. Applying methods to obtain the variance of a product of two random variables, a simple formula for the assessment of uncertainties is obtained which is slightly different from the 'history by history' method. Interestingly, both formulas yield indistinguishable results. This finding is attributed to the large number of histories used in MC simulations. Due on the fact that the values of a MC calculated absorbed dose are the product of two approximately Normal distributions it can be demonstrated that the resulting product is also approximately normally distributed.

CONCLUSIONS

The event by event approach appears to be more suitable than the history by history approach because it takes into account the randomness of the number of events involved in MC dose calculations. Under the condition of large numbers of histories, however, both approaches lead to the same simple expression for the determination of uncertainty in MC dose calculations. It is suggested to replace the formula currently used by the new expression. Finally, it turned out that the concept and ideas that were developed in the field of microdosimetry already 50 years ago can be usefully applied also in MC calculations.

Heterogeneity of dose distribution in normal tissues in case of radiopharmaceutical therapy with alpha-emitting radionuclides

Heterogeneity of dose distribution has been shown at different spatial scales in diagnostic nuclear medicine. In cancer treatment using new radiopharmaceuticals with alpha-particle emitters, it has shown an extensive degree of dose heterogeneity affecting both tumour control and toxicity of organs at risk. This review aims to provide an overview of generalized internal dosimetry in nuclear medicine and highlight the need of consideration of the dose heterogeneity within organs at risk. The current methods used for patient dosimetry in radiopharmaceutical therapy are summarized. Bio-distribution and dose heterogeneities of alpha-particle emitting pharmaceutical ²²³Ra (Xofigo) within bone tissues are presented as an example. In line with the strategical research agendas of the Multidisciplinary European Low Dose Initiative (MELODI) and the European Radiation Dosimetry Group (EURADOS), future research direction of pharmacokinetic modelling and dosimetry in patient radiopharmaceutical therapy are recommended.

Direct Transmittance Estimation in Heterogeneous Participating Media Using Approximated Taylor Expansions

Evaluating the transmittance between two points along a ray is a key component in solving the light transport through heterogeneous participating media and entails computing an intractable exponential of the integrated medium's extinction coefficient. While algorithms for estimating this transmittance exist, there is a lack of theoretical knowledge about their behaviour, which also prevent new theoretically sound algorithms from being developed. For this purpose, we introduce a new class of unbiased transmittance estimators based on random sampling or truncation of a Taylor expansion of the exponential function. In contrast to classical tracking algorithms, these estimators are non-analogous to the physical light transport process and directly sample the underlying extinction function without performing incremental advancement. We present several versions of the new class of estimators, based on either importance sampling or Russian roulette to provide finite unbiased estimators of the infinite Taylor series expansion. We also show that the well known ratio tracking algorithm can be seen as a special case of the new class of estimators. Lastly, we conduct performance evaluations on both the central processing unit (CPU) and the graphics processing unit (GPU), and the results demonstrate that the new algorithms outperform traditional algorithms for heterogeneous mediums.

Model-Based X-Ray-Induced Acoustic Computed Tomography

X-ray-induced acoustic computed tomography (XACT) provides X-ray absorption-based contrast with acoustic detection. For its clinical translation, XACT imaging often has a limited field of view. This can result in image artifacts and overall loss of quantification accuracy. In this article, we aim to demonstrate model-based XACT image reconstruction to address these problems. An efficient matrix-free implementation of the regularized LSQR (MF-LSQR)-based minimization scheme and a noniterative model back-projection (MBP) scheme for computing XACT reconstructions have been demonstrated in this article. The proposed algorithms have been numerically validated and then used to perform reconstructions from experimental measurements obtained from an XACT setup. While the commonly used back-projection (BP) algorithm produces limited-view and noisy artifacts in the region of interest (ROI), model-based LSQR minimization overcomes these issues. The model-based algorithms also reduce the ring artifacts caused due to the nonuniformity response of the multichannel data acquisition. Using the model-based reconstruction algorithms, we are able to obtain reasonable XACT reconstructions for acoustic measurements of up to 120° view. Although the MBP is more efficient than the model-based LSQR algorithm, it provides only the structural information of the ROI. Overall, it has been demonstrated that the model-based image reconstruction yields better image quality for XACT than the standard BP. Moreover, the combination of model-based image reconstruction with different regularization methods can solve the limited-view problem for XACT imaging (in many realistic cases where the full-view dataset is unavailable), and hence pave the way for future clinical translation.

Dosimetry and radioprotection evaluations of very high energy electron beams

Very high energy electrons (VHEEs) represent a promising alternative for the treatment of deep-seated tumors over conventional radiotherapy (RT), owing to their favourable dosimetric characteristics. Given the high energy of the electrons, one of the concerns has been the production of photoneutrons. In this article we explore the consequence, in terms of neutron yield in a water phantom, of using a typical electron applicator in conjunction with a 2 GeV and 200 MeV VHEE beam. Additionally, we evaluate the resulting ambient neutron dose equivalent at various locations between the phantom and a concrete wall. Through Monte Carlo (MC) simulations it was found that an applicator acts to reduce the depth of the dose build-up region, giving rise to lower exit doses but higher entrance doses. Furthermore, neutrons are injected into the entrance region of the phantom. The highest dose equivalent found was approximately 1.7 mSv/Gy in the vicinity of the concrete wall. Nevertheless, we concluded that configurations of VHEEs studied in this article are similar to conventional proton therapy treatments in terms of their neutron yield and ambient dose equivalent. Therefore, a clinical implementation of VHEEs would likely not warrant additional radioprotection safeguards compared to conventional RT treatments.

Monte Carlo methods for device simulations in radiation therapy

Monte Carlo (MC) simulations play an important role in radiotherapy, especially as a method to evaluate physical properties that are either impossible or difficult to measure. For example, MC simulations (MCSs) are used to aid in the design of radiotherapy devices or to understand their properties. The aim of this article is to review the MC method for device simulations in radiation therapy. After a brief history of the MC method and popular codes in medical physics, we review applications of the MC method to model treatment heads for neutral and charged particle radiation therapy as well as specific in-room devices for imaging and therapy purposes. We conclude by discussing the impact that MCSs had in this field and the role of MC in future device design.

Brain-Specific Relative Biological Effectiveness of Protons Based on Long-term Outcome of Patients With Nasopharyngeal Carcinoma

PURPOSE

Uncertainties in relative biological effectiveness (RBE) constitute a major pitfall of the use of protons in clinics. An RBE value of 1.1, which is based on cell culture and animal models, is currently used in clinical proton planning. The purpose of this study was to determine RBE for temporal lobe radiographic changes using long-term follow-up data from patients with nasopharyngeal carcinoma.

METHODS AND MATERIALS

Five hundred sixty-six patients with newly diagnosed nasopharyngeal carcinoma received double-scattering proton therapy or intensity modulated radiation therapy at our institutions. The 2 treatment cohorts were well matched. Proton dose distributions were simulated using Monte Carlo and compared with those obtained from the proton clinical treatment planning system. Late treatment effect was defined as development of enhancement of temporal lobe on T1-weighted magnetic resonance imaging, with or without accompanying clinical symptoms. The tolerance dose was calculated with receiving operator characteristic analysis and the Youden index. Tolerance curves, expressed as a cumulative dose-volume histogram, were generated using the cutoff points.

RESULTS

With a median follow-up period >5 years for both cohorts, 10% of proton patients and 4% of patients undergoing intensity modulated radiation therapy developed temporal lobe enhancement in unilateral temporal lobe. There was no significant difference in dose distributions between the Monte Carlo method and treatment planning system. The tolerance dose-volume levels were V10 (26.1%), V20 (21.9%), V30 (14.0%), V40 (7.7%), V50 (4.8%), and V60 (3.3%) for proton therapy (P < .03). Comparison of the two tolerance curves revealed that tolerance doses of proton treatments were lower than that of photon treatments at all dose levels. The dose tolerance at D1% was 58.56 Gy for protons and 69.07 Gy for photons. The RBE for temporal lobe enhancement from proton treatments were calculated to be 1.18.

CONCLUSIONS

Using long-term clinical outcome of patients with nasopharyngeal carcinoma, our data suggest that the RBE for temporal lobe enhancement is 1.18 at D1%. A prospective study in a large cohort would be necessary to confirm these findings.

Monte Carlo-based patient internal dosimetry in fluoroscopy-guided interventional procedures: A review

PURPOSE

This systematic review aims to understand the dose estimation approaches and their major challenges. Specifically, we focused on state-of-the-art Monte Carlo (MC) methods in fluoroscopy-guided interventional procedures.

METHODS

All relevant studies were identified through keyword searches in electronic databases from inception until September 2020. The searched publications were reviewed, categorised and analysed based on their respective methodology.

RESULTS

Hundred and one publications were identified which utilised existing MC-based applications/programs or customised MC simulations. Two outstanding challenges were identified that contribute to uncertainties in the virtual simulation reconstruction. The first challenge involves the use of anatomical models to represent individuals. Currently, phantom libraries best balance the needs of clinical practicality with those of specificity. However, mismatches of anatomical variations including body size and organ shape can create significant discrepancies in dose estimations. The second challenge is that the exact positioning of the patient relative to the beam is generally unknown. Most dose prediction models assume the patient is located centrally on the examination couch, which can lead to significant errors.

CONCLUSION

The continuing rise of computing power suggests a near future where MC methods become practical for routine clinical dosimetry. Dynamic, deformable phantoms help to improve patient specificity, but at present are only limited to adjustment of gross body volume. Dynamic internal organ displacement or reshaping is likely the next logical frontier. Image-based alignment is probably the most promising solution to enable this, but it must be automated to be clinically practical.

Monte Carlo simulation and dosimetry measurements of an experimental approach for in vitro HDR brachytherapy irradiation

Irradiation of tumor cell lines is a useful way to investigate the effects of ionizing radiation on biological molecules. We designed an easy and reproducible approach for in vitro experimental high dose rate brachytherapy, which was simulated by a Monte Carlo code and dosimetrically characterized by experimental methods to evaluate the correspondence between planned doses and doses absorbed by the cells. This approach is an acrylic platform containing T25 tissue culture flasks and multiwell tissue culture plates. It allows nine parallel needles carrying an ¹⁹²Ir source to irradiate the adherent cells. The whole system composed of the acrylic platform, tissue culture flasks and ¹⁹²Ir source tracking was simulated by the Monte Carlo N-Particle transport code (MCNPX). Dosimetric measurements were taken by well ionization chamber and radiochromic films. There was a slight difference, averaging from 2% to 7%, between the MCNPX results and film dosimetry results regarding uniform radiation created by the source arrangement. The results showed different values for planned and measured doses in each cell culture plate, which was attributed to the non-equivalent water material used and to the lack of full scattering coming from the top of the platform. This last contribution was different for each tissue culture plate and an individual dose correction factor was calculated. The dose correction factor must be applied to match the planned dose and the actual doses absorbed by the cells. The designed approach is an efficient tool for in vitro brachytherapy experiments for most commercial cell culture plates.

Relationship between dose and stopping power values for electrons in skin and muscle tissues

Absorbed dose and stopping power of the target material are two important parameters for determining the radiation effects. In this work, the relationship between these two parameters has been investigated for electron beams incident on skin and muscle tissue. Absorbed dose was obtained by using the EGSnrc code and the stopping power values were calculated by considering the velocity-depended effective charge and mean excitation values. To obtain the relationship between absorbed dose and stopping power values, these parameters were graphed together and simple fitting functions have been obtained. The results obtained show that these parameters are linearly correlated with each other.

A Comparison between Electron Gamma Shower, National Research Council/Easy Particle Propagation (EGSnrc/Epp) and Monte Carlo N-Particle Transport Code (MCNP) in Simulation of the INTRABEAM ® System with Spherical Applicators

BACKGROUND

Online Monte Carlo (MC) treatment planning is very crucial to increase the precision of intraoperative radiotherapy (IORT). However, the performance of MC methods depends on the geometries and energies used for the problem under study.

OBJECTIVE

This study aimed to compare the performance of MC N-Particle Transport Code version 4c (MCNP4c) and Electron Gamma Shower, National Research Council/easy particle propagation (EGSnrc/Epp) MC codes using similar geometry of an INTRABEAM^® system.

MATERIAL AND METHODS

This simulation study was done by increasing the number of particles and compared the performance of MCNP4c and EGSnrc/Epp simulations using an INTRABEAM^® system with 1.5 and 5 cm diameter spherical applicators. A comparison of these two codes was done using simulation time, statistical uncertainty, and relative depth-dose values obtained after doing the simulation by each MC code.

RESULTS

The statistical uncertainties for the MCNP4c and EGSnrc/Epp MC codes were below 2% and 0.5%, respectively. 1e9 particles were simulated in 117.89 hours using MCNP4c but a much greater number of particles (5e10 particles) were simulated in a shorter time of 90.26 hours using EGSnrc/Epp MC code. No significant deviations were found in the calculated relative depth-dose values for both in the presence and absence of an air gap between MCNP4c and EGSnrc/Epp MC codes. Nevertheless, the EGSnrc/Epp MC code was found to be speedier and more efficient to achieve accurate statistical precision than MCNP4c.

CONCLUSION

Therefore, in all comparisons criteria used, EGSnrc/Epp MC code is much better than MCNP4c MC code for simulating an INTRABEAM^® system.

Using Monte Carlo methods for Hp(0.07) values assessment during the handling of 18F-FDG

The dose limit for the skin of the hand is typically converted to a surface of 1 cm², which means that one needs to measure point doses in different places on the hand. However, the commonly used method of measuring doses on the hand, i.e., using a dosimetric ring including one or several thermoluminescent detectors worn at the base of a finger, is not adequate for manual procedures such as labeling or radiopharmaceutical injection. Consequently, the purpose of this study was to create and conduct a series of computer simulations that, by recreating the actual working conditions, would provide information on the values of ionizing radiation doses received by the most exposed parts of the hands of employees of radiopharmaceutical production facilities, as well as those of nurses during the injection of radiopharmaceuticals. The simulations were carried out using Monte Carlo radiation transport calculations. The H_p(0.07) personal dose equivalent values obtained for the fingertips of the index and middle fingers of nursing staff and chemists were within the range limited by the minimum and maximum H_p(0.07) values obtained as a result of dosimetric measurements carried out in diagnostic and production centers. Only in the case of the nurse's fingertip, the simulated value of H_p(0.07 slightly exceeded the measured maximum H_p(0.07) value. The comparison of measured and simulated dose values showed that the largest differences in H_p(0.07) values occurred at the thumb tip, and for ring finger and middle finger of some of the nurses investigated.

Validation of the dosimetry of total skin irradiation techniques by Monte Carlo simulation

Purpose

To validate the dose measurements for two total skin irradiation techniques with Monte Carlo simulation, providing more information on dose distributions, and guidance on further technique optimization.

Methods

Two total skin irradiation techniques (stand‐up and lay‐down) with different setup were simulated and validated. The Monte Carlo simulation was primarily performed within the EGSnrc environment. Parameters of jaws, MLCs, and a customized copper (Cu) filter were first tuned to match the profiles and output measured at source‐to‐skin distance (SSD) of 100 cm where the secondary source is defined. The secondary source was rotated to simulate gantry rotation. VirtuaLinac, a cloud‐based Monte Carlo package, was used for Linac head simulation as a secondary validation. The following quantities were compared with measurements: for each field/direction at the treatment SSDs, the percent depth dose (PDD), the profiles at the depth of maximum, and the absolute dosimetric output; the composite dose distribution on cylindrical phantoms of 20 to 40 cm diameters.

Results

Cu filter broadened the FWHM of the electron beam by 44% and degraded the mean energy by 0.7 MeV. At SSD = 100 cm, MC calculated PDDs agreed with measured data within 2%/2 mm (except for the surface voxel) and lateral profiles agreed within 3%. At the treatment SSD, profiles and output factors of individual field matched within 4%; d_max and R₈₀ of the simulated PDDs also matched with measurement within 2 mm. When all fields were combined on the cylindrical phantom, the d_max shifted toward the surface. For lay‐down technique, the maximum x‐ray contamination at the central axis was (MC: 2.2; Measurement: 2.1)% and reduced to 0.2% at 40 cm off the central axis.

Conclusions

The Monte Carlo results in general agree well with the measurement, which provides support in our commissioning procedure, as well as the full three‐dimensional dose distribution of the patient phantom.

A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation

The Monte Carlo (MC) method is widely used to solve various problems in radiotherapy. There has been an impetus to accelerate MC simulation on GPUs whereas thread divergence remains a major issue for MC codes based on acceptance-rejection sampling. Inverse transform sampling has the potential to eliminate thread divergence but it is only implemented for photon transport. Here, we report a MC package Particle Transport in Media (PTM) to demonstrate the implementation of coupled photon-electron transport simulation using inverse transform sampling. Rayleigh scattering, Compton scattering, photo-electric effect and pair production are considered in an analogous manner for photon transport. Electron transport is simulated in a class II condensed history scheme, i.e., catastrophic inelastic scattering and Bremsstrahlung events are simulated explicitly while subthreshold interactions are subject to grouping. A random-hinge electron step correction algorithm and a modified PRESTA boundary crossing algorithm are employed to improve simulation accuracy. Benchmark studies against both EGSnrc simulations and experimental measurements are performed for various beams, phantoms and geometries. Gamma indices of the dose distributions are better than 99.6% for all the tested scenarios under the 2%/2 mm criteria. These results demonstrate the successful implementation of inverse transform sampling in coupled photon-electron transport simulation.

Validation of PRIMO Monte Carlo Model of Clinac®iX 6MV Photon Beam

Purpose

This study aims to model 6MV photon of Clinac^®iX linear accelerator using PRIMO Monte Carlo (MC) code and to assess PRIMO as an independent MC-based dose verification and quality assurance tool.

Materials and Methods

The modeling of Clinac^®iX linear accelerator has been carried out by using PRIMO simulation software (Version 0.3.1.1681). The simulated beam parameters were compared against the measured beam data of the Clinac^®iX machine. The PRIMO simulation model of Clinac^®iX was also validated against Eclipse^® Acuros XB dose calculations in the case of both homogenous and inhomogeneous mediums. The gamma analysis method with the acceptance criteria of 2%, 2 mm was used for the comparison of dose distributions.

Results

Gamma analysis shows a minimum pass percentage of 99% for depth dose curves and 95.4% for beam profiles. The beam quality index and output factors and absolute point dose show good agreement with measurements. The validation of PRIMO dose calculations, in both homogeneous and inhomogeneous medium, against Acuros^® XB shows a minimum gamma analysis pass rate of 99%.

Conclusions

This study shows that the research software PRIMO can be used as a treatment planning system-independent quality assurance and dose verification tool in daily clinical practice. Further validation will be performed with different energies, complex multileaf collimators fields, and with dynamic treatment fields.

Microdosimetric calculations of the direct DNA damage induced by low energy electrons using the Geant4-DNA Monte Carlo code

To calculate the yield of direct DNA damage induced by low energy electrons using Monte Carlo generated microdosimetric spectra at the nanometer scale and examine the influence of various simulation inputs. The potential of classical microdosimetry to offer a viable and simpler alternative to more elaborate mechanistic approaches for practical applications is discussed. Track-structure simulations with the Geant4-DNA low-energy extension of the Geant4 Monte Carlo toolkit were used for calculating lineal energy spectra in spherical volumes with dimensions relevant to double-strand-break (DSB) induction. The microdosimetric spectra were then used to calculate the yield of simple and clustered DSB based on literature values of the threshold energy of DNA damage. The influence of the different implementations of the dielectric function of liquid water available in Geant4-DNA (Option 2 and Option 4 constructors), as well as the effect of particle tracking cutoff energy and target size are examined. Frequency- and dose-mean lineal energies in liquid-water spheres of 2, 2.3, 2.6, and 3.4 nm diameter, as well as, number of simple and clustered DSB/Gy/cell are presented for electrons over the 100 eV to 100 keV energy range. Results are presented for both the 'default' (Option 2) and 'Ioannina' (Option 4) physics models of Geant4-DNA applying several commonly used tracking cutoff energies (10, 20, 50, 100 eV). Overall, the choice of the physics model and target diameter has a moderate effect (up to ~10%-30%) on the DSB yield whereas the effect of the tracking cutoff energy may be significant (>100%). Importantly, the yield of both simple and clustered DSB was found to vary significantly (by a factor of 2 or more) with electron energy over the examined range. The yields of electron-induced simple and clustered DSB exhibit a strong energy dependence over the 100 eV-100 keV range with implications to radiation quality issues. It is shown that a classical microdosimetry approach for the calculation of DNA damage based on lineal energy spectra in nanometer-size targets predicts comparable results to computationally intensive mechanistic approaches which use detailed atomistic DNA geometries, thus, offering a relatively simple and robust alternative for some practical applications.

Deep DoseNet: a deep neural network for accurate dosimetric transformation between different spatial resolutions and/or different dose calculation algorithms for precision radiation therapy

The purpose of this work is to introduce a novel deep learning strategy to obtain highly accurate dose plan by transforming from a dose distribution calculated using a low-cost algorithm (or algorithmic settings). 25 168 slices of dose distribution are calculated using Eclipse treatment planning system V15.6 (Varian Medical Systems, Palo Alto, CA) on ten patient CTs whose treatment sites ranging from lung, brain, abdomen and pelvis, with a grid size of 1.25  ×  1.25  ×  1.25 mm using both anisotropic analytical algorithm (AAA) in 5 mm resolution and Acuros XB algorithm (AXB) in 1.25 mm resolution. The AAA dose slices, and the corresponding down sampled CT slices are combined to form a tensor with a size of 2  ×  64  ×  64, working as the input to the deep learning-based dose calculation network (deep DoseNet), which outputs the calculated Acuros dose with a size of 256  ×  256. The deep DoseNet (DDN) consists of a feature extraction component and an upscaling part. The DDN converges after ~100 epochs with a learning rate of [Formula: see text], using ADAM. We compared up sampled AAA dose and DDN output with that of AXB. For the evaluation set, the average mean-square-error decreased from 4.7  ×  [Formula: see text] between AAA and AXB to 7.0  ×  10^-5 between DDN and AXB, with an average improvement of ~12 times. The average Gamma index passing rate at 3mm3% improved from 76% between AAA and AXB to 91% between DDN and AXB. The average calculation time is less than 1 ms for a single slice on a NVIDIA DGX workstation. DDN, trained with a large amount of dosimetric data, can be employed as a general-purpose dose calculation acceleration engine across various dose calculation algorithms.

Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157

Dose calculation plays an important role in the accuracy of radiotherapy treatment planning and beam delivery. The Monte Carlo (MC) method is capable of achieving the highest accuracy in radiotherapy dose calculation and has been implemented in many commercial systems for radiotherapy treatment planning. The objective of this task group was to assist clinical physicists with the potentially complex task of acceptance testing and commissioning MC-based treatment planning systems (TPS) for photon and electron beam dose calculations. This report provides an overview on the general approach of clinical implementation and testing of MC-based TPS with a specific focus on models of clinical photon and electron beams. Different types of beam models are described including those that utilize MC simulation of the treatment head and those that rely on analytical methods and measurements. The trade-off between accuracy and efficiency in the various source-modeling approaches is discussed together with guidelines for acceptance testing of MC-based TPS from the clinical standpoint. Specific recommendations are given on methods and practical procedures to commission clinical beam models for MC-based TPS.

Bragg peak characteristics of proton beams within therapeutic energy range and the comparison of stopping power using the GATE Monte Carlo simulation and the NIST data

Purpose:

To examine detail depth dose characteristics of ideal proton beams using the GATE Monte Carlo technique.

Methods:

In this study, in order to improve simulation efficiency, we used pencil beam geometry instead of parallel broad-field geometry. Depth dose distributions for beam energies from 5 to 250 MeV in a water phantom were obtained. This study used parameters namedRpeak,R90,R80,R73,R50, full width at half maximum (FWHM), width of 80–20% distal fall-off (W(80–20)) and peak-to-entrance ratio to represent Bragg peak characteristics. The obtained energy–range relationships were fitted into third-order polynomial formulae. The present study also used the GATE Monte Carlo code to calculate the stopping power of proton pencil beams in a water cubic phantom and compared results with the National Institute of Standards and Technology (NIST) standard reference database.

Results:

The study results revealed deeper penetration, broader FWHM and distal fall-off and decreased peak-to-entrance dose ratio with increasing beam energy. Study results for monoenergetic proton beams showed thatR73can be a good indicator to characterise a range of incident beams. These also suggest FWHM is more sensitive thanW(80–20)distal fall-off in finding initial energy spread. Furthermore, the difference between the obtained stopping power from simulation and NIST data almost in all energies was lower than 1%.

Conclusion:

Detail depth dose characteristics for monoenergetic proton beams within therapeutic energy ranges were reported. These results can serve as a good reference for clinical practitioners in their daily practice.

Efficacy of the Monte Carlo method and dose reduction strategies in paediatric panoramic radiography

Monte Carlo (MC) simulation is a simpler radiation dose assessment method than the conventional method, thermoluminescent dosimetry (TLD). MC simulation and TLD were compared as tools to evaluate the effective dose from paediatric panoramic radiography. Various exposure conditions and machine geometries were simulated using the MC method to investigate factors resulting in effective dose reduction. The effective dose of paediatric panoramic radiography was obtained using an MC simulation and its reliability was verified by a comparison with the value obtained using TLD. Next, 7 factors determining the effective dose in the MC simulation were input with 6 equally-spaced values, and a total of 36 simulations were performed to obtain effective dose values. The correlations between each dose-determining factor and the resulting effective dose were evaluated using linear regression analysis. The TLD-measured dose was 3.850 µSv, while the MC simulation yielded a dose of 3.474 µSv. Beam height was the factor that most strongly influenced the effective dose, while rotation angle and focus-to-patient distance were the least influential factors. MC simulation is comparable to TLD for obtaining effective dose values in paediatric panoramic radiography. Obtaining panoramic radiography with a short beam height can effectively reduce the dose in paediatric patients.

Innovations in Computer Technologies Have Impacted Radiation Dosimetry Through Anatomically Realistic Phantoms and Fast Monte Carlo Simulations

Radiological physics principles have not changed in the past 60 y when computer technologies advanced exponentially. The research field of anatomical modeling for the purpose of radiation dose calculations has experienced an explosion in activity in the past two decades. Such an exciting advancement is due to the feasibility of creating three-dimensional geometric details of the human anatomy from tomographic imaging and of performing Monte Carlo radiation transport simulations on increasingly fast and cheap personal computers. The advent of a new type of high-performance computing hardware in recent years-graphics processing units-has made it feasible to carry out time-consuming Monte Carlo calculations at near real-time speeds. This paper introduces the history of three generations of computational human phantoms (the stylized medical internal radiation dosimetry-type phantoms, the voxelized tomographic phantoms, and the boundary representation deformable phantoms) and new development of the graphics processing unit-based Monte Carlo radiation dose calculations. Examples are given for research projects performed by my students in applying computational phantoms and a new Monte Carlo code, ARCHER, to problems in radiation protection, imaging, and radiotherapy. Finally, the paper discusses challenges and future opportunities for research.

PENELOPE/PRIMO-calculated photon and electron spectra from clinical accelerators

BACKGROUND

The availability of photon and electron spectra in digital form from current accelerators and Monte Carlo (MC) systems is scarce, and one of the packages widely used refers to linacs with a reduced clinical use nowadays. Such spectra are mainly intended for the MC calculation of detector-related quantities in conventional broad beams, where the use of detailed phase-space files (PSFs) is less critical than for MC-based treatment planning applications, but unlike PSFs, spectra can easily be transferred to other computer systems and users.

METHODS

A set of spectra for a range of Varian linacs has been calculated using the PENELOPE/PRIMO MC system. They have been extracted from PSFs tallied for field sizes of 10 cm × 10 cm and 15 cm × 15 cm for photon and electron beams, respectively. The influence of the spectral bin width and of the beam central axis region used to extract the spectra have been analyzed.

RESULTS

Spectra have been compared to those by other authors showing good agreement with those obtained using the, now superseded, EGS4/BEAM MC code, but significant differences with the most widely used photon data set. Other spectra, particularly for electron beams, have not been published previously for the machines simulated in this work. The influence of the bin width on the spectrum mean energy for 6 and 10 MV beams has been found to be negligible. The size of the region used to extract the spectra yields differences of up to 40% for the mean energies in 10 MV beams, but the maximum difference for TPR _20,10 values derived from depth-dose distributions does not exceed 2% relative to those obtained using the PSFs. This corresponds to k_Q differences below 0.2% for a typical Farmer-type chamber, considered to be negligible for reference dosimetry. Different configurations for using electron spectra have been compared for 6 MeV beams, concluding that the geometry used for tallying the PSFs used to extract the spectra must be accounted for in subsequent calculations using the spectra as a source.

CONCLUSIONS

An up-to-date set of consistent spectra for Varian accelerators suitable for the calculation of detector-related quantities in conventional broad beams has been developed and made available in digital form.

Dosimetric comparison of pencil beam and Monte Carlo algorithms in conformal lung radiotherapy

PURPOSE

In this study, lung radiotherapy target volumes as well as critical organs such as the lungs, spinal cord, esophagus, and heart doses calculated using pencil beam (PB) and Monte Carlo (MC) algorithm-based treatment planning systems (TPSs) were compared. The main aim was the evaluation of calculated dose differences between the PB and MC algorithms in a highly heterogeneous medium.

METHODS

A total of 6 MV photon energy conformal treatment plans were created for a RANDO lung phantom using one PB algorithm-based Precise Plan Release 2.16 TPS and one MC algorithm-based Monaco TPS. Thermoluminescence dosimeters (TLDs) were placed into appropriate slices within the RANDO phantom and then irradiated with an Elekta-Synergy® Linear Accelerator for dose verification. Doses were calculated for the V5, V10, V20, and mean lung doses (MLDs) in bilateral lungs and D50, D98, D2, and mean doses in the target volume (planning target volume, PTV).

RESULTS

The minimum, maximum, and mean doses of the target volumes and critical organs in two treatment plans were compared using dose volume histograms (DVHs). The mean dose difference between the PB and MC algorithms for the PTV was 0.3%, whereas the differences in V5, V10, V20, and MLD were 12.5%, 15.8%, 14.4%, and 9.1%, respectively. The differences in PTV coverage between the two algorithms were 0.9%, 2.7% and 0.7% for D50, D98 and D2, respectively.

CONCLUSIONS

A comparison of the dose data acquired in this study reveals that the MC algorithm calculations are closer to the 60 Gy prescribed dose for PTV, while the difference between the PB and MC algorithms was found to be non-significant. Because of the major difference arising from the dose calculation techniques by TPS that was observed in the MLD with significant medium heterogeneity, we recommend the use of the MC algorithm in such heterogeneous sites.

Monte Carlo simulations in radiotherapy dosimetry

BACKGROUND

The use of the Monte Carlo (MC) method in radiotherapy dosimetry has increased almost exponentially in the last decades. Its widespread use in the field has converted this computer simulation technique in a common tool for reference and treatment planning dosimetry calculations.

METHODS

This work reviews the different MC calculations made on dosimetric quantities, like stopping-power ratios and perturbation correction factors required for reference ionization chamber dosimetry, as well as the fully realistic MC simulations currently available on clinical accelerators, detectors and patient treatment planning.

CONCLUSIONS

Issues are raised that include the necessity for consistency in the data throughout the entire dosimetry chain in reference dosimetry, and how Bragg-Gray theory breaks down for small photon fields. Both aspects are less critical for MC treatment planning applications, but there are important constraints like tissue characterization and its patient-to-patient variability, which together with the conversion between dose-to-water and dose-to-tissue, are analysed in detail. Although these constraints are common to all methods and algorithms used in different types of treatment planning systems, they make uncertainties involved in MC treatment planning to still remain "uncertain".

Independent dose validation system for Gamma Knife radiosurgery, using a DICOM-RT interface and Geant4

Leksell GammaPlan was specifically designed for Gamma Knife (GK) radiosurgery planning, but it has limited accuracy for estimating the dose distribution in inhomogeneous areas, such as the embolization of arteriovenous malformations. We aimed to develop an independent patient dose validation system based on a patient-specific model, constructed using a DICOM-RT interface and the Geant4 toolkit. Leksell Gamma Knife Perfexion was designed in Geant4.10.00 and includes a DICOM-RT interface. Output factors for each collimator in a sector and dose distributions in a spherical water phantom calculated using a Monte Carlo (MC) algorithm were compared with the output factors calculated by the tissue maximum ratio (TMR) 10 algorithm and dose distributions measured using film, respectively. Studies using two types of water phantom and two patient simulation cases were evaluated by comparing the dose distributions calculated by the MC, the TMR and the convolution algorithms. The water phantom studies showed that if the beam size is small and the target is located in heterogeneous media, the dose difference could be up to 11%. In the two patient simulations, the TMR algorithm overestimated the dose by about 4% of the maximum dose if a complex and large bony structure was located on the beam path, whereas the convolution algorithm showed similar results to those of the MC algorithm. This study demonstrated that the in-house system could accurately verify the patient dose based on full MC simulation and so would be useful for patient cases where the dose differences are suspected.