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To further improve the understanding of in vitro biological effects of incorporated radionuclides, it is essential to accurately determine cellular absorbed doses. In the case of β emitters, the cross-dose is a major contribution, and can involve up to millions of cells. Realistic and efficient computational models are needed for that purpose. Conventionally, distances between each cell are calculated and the related dose contributions are cumulated to get the total cross-dose (standard method). In this work, we developed a novel approach for the calculation of the cross-absorbed dose, based on the use of the radial distribution function (rdf)) that describes the spatial properties of the cellular model considered. The dynamic molecular tool LAMMPS was used to create 3D cellular models and compute rdfs for various conditions of cell density, volume size, and configuration type (lattice and randomized geometry). The novel method is suitable for any radionuclide of nuclear medicine. Here, the model was applied for the labeling of cells with 18F-FDG used for PET imaging, and first validated by comparison with other reference methods. Mean Scross values calculated with the novel approach versus the standard method agreed very well (relative differences less that 0.1%). Implementation of the rdf -based approach with LAMMPS allowed to achieved results considerably faster than with the standard method, the computing time decreasing from hours to seconds for 106 cells. The rdf -based approach was also faster and easier to accommodate more complex cellular models than the standard and other published methods. Finally, a comparative study of the mean Scross for different types of configuration was carried out, as a function of the cell density and the volume size, allowing to better understand the impact of the configuration on the cross-absorbed dose. [ABSTRACT FROM AUTHOR]

Objective. Molecular radiotherapy is the most used treatment modality against malign and benign diseases of thyroid. In that context, the large heterogeneity of therapeutic doses in patients and the range of effects observed show that individualized dosimetry is essential for optimizing treatments according to the targeted clinical outcome. Approach. We developed a high-resolution mobile gamma camera specifically designed to improve the quantitative assessment of the distribution and biokinetics of 131 I at patients's bedside after treatment of thyroid diseases. The first prototype has a field of view of 5 × 5 cm 2 and consists of a high-energy parallel-hole collimator made of 3D-printed tungsten, coupled to a 6 mm thick CeBr 3 scintillator readout by an array of silicon photomultiplier detectors. The intrinsic and overall imaging performance of the camera was evaluated with 133 Ba and 131 I sources. In order to test its quantification capability in realistic clinical conditions, two different 3D-printed thyroid phantoms homogeneously filled with 131 I were used. Both single view and conjugate view approaches have been applied, with and without scatter correction technique. Main Results. The camera exhibits high imaging performance with an overall energy resolution of 7.68 ± 0.01%, a submillimetric intrinsic spatial resolution of 0.74 ± 0.28 mm and a very low spatial distortion 0.15 ± 0.10 mm. The complete calibration of the camera shows an overall spatial resolution of 3.14 ± 0.03 mm at a distance of 5 cm and a corresponding sensitivity of 1.23 ± 0.01 cps/MBq, which decreases with distance and slightly changes with source size due to the influence of scattering. Activity recovery factors better than 97% were found with the thyroid phantoms. Significance. These preliminary results are very encouraging for the use of our camera as a tool for accurate quantification of absorbed doses and currently motivates the development of a fully operational clinical camera with a 10 × 10 cm 2 field of view and improved imaging capabilities., (Creative Commons Attribution license.)

To further improve the understanding of in vitro biological effects of incorporated radionuclides, it is essential to accurately determine cellular absorbed doses. In the case of β emitters, the cross-dose is a major contribution, and can involve up to millions of cells. Realistic and efficient computational models are needed for that purpose. Conventionally, distances between each cell are calculated and the related dose contributions are cumulated to get the total cross-dose (standard method). In this work, we developed a novel approach for the calculation of the cross-absorbed dose, based on the use of the radial distribution function ( rdf )) that describes the spatial properties of the cellular model considered. The dynamic molecular tool LAMMPS was used to create 3D cellular models and compute rdfs for various conditions of cell density, volume size, and configuration type (lattice and randomized geometry). The novel method is suitable for any radionuclide of nuclear medicine. Here, the model was applied for the labeling of cells with 18 F-FDG used for PET imaging, and first validated by comparison with other reference methods. Mean S cross values calculated with the novel approach versus the standard method agreed very well (relative differences less that 0.1%). Implementation of the rdf -based approach with LAMMPS allowed to achieved results considerably faster than with the standard method, the computing time decreasing from hours to seconds for 10 6 cells. The rdf -based approach was also faster and easier to accommodate more complex cellular models than the standard and other published methods. Finally, a comparative study of the mean S cross for different types of configuration was carried out, as a function of the cell density and the volume size, allowing to better understand the impact of the configuration on the cross-absorbed dose., (© 2021 Institute of Physics and Engineering in Medicine.)

Positron emission tomography (PET) offers an effective method for tracking β + emitters-labeled cells in vivo. However, in vitro high labelling activities used may cause cell damage or death. Our understanding of the impact of such procedure remains limited by the fact that the biological effects are usually linked to the activity per cell rather than the absorbed dose. To assess the dose delivered to the cells during the radiolabelling, a multi-cellular dosimetry computational tool was developed, allowing the study of two key parameters: the cell density and the labelling efficiency. Through a hybrid method based on Monte Carlo simulations (MCNP6 code) and an analytical approach implemented in Python, the mean absorbed dose received by a target cell was calculated for distributions with a very large number of cells-up to hundreds of millions. An advanced investigation of in vitro cell labelling with β-emitting radionuclides was carried out via (i) a systematic study of the effects of the labelling parameters on the cell absorbed dose for 18 F, 64 Cu and 68 Ga, and (ii) a quantitative comparison between cellular and conventional dosimetry. The results provided a thorough analysis of how the dose (self, cross and extracellular medium dose contributions) varies with the initial labelling parameters selected and highlighted the conditions where the cellular dosimetry is required over the conventional dosimetry. The dosimetric model was finally applied to real conditions of 18 F-FDG labelling on the basis of eight reported studies. The results showed that similar activity per cell can lead to significantly different absorbed dose and pointed out differences between cellular and conventional dosimetry up to a factor of 5.

In the case of a nuclear reactor accident the release contains a high proportion of iodine-131 that can be inhaled or ingested by members of the public. Iodine-131 is naturally retained in the thyroid and increases the thyroid cancer risk. Since the radiation induced thyroid cancer risk is greater for children than for adults, the thyroid dose to children should be assessed as accurately as possible. For that purpose direct measurements should be carried out with age-specific calibration factors but, currently, there is no age-specific thyroid phantoms allowing a robust measurement protocol. A set of age-specific thyroid phantoms for 5, 10, 15 year old children and for the adult has been designed and 3D printed. A realistic thyroid shape has been selected and material properties taken into account to simulate the attenuation of biological tissues. The thyroid volumes follow ICRP recommendations and the phantoms also include the trachea and a spine model. Several versions, with or without spine, with our without trachea, with or without age-specific neck have been manufactured, in order to study the influence of these elements on calibration factors. The calibration factor obtained with the adult phantom and a reference phantom are in reasonable agreement. In vivo calibration experiments with germanium detectors have shown that the difference in counting efficiency, the inverse of the calibration factor, between the 5 year and adult phantoms is 25% for measurement at contact. It is also experimentally evidenced that the inverse of the calibration factor varies linearly with the thyroid volume. The influence of scattering elements like the neck or spine is not evidenced by experimental measurements.

This paper addresses the question of the morphological dependence of counting efficiency curves for in vivo lung monitoring of workers, with a particular focus on the case of female workers for whom different chest girth and cup size are considered. A library of 24 female torsos, with chest girth varying from 85 to 120 and cup size from A to F, was constructed using mesh and NURBS formats. The anatomical realism and usefulness of these models for simulating in vivo counting measurements are illustrated and simulations are reported for a typical 4-germanium (Ge) counting system. A simple analytic formula describing the relation between efficiency curves obtained for each female phantom is given. This formula uses the mass attenuation coefficient for adipose tissue and two parameters which are dependant on lung volume and breast weight. The model is tested against Monte Carlo simulated data, experimental data obtained with the Livermore phantom and published data. The model correctly describes the efficiency curve and, since the parameters depend on the counting geometry, it is shown how to estimate them from experimental measurements.