A personalized, Monte Carlo-based method for internal dosimetric evaluation of radiopharmaceuticals in children

Simplified image-based dosimetry using planar images and patient-specific S-values

BACKGROUND

Single time point measurement approach and hybrid dosimetry were proposed to simplify the dosimetry process. It is anticipated that utilizing patient-specific S-value would enable more accurate dosimetry assessment based on imaging compared to using the conventional MIRD S-values.

PURPOSE

We performed planar image-based dosimetry scaled with a single SPECT image for the entire treatment cycle using patient-specific S-values (PSS dosimetry) of organs. PSS dosimetry could further simplify the dosimetry procedure compared with a conventional 2D planar/3D SPECT hybrid dosimetry, as PSS dosimetry requires only one SPECT/CT image for the treatment of the entire cycle, whereas the conventional hybrid dosimetry requires a SPECT/CT image for each treatment cycle.

METHODS

177Lu-DOTATATE SPECT/CT and planar image datasets acquired from Seoul National University Hospital (SNUH, Seoul, Republic of Korea) were utilized for the evaluation. Images were acquired 4, 24, 48, and 120 h after patients' intravenous injection of 177Lu-DOTATATE. Dose estimations based on a Monte Carlo (MC) simulation using the Geant4 Application for Emission Tomography (GATE) (v.8.2) were considered as the reference. Planar image-based dosimetry scaled with a single SPECT image was performed using the patient-specific S-value (PSS). Briefly, the CT image was considered as the patient's anatomical reference and PSSs were quantified using the multiple voxel S-value (VSV) method. Then, PSS dosimetry was performed by obtaining activity information from sequential planar images and a scaling factor derived from a single SPECT/planar image pair. Hybrid dosimetry using sequential planar images and a single SPECT image was performed for comparison. The absorbed doses of the kidneys, bone marrow (BM) in the lumbar spine, liver, and spleen calculated using the PSS and hybrid dosimetries were compared with the reference MC results.

RESULTS

The mean differences (MDs) of the self-absorption S-values between S-value of OLINDA/EXM and PSS for the kidneys, liver, and spleen were -0.04%, -2.39%, and -2.62%, respectively. However, the differences in the self-absorption S-values were significantly higher for the BM (84.99%) and the remainder of the body (ROB) (280.84%). The absorbed doses estimated by the PSS and hybrid dosimetries showed relatively high errors compared with MC simulation result, regardless of the organ. In contrast, the PSS and hybrid dosimetries produced similar dose estimates. For the entire cycles of the treatment, the MDs of absorbed doses between PSS and hybrid dosimetries were -3.31%, -6.04%, 3.37%, and -2.17% for the kidneys, BM, liver, and spleen, respectively. Through a correlation analysis and the Wilcoxon signed-rank test, we concluded that there was no significant difference between the results obtained by the two dosimetry methods.

CONCLUSIONS

As the PSS was derived using CT images with actual anatomical information and organ-specific volume of interest (VOI), PSS dosimetry provided reliable results. PSS dosimetry was robust in estimating the absorbed dose for the later treatment cycles. Therefore, PSS dosimetry outperformed hybrid dosimetry in terms of dose estimation for a greater number of treatment cycles.

Simulation of X-ray projections on GPU: Benchmarking gVirtualXray with clinically realistic phantoms

BACKGROUND AND OBJECTIVES

This study provides a quantitative comparison of images created using gVirtualXray (gVXR) to both Monte Carlo (MC) and real images of clinically realistic phantoms. gVirtualXray is an open-source framework that relies on the Beer-Lambert law to simulate X-ray images in realtime on a graphics processor unit (GPU) using triangular meshes.

METHODS

Images are generated with gVirtualXray and compared with a corresponding ground truth image of an anthropomorphic phantom: (i) an X-ray projection generated using a Monte Carlo simulation code, (ii) real digitally reconstructed radiographs (DRRs), (iii) computed tomography (CT) slices, and (iv) a real radiograph acquired with a clinical X-ray imaging system. When real images are involved, the simulations are used in an image registration framework so that the two images are aligned.

RESULTS

The mean absolute percentage error (MAPE) between the images simulated with gVirtualXray and MC is 3.12%, the zero-mean normalised cross-correlation (ZNCC) is 99.96% and the structural similarity index (SSIM) is 0.99. The run-time is 10 days for MC and 23 ms with gVirtualXray. Images simulated using surface models segmented from a CT scan of the Lungman chest phantom were similar to (i) DRRs computed from the CT volume and (ii) an actual digital radiograph. CT slices reconstructed from images simulated with gVirtualXray were comparable to the corresponding slices of the original CT volume.

CONCLUSIONS

When scattering can be ignored, accurate images that would take days using MC can be generated in milliseconds with gVirtualXray. This speed of execution enables the use of repetitive simulations with varying parameters, e.g. to generate training data for a deep-learning algorithm, and to minimise the objective function of an optimisation problem in image registration. The use of surface models enables the combination of X-ray simulation with real-time soft-tissue deformation and character animation, which can be deployed in virtual reality applications.

Stylized versus voxel phantoms: quantification of internal organ chord length distances

Dosimetric calculations, whether for radiation protection or nuclear medicine applications, are greatly influenced by the use of computational models of humans, called anthropomorphic phantoms. As anatomical models of phantoms have evolved and expanded, thus has the need for quantifying differences among each of these representations that yield variations in organ dose coefficients, whether from external radiation sources or internal emitters. This work represents an extension of previous efforts to quantify the differences in organ positioning within the body between a stylized and voxel phantom series. Where prior work focused on the organ depth distribution vis-à-vis the surface of the phantom models, the work described here quantifies the intra-organ and inter-organ distributions through calculation of the mean chord lengths. The revised Oak Ridge National Laboratory stylized phantom series and the University of Florida/National Cancer Institute voxel phantom series including a newborn, 1-, 5-, 10- and 15 year old, and adult phantoms were compared. Organ distances in the stylized phantoms were computed using a ray-tracing technique available through Monte Carlo radiation transport simulations in MCNP6. Organ distances in the voxel phantom were found using phantom matrix manipulation. Quantification of differences in organ chord lengths between the phantom series displayed that the organs of the stylized phantom series are typically situated farther away from one another than within the voxel phantom series. The impact of this work was to characterize the intra-organ and inter-organ distributions to explain the variations in updated internal dose coefficient quantities (i.e. specific absorbed fractions) while providing relevant data defining the spatial and volumetric organ distributions in the phantoms for use in subsequent internal dosimetric computations, with prospective relevance to patient-specific individualized dosimetry, as well as informing machine learning definition of organs using these reference models.

Evaluation of radiation dose to pediatric models from whole body PET/CT imaging

Positron emission tomography (PET)/computed tomography (CT) is a well-known modality for the diagnosis of various diseases in children and adult patients. On the other hand, younger patients are more radiosensitive than adults, so there are concerns about the level of ionizing radiation exposure in pediatric whole body PET/CT imaging. In this regard, comprehensive specific radiation dosimetry for whole body PET/CT imaging is highly desired for different ages, sizes, and shapes. Therefore, in this study, organ absorbed doses were evaluated for pediatric voxel models from 4 to 14 years old and compared with those of ICRP phantoms. Monte Carlo calculation was performed to evaluate S-value, absorbed dose, and effective dose from ¹⁸ F-FDG radiotracers and whole body CT scan for different computational models, including 4- to 14-year-old phantoms. The results showed that the S-value and, therefore, absorbed dose of ¹⁸ F-FDG strongly depended on the phantom anatomy. These variations were justified by the distance between source and target organs. Moreover, on average, the absorbed doses from whole body CT scans were 13.5 times lower than those from ¹⁸ F-FDG for all organs. According to the results, various anatomies and ages should be considered for accurate dose evaluation. These data can be used for specific risk assessment of the pediatric population in clinical nuclear imaging.

Specific absorbed fractions for a revised series of the UF/NCI pediatric reference phantoms: internal photon sources

Assessment of radiation absorbed dose to internal organs of the body from the intake of radionuclides, or in the medical setting through the injection of radiopharmaceuticals, is generally performed based upon reference biokinetic models or patient imaging data, respectively. Biokinetic models estimate the time course of activity localized to source organs. The time-integration of these organ activity profiles are then scaled by the radionuclide S-value, which defines the absorbed dose to a target tissue per nuclear transformation in various source tissues. S-values are computed using established nuclear decay information (particle energies and yields), and a parameter termed the specific absorbed fraction (SAF). The SAF is the ratio of the absorbed fraction-fraction of particle energy emitted in the source tissue that is deposited in the target tissue-and the target organ mass. While values of the SAF may be computed using patient-specific or individual-specific anatomic models, they have been more widely available through the use of computational reference phantoms. In this study, we report on an extensive series of photon SAFs computed in a revised series of the University of Florida and the National Cancer Institute pediatric reference phantoms which have been modified to conform to the specifications embodied in the ICRP reference adult phantoms of Publication 110 (e.g. organs modeled, organ ID numbers, blood contribution to elemental compositions). Following phantom anatomical revisions, photon radiation transport simulations were performed using MCNPX v2.7 in each of the ten phantoms of the series-male and female newborn, 1 year old, 5 year old, 10 year old, and 15 year old-for 60 different tissues serving as source and/or target regions. A total of 25 photon energies were considered from 10 keV to 10 MeV along a logarithm energy grid. Detailed analyses were conducted of the relative statistical errors in the Monte Carlo target tissue energy deposition tallies at low photon energies and over all energies for source-target combinations at large intra-organ separation distances. Based on these analyses, various data smoothing algorithms were employed, including multi-point weighted data smoothing, and log-log interpolation at low energies (1 keV and 5 keV) using limiting SAF values based upon target organ mass to bound the interpolation interval. The final dataset is provided in a series of ten electronic supplemental files in MS Excel format. The results of this study were further used as the basis for assessing the radiative component of internal electron source SAFs as described in our companion paper (Schwarz et al 2021) for this same pediatric phantom series.

Advances in Computational Human Phantoms and Their Applications in Biomedical Engineering - A Topical Review

Over the past decades, significant improvements have been made in the field of computational human phantoms (CHPs) and their applications in biomedical engineering. Their sophistication has dramatically increased. The very first CHPs were composed of simple geometric volumes, e.g., cylinders and spheres, while current CHPs have a high resolution, cover a substantial range of the patient population, have high anatomical accuracy, are poseable, morphable, and are augmented with various details to perform functionalized computations. Advances in imaging techniques and semi-automated segmentation tools allow fast and personalized development of CHPs. These advances open the door to quickly develop personalized CHPs, inherently including the disease of the patient. Because many of these CHPs are increasingly providing data for regulatory submissions of various medical devices, the validity, anatomical accuracy, and availability to cover the entire patient population is of utmost importance. The article is organized into two main sections: the first section reviews the different modeling techniques used to create CHPs, whereas the second section discusses various applications of CHPs in biomedical engineering. Each topic gives an overview, a brief history, recent developments, and an outlook into the future.

Quantification of DNA double-strand breaks using Geant4-DNA

PURPOSE

This study aims to standardize the simulation procedure in measuring DNA double-strand breaks (DSBs), by using advanced Monte Carlo toolkits, and newly introduced experimental methods for DNA DSB measurement.

METHODS

For the experimental quantification of DNA DSB, an innovative DNA dosimeter was used to produce experimental data. GATE in combination with Geant4-DNA toolkit were exploited to simulate the experimental environment. The PDB4DNA example of Geant4-DNA was upgraded and investigated. Parameters of the simulation such energy threshold (ET) for a strand break and base pair threshold (BPT) for a DSB were evaluated, depending on the dose.

RESULTS

Simulations resulted to minimum differentiation in comparison to experimental data for ET = 19 ± 1 eV and BPT = 10 bp, and high differentiation for ET<17.5 eV or ET>22.5 eV and BPT = 10 bp. There was also small differentiation for ET = 17.5 eV and BPT = 6 bp. Uncertainty has been kept lower than 3%.

CONCLUSIONS

This study includes first results on the quantification of DNA double-strand breaks. The energy spectrum of a LINAC was simulated and used for the first time to irradiate DNA molecules. Simulation outcome was validated on experimental data that were produced by a prototype DNA dosimeter.