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

Exploring the Potential of Gold Nanoparticles in Proton Therapy: Mechanisms, Advances, and Clinical Horizons

Proton therapy represents a groundbreaking advancement in cancer radiotherapy, leveraging the unique spatial energy distribution of protons to deliver precise, high-dose radiation to tumors while sparing surrounding healthy tissues. Despite its clinical success, proton therapy faces challenges in optimizing its therapeutic precision and efficacy. Recent research has highlighted the potential of gold nanoparticles to enhance proton therapy outcomes. Due to their high atomic number and favorable biological properties, gold nanoparticles act as radiosensitizers by amplifying the generation of secondary electrons and reactive oxygen species upon proton irradiation. This enhances DNA damage in tumor cells while preserving healthy tissues. Additionally, functionalization of gold nanoparticles with tumor-targeting ligands offers improved precision, making proton therapy more effective against a broader range of cancers. This review synthesizes current knowledge on the mechanisms of gold nanoparticle radiosensitization, preclinical evidence, and the technological hurdles that must be addressed to integrate this promising approach into clinical practice, aiming to advance the efficacy and accessibility of proton therapy in cancer therapy.

Nanoscale dosimetry for a radioisotope-labeled metal nanoparticle using MCNP6.2 and Geant4

BACKGROUND

Metal nanoparticles (MNPs) labeled with radioisotopes (RIs) are utilized as radio-enhancers due to their ability to amplify the radiation dose in their immediate vicinity. A thorough understanding of nanoscale dosimetry around MNPs enables their effective application in radiotherapy. However, nanoscale dosimetry around MNPs still requires further investigation.

PURPOSE

This study aims to provide insight into the radio-enhancement effects of MNPs by elucidating nanoscale dosimetry surrounding MNPs labeled with Auger-emitting RIs. We particularly focus on distinguishing the respective dose contributions of photons and electrons emitted by Auger-emitting RIs in the context of dose enhancement.

METHODS

A 50 nm diameter NP of silver (Ag) core and gold (Au) shell (Ag@Au NP) was assumed to emit mono-energetic electrons and photons (3, 5, 10, 20, and 30 keV), or the energy spectrum corresponding to one of three Auger-emitting RIs (103Pd, 125I, and 131Cs) from the Ag core. Nanoscale radial dose distributions around a single radioactive Ag@Au NP were evaluated in spherical shells of water. Monte Carlo simulations were conducted using single-event and track structure transport methods implemented in MCNP6.2 and Geant4-DNA-Au physics, respectively. To evaluate the extent of radio-enhancement by the Ag@Au NP, two scenarios were considered: Ag@Au NPs (Au shell included) and Ag@water NPs (Au shell replaced by water).

RESULTS

The radial doses of 10, 20, and 30 keV electrons estimated by both codes were comparable. However, the radial doses of 3 and 5 keV electrons by MCNP6.2 were much larger near the NP surface than those by Geant4. There was a dose enhancement of a few % to tens % by the Au shell in the region of the NP surface to 10 µm, depending on the electron energy. The radial doses of photons with the Au shell were higher up to their secondary electron ranges than those without the Au shell. The maximum dose enhancement factor of photons occurred at 20 keV and was 63.4 by MCNP6.2 and 50.5 by Geant4. The overall radial doses of electrons were 1-2 orders of magnitude larger than those of photons. As a result, in cases of RIs emitting both electrons and photons, the radial doses up to electron ranges were dominantly governed by electrons. The dose enhancement estimated by both codes for the RIs ranged from a few % except in the immediate vicinity of the NP surface.

CONCLUSION

Given the dominant contribution of electrons to radial doses of MNP labeled with Auger-emitting RIs, physical dose enhancement expected by interactions with photons was hindered. Since there are no available RIs emitting exclusively photons, achieving enhanced physical doses within a cell through a combination of MNPs and RIs appears currently unattainable. The radial doses of photons near the NP surface exhibited considerable discrepancies between the codes, primarily attributed to low-energy electrons. The difference may arise from higher cross-sections of Au inelastic scattering in Geant4-DNA-Au compared to MCNP6.2.

Enhancing Proton Therapy Efficacy Through Nanoparticle-Mediated Radiosensitization

Proton therapy, characterized by its unique Bragg peak, offers the potential to optimize the destruction of cancer cells while sparing healthy tissues, positioning it as one of the most advanced cancer treatment modalities currently available. However, in comparison to heavy ions, protons exhibit a relatively lower relative biological effectiveness (RBE), which limits the efficacy of proton therapy. The incorporation of nanoparticles for radiosensitization presents a novel approach to enhance the RBE of protons. This review provides a comprehensive discussion of the recent advancements in augmenting the biological effects of proton therapy through the use of nanoparticles. It examines the various types of nanoparticles that have been the focus of extensive research, elucidates their mechanisms of radiation sensitization, and evaluates the factors influencing the efficiency of this sensitization process. Furthermore, this review discusses the latest synergistic therapeutic strategies that integrate nanoparticle-mediated radiosensitization and outlines prospective directions for the future application of nanoparticles in conjunction with proton therapy.

PhoenixMR: A GPU-based MRI simulation framework with runtime-dynamic code execution

BACKGROUND

Simulations of physical processes and behavior can provide unique insights and understanding of real-world problems. Magnetic Resonance Imaging (MRI) is an imaging technique with several components of complexity. Several of these components have been characterized and simulated in the past. However, several computational challenges prevent simulations from being simultaneously fast, flexible, and accurate.

PURPOSE

The simulation of MRI experiments is underutilized by medical physicists and researchers using currently available simulators due to reasons including speed, accuracy, and extensibility constraints. This paper introduces an innovative MRI simulation engine and framework that aims to overcome these issues making available realistic and fast MRI simulation.

METHODS

Using the CUDA C/C++ programing language, an MRI simulation engine (PhoenixMR), incorporating a Turing-complete virtual machine (VM) to simulate abstract spatiotemporal complexities, was developed. This engine solves a set of time-discrete Bloch equations using the symmetric operator splitting technique. An extensible front-end framework package (written in Python) aids the use of PhoenixMR to simplify simulation development.

RESULTS

The PhoenixMR library and front-end codes have been developed and tested. A set of example simulations were performed to demonstrate the ease of use and flexibility of simulation components such as geometrical setup, pulse sequence design, phantom design, and so forth. Initial validation of PhoenixMR is performed by comparing its accuracy and performance against a widely used MRI simulator using identical simulation parameters. Validation results show PhoenixMR simulations are three orders of magnitude faster. There is also strong agreement between models.

CONCLUSIONS

A novel MRI simulation platform called PhoenixMR has been introduced. This research tool is designed to be usable by physicists and engineers interested in performing MRI simulations. Examples are shown demonstrating the accuracy, flexibility, and usability of PhoenixMR in several key areas of MRI simulation.

Utility of realistic microscopy-based cell models in simulation studies of nanoparticle-enhanced photon radiotherapy

To enhance the effect of radiation on the tumor without increasing the dose to the patient, the combination of high-Z nanoparticles with radiotherapy has been proposed. In this work, we investigate the effects of the physical parameters of nanoparticles (NPs) on the Dose Enhancement Factor (DEF), and on the Sensitive Enhancement Ratio (SER) by applying a version of the Linear Quadratic Model. A method for constructing voxelized realistic cell geometries in Monte Carlo simulations from confocal microscopy images was developed and applied to Gliobastoma Multiforme cell lines (U87 and U373). The comparison of simulations with realistic geometry and spherical geometry shows that there is significant impact on the survival curves obtained for the same irradiation conditions. Using this model, the DEF and the SER are determined as a function of the concentration, size and distribution of gold nanoparticles within the cell. For small NPs,dAuNP= 10 nm, no clear trend in the DEF and SER was observed when the number of NPs within the cell increases. Experimentally, the variable number of NPs measured inside the U373 cells (ranging between 1.48 × 105and 1.19 × 106) also did not influence much the observed cell survival upon irradiation of the cells with a Co-60 source. The same lack of trend is obtained when the Au content in the cell is kept constant, 0.897 mg/g, but the size of the NPs is changed. However, if the number of NPs is kept constant (7.91 × 105) and the size changes, there is a critical diameter above which the dose effect increases significantly. Using the realistic geometries, it was verified that the key parameter for the DEF and the SER enhancement is the volume fraction of Au in the cell, with NP size being a more important parameter than the number of NPs.

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.