A Monte Carlo model for the internal dosimetry of choroid plexuses in nuclear medicine procedures

Choroid plexuses are vascular structures located in the brain ventricles, showing specific uptake of some diagnostic and therapeutic radiopharmaceuticals currently under clinical investigation, such as integrin-binding arginine-glycine-aspartic acid (RGD) peptides. No specific geometry for choroid plexuses has been implemented in commercially available software for internal dosimetry.The aims of the present study were to assess the dependence of absorbed dose to the choroid plexuses on the organ geometry implemented in Monte Carlo simulations, and to propose an analytical model for the internal dosimetry of these structures for ¹⁸F, ⁶⁴Cu, ⁶⁷Cu, ⁶⁸Ga, ⁹⁰Y, ¹³¹I and ¹⁷⁷Lu nuclides. A GAMOS Monte Carlo simulation based on direct organ segmentation was taken as the gold standard to validate a second simulation based on a simplified geometrical model of the choroid plexuses. Both simulations were compared with the OLINDA/EXM sphere model.The gold standard and the simplified geometrical model gave similar dosimetry results (dose difference < 3.5%), indicating that the latter can be considered as a satisfactory approximation of the real geometry. In contrast, the sphere model systematically overestimated the absorbed dose compared to both Monte Carlo models (range: 4–50% dose difference), depending on the isotope energy and organ mass. Therefore, the simplified geometric model was adopted to introduce an analytical approach for choroid plexuses dosimetry in the mass range 2–16 g. The proposed model enables the estimation of the choroid plexuses dose by a simple bi-parametric function, once the organ mass and the residence time of the radiopharmaceutical under investigation are provided.     

Determination of the correction factors used in Fricke dosimetry for HDR 192Ir sources employing the Monte Carlo method

PurposeFricke dosimetry has shown great potential in the direct measurement of the absolute absorbed dose for ¹⁹²Ir sources used in HDR brachytherapy. This work describes the determination of the correction factors necessary to convert the absorbed dose in the Fricke solution to the absorbed dose to water. Methods: The experimental setup for Fricke irradiation using a ¹⁹²Ir source was simulated. The holder geometry used for the Fricke solution irradiation was modelled for MC simulation, using the PENELOPE. Results: The values of the factors determined for validation purposes demonstrated differences of less than 0.2% when compared to the published values. Four factors were calculated to correct: the differences in the density of the solution (1.0004 ± 0.0004); the perturbations caused by the holder (0.9989 ± 0.0004); the source anisotropy and the water attenuation effects (1.0327 ± 0.0012); and the distance from the center of the detection volume to the source (7.1932 ± 0.0065). Conclusion: Calculated corrections in this work show that the largest correction comes from the inverse squared reduction of the dose due to the point of measurement shift from the reference position of 1 cm. This situation also causes the correction due to volume averaging and attenuation in water to be significant. Future versions of the holder will aim to reduce these effects by having a position of measurement closer to the reference point thus requiring smaller corrections.     

Assessment of skin dose in breast cancer radiotherapy: on-phantom measurement and Monte Carlo simulation

AimThe main purpose of the present study is assessment of skin dose in breast cancer radiotherapy.BackgroundAccurate assessment of skin dose in radiotherapy can provide useful information for clinical considerations.Materials and methodsA RANDO phantom was irradiated using a 6 MV Siemens Primus linac with medial and tangential radiotherapy fields for simulating breast cancer treatment. Dosimetry was also performed on various positions across the fields using an EBT3 radiochromic film. Similar conditions of measurement on the RANDO phantom including field size, irradiation angle, number of fields, etc. were subsequently simulated via the Monte Carlo N-Particle Transport code (MCNP). Ultimately, dose values for corresponding points from both methods were compared.ResultsConsidering dosimetry using radiochromic films on the RANDO phantom, there were points having underdose and overdose based on the prescribed dose and skin tolerance levels. In this respect, 81.25% and 18.75% of the points had underdose and overdose, respectively. In some cases, several differences were observed between the measurement and the MCNP simulation results associated with skin dose.ConclusionBased on the results of the points which had underdose, it was suggested that a bolus should be used for the given points. With regard to overdose points, it was advocated to consider skin tolerance dose in treatment planning. Differences between the measurement and the MCNP simulation results might be due to voxel size of tally cells in simulations, effect of beam’s angle of incidence, validation time of linac’s head, lack of electronic equilibrium in the build-up region, as well as MCNP tally type.     

Implementation and application of a Monte Carlo model for an in vivo micro computed tomography system

Micro computed tomography (µCT) scanners are used to create high-resolution images and to quantify properties of the scanned objects. While modern µCT scanners benefit from the cone beam geometry, they are compromised by scatter radiation. This work aims to develop a Monte Carlo (MC) model of a µCT scanner in order to characterize the scatter radiation in the detector plane.The EGS++ framework with the MC code EGSnrc was used to simulate the particle transport through the main components of the XtremeCT (SCANCO Medical AG, Switzerland). The developed MC model was based on specific information of the manufacturer and was validated against measurements. The primary and the scatter radiation were analyzed and by implementing a dedicated tracing method, the scatter radiation was subdivided into different scatter components.The comparisons of measured and simulated transmission values for different absorber and filter combinations result in a mean difference of 0.2% ± 1.4%, with a maximal local difference of 3.4%. The reconstructed image of the phantom based on measurements agrees well with the image reconstructed using the MC model. The local contribution of scattered radiation is up to 10% of the total radiation in the detector plane and most of the scattered particles result from interactions in the scanned object. The MC simulations show that scatter radiation contains information about the structure of the object.In conclusion, a MC model for a µCT scanner was successfully validated and applied to analyze the characteristics of the scatter radiation for a µCT scanner.     

Monte Carlo kilovoltage X-ray tube simulation: A statistical analysis and compact simulation method

IntroductionMonte Carlo (MC) simulations are a powerful tool for improving image quality in X-ray based imaging modalities. An accurate X-ray source model is essential to MC modeling for CBCT but can be difficult to implement on a GPU while maintaining efficiency and memory limitations. A statistical analysis of the photon distribution from a MC X-ray tube simulation is conducted in hopes of building a compact source model.Materials & methodsMC simulations of an X-ray tube were carried out using BEAMnrc. The resulting photons were sorted into four categories: primary, scatter, off-focal radiation (OFR), and both (scatter and OFR). A statistical analysis of the photon components (energy, position, direction) was completed. A novel method for a compact (memory efficient) representation of the PHSP data was implemented and tested using different statistical based linear transformations (PCA, ZCA, ICA), as well as a geometrical transformation.ResultsThe statistical analysis showed all photon groupings had strong correlations between position and direction, with the largest correlation in the primary data. The novel method was successful in compactly representing the primary (error < 2%) and scatter (error < 6%) photon groupings by reducing the component correlations.Discussion & conclusionStatistical linear transforms provide a method of reducing the memory required to accurately simulate an X-ray source in a GPU MC system. If all photon types are required, the proposed method reduces the memory requirements by 3.8 times. When only primary and scatter data is needed, the memory requirement is reduced from gigabytes to kilobytes.     

A Monte Carlo method for the simulation of kinetie models

The purpose of this note is to illustrate the feasibility of simulating kinetic systems, such as commonly encountered in photosynthesis research, using the Monte Carlo (MC) method. In this approach, chemical events are considered at the molecular level where they occur randomly and the macroscopic kinetic evolution results from averaging a large number of such events. Their repeated simulation is easily accomplished using digital computing. It is shown that the MC approach is well suited to the capabilities and resources of modern microcomputers. A software package is briefly described and discussed, allowing a simple programming of any kinetic model system and its resolution. The execution is reasonably fast and accurate; it is not subject to such instabilities as found with the conventional analytical approach.Abbreviations MC Monte Carlo - RN random number - PSU photosynthetic unit Dedicated to Prof. L.N.M. Duysens on the occasion of his retirement.     

Monte Carlo-based patient internal dosimetry in fluoroscopy-guided interventional procedures: A review

PurposeThis systematic review aims to understand the dose estimation approaches and their major challenges. Specifically, we focused on state-of-the-art Monte Carlo (MC) methods in fluoroscopy-guided interventional procedures.MethodsAll relevant studies were identified through keyword searches in electronic databases from inception until September 2020. The searched publications were reviewed, categorised and analysed based on their respective methodology.ResultsHundred and one publications were identified which utilised existing MC-based applications/programs or customised MC simulations. Two outstanding challenges were identified that contribute to uncertainties in the virtual simulation reconstruction. The first challenge involves the use of anatomical models to represent individuals. Currently, phantom libraries best balance the needs of clinical practicality with those of specificity. However, mismatches of anatomical variations including body size and organ shape can create significant discrepancies in dose estimations. The second challenge is that the exact positioning of the patient relative to the beam is generally unknown. Most dose prediction models assume the patient is located centrally on the examination couch, which can lead to significant errors.ConclusionThe continuing rise of computing power suggests a near future where MC methods become practical for routine clinical dosimetry. Dynamic, deformable phantoms help to improve patient specificity, but at present are only limited to adjustment of gross body volume. Dynamic internal organ displacement or reshaping is likely the next logical frontier. Image-based alignment is probably the most promising solution to enable this, but it must be automated to be clinically practical.     

Gold coated contact lens-type ocular in vivo dosimeter (CLOD) for monitoring of low dose in computed tomography: A Monte Carlo study

PurposeThis study reports a sensitivity enhancement of gold-coated contact lens-type ocular in vivo dosimeters (CLODs) for low-dose measurements in computed tomography (CT).MethodsMonte Carlo (MC) simulations were conducted to evaluate the dose enhancement from the gold (Au) layers on the CLODs. The human eye and CLODs were modeled, and the X-ray tube voltages were defined as 80, 120, and 140 kVp. The thickness of the Au layer attached to a CLOD ranged from 100 nm to 10 μm. The thickness of the active layer ranged from 20 to 140 μm. The dose ratio between the active layer of the Au-coated CLOD and a CLOD without a layer, i.e., the dose enhancement factor (DEF), was calculated.ResultsThe DEFs of the first 20-μm thick active layer of the 5-μm thick Au-coated CLOD were 18.4, 19.7, 20.2 at 80, 120, and 140 kVp, respectively. The DEFs decreased as the thickness of the active layer increased. The DEFs of 100-nm to 5-μm thick Au layers increased from 1.7 to 5.4 for 120-kVp X-ray tube voltage when the thickness of the active layer was 140 μm.ConclusionsThe MC results presented a higher sensitivity of Au-coated CLODs (∼20-times higher than that of CLODs without a gold layer). Au-coated CLODs can be applied to an evaluation of very low doses (a few cGy) delivered to patients during CT imaging.     

A Monte Carlo software bench for simulation of spectral k-edge CT imaging: Initial results

PurposeSpectral Computed Tomography (SCT) systems equipped with photon counting detectors (PCD) are clinically desired, since such systems provide not only additional diagnostic information but also radiation dose reductions by a factor of two or more. The current unavailability of clinical PCDs makes a simulation of such systems necessary.MethodsIn this paper, we present a Monte Carlo-based simulation of a SCT equipped with a PCD. The aim of this development is to facilitate research on potential clinical applications. Our MC simulator takes into account scattering interactions within the scanned object and has the ability to simulate scans with and without scatter and a wide variety of imaging parameters. To demonstrate the usefulness of such a MC simulator for development of SCT applications, a phantom with contrast targets covering a wide range of clinically significant iodine concentrations is simulated. With those simulations the impact of scatter and exposure on image quality and material decomposition results is investigated.ResultsOur results illustrate that scatter radiation plays a significant role in visual as well as quantitative results. Scatter radiation can reduce the accuracy of contrast agent concentration by up to 15%.ConclusionsWe present a reliable and robust software bench for simulation of SCTs equipped with PCDs.     

Generation of clinical 177Lu SPECT/CT images based on Monte Carlo simulation with GATE

PurposePatient-specific dosimetry in MRT relies on quantitative imaging, pharmacokinetic assessment and absorbed dose calculation. The DosiTest project was initiated to evaluate the uncertainties associated with each step of the clinical dosimetry workflow through a virtual multicentric clinical trial. This work presents the generation of simulated clinical SPECT datasets based on GATE Monte Carlo modelling with its corresponding experimental CT image, which can subsequently be processed by commercial image workstations.MethodsThis study considers a therapy cycle of 6.85 GBq ¹⁷⁷Lu-labelled DOTATATE derived from an IAEA-Coordinated Research Project (E23005) on “Dosimetry in Radiopharmaceutical therapy for personalised patient treatment”. Patient images were acquired on a GE Infinia-Hawkeye 4 gamma camera using a medium energy (ME) collimator. Simulated SPECT projections were generated based on experimental time points and validated against experimental SPECT projections using flattened profiles and gamma index. The simulated projections were then incorporated into the patient SPECT/CT DICOM envelopes for processing and their reconstruction within a commercial image workstation.ResultsGamma index passing rate (2% − 1 pixel criteria) between 95 and 98% and average gamma between 0.28 and 0.35 among different time points revealed high similarity between simulated and experimental images. Image reconstruction of the simulated projections was successful on HERMES and Xeleris workstations, a major step forward for the initiation of a multicentric virtual clinical dosimetry trial based on simulated SPECT/CT images.ConclusionsRealistic ¹⁷⁷Lu patient SPECT projections were generated in GATE. These modelled datasets will be circulated to different clinical departments to perform dosimetry in order to assess the uncertainties in the entire dosimetric chain.     

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

PurposeMonte Carlo (MC) simulations are highly desirable for dose treatment planning and evaluation in radiation oncology. This is true also in emerging nuclear medicine applications such as internal radiotherapy with radionuclides. The purpose of this study is the validation of irtGPUMCD, a GPU-based MC code for dose calculations in internal radiotherapy.MethodsThe female and male phantoms of the International Commission on Radiological Protection (ICRP 110) were used as benchmarking geometries for this study focused on ¹⁷⁷Lu and including ^99mTc and ¹³¹I. Dose calculations were also conducted for a real patient. For phantoms, twelve anatomical structures were considered as target/source organs. The S-values were evaluated with irtGPUMCD simulations (10⁸ photons), with gamma branching ratios of ICRP 107 publication. The ¹⁷⁷Lu electrons S-values were calculated for source organs only, based on local deposition of dose in irtGPUMCD. The S-value relative difference between irtGPUMCD and IDAC-DOSE were evaluated for all targets/sources considered. A DVHs comparison with GATE was conducted. An exponential track length estimator was introduced in irtGPUMCD to increase computational efficiency.ResultsThe relative S-value differences between irtGPUMCD and IDAC-DOSE were <5% while this comparison with GATE was <1%. The DVHs dosimetric indices comparison between GATE and irtGPUMCD for the patient led to an excellent agreement (<2%). The time required for the simulation of 10⁸ photons was 1.5 min for the female phantom, and one minute for the real patient (<1% uncertainty). These results are promising and let envision the use of irtGPUMCD for internal dosimetry in clinical applications.     

A Monte Carlo approach to small-scale dosimetry of solid tumour microvasculature for nuclear medicine therapies with 223Ra-, 131I-, 177Lu- and 111In-labelled radiopharmaceuticals

The small-scale dosimetry of radionuclides in solid-tumours is directly related to the intra-tumoral distribution of the administered radiopharmaceutical, which is affected by its egress from the vasculature and dispersion within the tumour. The aim of the present study was to evaluate the combined dosimetric effects of radiopharmaceutical distribution and range of the emitted radiation in a model of tumour microvasculature.We developed a computational model of solid-tumour microenvironment around a blood capillary vessel, and we simulated the transport of radiation emitted by ²²³Ra, ¹¹¹In, ¹³¹I and ¹⁷⁷Lu using the GEANT4 Monte Carlo. For each nuclide, several models of radiopharmaceutical dispersion throughout the capillary vessel were considered.Radial dose profiles around the capillary vessel, the Initial Radioactivity (IR) necessary to deposit 100 Gy of dose at the edge of the viable tumour-cell region, the Endothelial Cell Mean Dose (ECMD) and the Tumour Edge Mean Dose (TEMD), i.e. the mean dose imparted at the 250-μm layer of tissue, were computed. The results for beta and Auger emitters demonstrate that the photon dose is about three to four orders of magnitude lower than that deposited by electrons. For ²²³Ra, the beta emissions of its progeny deliver a dose about three orders of magnitude lower than that delivered by the alpha emissions.Such results may help to characterize the dose inhomogeneities in solid tumour therapies with radiopharmaceuticals, taking into account the interplay between drug distribution from vasculature and range of ionizing radiations.     

Receptor aggregation by intermembrane interactions: a Monte Carlo study

The lateral organization of receptors on cell surfaces is critically important to their function; many receptors transmit transmembrane signals when redistributed into clusters, while the response of others is potentiated by their aggregation. Cell-cell contact can play a crucial role in receptor aggregation, even when the bonds between receptors on one cell and ligands on the other are monovalent. Monte Carlo simulations on a two-membrane model were carried out to determine whether weak enthalpic interactions among receptors in one membrane, and among ligands in another, can work synergistically to give large-scale clustering when the two membranes are brought into contact. The simulations give support to such a clustering mechanism. In addition, because clustering is a cooperative process akin to a phase separation, individual receptors and ligands may undergo repeated binding and unbinding while in a clustered "phase," and a single ligand could interact with multiple different receptor partners. The results suggest a resolution of the dichotomy between serial triggering and aggregation models of T cell activation.     

A multiple-start Monte Carlo docking method.

We present a method to search for possible binding modes of molecular fragments at a specific site of a potential drug target of known structure. Our method is based on a Monte Carlo (MC) algorithm applied to the translational and rotational degrees of freedom of the probe fragment. Starting from a randomly generated initial configuration, favorable binding modes are generated using a two-step process. An MC run is first performed in which the energy in the Metropolis algorithm is substituted by a score function that measures the average distance of the probe to the target surface. This has the effect of making buried probes move toward the target surface and also allows enhanced sampling of deep pockets. In a second MC run, a pairwise atom potential function is used, and the temperature parameter is slowly lowered during the run (Simulated Annealing). We repeat this procedure starting from a large number of different randomly generated initial configurations in order to find all energetically favorable docking modes in a specified region around the target. We test this method using two inhibitor-receptor systems: Streptomyces griseus proteinase B in complex with the third domain of the ovomucoid inhibitor from turkey, and dihydrofolate reductase from E. coli in complex with methotrexate. The method could consistently reproduce the complex found in the crystal structure searching from random initial positions in cubes ranging from 25 A to 50 A about the binding site. In the case of SGPB, we were also successful in docking to the native structure. In addition, we were successful in docking small probes in a search that included the entire protein surface.     

Monte Carlo simulation of the dose distribution of ICRP adult reference computational phantoms for acquisitions with a 320 detector-row cone-beam CT scanner

PurposeThe purpose of this study was to develop and validate a Monte Carlo (MC) simulation tool for patient dose assessment for a 320 detector-row CT scanner, based on the recommendations of International Commission on Radiological Protection (ICRP). Additionally, the simulation was applied on four clinical acquisition protocols, with and without automatic tube current modulation (TCM).MethodsThe MC simulation was based on EGS4 code and was developed specifically for a 320 detector-row cone-beam CT scanner. The ICRP adult reference phantoms were used as patient models. Dose measurements were performed free-in-air and also in four CTDI phantoms: 150 mm and 350 mm long CT head and CT body phantoms. The MC program was validated by comparing simulations results with these actual measurements acquired under the same conditions. The measurements agreed with the simulations across all conditions within 5%. Patient dose assessment was performed for four clinical axial acquisitions using the ICRP adult reference phantoms, one of them using TCM.ResultsThe results were nearly always lower than those obtained from other dose calculator tools or published in other studies, which were obtained using mathematical phantoms in different CT systems. For the protocol with TCM organ doses were reduced by between 28 and 36%, compared to the results obtained using a fixed mA value.ConclusionsThe developed simulation program provides a useful tool for assessing doses in a 320 detector-row cone-beam CT scanner using ICRP adult reference computational phantoms and is ready to be applied to more complex protocols.     

Monte Carlo evaluation of glandular dose in cone-beam X-ray computed tomography dedicated to the breast: Homogeneous and heterogeneous breast models

PurposeIn cone-beam computed tomography dedicated to the breast (BCT), the mean glandular dose (MGD) is the dose metric of reference, evaluated from the measured air kerma by means of normalized glandular dose coefficients (DgN_CT). This work aimed at computing, for a simple breast model, a set of DgN_CT values for monoenergetic and polyenergetic X-ray beams, and at validating the results vs. those for patient specific digital phantoms from BCT scans.MethodsWe developed a Monte Carlo code for calculation of monoenergetic DgN_CT coefficients (energy range 4.25–82.25 keV). The pendant breast was modelled as a cylinder of a homogeneous mixture of adipose and glandular tissue with glandular fractions by mass of 0.1%, 14.3%, 25%, 50% or 100%, enveloped by a 1.45 mm-thick skin layer. The breast diameter ranged between 8 cm and 18 cm. Then, polyenergetic DgN_CT coefficients were analytically derived for 49-kVp W-anode spectra (half value layer 1.25–1.50 mm Al), as in a commercial BCT scanner. We compared the homogeneous models to 20 digital phantoms produced from classified 3D breast images.ResultsPolyenergetic DgN_CT resulted 13% lower than most recent published data. The comparison vs. patient specific breast phantoms showed that the homogeneous cylindrical model leads to a DgN_CT percentage difference between −15% and +27%, with an average overestimation of 8%.ConclusionsA dataset of monoenergetic and polyenergetic DgN_CT coefficients for BCT was provided. Patient specific breast models showed a different volume distribution of glandular dose and determined a DgN_CT 8% lower, on average, than homogeneous breast model.     

Prediction of protein conformation in water and on surfaces by Monte Carlo simulations using united-atom method

The united-atom method has been used to model an avian pancreatic polypeptide (APP) in water and the adsorption process of an albumin subdomain (AS) onto graphite surface to observe the capability of this lumped modelling approach to generate structures observed in protein data bank (PDB) and from atomistic modelling. The subdomain structure of a protein is simplified by the united-atom approximation where the side chains and peptide groups are represented by lumped spheres. The total potential energy of the adsorption process involves the interaction between these lumped spheres by means of virtual bond chain interaction and the interaction of the spheres with the graphite surface by means of Lennard-Jones potential. The protein/polypeptide structure has been perturbed by Monte Carlo with energy minimisation to obtain the global minimum. Results on the APP in water showed a near-to-experimental PDB conformation revealing the two α-helix structures of this small protein molecule with the root mean square deviation among carbon backbone atoms of 5.9 Å. Protein adsorption on biosurfaces has been made by modelling AS, which has 60 amino acids. The surface is graphite, which is characterised by its hydrophobicity. Graphite was chosen because of its widely used applications in certain implants that interact with blood. Our simulation results showed final conformation close to that obtained by atomistic modelling. It also proved that the whole pattern of intramolecular hydrogen bonds was distorted. The model also demonstrated the random conformation of the original α-helix secondary structures of AS consistent with experimental and atomistic results. While atomistic simulation works well for simulating individual small proteins, the united-atom model is more efficient when simulating macromolecular and multiple protein adsorption where time and limiting computer capacity are key factors.