MCPI©: A sub-minute Monte Carlo dose calculation engine for prostate implants

An efficient quasi-Monte Carlo method with forced fixed detection for photon scatter simulation in CT

Detected scattered photons can cause cupping and streak artifacts, significantly degrading the quality of CT images. For fast and accurate estimation of scatter intensities resulting from photon interactions with a phantom, we first transform the path probability of photons interacting with the phantom into a high-dimensional integral. Secondly, we develope a new efficient algorithm called gQMCFFD, which combines graphics processing unit(GPU)-based quasi-Monte Carlo (QMC) with forced fixed detection to approximate this integral. QMC uses low discrepancy sequences for simulation and is deterministic versions of Monte Carlo. Numerical experiments show that the results are in excellent agreement and the efficiency improvement factors are 4 ∼ 46 times in all simulations by gQMCFFD with comparison to GPU-based Monte Carlo methods. And by combining gQMCFFD with sparse matrix method, the simulation time is reduced to 2 seconds in a single projection angle and the relative difference is 3.53%.

Haralick texture feature analysis for characterization of specific energy and absorbed dose distributions across cellular to patient length scales

Objective.To investigate an approach for quantitative characterization of the spatial distribution of dosimetric data by introducing Haralick texture feature analysis in this context.Approach.Monte Carlo simulations are used to generate 3D arrays of dosimetric data for 2 scenarios: (1) cell-scale microdosimetry: specific energy (energy imparted per unit mass) in cell-scale targets irradiated by photon spectra (¹²⁵I,¹⁹²Ir, 6 MV); (2) tumour-scale dosimetry: absorbed dose in voxels for idealized models of¹²⁵I permanent implant prostate brachytherapy, considering 'TG186' (realistic tissues including 0% to 5% intraprostatic calcifications; interseed attenuation) and 'TG43' (water model, no interseed attenuation) conditions. Five prominent Haralick features (homogeneity, contrast, correlation, local homogeneity, entropy) are computed and trends are interpreted using fundamental radiation physics.Main results.In the cell-scale scenario, the Haralick measures quantify differences in 3D specific energy distributions due to source spectra. For example, contrast and entropy are highest for¹²⁵I reflecting the large variations in specific energy in adjacent voxels (photoelectric interactions; relatively short range of electrons), while 6 MV has the highest homogeneity with smaller variations in specific energy between voxels (Compton scattering dominates; longer range of electrons). For the tumour-scale scenario, the Haralick measures quantify differences due to TG186/TG43 simulation conditions and the presence of calcifications. For example, as calcifications increase from 0% to 5%, contrast increases while correlation decreases, reflecting the large differences in absorbed dose in adjacent voxels (higher absorbed dose in voxels with calcification due to photoelectric interactions).Significance.Haralick texture analysis provides a quantitative method for the characterization of 3D dosimetric distributions across cellular to tumour length scales, with promising future applications including analyses of multiscale tissue models, patient-specific data, and comparison of treatment approaches.

Validation of the TOPAS Monte Carlo toolkit for LDR brachytherapy simulations

PURPOSE

This work has the purpose of validating the Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for low-dose-rate (LDR) brachytherapy uses.

METHODS AND MATERIALS

Simulations of 12 LDR sources and 2 COMS eye plaques (10 mm and 20 mm in diameter) and comparisons with published reference data from the Carleton Laboratory for Radiotherapy Physics (CLRP), the TG-43 consensus data and the TG-129 consensus data were performed. Sources from the IROC Houston Source Registry were modeled. The OncoSeed 6711 and the SelectSeed 130.002 were also modeled for historical reasons. For each source, the dose rate constant, the radial dose function and the anisotropy functions at 0.5, 1 and 5 cm were extracted. For the eye plaques (loaded with ¹²⁵I sources), dose distribution maps, dose profiles along the central axis and transverse axis were calculated.

RESULTS

Dose rate constants for 11 of the 12 sources are within 4% of the consensus data and within 2% of the CLRP data. The radial dose functions and anisotropy functions are mostly within 2% of the CLRP data. In average, 92% of all voxels are within 1% of the CLRP data for the eye plaques dose distributions. The dose profiles are within 0.5% (central axis) and 1% (transverse axis) of the reference data.

CONCLUSION

The TOPAS MC toolkit was validated for LDR brachytherapy applications. Single-seed and multi-seed results agree with the published reference data. TOPAS has several benefits such as a simplified approach to MC simulations and an accessible brachytherapy package including comprehensive learning resources.

Evaluation of dosimetric effects of metallic artifact reduction and tissue assignment on Monte Carlo dose calculations for 125 I prostate implants

PURPOSE

Monte Carlo (MC) simulation studies, aimed at evaluating the magnitude of tissue heterogeneity in ¹²⁵ I prostate permanent seed implant brachytherapy (BT), customarily use clinical post-implant CT images to generate a virtual representation of a realistic patient model (virtual patient model). Metallic artifact reduction (MAR) techniques and tissue assignment schemes (TAS) are implemented on the post-implant CT images to mollify metallic artifacts due to BT seeds and to assign tissue types to the voxels corresponding to the bright seed spots and streaking artifacts, respectively. The objective of this study is to assess the combined influence of MAR and TAS on MC absorbed dose calculations in post-implant CT-based phantoms. The virtual patient models used for ¹²⁵ I prostate implant MC absorbed dose calculations in this study are derived from the CT images of an external radiotherapy prostate patient without BT seeds and prostatic calcifications, thus averting the need to implement MAR and TAS.

METHODS

The geometry of the IsoSeed I25.S17plus source is validated by comparing the MC calculated results of the TG-43 parameters for the line source approximation with the TG-43U1S2 consensus data. Four MC absorbed dose calculations are performed in two virtual patient models using the egs_brachy MC code: (1) TG-43-based D_{w,w-TG 43} , (2) D_w,w-MBDC that accounts for interseed scattering and attenuation (ISA), (3) D_m,m that examines ISA and tissue heterogeneity by scoring absorbed dose in tissue, and (4) D_w,m that unlike D_m,m scores absorbed dose in water. The MC absorbed doses (1) and (2) are simulated in a TG-43 patient phantom derived by assigning the densities of every voxel to 1.00 g cm^-3 (water), whereas MC absorbed doses (3) and (4) are scored in the TG-186 patient phantom generated by mapping the mass density of each voxel to tissue according to a CT calibration curve. The MC absorbed doses calculated in this study are compared with VariSeed v8.0 calculated absorbed doses. To evaluate the dosimetric effect of MAR and TAS, the MC absorbed doses of this work (independent of MAR and TAS) are compared to the MC absorbed doses of different ¹²⁵ I source models from previous studies that were calculated with different MC codes using post-implant CT-based phantoms generated by implementing MAR and TAS on post-implant CT images.

RESULTS

The very good agreement of TG-43 parameters of this study and the published consensus data within 3% validates the geometry of the IsoSeed I25.S17plus source. For the clinical studies, the TG-43-based calculations show a D₉₀ overestimation of more than 4% compared to the more realistic MC methods due to ISA and tissue composition. The results of this work generally show few discrepancies with the post-implant CT-based dosimetry studies with respect to the D₉₀ absorbed dose metric parameter. These discrepancies are mainly Type B uncertainties due to the different ¹²⁵ I source models and MC codes.

CONCLUSIONS

The implementation of MAR and TAS on post-implant CT images have no dosimetric effect on the ¹²⁵ I prostate MC absorbed dose calculation in post-implant CT-based phantoms.

Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations

PURPOSE

The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications.

METHODS AND MATERIALS

Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. The four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated.

RESULTS

The air-kerma strength was (9.772 ± 0.001) × 10-8 U Bq-1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h-1 U-1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data.

CONCLUSIONS

TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.

Quasi-Monte Carlo method for calculating X-ray scatter in CT

In this paper we transform the trajectories of X-ray as it interacts with a phantom into a high-dimensional integration problem and give the integral formula for the probability of photons emitted from the X-ray source through the phantom to reach the detector. We propose a superior algorithm called gQMCFRD, which combines GPU-based quasi-Monte Carlo (gQMC) method with forced random detection (FRD) technique to simulate this integral. QMC simulation is deterministic versions of Monte Carlo (MC) simulation, which uses deterministic low discrepancy points (such as Sobol' points) instead of the random points. By using the QMC and FRD technique, the gQMCFRD greatly increases the simulation convergence rate and efficiency. We benchmark gQMCFRD, GPU based MC tool (gMCDRR), which performs conventional simulations, a GPU-based Metropolis MC tool (gMMC), which uses the Metropolis-Hasting algorithm to sample the entire photon path from the X-ray source to the detector and gMCFRD, that uses random points for sampling against PENELOPE subroutines: MC-GPU. The results are in excellent agreement and the Efficiency Improvement Factor range 27 ∼ 37 (or 1.09 ∼ 1.16, or 0.12 ∼ 0.15, or 3.62 ∼ 3.70) by gQMCFRD (or gMCDRR, or gMMC, or gMCFRD) with comparison to MC-GPU in all cases. It shows that gQMCFRD is more effective in these cases.

Model-Based Dose Calculation Algorithms for Brachytherapy Dosimetry

The purpose of this study was to review the limitations of dose calculation formalisms for photon-emitting brachytherapy sources based on the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) report and to provide recommendations to transition to model-based dose calculation algorithms. Additionally, an overview of these algorithms and approaches is presented. The influence of tissue and seed/applicator heterogeneities on brachytherapy dose distributions for breast, gynecologic, head and neck, rectum, and prostate cancers as well as eye plaques and electronic brachytherapy treatments were investigated by comparing dose calculations based on the TG-43 formalism and model-based dose calculation algorithms.

Improved Woodcock tracking on Monte Carlo simulations for medical applications

This paper presents a new variance reduction technique called super voxel Woodcock (SVW), which combines Woodcock tracking technique with the super voxel concept, used in computer graphics. It consists in grouping the voxels of the volume in a super voxel grid (pre-processing step) by associating to each of the super voxels a local value of the most attenuate medium which will later serve to the interaction distances sampling. SVW allows reducing the sampling of the particle path while a high-density material is present within the simulated phantom. In order to evaluate the performance of the SVW method compare to both standard and Woodcock tracking methods, algorithms were implemented within the same GPU MCS framework GGEMS. This method improves the performance of the standard Woodcock method by a factor of 4.5 and 4.3 for x-ray imaging application and intraoperative radiotherapy respectively. The proposed SVW method did not introduce any bias on the simulations.

Neutron track length estimator for GATE Monte Carlo dose calculation in radiotherapy

The out-of-field dose in radiation therapy is a growing concern in regards to the late side-effects and secondary cancer induction. In high-energy x-ray therapy, the secondary neutrons generated through photonuclear reactions in the accelerator are part of this secondary dose. The neutron dose is currently not estimated by the treatment planning system while it appears to be preponderant for distances greater than 50 cm from the isocenter. Monte Carlo simulation has become the gold standard for accurately calculating the neutron dose under specific treatment conditions but the method is also known for having a slow statistical convergence, which makes it difficult to be used on a clinical basis. The neutron track length estimator, a neutron variance reduction technique inspired by the track length estimator method has thus been developped for the first time in the Monte Carlo code GATE to allow a fast computation of the neutron dose in radiotherapy. The details of its implementation, as well as the comparison of its performances against the analog MC method, are presented here. A gain of time from 15 to 400 can be obtained by our method, with a mean difference in the dose calculation of about 1% in comparison with the analog MC method.

The influence of tissue composition uncertainty on dose distributions in brachytherapy

BACKGROUND AND PURPOSE

Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.

MATERIALS AND METHODS

Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D₉₀), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μ_en/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability.

RESULTS

Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D₉₀ for target tissues and doses to OAR for brachytherapy with low energy sources and less for ¹⁹²Ir-based brachytherapy. Discrepancies in μ_en/ρ are also indicative of dose differences.

CONCLUSIONS

Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.

Dosimetric impact of dual-energy CT tissue segmentation for low-energy prostate brachytherapy: a Monte Carlo study

The purpose of this study is to evaluate the impact of a novel tissue characterization method using dual-energy over single-energy computed tomography (DECT and SECT) on Monte Carlo (MC) dose calculations for low-dose rate (LDR) prostate brachytherapy performed in a patient like geometry. A virtual patient geometry is created using contours from a real patient pelvis CT scan, where known elemental compositions and varying densities are overwritten in each voxel. A second phantom is made with additional calcifications. Both phantoms are the ground truth with which all results are compared. Simulated CT images are generated from them using attenuation coefficients taken from the XCOM database with a 100 kVp spectrum for SECT and 80 and 140Sn kVp for DECT. Tissue segmentation for Monte Carlo dose calculation is made using a stoichiometric calibration method for the simulated SECT images. For the DECT images, Bayesian eigentissue decomposition is used. A LDR prostate brachytherapy plan is defined with ¹²⁵I sources and then calculated using the EGSnrc user-code Brachydose for each case. Dose distributions and dose-volume histograms (DVH) are compared to ground truth to assess the accuracy of tissue segmentation. For noiseless images, DECT-based tissue segmentation outperforms the SECT procedure with a root mean square error (RMS) on relative errors on dose distributions respectively of 2.39% versus 7.77%, and provides DVHs closest to the reference DVHs for all tissues. For a medium level of CT noise, Bayesian eigentissue decomposition still performs better on the overall dose calculation as the RMS error is found to be of 7.83% compared to 9.15% for SECT. Both methods give a similar DVH for the prostate while the DECT segmentation remains more accurate for organs at risk and in presence of calcifications, with less than 5% of RMS errors within the calcifications versus up to 154% for SECT. In a patient-like geometry, DECT-based tissue segmentation provides dose distributions with the highest accuracy and the least bias compared to SECT. When imaging noise is considered, benefits of DECT are noticeable if important calcifications are found within the prostate.

New hybrid voxelized/analytical primitive in Monte Carlo simulations for medical applications

Monte Carlo simulations (MCS) applied in particle physics play a key role in medical imaging and particle therapy. In such simulations, particles are transported through voxelized phantoms derived from predominantly patient CT images. However, such voxelized object representation limits the incorporation of fine elements, such as artificial implants from CAD modeling or anatomical and functional details extracted from other imaging modalities. In this work we propose a new hYbrid Voxelized/ANalytical primitive (YVAN) that combines both voxelized and analytical object descriptions within the same MCS, without the need to simultaneously run two parallel simulations, which is the current gold standard methodology. Given that YVAN is simply a new primitive object, it does not require any modifications on the underlying MC navigation code. The new proposed primitive was assessed through a first simple MCS. Results from the YVAN primitive were compared against an MCS using a pure analytical geometry and the layer mass geometry concept. A perfect agreement was found between these simulations, leading to the conclusion that the new hybrid primitive is able to accurately and efficiently handle phantoms defined by a mixture of voxelized and analytical objects. In addition, two application-based evaluation studies in coronary angiography and intra-operative radiotherapy showed that the use of YVAN was 6.5% and 12.2% faster than the layered mass geometry method, respectively, without any associated loss of accuracy. However, the simplification advantages and differences in computational time improvements obtained with YVAN depend on the relative proportion of the analytical and voxelized structures used in the simulation as well as the size and number of triangles used in the description of the analytical object meshes.

A generic high-dose rate (192)Ir brachytherapy source for evaluation of model-based dose calculations beyond the TG-43 formalism

PURPOSE

In order to facilitate a smooth transition for brachytherapy dose calculations from the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) formalism to model-based dose calculation algorithms (MBDCAs), treatment planning systems (TPSs) using a MBDCA require a set of well-defined test case plans characterized by Monte Carlo (MC) methods. This also permits direct dose comparison to TG-43 reference data. Such test case plans should be made available for use in the software commissioning process performed by clinical end users. To this end, a hypothetical, generic high-dose rate (HDR) (192)Ir source and a virtual water phantom were designed, which can be imported into a TPS.

METHODS

A hypothetical, generic HDR (192)Ir source was designed based on commercially available sources as well as a virtual, cubic water phantom that can be imported into any TPS in DICOM format. The dose distribution of the generic (192)Ir source when placed at the center of the cubic phantom, and away from the center under altered scatter conditions, was evaluated using two commercial MBDCAs [Oncentra(®) Brachy with advanced collapsed-cone engine (ACE) and BrachyVision ACUROS™ ]. Dose comparisons were performed using state-of-the-art MC codes for radiation transport, including ALGEBRA, BrachyDose, GEANT4, MCNP5, MCNP6, and PENELOPE2008. The methodologies adhered to recommendations in the AAPM TG-229 report on high-energy brachytherapy source dosimetry. TG-43 dosimetry parameters, an along-away dose-rate table, and primary and scatter separated (PSS) data were obtained. The virtual water phantom of (201)(3) voxels (1 mm sides) was used to evaluate the calculated dose distributions. Two test case plans involving a single position of the generic HDR (192)Ir source in this phantom were prepared: (i) source centered in the phantom and (ii) source displaced 7 cm laterally from the center. Datasets were independently produced by different investigators. MC results were then compared against dose calculated using TG-43 and MBDCA methods.

RESULTS

TG-43 and PSS datasets were generated for the generic source, the PSS data for use with the ace algorithm. The dose-rate constant values obtained from seven MC simulations, performed independently using different codes, were in excellent agreement, yielding an average of 1.1109 ± 0.0004 cGy/(h U) (k = 1, Type A uncertainty). MC calculated dose-rate distributions for the two plans were also found to be in excellent agreement, with differences within type A uncertainties. Differences between commercial MBDCA and MC results were test, position, and calculation parameter dependent. On average, however, these differences were within 1% for ACUROS and 2% for ace at clinically relevant distances.

CONCLUSIONS

A hypothetical, generic HDR (192)Ir source was designed and implemented in two commercially available TPSs employing different MBDCAs. Reference dose distributions for this source were benchmarked and used for the evaluation of MBDCA calculations employing a virtual, cubic water phantom in the form of a CT DICOM image series. The implementation of a generic source of identical design in all TPSs using MBDCAs is an important step toward supporting univocal commissioning procedures and direct comparisons between TPSs.

Development of virtual patient models for permanent implant brachytherapy Monte Carlo dose calculations: interdependence of CT image artifact mitigation and tissue assignment

This work investigates and compares CT image metallic artifact reduction (MAR) methods and tissue assignment schemes (TAS) for the development of virtual patient models for permanent implant brachytherapy Monte Carlo (MC) dose calculations. Four MAR techniques are investigated to mitigate seed artifacts from post-implant CT images of a homogeneous phantom and eight prostate patients: a raw sinogram approach using the original CT scanner data and three methods (simple threshold replacement (STR), 3D median filter, and virtual sinogram) requiring only the reconstructed CT image. Virtual patient models are developed using six TAS ranging from the AAPM-ESTRO-ABG TG-186 basic approach of assigning uniform density tissues (resulting in a model not dependent on MAR) to more complex models assigning prostate, calcification, and mixtures of prostate and calcification using CT-derived densities. The EGSnrc user-code BrachyDose is employed to calculate dose distributions. All four MAR methods eliminate bright seed spot artifacts, and the image-based methods provide comparable mitigation of artifacts compared with the raw sinogram approach. However, each MAR technique has limitations: STR is unable to mitigate low CT number artifacts, the median filter blurs the image which challenges the preservation of tissue heterogeneities, and both sinogram approaches introduce new streaks. Large local dose differences are generally due to differences in voxel tissue-type rather than mass density. The largest differences in target dose metrics (D90, V100, V150), over 50% lower compared to the other models, are when uncorrected CT images are used with TAS that consider calcifications. Metrics found using models which include calcifications are generally a few percent lower than prostate-only models. Generally, metrics from any MAR method and any TAS which considers calcifications agree within 6%. Overall, the studied MAR methods and TAS show promise for further retrospective MC dose calculation studies for various permanent implant brachytherapy treatments.

A simple analytical method for heterogeneity corrections in low dose rate prostate brachytherapy

In low energy brachytherapy, the presence of tissue heterogeneities contributes significantly to the discrepancies observed between treatment plan and delivered dose. In this work, we present a simplified analytical dose calculation algorithm for heterogeneous tissue. We compare it with Monte Carlo computations and assess its suitability for integration in clinical treatment planning systems. The algorithm, named as RayStretch, is based on the classic equivalent path length method and TG-43 reference data. Analytical and Monte Carlo dose calculations using Penelope2008 are compared for a benchmark case: a prostate patient with calcifications. The results show a remarkable agreement between simulation and algorithm, the latter having, in addition, a high calculation speed. The proposed analytical model is compatible with clinical real-time treatment planning systems based on TG-43 consensus datasets for improving dose calculation and treatment quality in heterogeneous tissue. Moreover, the algorithm is applicable for any type of heterogeneities.

Dosimetry Modeling for Focal Low-Dose-Rate Prostate Brachytherapy

PURPOSE

Focal brachytherapy targeted to an individual lesion(s) within the prostate may reduce side effects experienced with whole-gland brachytherapy. The outcomes of a consensus meeting on focal prostate brachytherapy were used to investigate optimal dosimetry of focal low-dose-rate (LDR) prostate brachytherapy targeted using multiparametric magnetic resonance imaging (mp-MRI) and transperineal template prostate mapping (TPM) biopsy, including the effects of random and systematic seed displacements and interseed attenuation (ISA).

METHODS AND MATERIALS

Nine patients were selected according to clinical characteristics and concordance of TPM and mp-MRI. Retrospectively, 3 treatment plans were analyzed for each case: whole-gland (WG), hemi-gland (hemi), and ultra-focal (UF) plans, with 145-Gy prescription dose and identical dose constraints for each plan. Plan robustness to seed displacement and ISA were assessed using Monte Carlo simulations.

RESULTS

WG plans used a mean 28 needles and 81 seeds, hemi plans used 17 needles and 56 seeds, and UF plans used 12 needles and 25 seeds. Mean D90 (minimum dose received by 90% of the target) and V100 (percentage of the target that receives 100% dose) values were 181.3 Gy and 99.8% for the prostate in WG plans, 195.7 Gy and 97.8% for the hemi-prostate in hemi plans, and 218.3 Gy and 99.8% for the focal target in UF plans. Mean urethra D10 was 205.9 Gy, 191.4 Gy, and 92.4 Gy in WG, hemi, and UF plans, respectively. Mean rectum D2 cm(3) was 107.5 Gy, 77.0 Gy, and 42.7 Gy in WG, hemi, and UF plans, respectively. Focal plans were more sensitive to seed displacement errors: random shifts with a standard deviation of 4 mm reduced mean target D90 by 14.0%, 20.5%, and 32.0% for WG, hemi, and UF plans, respectively. ISA has a similar impact on dose-volume histogram parameters for all plan types.

CONCLUSIONS

Treatment planning for focal LDR brachytherapy is feasible. Dose constraints are easily met with a notable reduction to organs at risk. Treating smaller targets makes seed positioning more critical.

Calcifications in low-dose rate prostate seed brachytherapy treatment: post-planning dosimetry and predictive factors

BACKGROUND AND PURPOSE

The brachytherapy dose algorithm of the American Association of Physicists in Medicine Task Group (TG) Report 43 overrides all tissue materials with water. In reality, dose discrepancies will occur around tissue calcifications. This study investigates these perturbations in low dose rate prostate brachytherapy dosimetry.

MATERIALS AND METHODS

43 cancer patients with prostatic calcifications are identified. Geant4 Monte Carlo (MC) simulations are made with materials assigned based on TG186 recommendations. Five dose calculation scenarios are presented: MC in water (MCW), MCW with calcifications, (MCCA), MCCA with seeds (MCCASEED) and full tissue definition and seeds with dose to medium in medium (FMC) and dose to water in medium (FMC-Dw,m).

RESULTS

The mean FMC prostate D90 (V100) difference relative to TG43 is -6.4% (range [-1.8, -14.1]) (-2.6% [-0.3, -6.7]). For MCCA we obtained -3.9% [-1.0, -8.7] (-1.5% [-0.2, -4.1]). The mean urethra D10 difference is -4.5% [-1.3, -9.9] for FMC, -2.4% [-0.7, -5.1] with MCCA. FMC-Dw,m D90 has a -0.45% smaller dose difference than FMC on average. The calcification/prostate volume ratio is a good predictor of dose perturbation (R(2)=0.75).

CONCLUSION

Based on these results, calcifications alter the dose coverage and may have severe dose perturbation that requires recalculation.

Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual-energy CT imaging on a commercial scanner: comparison of analytic and polyenergetic statistical reconstruction algorithms

PURPOSE

Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasive in vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries.

METHODS

Eight test materials of known composition and density were used to compare pDECT-estimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images.

RESULTS

Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm(3) grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean. Reconstruction with the statistical AM algorithm led to standard deviations roughly 40% to 60% less than FBP reconstruction. Additional tin filtration of the high energy beam exhibits similar pDECT estimation accuracy as the unfiltered beam, even when scanning with only 25% of the dose. Using the law of propagated uncertainty, low Z materials are found to be more sensitive to image reconstruction errors than high Z materials. Furthermore, it is estimated that reconstructed CT image uncertainty must be limited to less than 0.25% to achieve a target linear-attenuation coefficient estimation uncertainty of 3% at 28 keV.

CONCLUSIONS

That pDECT supports mean linear attenuation coefficient measurement accuracies of 1% of reference values for energies greater than 30 keV is encouraging. However, the sensitivity of the pDECT measurements to noise and systematic errors in reconstructed CT images warrants further investigation in more complex phantom geometries. The investigated statistical reconstruction algorithm, AM, reduced random measurement uncertainty relative to FBP owing to improved noise performance. These early results also support efforts to increase DE spectral separation, which can further reduce the pDECT sensitivity to measurement uncertainty.

Current state of the art brachytherapy treatment planning dosimetry algorithms

Following literature contributions delineating the deficiencies introduced by the approximations of conventional brachytherapy dosimetry, different model-based dosimetry algorithms have been incorporated into commercial systems for (192)Ir brachytherapy treatment planning. The calculation settings of these algorithms are pre-configured according to criteria established by their developers for optimizing computation speed vs accuracy. Their clinical use is hence straightforward. A basic understanding of these algorithms and their limitations is essential, however, for commissioning; detecting differences from conventional algorithms; explaining their origin; assessing their impact; and maintaining global uniformity of clinical practice.

Monte Carlo investigation of I-125 interseed attenuation for standard and thinner seeds in prostate brachytherapy with phantom validation using a MOSFET

PURPOSE

In permanent seed implant prostate brachytherapy the actual dose delivered to the patient may be less than that calculated by TG-43U1 due to interseed attenuation (ISA) and differences between prostate tissue composition and water. In this study the magnitude of the ISA effect is assessed in a phantom and in clinical prostate postimplant cases. Results are compared for seed models 6711 and 9011 with 0.8 and 0.5 mm diameters, respectively.

METHODS

A polymethyl methacrylate (PMMA) phantom was designed to perform ISA measurements in a simple eight-seed arrangement and at the center of an implant of 36 seeds. Monte Carlo (MC) simulation and experimental measurements using a MOSFET dosimeter were used to measure dose rate and the ISA effect. MC simulations of 15 CT-based postimplant prostate treatment plans were performed to compare the clinical impact of ISA on dose to prostate, urethra, rectum, and the volume enclosed by the 100% isodose, for 6711 and 9011 seed models.

RESULTS

In the phantom, ISA reduced the dose rate at the MOSFET position by 8.6%-18.3% (6711) and 7.8%-16.7% (9011) depending on the measurement configuration. MOSFET measured dose rates agreed with MC simulation predictions within the MOSFET measurement uncertainty, which ranged from 5.5% to 7.2% depending on the measurement configuration (k = 1, for the mean of four measurements). For 15 clinical implants, the mean ISA effect for 6711 was to reduce prostate D90 by 4.2 Gy (3%), prostate V100 by 0.5 cc (1.4%), urethra D10 by 11.3 Gy (4.4%), rectal D2cc by 5.5 Gy (4.6%), and the 100% isodose volume by 2.3 cc. For the 9011 seed the mean ISA effect reduced prostate D90 by 2.2 Gy (1.6%), prostate V100 by 0.3 cc (0.7%), urethra D10 by 8.0 Gy (3.2%), rectal D2cc by 3.1 Gy (2.7%), and the 100% isodose volume by 1.2 cc. Differences between the MC simulation and TG-43U1 consensus data for the 6711 seed model had a similar impact, reducing mean prostate D90 by 6 Gy (4.2%) and V100 by 0.6 cc (1.8%).

CONCLUSIONS

ISA causes the delivered dose in prostate seed implant brachytherapy to be lower than the dose calculated by TG-43U1. MC simulation of phantom seed arrangements show that dose at a point can be reduced by up to 18% and this has been validated using a MOSFET dosimeter. Clinical simulations show that ISA reduces DVH parameter values, but the reduction is less for thinner seeds.

An efficient numerical tool for dose deposition prediction applied to synchrotron medical imaging and radiation therapy

Medical imaging and radiation therapy are widely used synchrotron-based techniques which have one thing in common: a significant dose delivery to typically biological samples. Among the ways to provide the experimenters with image guidance techniques indicating optimization strategies, Monte Carlo simulation has become the gold standard for accurately predicting radiation dose levels under specific irradiation conditions. A highly important hampering factor of this method is, however, its slow statistical convergence. A track length estimator (TLE) module has been coded and implemented for the first time in the open-source Monte Carlo code GATE/Geant4. Results obtained with the module and the procedures used to validate them are presented. A database of energy-absorption coefficients was also generated, which is used by the TLE calculations and is now also included in GATE/Geant4. The validation was carried out by comparing the TLE-simulated doses with experimental data in a synchrotron radiation computed tomography experiment. The TLE technique shows good agreement versus both experimental measurements and the results of a classical Monte Carlo simulation. Compared with the latter, it is possible to reach a pre-defined statistical uncertainty in about two to three orders of magnitude less time for complex geometries without loss of accuracy.

Specification of absorbed dose to water using model-based dose calculation algorithms for treatment planning in brachytherapy

Model-based dose calculation algorithms (MBDCAs), recently introduced in treatment planning systems (TPS) for brachytherapy, calculate tissue absorbed doses. In the TPS framework, doses have hereto been reported as dose to water and water may still be preferred as a dose specification medium. Dose to tissue medium Dmed then needs to be converted into dose to water in tissue Dw,med. Methods to calculate absorbed dose to differently sized water compartments/cavities inside tissue, infinitesimal (used for definition of absorbed dose), small, large or intermediate, are reviewed. Burlin theory is applied to estimate photon energies at which cavity sizes in the range 1 nm-10 mm can be considered small or large. Photon and electron energy spectra are calculated at 1 cm distance from the central axis in cylindrical phantoms of bone, muscle and adipose tissue for 20, 50, 300 keV photons and photons from (125)I, (169)Yb and (192)Ir sources; ratios of mass-collision-stopping powers and mass energy absorption coefficients are calculated as applicable to convert Dmed into Dw,med for small and large cavities. Results show that 1-10 nm sized cavities are small at all investigated photon energies; 100 µm cavities are large only at photon energies <20 keV. A choice of an appropriate conversion coefficient Dw, med/Dmed is discussed in terms of the cavity size in relation to the size of important cellular targets. Free radicals from DNA bound water of nanometre dimensions contribute to DNA damage and cell killing and may be the most important water compartment in cells implying use of ratios of mass-collision-stopping powers for converting Dmed into Dw,med.

Layered mass geometry: a novel technique to overlay seeds and applicators onto patient geometry in Geant4 brachytherapy simulations

A problem faced by all Monte Carlo (MC) particle transport codes is how to handle overlapping geometries. The Geant4 MC toolkit allows the user to create parallel geometries within a single application. In Geant4 the standard mass-containing geometry is defined in a simulation volume called the World Volume. Separate parallel geometries can be defined in parallel worlds, that is, alternate three dimensional simulation volumes that share the same coordinate system with the World Volume for geometrical event biasing, scoring of radiation interactions, and/or the creation of hits in detailed readout structures. Until recently, only one of those worlds could contain mass so these parallel worlds provided no solution to simplify a complex geometric overlay issue in brachytherapy, namely the overlap of radiation sources and applicators with a CT based patient geometry. The standard method to handle seed and applicator overlay in MC requires removing CT voxels whose boundaries would intersect sources, placing the sources into the resulting void and then backfilling the remaining space of the void with a relevant material. The backfilling process may degrade the accuracy of patient representation, and the geometrical complexity of the technique precludes using fast and memory-efficient coding techniques that have been developed for regular voxel geometries. The patient must be represented by the less memory and CPU-efficient Geant4 voxel placement technique, G4PVPlacement, rather than the more efficient G4NestedParameterization (G4NestedParam). We introduce for the first time a Geant4 feature developed to solve this issue: Layered Mass Geometry (LMG) whereby both the standard (CT based patient geometry) and the parallel world (seeds and applicators) may now have mass. For any area where mass is present in the parallel world, the parallel mass is used. Elsewhere, the mass of the standard world is used. With LMG the user no longer needs to remove patient CT voxels that would include for example seeds. The patient representation can be a regular voxel grid, conducive to G4NestedParam, and the patient CT derived materials remain exact, avoiding the inaccuracy of the backfilling technique. Post-implant dosimetry for one patient with (125)I permanent seed implant was performed using Geant4 version 9.5.p01 using three different geometrical techniques. The first technique was the standard described above (G4PVPlacement). The second technique placed patient voxels as before, but placed seeds with LMG (G4PVPlacement+LMG). The third technique placed patient voxels through G4NestedParam and seeds through LMG (G4NestedParam+LMG). All the scenarios were calculated with 3 different image compression factors to manipulate the number of voxels. Additionally, the dosimetric impact of the backfilling technique was investigated for the case of calcifications in close proximity of sources. LMG eliminated the need for backfilling and simplified geometry description. Of the two LMG techniques, G4PVPlacement+LMG had no benefit to calculation time or memory use, actually increasing calculation time, but G4NestedParam+LMG reduced both calculation time and memory. The benefits of G4NestedParam+LMG over standard G4PVPlacement increased with increasing voxel numbers. For the case of calcifications in close proximity to sources, LMG not only increased efficiency but also yielded more accurate dose calculation than G4PVPlacement. G4NestedParam in combination with LMG present a new, efficient approach to simulate radiation sources that overlap patient geometry. Cases with brachytherapy applicators would constitute a direct extension of the method.

Fast patient-specific Monte Carlo brachytherapy dose calculations via the correlated sampling variance reduction technique

PURPOSE

To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy.

METHODS

CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, ΔD, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 (125)I seeds. The breast case consisted of 87 Model-200 (103)Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D(90), as well as for various anatomical regions.

RESULTS

Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 × 1 × 1 mm(3) dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and heterogeneous doses. On an AMD 1090T processor, computing times of 38 and 21 sec were required to achieve an average statistical uncertainty of 2% within the prostate (1 × 1 × 1 mm(3)) and breast (0.67 × 0.67 × 0.8 mm(3)) CTVs, respectively.

CONCLUSIONS

CMC supports an additional average 38-60 fold improvement in average efficiency relative to conventional uncorrelated MC techniques, although some voxels experience no gain or even efficiency losses. However, for the two investigated case studies, the maximum variance within clinically significant structures was always reduced (on average by a factor of 6) in the therapeutic dose range generally. CMC takes only seconds to produce an accurate, high-resolution, low-uncertainly dose distribution for the low-energy PSB implants investigated in this study.

An algorithm for efficient metal artifact reductions in permanent seed

PURPOSE

In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.

METHODS

The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.

RESULTS

In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.

CONCLUSIONS

An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.

On Monte Carlo modeling of megavoltage photon beams: a revisited study on the sensitivity of beam parameters

PURPOSE

To commission Monte Carlo beam models for five Varian megavoltage photon beams (4, 6, 10, 15, and 18 MV). The goal is to closely match measured dose distributions in water for a wide range of field sizes (from 2 x 2 to 35 x 35 cm2). The second objective is to reinvestigate the sensitivity of the calculated dose distributions to variations in the primary electron beam parameters.

METHODS

The GEPTS Monte Carlo code is used for photon beam simulations and dose calculations. The linear accelerator geometric models are based on (i) manufacturer specifications, (ii) corrections made by Chibani and Ma ["On the discrepancies between Monte Carlo dose calculations and measurements for the 18 MV Varian photon beam," Med. Phys. 34, 1206-1216 (2007)], and (iii) more recent drawings. Measurements were performed using pinpoint and Farmer ionization chambers, depending on the field size. Phase space calculations for small fields were performed with and without angle-based photon splitting. In addition to the three commonly used primary electron beam parameters (E(AV) is the mean energy, FWHM is the energy spectrum broadening, and R is the beam radius), the angular divergence (theta) of primary electrons is also considered.

RESULTS

The calculated and measured dose distributions agreed to within 1% local difference at any depth beyond 1 cm for different energies and for field sizes varying from 2 x 2 to 35 x 35 cm2. In the penumbra regions, the distance to agreement is better than 0.5 mm, except for 15 MV (0.4-1 mm). The measured and calculated output factors agreed to within 1.2%. The 6, 10, and 18 MV beam models use theta = 0 degrees, while the 4 and 15 MV beam models require theta = 0.5 degrees and 0.6 degrees, respectively. The parameter sensitivity study shows that varying the beam parameters around the solution can lead to 5% differences with measurements for small (e.g., 2 x 2 cm2) and large (e.g., 35 x 35 cm2) fields, while a perfect agreement is maintained for the 10 x 10 cm2 field. The influence of R on the central-axis depth dose and the strong influence of theta on the lateral dose profiles are demonstrated.

CONCLUSIONS

Dose distributions for very small and very large fields were proved to be more sensitive to variations in E(AV), R, and theta in comparison with the 10 x 10 cm2 field. Monte Carlo beam models need to be validated for a wide range of field sizes including small field sizes (e.g., 2 x 2 cm2).

Treatment planning of a skin-sparing conical breast brachytherapy applicator using conventional brachytherapy software

PURPOSE

AccuBoost is a noninvasive image-guided technique for the delivery of partial breast irradiation to the tumor bed and currently serves as an alternate to conventional electron beam boost. To irradiate the target volume while providing dose sparing to the skin, the round applicator design was augmented through the addition of an internally truncated conical shield and the reduction of the source to skin distance.

METHODS

Brachytherapy dose distributions for two types of conical applicators were simulated and estimated using Monte Carlo (MC) methods for radiation transport and a conventional treatment planning system (TPS). MC-derived and TPS-generated dose volume histograms (DVHs) and dose distribution data were compared for both the conical and round applicators for benchmarking purposes.

RESULTS

Agreement using the gamma-index test was > or = 99.95% for distance to agreement and dose accuracy criteria of 2 mm and 2%, respectively. After observing good agreement, TPS DVHs and dose distributions for the conical and round applicators were obtained and compared. Brachytherapy dose distributions generated using Pinnacle for ten CT data sets showed that the parallel-opposed beams of the conical applicators provided similar PTV coverage to the round applicators and reduced the maximum dose to skin, chest wall, and lung by up to 27%, 42%, and 43%, respectively.

CONCLUSIONS

Brachytherapy dose distributions for the conical applicators have been generated using MC methods and entered into the Pinnacle TPS via the Tufts technique. Treatment planning metrics for the conical AccuBoost applicators were significantly improved in comparison to those for conventional electron beam breast boost.