Monte Carlo simulation of electron beams from an accelerator head using PENELOPE

Characterizing the voxel-based approaches in radioembolization dosimetry with reDoseMC

BACKGROUND

Yttrium-90 (90 Y $^{90}{\rm {Y}}$ ) represents the primary radioisotope used in radioembolization procedures, while holmium-166 (166 Ho $^{166}{\rm {Ho}}$ ) is hypothesized to serve as a viable substitute for90 Y $^{90}{\rm {Y}}$ due to its comparable therapeutic potential and improved quantitative imaging. Voxel-based dosimetry for these radioisotopes relies on activity images obtained through PET or SPECT and dosimetry methods, including the voxel S-value (VSV) and the local deposition method (LDM). However, the evaluation of the accuracy of absorbed dose calculations has been limited by the use of non-ideal reference standards and investigations restricted to the liver. The objective of this study was to expand upon these dosimetry characterizations by investigating the impact of image resolutions, voxel sizes, target volumes, and tissue materials on the accuracy of90 Y $^{90}{\rm {Y}}$ and166 Ho $^{166}{\rm {Ho}}$ dosimetry techniques.

METHODS

A specialized radiopharmaceutical dosimetry software called reDoseMC was developed using the Geant4 Monte Carlo toolkit and validated by benchmarking the generated90 Y $^{90}{\rm {Y}}$ kernels with published data. The decay spectra of both90 Y $^{90}{\rm {Y}}$ and166 Ho $^{166}{\rm {Ho}}$ were also compared. Multiple VSV kernels were generated for the liver, lungs, soft tissue, and bone for isotropic voxel sizes of 1 mm, 2 mm, and 4 mm. Three theoretical phantom setups were created with 20 or 40 mm activity and mass density inserts for the same three voxel sizes. To replicate the limited spatial resolutions present in PET and SPECT images, image resolutions were modeled using a 3D Gaussian kernel with a Full Width at Half Maximum (FWHM) ranging from 0 to 16 mm and with no added noise. The VSV and LDM dosimetry methods were evaluated by characterizing their respective kernels and analyzing their absorbed dose estimates calculated on theoretical phantoms. The ground truth for these estimations was calculated using reDoseMC.

RESULTS

The decay spectra obtained through reDoseMC showed less than a 1% difference when compared to previously published experimental data for energies below 1.9 MeV in the case of90 Y $^{90}{\rm {Y}}$ and less than 1% for energies below 1.5 MeV for166 Ho $^{166}{\rm {Ho}}$ . Additionally, the validation kernels for90 Y $^{90}{\rm {Y}}$ VSV exhibited results similar to those found in published Monte Carlo codes, with source dose depositions having less than a 3% error margin. Resolution thresholds (FWHM thresh s ${\rm {FWHM}}_\mathrm{thresh}{\rm {s}}$ ), defined as resolutions that resulted in similar dose estimates between the LDM and VSV methods, were observed for90 Y $^{90}{\rm {Y}}$ . They were 1.5 mm for bone, 2.5 mm for soft tissue and liver, and 8.5 mm for lungs. For166 Ho $^{166}{\rm {Ho}}$ , the accuracy of absorbed dose deposition was found to be dependent on the contributions of absorbed dose from photons. Volume errors due to variations in voxel size impacted the final dose estimates. Larger target volumes yielded more accurate mean doses than smaller volumes. For both radioisotopes, the radial dose profiles for the VSV and LDM approximated but never matched the reference standard.

CONCLUSIONS

reDoseMC was developed and validated for radiopharmaceutical dosimetry. The accuracy of voxel-based dosimetry was found to vary widely with changes in image resolutions, voxel sizes, chosen target volumes, and tissue material; hence, the standardization of dosimetry protocols was found to be of great importance for comparable dosimetry analysis.

Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO

BACKGROUND

Monte Carlo simulation of radiation transport for medical linear accelerators (linacs) requires accurate knowledge of the geometrical description of the linac head. Since the geometry of Varian TrueBeam machines has not been disclosed, the manufacturer distributes phase-space files of the linac patient-independent part to allow researchers to compute absorbed dose distributions using the Monte Carlo method. This approach limits the possibility of achieving an arbitrarily small statistical uncertainty. This work investigates the use of the geometry of the Varian Clinac 2100, which is included in the Monte Carlo system PRIMO, as a surrogate.

METHODS

Energy, radial and angular distributions extracted from the TrueBeam phase space files published by the manufacturer and from phase spaces tallied with PRIMO for the Clinac 2100 were compared for the 6, 8, 10 and 15 MV flattened-filtered beams. Dose distributions in water computed for the two sets of PSFs were compared with the Varian Representative Beam Data (RBD) for square fields with sides ranging from 3 to 30 cm. Output factors were calculated for square fields with sides ranging from 2 to 40 cm.

RESULTS

Excellent agreement with the RBD was obtained for the simulations that employed the phase spaces distributed by Varian as well as for those that used the surrogate geometry, reaching in both cases Gamma ([Formula: see text], 2 mm) pass rates larger than [Formula: see text], except for the 15 MV surrogate. This result supports previous investigations that suggest a change in the material composition of the TrueBeam 15 MV flattening filter. In order to get the said agreement, PRIMO simulations were run using enlarged transport parameters to compensate the discrepancies between the actual and surrogate geometries.

CONCLUSIONS

This work sustains the claim that the simulation of the 6, 8 and 10 MV flattening-filtered beams of the TrueBeam linac can be performed using the Clinac 2100 model of PRIMO without significant loss of accuracy.

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.

Assessment of Surface and Build-up Doses for a 6 MV Photon Beam using Parallel Plate Chamber, EBT3 Gafchromic Films, and PRIMO Monte Carlo Simulation Code

Background:

Accurate assessment of surface and build-up doses has a key role in radiotherapy, especially for the superficial lesions with uncertainties involved while performing measurements in the build-up region.

Objective:

This study aimed to assess surface and build-up doses for 6 MV photon beam from linear accelerator using parallel plate ionization chamber, EBT3 Gafchromic films, and PRIMO Monte Carlo (MC) simulation code.

Material and Methods:

In this experimental study, parallel plate chamber (PPC05) and EBT3 Gafchromic films were used to measure doses in a build-up region for 6 MV beam from the linear accelerator for different field sizes at various depths ranging from 0 to 2 cm from the surface with 100 cm source to surface distance (SSD) in a solid water phantom. Measured results were compared with Monte Carlo simulated results using PENELOPE-based PRIMO simulation code for the same setup conditions. Effect of gantry angle incidence and SSD were also analyzed for depth doses at the surface and build-up regions using PPC05 ion chamber and EBT3 Gafchromic films.

Results:

Doses measured at the surface were 14.78%, 19.87%, 25.83%, and 31.54% for field sizes of 5×5, 10×10, 15×15, and 20×20 cm², respectively for a 6 MV photon beam with a parallel plate chamber and 14.20%, 19.14%, 25.149%, and 30.90%, respectively for EBT3 Gafchromic films. Both measurement sets were in good agreement with corresponding simulated results from the PRIMO MC simulation code; doses increase with the increase in field sizes.

Conclusion:

Good agreement was observed between the measured depth doses using parallel plate ionization chamber, EBT3 Gafchromic films, and the simulated depth doses using PRIMO Monte Carlo simulation code.

Experimental Validation of an Analytical Program and a Monte Carlo Simulation for the Computation of the Far Out-of-Field Dose in External Beam Photon Therapy Applied to Pediatric Patients

Background

The out-of-the-field absorbed dose affects the probability of primary second radiation-induced cancers. This is particularly relevant in the case of pediatric treatments. There are currently no methods employed in the clinical routine for the computation of dose distributions from stray radiation in radiotherapy. To overcome this limitation in the framework of conventional teletherapy with photon beams, two computational tools have been developed—one based on an analytical approach and another depending on a fast Monte Carlo algorithm. The purpose of this work is to evaluate the accuracy of these approaches by comparison with experimental data obtained from anthropomorphic phantom irradiations.

Materials and Methods

An anthropomorphic phantom representing a 5-year-old child (ATOM, CIRS) was irradiated considering a brain tumor using a Varian TrueBeam linac. Two treatments for the same planned target volume (PTV) were considered, namely, intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). In all cases, the irradiation was conducted with a 6-MV energy beam using the flattening filter for a prescribed dose of 3.6 Gy to the PTV. The phantom had natLiF : Mg, Cu, P (MCP-N) thermoluminescent dosimeters (TLDs) in its 180 holes. The uncertainty of the experimental data was around 20%, which was mostly attributed to the MCP-N energy dependence. To calculate the out-of-field dose, an analytical algorithm was implemented to be run from a Varian Eclipse TPS. This algorithm considers that all anatomical structures are filled with water, with the exception of the lungs which are made of air. The fast Monte Carlo code dose planning method was also used for computing the out-of-field dose. It was executed from the dose verification system PRIMO using a phase-space file containing 3x109 histories, reaching an average standard statistical uncertainty of less than 0.2% (coverage factor k = 1 ) on all voxels scoring more than 50% of the maximum dose. The standard statistical uncertainty of out-of-field voxels in the Monte Carlo simulation did not exceed 5%. For the Monte Carlo simulation the actual chemical composition of the materials used in ATOM, as provided by the manufacturer, was employed.

Results

In the out-of-the-field region, the absorbed dose was on average four orders of magnitude lower than the dose at the PTV. For the two modalities employed, the discrepancy between the central values of the TLDs located in the out-of-the-field region and the corresponding positions in the analytic model were in general less than 40%. The discrepancy in the lung doses was more pronounced for IMRT. The same comparison between the experimental and the Monte Carlo data yielded differences which are, in general, smaller than 20%. It was observed that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT.

Conclusions

The proposed computational methods for the routine calculation of the out-of-the-field dose produce results that are similar, in most cases, with the experimental data. It has been experimentally found that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT for a given PTV.

[Determination and Verification of Parameters of Lévy Distribution Incident Energy Spectrum of High-energy Electron Beam]

PURPOSE

The incident electron energy spectrum was determined by an estimation formula based on the Lévy distribution in order to calculate the PDD and OAR that is consistent with the measurement.

METHODS

EGSnrc was used to calculate PDD and OAR at nominal energies of 4, 6, 9, 12, and 15 MeV. The parameters for determining the incident electron energy spectrum were adjusted to be a reasonable value in the error between the measured and the calculated values.

RESULTS

Location and scaling parameters were determined to be 0.5 and 0.001, respectively. The calculated PDD based on the determination formula was in agreement with the measurement within 2 mm/2% at all depths. The OAR also was in agreement with the measurement within 2 mm/2%.

CONCLUSION

In this study, the incident electron energy spectrum was estimated by determining the location and scaling parameters. This method is simpler and more accurate than previously reported, and can be applied to the calculation of dose distributions in Monte Carlo simulations.

Latent track formation and recrystallization in swift heavy ion irradiation

Swift heavy ions (SHI) irradiation is a complex coupled multiphysics phenomenon with applications in studying the effects of fission fragments, nano-patterning, and material modification.

A comprehensive Monte Carlo study of CT dose metrics proposed by the AAPM Reports 111 and 200

PURPOSE

A Monte Carlo (MC) modeling of single axial and helical CT scan modes has been developed to compute single and accumulated dose distributions. The radiation emission characteristics of an MDCT scanner has been modeled and used to evaluate the dose deposition in infinitely long head and body PMMA phantoms. The simulated accumulated dose distributions determined the approach to equilibrium function, H(L). From these H ( L ) curves, dose-related information was calculated for different head and body clinical protocols.

METHODS

The PENELOPE/penEasy package has been used to model the single axial and helical procedures and the radiation transport of photons and electrons in the phantoms. The bowtie filters, heel effect, focal-spot angle, and fan-beam geometry were incorporated. Head and body protocols with different pitch values were modeled for x-ray spectra corresponding to 80, 100, 120, and 140 kV. The analytical formulation for the single dose distributions and experimental measurements of single and accumulated dose distributions were employed to validate the MC results. The experimental dose distributions were measured with OSLDs and a thimble ion chamber inserted into PMMA phantoms. Also, the experimental values of the C T D I 100 along the center and peripheral axes of the CTDI phantom served to calibrate the simulated single and accumulated dose distributions.

RESULTS

The match of the simulated dose distributions with the reference data supports the correct modeling of the heel effect and the radiation transport in the phantom material reflected in the tails of the dose distributions. The validation of the x-ray source model was done comparing the CTDI ratios between simulated, measured and CTDosimetry data. The average difference of these ratios for head and body protocols between the simulated and measured data was in the range of 13-17% and between simulated and CTDosimetry data varied 10-13%. The distributions of simulated doses and those measured with the thimble ion chamber are compatible within 3%. In this study, it was demonstrated that the efficiencies of the C T D I 100 measurements in head phantoms with nT = 20 mm and 120 kV are 80.6% and 87.8% at central and peripheral axes, respectively. In the body phantoms with n T = 40 mm and 120 kV, the efficiencies are 56.5% and 86.2% at central and peripheral axes, respectively. In general terms, the clinical parameters such as pitch, beam intensity, and voltage affect the D_eq values with the increase of the pitch decreasing the D_eq and the beam intensity and the voltage increasing its value. The H(L) function does not change with the pitch values, but depends on the phantom axis (central or peripheral).

CONCLUSIONS

The computation of the pitch-equilibrium dose product, D ̂ eq , evidenced the limitations of the C T D I 100 method to determine the dose delivered by a CT scanner. Therefore, quantities derived from the C T D I 100 propagate this limitation. The developed MC model shows excellent compatibility with both measurements and literature quantities defined by AAPM Reports 111 and 200. These results demonstrate the robustness and versatility of the proposed modeling method.

Technical note: MC-GPU breast dosimetry validations with other Monte Carlo codes and phase space file implementation

PURPOSE

To validate the MC-GPU Monte Carlo (MC) code for dosimetric studies in X-ray breast imaging modalities: mammography, digital breast tomosynthesis, contrast enhanced digital mammography, and breast-CT. Moreover, to implement and validate a phase space file generation routine.

METHODS

The MC-GPU code (v. 1.5 DBT) was modified in order to generate phase space files and to be compatible with PENELOPE v. 2018 derived cross-section database. Simulations were performed with homogeneous and anthropomorphic breast phantoms for different breast imaging techniques. The glandular dose was computed for each case and compared with results from the PENELOPE (v. 2014) + penEasy (v. 2015) and egs _ brachy (EGSnrc) MC codes. Afterward, several phase space files were generated with MC-GPU and the scored photon spectra were compared between the codes. The phase space files generated in MC-GPU were used in PENELOPE and EGSnrc to calculate the glandular dose, and compared with the original dose scored in MC-GPU.

RESULTS

MC-GPU showed good agreement with the other codes when calculating the glandular dose distribution for mammography, mean glandular dose for digital breast tomosynthesis, and normalized glandular dose for breast-CT. The latter case showed average/maximum relative differences of 2.3%/27%, respectively, compared to other literature works, with the larger differences observed at low energies (around 10 keV). The recorded photon spectra entering a voxel were similar (within statistical uncertainties) between the three MC codes. Finally, the reconstructed glandular dose in a voxel from a phase space file differs by less than 0.65%, with an average of 0.18%-0.22% between the different MC codes, agreement within approximately 2 σ statistical uncertainties. In some scenarios, the simulations performed in MC-GPU were from 20 up to 40 times faster than those performed by PENELOPE.

CONCLUSIONS

The results indicate that MC-GPU code is suitable for breast dosimetric studies for different X-ray breast imaging modalities, with the advantage of a high performance derived from GPUs. The phase space file implementation was validated and is compatible with the IAEA standard, allowing multiscale MC simulations with a combination of CPU and GPU codes.

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.

Fast Monte Carlo codes for occupational dosimetry in interventional radiology

PURPOSE

Interventional radiology techniques cause radiation exposure both to patient and personnel. The radiation dose to the operator is usually measured with dosimeters located at specific points above or below the lead aprons. The aim of this study is to develop and validate two fast Monte Carlo (MC) codes for radiation transport in order to improve the assessment of individual doses in interventional radiology. The proposed methodology reduces the number of required dosemeters and provides immediate dose results.

METHODS

Two fast MC simulation codes, PENELOPE/penEasyIR and MCGPU-IR, have been developed. Both codes have been validated by comparing fast MC calculations with the multipurpose PENELOPE MC code and with measurements during a realistic interventional procedure.

RESULTS

The new codes were tested with a computation time of about 120 s to estimate operator doses while a standard simulation needs several days to obtain similar uncertainties. When compared with the standard calculation in simple set-ups, MCGPU-IR tends to underestimate doses (up to 5%), while PENELOPE/penEasyIR overestimates them (up to 18%). When comparing both fast MC codes with experimental values in realistic set-ups, differences are within 25%. These differences are within accepted uncertainties in individual monitoring.

CONCLUSION

The study highlights the fact that computational dosimetry based on the use of fast MC codes can provide good estimates of the personal dose equivalent and overcome some of the limitations of occupational monitoring in interventional radiology. Notably, MCGPU-IR calculates both organ doses and effective dose, providing a better estimate of radiation risk.

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation

The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly used in breast cancer screening and diagnostics. Still, the severely limited 3rd dimension information in DBT has not been used, until now, to estimate the true breast density or the patient-specific dose. This study proposes a reconstruction algorithm for DBT based on deep learning specifically optimized for these tasks. The algorithm, which we name DBToR, is based on unrolling a proximal-dual optimization method. The proximal operators are replaced with convolutional neural networks and prior knowledge is included in the model. This extends previous work on a deep learning-based reconstruction model by providing both the primal and the dual blocks with breast thickness information, which is available in DBT. Training and testing of the model were performed using virtual patient phantoms from two different sources. Reconstruction performance, and accuracy in estimation of breast density and radiation dose, were estimated, showing high accuracy (density <±3%; dose <±20%) without bias, significantly improving on the current state-of-the-art. This work also lays the groundwork for developing a deep learning-based reconstruction algorithm for the task of image interpretation by radiologists.

Monte Carlo verification of output correction factors for a TrueBeam STx®

The recent publication of the new code of practice IAEA/AAPM TRS-483 introduces output correction factors to correct detector response changes in relative dosimetry of small photon beams. In TRS-483, average correction factors are reported for several detectors in high-energy photon beams at 6 and 10 MV with and without flattening filter. These correction factors were determined by Monte Carlo simulation or experimental measurements using several linacs of different brands and vendors. The goal of this work was to validate the output correction factors reported in TRS-483 for 6 MV photon beams of a TrueBeam STx® linac. The validation was performed using Monte Carlo simulations of four radiation detectors employed in the dosimetry of small photon beams and whose output correction factors were determined using a different radiation source than TrueBeam STx®. The results show that Monte Carlo calculated output correction factors, and those reported in the code of practice TRS-483 fully agree within ∼1%. The use of generic correction factors for a TrueBeam STx® and the detectors studied in this work is suitable for small field dosimetry static beams within the uncertainties of Monte Carlo calculations and output correction factors reported in TRS-483.

Normalized glandular dose coefficients for digital breast tomosynthesis systems with a homogeneous breast model

This work aims at calculating and releasing tabulated values of dose conversion coefficients, DgN_DBT, for mean glandular dose (MGD) estimates in digital breast tomosynthesis (DBT). The DgN_DBT coefficients are proposed as unique conversion coefficients for MGD estimates, in place of dose conversion coefficients in mammography (DgN_DM or c, g, s triad as proposed in worldwide quality assurance protocols) used together with the T correction factor. DgN_DBT is the MGD per unit incident air kerma measured at the breast surface for a 0° projection and the entire tube load used for the scan. The dataset of polyenergetic DgN_DBT coefficients was derived via a Monte Carlo software based on the Geant4 toolkit. Dose coefficients were calculated for a grid of values of breast characteristics (breast thickness in the range 20-90 mm and glandular fraction by mass of 1%, 25%, 50%, 75%, 100%) and the simulated geometries, scan protocols, irradiation geometries and typical spectral qualities replicated those of six commercial DBT systems (GE SenoClaire, Hologic Selenia Dimensions, GE Senographe Pristina, Fujifilm Amulet Innovality, Siemens Mammomat Inspiration and IMS Giotto Class). For given breast characteristics, target/filter combination, tube voltage and half value layer (HVL), two spectra with two HVL values have been simulated in order to permit MGD estimates from experimental HVL values via mathematical interpolation from tabulated values. The adopted breast model assumes homogenous composition of glandular and adipose tissues; it includes a 1.45 mm thick skin envelope in place of the 4-5 mm envelope commonly adopted in dosimetry protocols. The simulation code was validated versus AAPM Task group 195 Monte Carlo reference data sets (absolute differences not higher than 1.1%) and by comparison to relative dosimetry measurements with radiochromic film in a PMMA test object (differences within the maximum experimental uncertainty of 11%). The calculated coefficients show maximum relative deviations of -17.6% and +6.1% from those provided by the DBT dose coefficients adopted in the EUREF protocol and of 1.5%, on average, from data in the AAPM TG223 report. A spreadsheet is provided for interpolating the tabulated DgN_DBT coefficients for arbitrary values of HVL, compressed breast thickness and glandular fraction, in the corresponding investigated ranges, for each DBT unit modeled in this work.

A structural analytic method on the phase space data of Linac 4 MV photons based on the real world

PURPOSE

It was given that the characteristics of the fluence distribution and the energy spectrum structure of 4MV photons on the Phase Space (PhSp) plane and a method to analyzing the characteristics.

METHODS

After the PhSp file of 4 MV photons was acquired by the method of Monte Carlo (MC) calculation, the photons recorded by PhSp file were grouped based on the energy bin, and it was analyzed that the spatial distribution and energy spectrum structure of the photons. The photons in each energy group were continually grouped to sub-files according to momentum bin, and the primary and scattered photons could be separated according to the character of the fluence distribution of the photons in the sub-files.

RESULTS

The energy of 4 MV beam is a continuous spectrum. The energy constituent on a pixel at different distances from the center point is different, and the average energy on the center axis of the field is the highest; The photons with 0-1.0 MeV had 42.6% of all; that with energy more than 3.0 MeV had 11.7%; greater than 4 MeV, just 1.5%. The primary and scattered photons were easy collected according to the distribution characteristics of sub-groups.

CONCLUSIONS

The work to acquire and analyze the PhSp file of the 4 MV beam is significant. 4 MV, 6 MV, 8 MV, 10 MV and 15 MV energy beams basically cover the beams of radiotherapy, and a database of the energy beams could be built for the MC related research of other scholars.

Accounting for prompt gamma emission and detection for range verification in proton therapy treatment planning

Prompt gamma (PG) imaging is widely investigated as one of the most promising methods for proton range verification in proton therapy. The performance of this technique is affected by several factors like tissue heterogeneity, number of protons in the considered pencil beam and the detection device. Our previous work proposed a new treatment planning concept which boosts the number of protons of a few PG monitoring-friendly pencil beams (PBs), selected on the basis of two proposed indicators quantifying the conformity between the dose and PG at the emission level, above the desired detectability threshold. To further explore this method at the detection level, in this work we investigated the response of a knife-edge slit PG camera which was deployed in the first clinical application of PG to proton therapy monitoring. The REGistration Graphical User Interface (REGGUI) is employed to simulate the PG emission, PG detection as well as the corresponding dose distribution. As the PG signal detected by this kind of PG camera is sensitive to the relative position of the camera and PG signal falloff, we optimized our PB selection method for this camera by introducing a new camera position indicator identifying whether the expected falloff of the PG signal is centered in the field of view of the camera or not. Our camera-adapted PB selection method is investigated using computed tomography (CT) scans at two different treatment time points of a head and neck, and a prostate cancer patient under scenarios considering different statistics level. The results show that a precision of 0.8 mm for PG falloff identification can be achieved when a PB has more than 2 × 10⁸ primary protons. Except for one case due to unpredictable and comparably large anatomical changes, the PG signals of most of the PBs recommended by all our indicators are observed to be reliable for proton range verification with deviations between the inter-fractional shift of proton range (as deduced from the PB dose distribution) and the detected PG signal within 2.0 mm. In contrast, a shift difference up to 9.6 mm has been observed for the rejected PBs. The magnitude of the proton range shift due to the inter-fractional anatomical changes is observed to be up to 23 mm. The proposed indicators are shown to be valuable for identifying and recommending reliable PBs to create new PG monitoring-friendly TPs. Comparison between our PB boosting method and the alternative PB aggregation, which combines the signal of nearby PBs to reach the desired counting statistics, is also discussed.

The impact of x-ray incident angle on indirect fluoroscopy skin dose estimation

Indirect dosimetry to calculate peak skin dose (PSD) is generally based on reference air kerma or kerma-area-product, with effects of table attenuation, inverse square law and backscatter factor applied. When the incident x-ray beam angle changes, these factors would change as well. The purpose of this study is to identify the impact of incident x-ray beam angle on the accuracy of indirect PSD calculation and develop a correction method. Monte Carlo simulation was conducted to assist analytical equation derivation and to validate the developed analytical method. Direct PSD measurements were performed a Siemens Artis Zee biplane fluoroscopy and a GE OEC C-Arm at different angles to validate the proposed correction method and its independence of fluoroscopy systems. Compared with MC simulated PSD, the derived analytical equation successfully predicts these PSD changes for incident angles of 0, 15, 30 and 40 degrees, with the residual error magnitude of 0.3%–3.1% corresponding to different SSDs. The agreement between calculated PSD also agrees well with direct measurement.

Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

BACKGROUND

Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing.

AIMS

To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics.

MATERIALS AND METHODS

G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes.

RESULTS

This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.

DISCUSSION

Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics.

CONCLUSION

The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

GPU-accelerated Monte Carlo simulation of MV-CBCT

Monte Carlo simulation (MCS) is one of the most accurate computation methods for dose calculation and image formation in radiation therapy. However, the high computational complexity and long execution time of MCS limits its broad use. In this paper, we present a novel strategy to accelerate MCS using a graphic processing unit (GPU), and we demonstrate the application in mega-voltage (MV) cone-beam computed tomography (CBCT) simulation. A new framework that generates a series of MV projections from a single simulation run is designed specifically for MV-CBCT acquisition. A Geant4-based GPU code for photon simulation is incorporated into the framework for the simulation of photon transport through a phantom volume. The FastEPID method, which accelerates the simulation of MV images, is modified and integrated into the framework. The proposed GPU-based simulation strategy was tested for its accuracy and efficiency in a Catphan 604 phantom and an anthropomorphic pelvis phantom with beam energies at 2.5 MV, 6 MV, and 6 MV FFF. In all cases, the proposed GPU-based simulation demonstrated great simulation accuracy and excellent agreement with measurement and CPU-based simulation in terms of reconstructed image qualities. The MV-CBCT simulation was accelerated by factors of roughly 900-2300 using an NVIDIA Tesla V100 GPU card against a 2.5 GHz AMD Opteron™ Processor 6380.

Validation of irtGPUMCD, a GPU-based Monte Carlo internal dosimetry framework for radionuclide therapy

PURPOSE

Monte Carlo (MC) simulations are highly desirable for dose treatment planning and evaluation in radiation oncology. This is true also in emerging nuclear medicine applications such as internal radiotherapy with radionuclides. The purpose of this study is the validation of irtGPUMCD, a GPU-based MC code for dose calculations in internal radiotherapy.

METHODS

The female and male phantoms of the International Commission on Radiological Protection (ICRP 110) were used as benchmarking geometries for this study focused on ¹⁷⁷Lu and including ^99mTc and ¹³¹I. Dose calculations were also conducted for a real patient. For phantoms, twelve anatomical structures were considered as target/source organs. The S-values were evaluated with irtGPUMCD simulations (10⁸ photons), with gamma branching ratios of ICRP 107 publication. The ¹⁷⁷Lu electrons S-values were calculated for source organs only, based on local deposition of dose in irtGPUMCD. The S-value relative difference between irtGPUMCD and IDAC-DOSE were evaluated for all targets/sources considered. A DVHs comparison with GATE was conducted. An exponential track length estimator was introduced in irtGPUMCD to increase computational efficiency.

RESULTS

The relative S-value differences between irtGPUMCD and IDAC-DOSE were <5% while this comparison with GATE was <1%. The DVHs dosimetric indices comparison between GATE and irtGPUMCD for the patient led to an excellent agreement (<2%). The time required for the simulation of 10⁸ photons was 1.5 min for the female phantom, and one minute for the real patient (<1% uncertainty). These results are promising and let envision the use of irtGPUMCD for internal dosimetry in clinical applications.

Small field output correction factors of the microSilicon detector and a deeper understanding of their origin by quantifying perturbation factors

Purpose

The aim of this study is the experimental and Monte Carlo‐based determination of small field correction factors for the unshielded silicon detector microSilicon for a standard linear accelerator as well as the Cyberknife System. In addition, a detailed Monte Carlo analysis has been performed by modifying the detector models stepwise to study the influences of the detector’s components.

Methods

Small field output correction factors have been determined for the new unshielded silicon diode detector, microSilicon (type 60023, PTW Freiburg, Germany) as well as for the predecessors Diode E (type 60017, PTW Freiburg, Germany) and Diode SRS (type 60018, PTW Freiburg, Germany) for a Varian TrueBeam linear accelerator at 6 MV and a Cyberknife system. For the experimental determination, an Exradin W1 scintillation detector (Standard Imaging, Middleton, USA) has been used as reference. The Monte Carlo simulations have been performed with EGSnrc and phase space files from IAEA as well as detector models according to manufacturer blueprints. To investigate the influence of the detector’s components, the detector models have been modified stepwise.

Results

The correction factors for the smallest field size investigated at the TrueBeam linear accelerator (equivalent dosimetric square field side length S_clin = 6.3 mm) are 0.983 and 0.939 for the microSilicon and Diode E, respectively. At the Cyberknife system, the correction factors of the microSilicon are 0.967 at the smallest 5‐mm collimator compared to 0.928 for the Diode SRS. Monte Carlo simulations show comparable results from the measurements and literature.

Conclusion

The microSilicon (type 60023) detector requires less correction than its predecessors, Diode E (type 60017) and Diode SRS (type 60018). The detector housing has been demonstrated to cause the largest perturbation, mainly due to the enhanced density of the epoxy encapsulation surrounding the silicon chip. This density has been rendered more water equivalent in case of the microSilicon detector to minimize the associated perturbation. The sensitive volume itself has been shown not to cause observable field size‐dependent perturbation except for the volume‐averaging effect, where the slightly larger diameter of the sensitive volume of the microSilicon (1.5 mm) is still small at the smallest field size investigated with corrections <2%. The new microSilicon fulfils the 5% correction limit recommended by the TRS 483 for output factor measurements at all conditions investigated in this work.

Calculated beam quality correction factors for ionization chambers in MV photon beams

The beam quality correction factor, [Formula: see text], which corrects for the difference in the ionization chamber response between the reference and clinical beam quality, is an integral part of radiation therapy dosimetry. The uncertainty of [Formula: see text] is one of the most significant sources of uncertainty in the dose determination. To improve the accuracy of available [Formula: see text] data, four partners calculated [Formula: see text] factors for 10 ionization chamber models in linear accelerator beams with accelerator voltages ranging from 6 MV to 25 MV, including flattening-filter-free (FFF) beams. The software used in the calculations were EGSnrc and PENELOPE, and the ICRU report 90 cross section data for water and graphite were included in the simulations. Volume averaging correction factors were calculated to correct for the dose averaging in the chamber cavities. A comparison calculation between partners showed a good agreement, as did comparison with literature. The [Formula: see text] values from TRS-398 were higher than our values for each chamber where data was available. The [Formula: see text] values for the FFF beams did not follow the same [Formula: see text], [Formula: see text] relation as beams with flattening filter (values for 10 MV FFF beams were below fits made to other data on average by 0.3%), although our FFF sources were only for Varian linacs.

Towards 4D dedicated breast CT perfusion imaging of cancer: development and validation of computer simulated images

Dedicated breast CT is a fully tomographic breast imaging modality with potential for various applications throughout breast cancer care. If implemented to perform dynamic contrast-enhanced (CE) imaging (4D breast CT), it could be useful to obtain functional information at high combined spatio-temporal resolution. Before developing a 4D dedicated breast CT system, a computer simulation method for breast CT perfusion imaging is proposed. The simulation uses previously developed patient-based 4D digital breast phantoms, and generates realistic images with the selected acquisition parameters, allowing to investigate the effect of different acquisition settings on image quality. The simulation pipeline includes all steps of the image generation process, from ray tracing and scatter map generation, to the addition of realistic resolution losses and noise models. The pipeline was validated against experimental measurements performed on physical phantoms with a dedicated breast CT system, in terms of average error compared to ground truth projections (6.0%  ±  1.65%), Hounsfield unit (HU) values in a homogeneous phantom (acquired: -149 HU  ±  2 HU; simulated:  -140 HU  ±  2 HU), signal-to-noise ratio (SNR) (average error 6.7%  ±  4.2%), noise power spectra (NPS) (average error 4.3%  ±  2.5%), modulation transfer function (MTF) (average error 8.4%  ±  7.2%), and attenuation of different adipose/glandular equivalent mixtures (average error 6.9%  ±  4.0%) and glandular plus iodinated contrast medium concentrations equivalent mixtures (average error of 9.1%  ±  9.0%). 4D patient images were then simulated for different 4D digital breast phantoms at different air kerma levels to determine the effect of noise on the extracted tumor perfusion curves. In conclusion, the proposed pipeline could simulate images with a good level of realism, resulting in a tool that can be used for the design, development, and optimization of a 4D dedicated breast CT system.

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.

Out-of-Field Dose Calculation by a Commercial Treatment Planning System and Comparison by Monte Carlo Simulation for Varian TrueBeam®

PURPOSE

The calculation accuracy of treatment planning systems (TPSs) drops drastically when the points outside the field edges are considered. The real accuracy of a TPS and linear accelerator (linac) combination for regions outside the field edge is a subject which demands more study. In this study, the accuracy of out-of-field dose calculated by a TPS, used with a TrueBeam® (TB) linac, is quantified.

MATERIALS AND METHODS

For dose calculation, Eclipse™ version 13.7 commissioned for TB machine was used. For comparison, Monte Carlo (MC) methods, as well as the measurements, were used. The VirtuaLinac, a Geant 4-based MC program which is offered as a cloud solution, is used for the generation of input phase-space (PS) files. This PS file was imported into PRIMO (PENELOPE based MC program) for the simulation of out-of-field dose.

RESULTS

In this study, the accuracy of the out-of-field dose calculated by a TPS for a TB linac was estimated. As per the results in comparison with MC simulations, the TPS underestimated the dose by around 45% on an average for the off-axis-distance range considered in this study. As the off-axis distance increased, the underestimation of the dose also increased.

CONCLUSION

In this work, it was observed that the TPS underestimates doses beyond the edges of treatment fields for a clinical treatment executed on a TB machine. This indicates that the out-of-field dose from TPSs should only be used with a clear understanding of the inaccuracy of dose calculations beyond the edge of the field.

Impact of backscatter material thickness on the depth dose of orthovoltage irradiators for radiobiology research

The orthovoltage x-ray energy frequently used in radiation research is prone to dosimetry errors due to insufficient backscatter conditions. In many radiobiology studies, especially for cell irradiations, precise dose calculation algorithms such as Convolution-Superposition or Monte Carlo are impractical and as such, less accurate hand calculation methods are used for dose estimation. These dose estimation methods typically assume full backscatter conditions. The purpose of this study is to demonstrate the magnitude of the dose error that results from insufficient backscatter, and to provide lookup tables to account this issue. The beam spectra of several widely used commercial systems (XRAD-225, XRAD-320, SARRP) were used in Monte Carlo (MC) simulations on a series of phantom setups to investigate the impact of varying backscatter conditions on dosimetry. The depth dose curves for different field sizes, water phantom thicknesses and beam qualities were generated. In addition, depth dependent backscatter factors for different field sizes and different beam qualities were calculated. It is demonstrated that as much as a 50% dose difference exists for different backscatter conditions at the beam qualities studied. The choice of cell dish size as well as other changes in the experiment setup can have more than 10% impact on the dose. The impact of backscatter is reduced with a decrease in field size. Further, the thickness needed to provide full backscatter can be approximated as being equal to the field size. It is imperative to ensure full backscatter conditions during system and dosimeter calibration, or to use the look-up table provided in this study.

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.

Monte Carlo study on optimal breast voxel resolution for dosimetry estimates in digital breast tomosynthesis

Digital breast tomosynthesis (DBT) is currently used as an adjunct technique to digital mammography (DM) for breast cancer imaging. Being a quasi-3D image, DBT is capable of providing depth information on the internal breast glandular tissue distribution, which may be enough to obtain an accurate patient-specific radiation dose estimate. However, for this, information regarding the location of the glandular tissue, especially in the vertical direction (i.e. x-ray source to detector), is needed. Therefore, a dedicated reconstruction algorithm designed to localize the amount of glandular tissue, rather than for optimal diagnostic value, could be desirable. Such a reconstruction algorithm, or, alternatively, a reconstructed DBT image classification algorithm, could benefit from the use of larger voxels, rather than the small sizes typically used for the diagnostic task. In addition, the Monte Carlo (MC) based dose estimates would be accelerated by the representation of the breast tissue with fewer and larger voxels. Therefore, in this study we investigate the optimal DBT reconstructed voxel size that allows accurate dose evaluations (i.e. within 5%) using a validated Geant4-based MC code. For this, sixty patient-based breast models, previously acquired using dedicated breast computed tomography (BCT) images, were deformed to reproduce the breast during compression under a given DBT scenario. Two re-binning approaches were applied to the compressed phantoms, leading to isotropic and anisotropic voxels of different volumes. MC DBT simulations were performed reproducing the acquisition geometry of a SIEMENS Mammomat Inspiration system. Results show that isotropic cubic voxels of 2.73 mm size provide a dose estimate accurate to within 5% for 51/60 patients, while a comparable accuracy is obtained with anisotropic voxels of dimension 5.46  ×  5.46  ×  2.73 mm³. In addition, the MC simulation time is reduced by more than half in respect to the original voxel dimension of 0.273  ×  0.273  ×  0.273 mm³ when either of the proposed re-binning approaches is used. No significant differences in the effect of binning on the dose estimates are observed (Wilcoxon-Mann-Whitney test, p-value  >  0.4) between the 0° the 23° (i.e. the widest angular range) exposure.

Validation and application of a fast Monte Carlo algorithm for assessing the clinical impact of approximations in analytical dose calculations for pencil beam scanning proton therapy

PURPOSE

Monte Carlo (MC) dose calculation is generally superior to analytical dose calculation (ADC) used in commercial TPS to model the dose distribution especially for heterogeneous sites, such as lung and head/neck patients. The purpose of this study was to provide a validated, fast, and open-source MC code, MCsquare, to assess the impact of approximations in ADC on clinical pencil beam scanning (PBS) plans covering various sites.

METHODS

First, MCsquare was validated using tissue-mimicking IROC lung phantom measurements as well as benchmarked with the general purpose Monte Carlo TOPAS for patient dose calculation. Then a comparative analysis between MCsquare and ADC was performed for a total of 50 patients with 10 patients per site (including liver, pelvis, brain, head-and-neck, and lung). Differences among TOPAS, MCsquare, and ADC were evaluated using four dosimetric indices based on the dose-volume histogram (target Dmean, D95, homogeneity index, V95), a 3D gamma index analysis (using 3%/3 mm criteria), and estimations of tumor control probability (TCP).

RESULTS

Comparison between MCsquare and TOPAS showed less than 1.8% difference for all of the dosimetric indices/TCP values and resulted in a 3D gamma index passing rate for voxels within the target in excess of 99%. When comparing ADC and MCsquare, the variances of all the indices were found to increase as the degree of tissue heterogeneity increased. In the case of lung, the D95s for ADC were found to differ by as much as 6.5% from the corresponding MCsquare statistic. The median gamma index passing rate for voxels within the target volume decreased from 99.3% for liver to 75.8% for lung. Resulting TCP differences can be large for lung (≤10.5%) and head-and-neck (≤6.2%), while smaller for brain, pelvis and liver (≤1.5%).

CONCLUSIONS

Given the differences found in the analysis, accurate dose calculation algorithms such as Monte Carlo simulations are needed for proton therapy, especially for disease sites with high heterogeneity, such as head-and-neck and lung. The establishment of MCsquare can facilitate patient plan reviews at any institution and can potentially provide unbiased comparison in clinical trials given its accuracy, speed and open-source availability.

Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system

PURPOSE

To validate Monte Carlo (MC)-based breast dosimetry estimations using both a homogeneous and a 3D anthropomorphic breast phantom under polyenergetic irradiation for internal breast dosimetry purposes.

METHODS

Experimental measurements were performed with a clinical digital mammography system (Mammomat Inspiration, Siemens Healthcare), using the x-ray spectrum selected by the automatic exposure control and a tube current-exposure time product of 360 mAs. A homogeneous 50% glandular breast phantom and a 3D anthropomorphic breast phantom were used to investigate the dose at different depths (range 0-4 cm with 1 cm steps) for the homogeneous case and at a depth of 2.25 cm for the anthropomorphic case. Local dose deposition was measured using thermoluminescent dosimeters (TLD), metal oxide semiconductor field-effect transistor dosimeters (MOSFET), and GafChromic™ films. A Geant4-based MC simulation was modified to match the clinical experimental setup. Thirty sensitive volumes (3.2 × 3.2 × 0.38 mm3 ) on the axial-phantom plane were included at each depth in the simulation to characterize the internal dose variation and compare it to the experimental TLD and MOSFET measurements. The experimental 2D dose maps obtained with the GafChromic™ films were compared to the simulated 2D dose distributions.

RESULTS

Due to the energy dependence of the dosimeters and due to x-ray beam hardening, dosimeters based on these three technologies have to be calibrated at each depth of the phantom. As expected, the dose was found to decrease with increasing phantom depth, with the reduction being ~93% after 4 cm for the homogeneous breast phantom. The 2D dose map showed nonuniformities in the dose distribution in the axial plane of the phantom. The mean combined standard uncertainty increased with phantom depth by up to 5.3% for TLD, 6.3% for MOSFET, and 9.6% for GafChromic™ film. In the case of a heterogeneous phantom, the dosimeters are able to detect local dose gradient variations. In particular, GafChromic™ film showed local dose variations of about 46% at the boundaries of two materials.

CONCLUSIONS

Results showed a good agreement between experimental measurements (with TLD and MOSFET) and MC data for both homogeneous and anthropomorphic breast phantoms. Larger discrepancies are found when comparing the GafChromic™ dose values to the MC results due to the inherent less precise nature of the former. MC validations in a heterogeneous background at the level of local dose deposition and in absolute terms play a fundamental role in the development of an accurate method to estimate radiation dose. The potential introduction of a breast dosimetry model involving a nonhomogeneous glandular/adipose tissue composition makes the validation of internal dose distributions estimates crucial.

CPU time optimization and precise adjustment of the Geant4 physics parameters for a VARIAN 2100 C/D gamma radiotherapy linear accelerator simulation using GAMOS

We have verified the GAMOS/Geant4 simulation model of a 6 MV VARIAN Clinac 2100 C/D linear accelerator by the procedure of adjusting the initial beam parameters to fit the percentage depth dose and cross-profile dose experimental data at different depths in a water phantom. Thanks to the use of a wide range of field sizes, from 2  ×  2 cm² to 40  ×  40 cm², a small phantom voxel size and high statistics, fine precision in the determination of the beam parameters has been achieved. This precision has allowed us to make a thorough study of the different physics models and parameters that Geant4 offers. The three Geant4 electromagnetic physics sets of models, i.e. Standard, Livermore and Penelope, have been compared to the experiment, testing the four different models of angular bremsstrahlung distributions as well as the three available multiple-scattering models, and optimizing the most relevant Geant4 electromagnetic physics parameters. Before the fitting, a comprehensive CPU time optimization has been done, using several of the Geant4 efficiency improvement techniques plus a few more developed in GAMOS.

Evaluation of latent variances in Monte Carlo dose calculations with Varian TrueBeam photon phase-spaces used as a particle source

The purpose of this study was to evaluate the latent variance (LV) of Varian TrueBeam photon phase-space files (PSF) for open 10  ×  10 cm² and small stereotactic fields and estimate the number of phase spaces required to be summed up in order to maintain sub-percent LV in Monte Carlo (MC) dose calculations. BEAMnrc/DOSXYZnrc software was used to transport particles from Varian phase-space files (PSF_A) through the secondary collimators. Transported particles were scored into another phase-space located under the jaws (PSF_B), or transported further through the cone collimators and scored straight below, forming PSF_C. Phase-space files (PSF_B) were scored for 6 MV-FFF, 6 MV, 10 MV-FFF, 10 MV and 15 MV beams with 10  ×  10 cm² field size, and PSF_C were scored for 6 MV beam under circular cones of 0.13, 0.25, 0.35, and 1 cm diameter. Both PSF_B and PSF_C were transported into a water phantom with particle recycling number ranging from 10 to 1000. For 10  ×  10 cm² fields 0.5  ×  0.5  ×  0.5 cm³ voxels were used to score the dose, whereas the dose was scored in 0.1  ×  0.1  ×  0.5 cm³ voxels for beams collimated with small cones. In addition, for small 0.25 cm diameter cone-collimated 6 MV beam, phantom voxel size varied as 0.02  ×  0.02  ×  0.5 cm³, 0.05  ×  0.05  ×  0.5 cm³ and 0.1  ×  0.1  ×  0.5 cm³. Dose variances were scored in all cases and LV evaluated as per Sempau et al. For the 10  ×  10 cm² fields calculated LVs were greatest at the phantom surface and decreased with depth until they reached a plateau at 5 cm depth. LVs were found to be 0.54%, 0.96%, 0.35%, 0.69% and 0.57% for the 6 MV-FFF, 6 MV, 10 MV-FFF, 10 MV and 15 MV energies, respectively at the depth of 10 cm. For the 6 MV phase-space collimated with cones of 0.13, 0.25, 0.35, 1.0 cm diameter, the LVs calculated at 1.5 cm depth were 75.6%, 25.4%, 17.6% and 8.0% respectively. Calculated LV for the 0.25 cm cone-collimated 6 MV beam were 61.2%, 40.7%, 22.5% in 0.02  ×  0.02  ×  0.5 cm³, 0.05  ×  0.05  ×  0.5 cm³ and 0.1  ×  0.1  ×  0.5 cm³ voxels respectively. In order to achieve sub-percent LV in open 10  ×  10 cm² field MC simulations a single PSF can be used, whereas for small SRS fields (0.13-1.0 cm) more PSFs (66-8 PSFs) would have to be summed.

Efficiency improvement in proton dose calculations with an equivalent restricted stopping power formalism

The equivalent restricted stopping power formalism is introduced for proton mean energy loss calculations under the continuous slowing down approximation. The objective is the acceleration of Monte Carlo dose calculations by allowing larger steps while preserving accuracy. The fractional energy loss per step length ϵ was obtained with a secant method and a Gauss-Kronrod quadrature estimation of the integral equation relating the mean energy loss to the step length. The midpoint rule of the Newton-Cotes formulae was then used to solve this equation, allowing the creation of a lookup table linking ϵ to the equivalent restricted stopping power L _eq, used here as a key physical quantity. The mean energy loss for any step length was simply defined as the product of the step length with L _eq. Proton inelastic collisions with electrons were added to GPUMCD, a GPU-based Monte Carlo dose calculation code. The proton continuous slowing-down was modelled with the L _eq formalism. GPUMCD was compared to Geant4 in a validation study where ionization processes alone were activated and a voxelized geometry was used. The energy straggling was first switched off to validate the L _eq formalism alone. Dose differences between Geant4 and GPUMCD were smaller than 0.31% for the L _eq formalism. The mean error and the standard deviation were below 0.035% and 0.038% respectively. 99.4 to 100% of GPUMCD dose points were consistent with a 0.3% dose tolerance. GPUMCD 80% falloff positions ([Formula: see text]) matched Geant's [Formula: see text] within 1 μm. With the energy straggling, dose differences were below 2.7% in the Bragg peak falloff and smaller than 0.83% elsewhere. The [Formula: see text] positions matched within 100 μm. The overall computation times to transport one million protons with GPUMCD were 31-173 ms. Under similar conditions, Geant4 computation times were 1.4-20 h. The L _eq formalism led to an intrinsic efficiency gain factor ranging between 30-630, increasing with the prescribed accuracy of simulations. The L _eq formalism allows larger steps leading to a [Formula: see text] algorithmic time complexity. It significantly accelerates Monte Carlo proton transport while preserving accuracy. It therefore constitutes a promising variance reduction technique for computing proton dose distributions in a clinical context.

Rat sensorimotor cortex tolerance to parallel transections induced by synchrotron-generated X-ray microbeams

Microbeam radiation therapy is a novel preclinical technique, which uses synchrotron-generated X-rays for the treatment of brain tumours and drug-resistant epilepsies. In order to safely translate this approach to humans, a more in-depth knowledge of the long-term radiobiology of microbeams in healthy tissues is required. We report here the result of the characterization of the rat sensorimotor cortex tolerance to microradiosurgical parallel transections. Healthy adult male Wistar rats underwent irradiation with arrays of parallel microbeams. Beam thickness, spacing and incident dose were 100 or 600 µm, 400 or 1200 µm and 360 or 150 Gy, respectively. Motor performance was carried over a 3-month period. Three months after irradiation rats were sacrificed to evaluate the effects of irradiation on brain tissues by histology and immunohistochemistry. Microbeam irradiation of sensorimotor cortex did not affect weight gain and motor performance. No gross signs of paralysis or paresis were also observed. The cortical architecture was not altered, despite the presence of cell death along the irradiation path. Reactive gliosis was evident in the microbeam path of rats irradiated with 150 Gy, whereas no increase was observed in rats irradiated with 360 Gy.

A single-source photon source model of a linear accelerator for Monte Carlo dose calculation

PURPOSE

To introduce a new method of deriving a virtual source model (VSM) of a linear accelerator photon beam from a phase space file (PSF) for Monte Carlo (MC) dose calculation.

MATERIALS AND METHODS

A PSF of a 6 MV photon beam was generated by simulating the interactions of primary electrons with the relevant geometries of a Synergy linear accelerator (Elekta AB, Stockholm, Sweden) and recording the particles that reach a plane 16 cm downstream the electron source. Probability distribution functions (PDFs) for particle positions and energies were derived from the analysis of the PSF. These PDFs were implemented in the VSM using inverse transform sampling. To model particle directions, the phase space plane was divided into a regular square grid. Each element of the grid corresponds to an area of 1 mm2 in the phase space plane. The average direction cosines, Pearson correlation coefficient (PCC) between photon energies and their direction cosines, as well as the PCC between the direction cosines were calculated for each grid element. Weighted polynomial surfaces were then fitted to these 2D data. The weights are used to correct for heteroscedasticity across the phase space bins. The directions of the particles created by the VSM were calculated from these fitted functions. The VSM was validated against the PSF by comparing the doses calculated by the two methods for different square field sizes. The comparisons were performed with profile and gamma analyses.

RESULTS

The doses calculated with the PSF and VSM agree to within 3% /1 mm (>95% pixel pass rate) for the evaluated fields.

CONCLUSION

A new method of deriving a virtual photon source model of a linear accelerator from a PSF file for MC dose calculation was developed. Validation results show that the doses calculated with the VSM and the PSF agree to within 3% /1 mm.

Monte Carlo dose calculations for high-dose-rate brachytherapy using GPU-accelerated processing

PURPOSE

Current clinical brachytherapy dose calculations are typically based on the Association of American Physicists in Medicine Task Group report 43 (TG-43) guidelines, which approximate patient geometry as an infinitely large water phantom. This ignores patient and applicator geometries and heterogeneities, causing dosimetric errors. Although Monte Carlo (MC) dose calculation is commonly recognized as the most accurate method, its associated long computational time is a major bottleneck for routine clinical applications. This article presents our recent developments of a fast MC dose calculation package for high-dose-rate (HDR) brachytherapy, gBMC, built on a graphics processing unit (GPU) platform.

METHODS AND MATERIALS

gBMC-simulated photon transport in voxelized geometry with physics in (192)Ir HDR brachytherapy energy range considered. A phase-space file was used as a source model. GPU-based parallel computation was used to simultaneously transport multiple photons, one on a GPU thread. We validated gBMC by comparing the dose calculation results in water with that computed TG-43. We also studied heterogeneous phantom cases and a patient case and compared gBMC results with Acuros BV results.

RESULTS

Radial dose function in water calculated by gBMC showed <0.6% relative difference from that of the TG-43 data. Difference in anisotropy function was <1%. In two heterogeneous slab phantoms and one shielded cylinder applicator case, average dose discrepancy between gBMC and Acuros BV was <0.87%. For a tandem and ovoid patient case, good agreement between gBMC and Acruos BV results was observed in both isodose lines and dose-volume histograms. In terms of the efficiency, it took ∼47.5 seconds for gBMC to reach 0.15% statistical uncertainty within the 5% isodose line for the patient case.

CONCLUSIONS

The accuracy and efficiency of a new GPU-based MC dose calculation package, gBMC, for HDR brachytherapy make it attractive for clinical applications.

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

PURPOSE

The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field.

METHODS

penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian's kmc.

RESULTS

An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm).

CONCLUSIONS

A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.

Investigation of dosimetric differences between the TMR 10 and convolution algorithm for Gamma Knife stereotactic radiosurgery

Since its inception, doses applied using Gamma Knife Radiosurgery (GKR) have been calculated using a simple TMR algorithm, which assumes the patient's head is of even density, the same as water. This results in a significant approximation of the dose delivered by the Gamma Knife. We investigated how GKR dose calculations varied when using a new convolution algorithm clinically available for GKR planning that takes into account density variations in the head compared with the established calculation algorithm. Fifty‐five patients undergoing GKR and harboring 85 lesions were voluntarily and prospectively enrolled into the study. Their clinical treatment plans were created and delivered using TMR 10, but were then recalculated using the density correction algorithm. Dosimetric differences between the planning algorithms were noted. Beam on time (BOT), which is directly proportional to dose, was the main value investigated. Changes of mean and maximum dose to organs at risk (OAR) were also assessed. Phantom studies were performed to investigate the effect of frame and pin materials on dose calculation using the convolution algorithm. Convolution yielded a mean increase in BOT of 7.4% (3.6%–11.6%). However, approximately 1.5% of this amount was due to the head contour being derived from the CT scans, as opposed to measurements using the Skull Scaling Instrument with TMR. Dose to the cochlea calculated with the convolution algorithm was approximately 7% lower than with the TMR 10 algorithm. No significant difference in relative dose distribution was noted and CT artifact typically caused by the stereotactic frame, glue embolization material or different fixation pin materials did not systematically affect convolution isodoses. Nonetheless, substantial error was introduced to the convolution calculation in one target located exactly in the area of major CT artifact caused by a fixation pin. Inhomogeneity correction using the convolution algorithm results in a considerable, but consistent, dose shift compared to the TMR 10 algorithm traditionally used for GKR. A reduction of the prescription dose may be necessary to obtain the same clinical effect with the convolution algorithm. Head shape definition using CT outlining can reduce treatment uncertainty from head shape approximations.

PACS number(s): 87.53.‐j; 87.55.D; 87.55.kd