Technical Note: Taking EGSnrc to new lows: Development of egs++ lattice geometry and testing with microscopic geometries

Multiscale Monte Carlo simulations for dosimetry in x-ray breast imaging: Part II - Microscopic scales

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 , D g ) $f(z,D_{g})$ ) 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 (D g $D_{g}$ ). 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 (D g $D_{g}$ ), with little dependence on the spatial location. For similarD g $D_{g}$ values,f ( z , D g ) $f(z,D_{g})$ for nuclei is different between DM/DBT and CEDM/BCT, indicating that distinct x-ray spectra play significant roles inf ( z , D g ) $f(z,D_{g})$ . In addition, this behavior is also present when the specific energy distribution (F g ( 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.

Multiscale Monte Carlo simulations of gold nanoparticle dose-enhanced radiotherapy II. Cellular dose enhancement within macroscopic tumor models

BACKGROUND

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.

PURPOSE

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.

METHODS

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 mgAu /gtissue ) 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).

RESULTS

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.

CONCLUSIONS

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.

Multiscale Monte Carlo simulations of gold nanoparticle dose-enhanced radiotherapy I: Cellular dose enhancement in microscopic models

BACKGROUND

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.

PURPOSE

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.

METHODS

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 radiusr cell = 7.35 $r_{\rm cell}=7.35$  µm and nucleusr nuc = 5 $r_{\rm nuc} = 5$  µm considering 10 to 370 keV incident photons, gold concentrations from 4 to 24 mgAu /gtissue , 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).

RESULTS

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 (rcell , rnuc ) = (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.

CONCLUSIONS

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.

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.

Radiolytic Water Splitting Sensitized by Nanoscale Metal-Organic Frameworks

High-energy radiation that is compatible with renewable energy sources enables direct H₂ production from water for fuels; however, the challenge is to convert it as efficiently as possible, and the existing strategies have limited success. Herein, we report the use of Zr/Hf-based nanoscale UiO-66 metal-organic frameworks as highly effective and stable radiation sensitizers for purified and natural water splitting under γ-ray irradiation. Scavenging and pulse radiolysis experiments with Monte Carlo simulations show that the combination of 3D arrays of ultrasmall metal-oxo clusters and high porosity affords unprecedented effective scattering between secondary electrons and confined water, generating increased precursors of solvated electrons and excited states of water, which are the main species responsible for H₂ production enhancement. The use of a small quantity (<80 mmol/L) of UiO-66-Hf-OH can achieve a γ-rays-to-hydrogen conversion efficiency exceeding 10% that significantly outperforms Zr-/Hf-oxide nanoparticles and the existing radiolytic H₂ promoters. Our work highlights the feasibility and merit of MOF-assisted radiolytic water splitting and promises a competitive method for creating a green H₂ economy.

Monte Carlo Simulation-Guided Design of a Thorium-Based Metal-Organic Framework for Efficient Radiotherapy-Radiodynamic Therapy

High-Z metal-based nanoscale metal-organic frameworks (nMOFs) with photosensitizing ligands can enhance radiation damage to tumors via a unique radiotherapy-radiodynamic therapy (RT-RDT) process. Here we report Monte Carlo (MC) simulation-guided design of a Th-based nMOF built from Th6 -oxo secondary building units and 5,15-di(p-benzoato)porphyrin (DBP) ligands, Th-DBP, for enhanced RT-RDT. MC simulations revealed that the Th-lattice outperformed the Hf-lattice in radiation dose enhancement owing to its higher mass attenuation coefficient. Upon X-ray or γ-ray radiation, Th-DBP enhanced energy deposition, generated more reactive oxygen species, and induced significantly higher cytotoxicity to cancer cells over the previously reported Hf-DBP nMOF. With low-dose X-ray irradiation, Th-DBP suppressed tumor growth by 88 % in a colon cancer and 97 % in a pancreatic cancer mouse model.

Fast beta-emitter Monte Carlo simulations and full patient dose calculations of targeted radionuclide therapy: introducing egs_mird

BACKGROUND

Targeted Radionuclide Therapy (TRT) is a fast-growing field garnering much interest, with several clinical trials currently underway, that has a steady increase in development of treatment techniques. Unfortunately, within the field and many clinical trials, the dosimetry calculation techniques used remain relatively simple, often using a mix of S-value calculations and kernel convolutions.

PURPOSE

The common TRT calculation techniques, although very quick, can often ignore important aspects of patient anatomy and radionuclide distribution, as well as the interplay there-in. This paper introduces egs_mird, a new Monte Carlo (MC) application built in EGSnrc which allows users to model full patient tissue and density (using clinical CT images) and radionuclide distribution (using clinical PET images) for fast and detailed dose TRT calculation.

METHODS

The novel application egs_mird is introduced along with a general outline of the structure of egs_mird simulations. The general structure of the code, and the track-length estimator scoring implementation for variance reduction, is described. A new egs++ source class egs_internal_source, created to allow detailed patient-wide source distribution, and a modified version of egs_radionuclide_source, changed to be able to work with egs_internal_source, are also described. The new code is compared to other MC calculations of S-values kernels of ¹³¹ I, ⁹⁰ Y, and ¹⁷⁷ Lu in the literature, along with further self-validation using a histogram variant of the electron Fano test. Several full patient prostate ¹⁷⁷ Lu TRT prostate cancer treatment simulations are performed using a single set of patient DICOM CT and [¹⁸ F]-DCFPyL PET data.

RESULTS

Good agreement is found between S-value kernels calculated using egs_mird with egs_internal_source and those found in the literature. Calculating 1000 doses (individual voxel uncertainties of ∼0.05%) in a voxel grid Fano test for monoenergetic 500 keV electrons and ¹⁷⁷ Lu electrons results in 94 and 99% of the doses being within 0.1% of the expected dose, respectively. For a hypothetical ¹⁷⁷ Lu treatment, patient prostate, rectum, bone marrow, and bladder dose volume histograms (DVHs) results did not vary significantly when using the track-length estimator and not modelling electron transport, modelling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Dose profiles through different regions demonstrate there are some differences with model choices not seen in the DVH. Simulations using the track-length estimator can be completed in under 15 minutes (∼30 minutes when using standard interaction scoring).

CONCLUSION

This work shows egs_mird to be a reliable MC code for computing TRT doses as realistically as the patient CT and PET data allow. Furthermore, the code can compute doses to sub-1% uncertainty within 15 minutes, with little to no optimization. Thus, this work supports the use of egs_mird for dose calculations in TRT. This article is protected by copyright. All rights reserved.

Monte Carlo Simulations Reveal New Design Principles for Efficient Nanoradiosensitizers Based on Nanoscale Metal-Organic Frameworks

Nanoscale metal-organic frameworks (nMOFs) have recently been shown to provide better radiosensitization than solid nanoparticles (NPs) when excited with X-rays. Here, a Monte Carlo simulation of different radiosensitization effects by NPs and nMOFs using a lattice model consisting of 3D arrays of nanoscale secondary building units (SBUs) is reported. The simulation results reveal that lattices outperform solid NPs regardless of radiation sources or particle sizes via enhanced scatterings of photons and electrons within the lattices. Optimum dose enhancement can be achieved by tuning SBU size and inter-SBU distance.

Evaluation of dose enhancement with gold nanoparticles in kilovoltage radiotherapy using the new EGS geometry library in Monte Carlo simulation

<abstract><sec> <title>Purpose</title> <p>This study compared the dose enhancement predicted in kilovoltage gold nanoparticle-enhanced radiotherapy using the newly developed EGS lattice and the typical gold-water mixture method in Monte Carlo simulation. This new method considered the gold nanoparticle-added volume consisting of solid nanoparticles instead of a gold-water mixture. In addition, this particle method is more realistic in simulation.</p> </sec><sec> <title>Methods</title> <p>A heterogeneous phantom containing bone and water was irradiated by the 105 and 220 kVp x-ray beams. Gold nanoparticles were added to the tumour volume with concentration varying from 3–40 mg/mL in the phantom. The dose enhancement ratio (DER), defined as the ratio of dose at the tumour with and without adding gold nanoparticles, was calculated by the gold-water mixture and particle method using Monte Carlo simulation for comparison.</p> </sec><sec> <title>Results</title> <p>It is found that the DER was 1.44–4.71 (105 kVp) and 1.27–2.43 (220 kVp) for the gold nanoparticle concentration range of 3–40 mg/mL, when they were calculated by the gold-water mixture method. The DER was slightly larger and equal to 1.47–4.84 (105 kVp) and 1.29–2.5 (220 kVp) for the same concentration range, when the particle method was used. Moreover, the DER predicted by both methods increased with an increase of nanoparticle concentration, and a decrease of x-ray beam energy.</p> </sec><sec> <title>Conclusion</title> <p>The deviation of DER determined by the particle and gold-water mixture method was insignificant when considering the uncertainty in the calculation of DER (2%) in the nanoparticle concentration range of 3–40 mg/mL. It is therefore concluded that the gold-water mixture method could predict the dose enhancement as accurate as the newly developed particle method.</p> </sec></abstract>