Purpose
To introduce the heterogeneous multiscale (HetMS) model for Monte Carlo simulations of gold nanoparticle dose‐enhanced radiation therapy (GNPT), a model characterized by its varying levels of ...detail on different length scales within a single phantom; to apply the HetMS model in two different scenarios relevant for GNPT and to compare computed results with others published.
Methods
The HetMS model is implemented using an extended version of the EGSnrc user‐code egs_chamber; the extended code is tested and verified via comparisons with recently published data from independent GNP simulations. Two distinct scenarios for the HetMS model are then considered: (a) monoenergetic photon beams (20 keV to 1 MeV) incident on a cylinder (1 cm radius, 3 cm length); (b) isotropic point source (brachytherapy source spectra) at the center of a 2.5 cm radius sphere with gold nanoparticles (GNPs) diffusing outwards from the center. Dose enhancement factors (DEFs) are compared for different source energies, depths in phantom, gold concentrations, GNP sizes, and modeling assumptions, as well as with independently published values. Simulation efficiencies are investigated.
Results
The HetMS MC simulations account for the competing effects of photon fluence perturbation (due to gold in the scatter media) coupled with enhanced local energy deposition (due to modeling discrete GNPs within subvolumes). DEFs are most sensitive to these effects for the lower source energies, varying with distance from the source; DEFs below unity (i.e., dose decreases, not enhancements) can occur at energies relevant for brachytherapy. For example, in the cylinder scenario, the 20 keV photon source has a DEF of 3.1 near the phantom's surface, decreasing to less than unity by 0.7 cm depth (for 20 mg/g). Compared to discrete modeling of GNPs throughout the gold‐containing (treatment) volume, efficiencies are enhanced by up to a factor of 122 with the HetMS approach. For the spherical phantom, DEFs vary with time for diffusion, radionuclide, and radius; DEFs differ considerably from those computed using a widely applied analytic approach.
Conclusions
By combining geometric models of varying complexity on different length scales within a single simulation, the HetMS model can effectively account for both macroscopic and microscopic effects which must both be considered for accurate computation of energy deposition and DEFs for GNPT. Efficiency gains with the HetMS approach enable diverse calculations which would otherwise be prohibitively long. The HetMS model may be extended to diverse scenarios relevant for GNPT, providing further avenues for research and development.
Gold NanoParticle (GNP) dose-enhanced radiation therapy (GNPT) requires consideration of physics across macro- to microscopic length scales, however, this presents computational challenges that have ...limited previous investigations.
To develop and apply multiscale Monte Carlo (MC) simulations to assess variations in nucleus and cytoplasm dose enhancement factors (n,cDEFs) over tumor-scale volumes.
The intrinsic variation of n,cDEFs (due to fluctuations in local gold concentration and cell/nucleus size variation) are estimated via MC modeling of varied cellular GNP uptake and cell/nucleus sizes. Then, the Heterogeneous MultiScale (HetMS) model is implemented in MC simulations by combining detailed models of populations of cells containing GNPs within simplified macroscopic tissue models to evaluate n,cDEFs. Simulations of tumors with spatially uniform gold concentrations (5, 10, or 20 mg
/g
) and spatially varying gold concentrations eluted from a point are performed to determine n,cDEFs as a function of distance from the source for 10 to 370 keV photons. All simulations are performed for three different intracellular GNP configurations: GNPs distributed on the surface of the nucleus (perinuclear) and GNPs packed into one or four endosome(s).
Intrinsic variations in n,cDEFs can be substantial, for example, if GNP uptake and cell/nucleus radii are varied by 20%, variations of up to 52% in nDEF and 25% in cDEF are observed compared to the nominal values for uniform cell/nucleus size and GNP concentration. In HetMS models of macroscopic tumors, subunity n,cDEFs (i.e., dose decreases) can occur for low energies and high gold concentrations due to attenuation of primary photons through the gold-filled volumes, for example, n,cDEF<1 is observed 3 mm from a 20 keV source for the four endosome configuration. In HetMS simulations of tumors with spatially uniform gold concentrations, n,cDEFs decrease with depth into the tumor as photons are attenuated, with relative differences between GNP models remaining approximately constant with depth in the tumor. Similar initial n,cDEF decreases with radius are seen in the tumors with spatially varying gold concentrations, but the n,cDEFs for all of the GNP configurations converge to a single value for each energy as gold concentration reaches zero.
The HetMS framework has been implemented for multiscale MC simulations of GNPT to compute n,cDEFs over tumor-scale volumes, with results demonstrating that cellular doses are highly sensitive to cell/nucleus size, GNP intracellular distribution, gold concentration, and cell position in tumor. This work demonstrates the importance of proper choice of computational model when simulating GNPT scenarios and the need to account for intrinsic variations in n,cDEFs due to variations in cell/nucleus size and gold concentration.
The charge of Task Group 186 (TG-186) is to provide guidance for early adopters of model-based dose calculation algorithms (MBDCAs) for brachytherapy (BT) dose calculations to ensure practice ...uniformity. Contrary to external beam radiotherapy, heterogeneity correction algorithms have only recently been made available to the BT community. Yet, BT dose calculation accuracy is highly dependent on scatter conditions and photoelectric effect cross-sections relative to water. In specific situations, differences between the current water-based BT dose calculation formalism (TG-43) and MBDCAs can lead to differences in calculated doses exceeding a factor of 10. MBDCAs raise three major issues that are not addressed by current guidance documents: (1) MBDCA calculated doses are sensitive to the dose specification medium, resulting in energy-dependent differences between dose calculated to water in a homogeneous water geometry (TG-43), dose calculated to the local medium in the heterogeneous medium, and the intermediate scenario of dose calculated to a small volume of water in the heterogeneous medium. (2) MBDCA doses are sensitive to voxel-by-voxel interaction cross sections. Neither conventional single-energy CT nor ICRU/ICRP tissue composition compilations provide useful guidance for the task of assigning interaction cross sections to each voxel. (3) Since each patient-source-applicator combination is unique, having reference data for each possible combination to benchmark MBDCAs is an impractical strategy. Hence, a new commissioning process is required. TG-186 addresses in detail the above issues through the literature review and provides explicit recommendations based on the current state of knowledge. TG-43-based dose prescription and dose calculation remain in effect, with MBDCA dose reporting performed in parallel when available. In using MBDCAs, it is recommended that the radiation transport should be performed in the heterogeneous medium and, at minimum, the dose to the local medium be reported along with the TG-43 calculated doses. Assignments of voxel-by-voxel cross sections represent a particular challenge. Electron density information is readily extracted from CT imaging, but cannot be used to distinguish between different materials having the same density. Therefore, a recommendation is made to use a number of standardized materials to maintain uniformity across institutions. Sensitivity analysis shows that this recommendation offers increased accuracy over TG-43. MBDCA commissioning will share commonalities with current TG-43-based systems, but in addition there will be algorithm-specific tasks. Two levels of commissioning are recommended: reproducing TG-43 dose parameters and testing the advanced capabilities of MBDCAs. For validation of heterogeneity and scatter conditions, MBDCAs should mimic the 3D dose distributions from reference virtual geometries. Potential changes in BT dose prescriptions and MBDCA limitations are discussed. When data required for full MBDCA implementation are insufficient, interim recommendations are made and potential areas of research are identified. Application of TG-186 guidance should retain practice uniformity in transitioning from the TG-43 to the MBDCA approach.
Background
X‐ray breast imaging modalities are commonly employed for breast cancer detection, from screening programs to diagnosis. Thus, dosimetry studies are important for quality control and risk ...estimation since ionizing radiation is used.
Purpose
To perform multiscale dosimetry assessments for different breast imaging modalities and for a variety of breast sizes and compositions. The first part of our study is focused on macroscopic scales (down to millimeters).
Methods
Nine anthropomorphic breast phantoms with a voxel resolution of 0.5 mm were computationally generated using the BreastPhantom software, representing three breast sizes with three distinct values of volume glandular fraction (VGF) for each size. Four breast imaging modalities were studied: digital mammography (DM), contrast‐enhanced digital mammography (CEDM), digital breast tomosynthesis (DBT) and dedicated breast computed tomography (BCT). Additionally, the impact of tissue elemental compositions from two databases were compared. Monte Carlo (MC) simulations were performed with the MC‐GPU code to obtain the 3D glandular dose distribution (GDD) for each case considered with the mean glandular dose (MGD) fixed at 4 mGy (to facilitate comparisons).
Results
The GDD within the breast is more uniform for CEDM and BCT compared to DM and DBT. For large breasts and high VGF, the ratio between the minimum/maximum glandular dose to MGD is 0.12/4.02 for DM and 0.46/1.77 for BCT; the corresponding results for a small breast and low VGF are 0.35/1.98 (DM) and 0.63/1.42 (BCT). The elemental compositions of skin, adipose and glandular tissue have a considerable impact on the MGD, with variations up to 30% compared to the baseline. The inclusion of tissues other than glandular and adipose within the breast has a minor impact on MGD, with differences below 2%. Variations in the final compressed breast thickness alter the shape of the GDD, with a higher compression resulting in a more uniform GDD.
Conclusions
For a constant MGD, the GDD varies with imaging modality and breast compression. Elemental tissue compositions are an important factor for obtaining MGD values, being a source of systematic uncertainties in MC simulations and, consequently, in breast dosimetry.
Background
Although the benefits of breast screening and early diagnosis are known for reducing breast cancer mortality rates, the effects and risks of low radiation doses to the cells in the breast ...are still ongoing topics of study.
Purpose
To study specific energy distributions (f(z,Dg)$f(z,D_{g})$) in cytoplasm and nuclei of cells corresponding to glandular tissue for different x‐ray breast imaging modalities.
Methods
A cubic lattice (500 μm length side) containing 4064 spherical cells was irradiated with photons loaded from phase space files with varying glandular voxel doses (Dg$D_{g}$). Specific energy distributions were scored for nucleus and cytoplasm compartments using the PENELOPE (v. 2018) + penEasy (v. 2020) Monte Carlo (MC) code. The phase space files, generated in part I of this work, were obtained from MC simulations in a voxelized anthropomorphic phantom corresponding to glandular voxels for different breast imaging modalities, including digital mammography (DM), digital breast tomosynthesis (DBT), contrast enhanced digital mammography (CEDM) and breast CT (BCT).
Results
In general, the average specific energy in nuclei is higher than the respective glandular dose scored in the same region, by up to 10%. The specific energy distributions for nucleus and cytoplasm are directly related to the magnitude of the glandular dose in the voxel (Dg$D_{g}$), with little dependence on the spatial location. For similar Dg$D_{g}$ values, f(z,Dg)$f(z,D_{g})$ for nuclei is different between DM/DBT and CEDM/BCT, indicating that distinct x‐ray spectra play significant roles in f(z,Dg)$f(z,D_{g})$. In addition, this behavior is also present when the specific energy distribution (Fg(z)$F_{g}(z)$) is considered taking into account the GDD in the breast.
Conclusions
Microdosimetry studies are complementary to the traditional macroscopic breast dosimetry based on the mean glandular dose (MGD). For the same MGD, the specific energy distribution in glandular tissue varies between breast imaging modalities, indicating that this effect could be considered for studying the risks of exposing the breast to ionizing radiation.
To investigate an approach for quantitative characterization of the spatial distribution of dosimetric data by introducing Haralick texture feature analysis in this context.
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 (
I,
Ir, 6 MV); (2) tumour-scale dosimetry: absorbed dose in voxels for idealized models of
I 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.
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 for
I 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).
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.
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 2σ 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.
The introduction of Gold NanoParticles (GNPs) in radiotherapy treatments necessitates considerations such as GNP size, location, and quantity, as well as patient geometry and beam quality. Physics ...considerations span length scales across many orders of magnitude (nanometer-to-centimeter), presenting challenges that often limit the scope of dosimetric studies to either micro- or macroscopic scales.
To investigate GNP dose-enhanced radiation Therapy (GNPT) through Monte Carlo (MC) simulations that bridge micro-to-macroscopic scales. The work is presented in two parts, with Part I (this work) investigating accurate and efficient MC modeling at the single cell level to calculate nucleus and cytoplasm Dose Enhancement Factors (n,cDEFs), considering a broad parameter space including GNP concentration, GNP intracellular distribution, cell size, and incident photon energy. Part II then evaluates cell dose enhancement factors across macroscopic (tumor) length scales.
Different methods of modeling gold within cells are compared, from a contiguous volume of either pure gold or gold-tissue mixture to discrete GNPs in a hexagonal close-packed lattice. MC simulations with EGSnrc are performed to calculate n,cDEF for a cell with radius
µm and nucleus
µm considering 10 to 370 keV incident photons, gold concentrations from 4 to 24 mg
/g
, and three different GNP configurations within the cell: GNPs distributed around the surface of the nucleus (perinuclear) or GNPs packed into one (or four) endosome(s). Select simulations are extended to cells with different cell (and nucleus) sizes: 5 µm (2, 3, and 4 µm), 7.35 µm (4 and 6 µm), and 10 µm (7, 8, and 9 µm).
n,cDEFs are sensitive to the method of modeling gold in the cell, with differences of up to 17% observed; the hexagonal lattice of GNPs is chosen (as the most realistic model) for all subsequent simulations. Across cell/nucleus radii, source energies, and gold concentrations, both nDEF and cDEF are highest for GNPs in the perinuclear configuration, compared with GNPs in one (or four) endosome(s). Across all simulations of the (r
, r
) = (7.35, 5) µm cell, nDEFs and cDEFs range from unity to 6.83 and 3.87, respectively. Including different cell sizes, nDEFs and cDEFs as high as 21.5 and 5.5, respectively, are observed. Both nDEF and cDEF are maximized at photon energies above the K- or L-edges of gold by 10 to 20 keV.
Considering 5000 unique simulation scenarios, this work comprehensively investigates many physics trends on DEFs at the cellular level, including demonstrating that cellular DEFs are sensitive to gold modeling approach, intracellular GNP configuration, cell/nucleus size, gold concentration, and incident source energy. These data should prove especially useful in research as well as treatment planning, allowing one to optimize or estimate DEF using not only GNP uptake, but also account for average tumor cell size, incident photon energy, and intracellular configuration of GNPs. Part II will expand the investigation, taking the Part I cell model and applying it in cm-scale phantoms.
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