Abstract Monte Carlo simulations were performed to evaluate treatment doses with wide spread used radionuclides 133Xe, 99mTc and 81mKr. These different radionuclides are used in perfusion or ventilation examinations in nuclear medicine and as indicators for cardiovascular and pulmonary diseases. The objective of this work was to estimate the specific absorbed fractions in surrounding organs and tissues, when these radionuclides are incorporated in the lungs. For this purpose a voxel thorax model has been developed and compared with the ORNL phantom. All calculations and simulations were performed by means of the MCNP5/X code. INTRODUCTION Radioactive isotopes and their compounds are commonly used in nuclear medicine for diagnosis and metabolic therapy. Accordingly, the use of different kinds of isotopes taking into account the procedure to be applied to patients or in laboratory conditions requires determination of the distribution of the dose. In order to minimize the harm to the patient and provide good results for diagnostic applications, the isotope must have a short half-life. Scintigraphy is one diagnostic method used in nuclear medicine to evaluate the distribution of radiopharmaceutical uptake in the body(1–4). Lung scintigraphy is a diagnostic imaging procedure that uses ventilation scintigraphy, perfusion scintigraphy or both. This method enables determination of the spatial and temporal distribution of radionuclides in the body, tissues or the whole body, depending on where the radiopharmaceutical accumulates(5–7). One of the most commonly used pharmaceutical agents in nuclear medicine imaging is 99mTc and its compounds(8–10). It emits gamma with energy of 141 keV and has a half-life of 6 h. It can be combined with various biologically active compounds or substances (nanoparticles comprised of Technetium-99m cores have recently been used) enabling transport to target organs(11). 99mTc—technegas is commonly used for lung scintigraphy imaging(12). 133Xe (T1/2 = 5.24 d) disintegrates by beta-emission and emits a 81 keV photon. 133Xe is inhaled to assess pulmonary functions and produce good quality imaging of the lungs. Ventilation scintigraphy which uses 133Xe is usually performed before perfusion scintigraphy(10). 81mKr has a half-life of 13 s and emits gamma with energy of 190 keV. 81mKr is obtained from the generator 81Rb/81mKr and 81mKr is used as a marker for ventilation scintigraphy(13). A disadvantage of 81mKr is that the short half-life of the parent radionuclide, 81Rb (4.57 h), decreases availability and increases the cost of the generator(10). In this work, only the most intensive gamma lines were considered. Other groups of gamma emitted by 133Xe and 99mTc have very low intensity and they were not taken into account. 81mKr emits only one gamma line with yields of 68%. In International Commission of Radiological Protection (ICRP) publications(14–16), Specific Absorbed Fraction (SAF) are given for some discrete values of energies, and some interpolation is needed in order to obtain SAF for energies which are different than those given in reports. There is also data on SAFs in literature, obtained with different Monte Carlo codes (MIRDSE, OLINDA, EGSnrc, FLUKA, MCNPX, PENELOPE, etc.)(17–24), but the data were again given for discrete values of energies. Interpolation is always the subject of uncertainty. Since the abovementioned radionuclides are important in nuclear medicine, and energies of gamma photons emitted by these radionuclides are different than those given in ICRP, the intention of this work was to calculate SAF for energies of these radionuclides, in order to avoid interpolation between discrete data and to fill this gap for lungs as a source region. Additional calculations were performed in order to estimate the error of interpolation. Some authors have published SAFs for the most intensive gamma energies which are specific for several radionuclides used in nuclear medicine as 18F, 117Lu, 131I and 90Y(20, 23, 24). In this work data are given for other groups of radionuclides, 133Xe, 99mTc and 81mKr, used in nuclear medicine not included in literature. In addition the objective of this work was to compare SAFs obtained with ORNL phantom and voxel thorax models(14). MATERIALS AND METHODS The 99mTc isotope is an almost pure gamma emitter, with energy 141 keV and half-life of 6 h that is long enough to perform scintigraphy; it is also very affordable for being eluted daily from the generator. In addition to 99mTc, two other isotopes, 81mKr and 133Xe, have been considered. Three types of phantoms are in use in protection against ionizing radiation: stylized mathematical phantoms, voxel phantoms and the latest generation of so-called hybrid phantoms(25–28). In this work, a voxel thorax model was obtained using a Digital Imaging and Communications in Medicine (DICOM) set of 108 Computed Tomography (CT) images of the thorax of a female patient under approved standard protocols. CT data of a 35-year-old female patient were segmented using image processing software ImageJ(29)—version 1.51n 2017, and converted to voxel geometry. ImageJ software can very effectively operate with multi objects. This is an open source image processing program designed for scientific purposes of recording multidimensional images and it is downloadable for MAC OS, Windows and Linux(30). Figure 1 shows raw CT data images of a thorax before processing of segmentations open in the ImageJ 3D viewer (Figure 1a) and a cross-section of the thorax (Figure 1b) using the same plugins. Figure 1. View largeDownload slide Thorax CT scans in ImageJ 3D viewer and cross-section of thorax. (a) Raw CT data images of a thorax before processing in the ImageJ 3D viewer. (b) Cross-section of the thorax. Figure 1. View largeDownload slide Thorax CT scans in ImageJ 3D viewer and cross-section of thorax. (a) Raw CT data images of a thorax before processing in the ImageJ 3D viewer. (b) Cross-section of the thorax. Digital images obtained from scanning of real persons by computed tomography or magnetic resonance(25, 26) should have sufficient resolution for the construction of voxel phantoms. This medical image set has been translated into a voxel geometry, which provides the tools for realistic description of human anatomy. The voxel thorax model was presented by a 3D array of voxels with Identification (ID) numbers. For each voxel the ID numbers indicate to which organ or tissue the voxel belongs. A large number of voxels requires the use of enhanced capability computer hardware and for this work, so massive calculations were performed on an AEGIS04-KG cluster(31), which is an integral part of the European Grid Initiative-EGI(32). The voxel model was used with the Monte Carlo code MCNP5/X(33). The developed voxel thorax model has several organs of interest as follows: skin, lungs, bones, heart, spinal cord, aorta, muscle and adipose tissue. In MCNP the voxel representation of the human body is based on repeated structures filled with a certain material corresponding to the specific organ. In a particular way the combined use of universe, fill and lattice cards permits definition of the voxel phantom geometry as a volume filled by rectangular lattices of cubic elements. A cross-section of a voxel thorax model after the segmentation process is shown as graphical output in Figure 2, containing a cross-section along the z axis at different positions. Figure 2a and b shows a cross-section of a voxel thorax model at pz = 23 and 55 cm, respectively Table 1. Selected organs of the voxel thorax model with a corresponding ID number, number of voxels, mass and density. ID number Organs/tissue Number of voxels Mass of voxelized organs/tissue (g) Density (g/cm3) 100 Adipose tissue 2 228 002 3734 0.95 110 Skin 133 485 257 1.09 120 Lungs 2 019 581 1055 0.296 130 Bone 605 734 2052 1.40 140 Heart 229 676 425 1.05 150 Spinal cord 23 257 43 1.04 160 Aorta 80 231 149 1.05 170 Muscle 1 983 323 3674 1.05 ID number Organs/tissue Number of voxels Mass of voxelized organs/tissue (g) Density (g/cm3) 100 Adipose tissue 2 228 002 3734 0.95 110 Skin 133 485 257 1.09 120 Lungs 2 019 581 1055 0.296 130 Bone 605 734 2052 1.40 140 Heart 229 676 425 1.05 150 Spinal cord 23 257 43 1.04 160 Aorta 80 231 149 1.05 170 Muscle 1 983 323 3674 1.05 Figure 2. View largeDownload slide Cross-section of a voxel thorax model with different horizontal planes. ID numbers of organs in this figure are given in Table 1. ID 256 is the outer space. Figure 2. View largeDownload slide Cross-section of a voxel thorax model with different horizontal planes. ID numbers of organs in this figure are given in Table 1. ID 256 is the outer space. Different organ/tissue is assigned a corresponding ID number, compatible with cell cards in the MCNP5/X input file. Corresponding ID number, organ/tissue, total numbers of voxels in each organ, mass and density are presented in Table 1. The total number of voxels in simulations was 13 592 124. As the volume of the voxel is 17.64⋅10−4cm3, the obtained thickness and mass values for the skin in the built voxel thorax model are compatible with reference ICRP values(14, 34). In this work, the results on SAF, obtained by a voxel thorax model were compared with an ORNL mathematical phantom. ORNL phantoms were described in(35, 36) and consist of three major sections: (1) an elliptical cylinder representing the trunk and arms; (2) two truncated circular cones representing the legs and feet; and (3) a circular cylinder on which sits an elliptical cylinder capped by half an ellipsoid representing the neck and head. It was assumed that decay of the investigated radionuclides is localized in the lungs, representing the source of gamma radiation. Each lung lobe is represented by half an ellipsoid with a section removed, as defined by the following equation for the right lung: (x+x0a)2+(yb)2+(z−z0c)2≤1andz≥z0 (1) If z1R≤z≤z2R, y<y1R and x≤x1R (The conditions for the planes that are normal at −z, −y and x-axes and cut an ellipsoid, so that they form a lung.). The appropriate values are: z1R=41.60cm, z2R=48.50cm, y1R=1.20cm and x1R=−5.00cm. The coordinates of the ellipsoid center are: x0=7.33cm, y0=0 and z0=39.21cm; a, b and c are the axes of the ellipsoid, whose values are 4.09, 6.98 and 20.55 cm, respectively. The letters R and L refer to the right and left lung lobe, respectively. For the left lung (x + x0) should be replaced with (x−x0); z1R with z0; z2R with z2L; y1R with y1L. The appropriate values for the left lung are: z2L=49.00cm and y1L=7.00cm. Figure 3 shows a cross-section of a phantom, as graphical output from MCNP code. Figure 3. View largeDownload slide Cross-section of an ORNL female phantom: (a) pz = 51 cm and (b) pz = 55 cm. (a) 1: lungs, 2: heart, 3: spine, 4: arm bones, 5: ribs. (b) 1: lungs, 2: spine, 3: arm bones, 4: ribs, 5: pelvis, 6: esophagus. Figure 3. View largeDownload slide Cross-section of an ORNL female phantom: (a) pz = 51 cm and (b) pz = 55 cm. (a) 1: lungs, 2: heart, 3: spine, 4: arm bones, 5: ribs. (b) 1: lungs, 2: spine, 3: arm bones, 4: ribs, 5: pelvis, 6: esophagus. The masses of voxelised organ/tissue were derived from CT scans. Considering the CT scan the cut should be a few cm from the lowest point of the lungs to the beginning of the neck. Knowing the number of voxels, n, (Table 1) which represent some organ/tissue, and the volume of one voxel V=0.084cm×0.084cm×0.25cm=17.64⋅10−4cm3, one can easily determine the volume of each organ/tissue in a voxel thorax model, i.e. organ volume = n · V and multiplication with the mean assumed density of the tissue, enables calculation of its mass. To compare the ORNL phantom to the voxel thorax model, the ORNL phantom was cut at the level of the bottom of the lungs. Monoenergetic photon sources were considered (81 keV for 133Xe, 141 keV for 99mTc and 190 for 81mKr) and a full ‘history’ of secondary charged particles was followed in the simulation. The sources were considered to be homogeneously distributed in the source organs (lungs). Energy cut-off was set to 1 keV in simulations. Tissue composition taken from ICRP110 was used for the voxel, while ORNL used data from references(14, 16). RESULTS AND DISCUSSION All simulations were done using MCNP5/X code(33). In total 108 particles were run to obtain a relative uncertainty lower than 1% for all organs and for both phantoms (voxel thorax model and ORNL). The SAFs were determined in the surrounding organs and tissues during the incorporation of radionuclides in the lungs, as the source region. For that purpose a *F8 tally card was used to calculate energy deposition in organ/tissue (in MeV per photon) for the voxel thorax model following secondary charged particles. Since the *F8 tally does not produce results normalized per mass, it was necessary to divide the output obtained from MCNP5/X calculations with the mass of tissue or organs. The obtained value was converted into the SAFs in Gy per source particle. Tally card F6 was used for dose estimation in organs of the ORNL phantom. This card of MCNP5/X code produces results in MeV g−1 per source particles but in KERMA approximation (i.e. without the secondary charged transport). The SAFs for selected organs were evaluated using the following formula: SAF=EdEi⋅m (2)where Ed is the average energy deposited in the target organ, Ei is the primary energy emitted by the source and m is the mass of the target organ. The results of SAFs calculations are presented in Tables 2 and 3 for 81mKr, 99mTc and 133Xe, respectively. From these tables, it can be seen that SAF are largest in the lungs, bones, muscle and adipose tissue while in other organs/tissue they are smaller. Table 2. Results of SAF (kg−1) for the voxel thorax model for 133Xe, 99mTc and 81mKr. Organs/tissue Volumes of organs (cm3) 133Xe Differences of SAF for voxel thorax model and ORNL phantom (%) 99mTc Differences of SAF for voxel thorax model and ORNL phantom (%) 81mKr Differences of SAF for voxel thorax model and ORNL phantom (%) Adipose tissue 3930.5 1.72 · 10−2 1.78 · 10−2 1.85 · 10−2 Skin 235.8 0.96 · 10−2 9.82 0.96 · 10−2 14.96 1.01 · 10−2 16.4 Lungs 3564.2 5.59 · 10−2 −24.3 5.09 · 10−2 −16.89 5.18 · 10−2 −15.9 Bones 1465.7 5.01 · 10−2 12.4 2.90 · 10−2 6.86 2.29 · 10−2 8.0 Heart 404.8 3.63 · 10−2 2.43 3.05 · 10−2 7.56 3.01 · 10−2 9.0 Spinal cord 41.3 2.35 · 10−2 2.42 · 10−2 2.48 · 10−2 Aorta 141.9 4.53 · 10−2 3.92 · 10−2 3.90 · 10−2 Muscle 3449 1.89 · 10−2 −16.5 1.76 · 10−2 −7.07 1.78 · 10−2 −4.5 Organs/tissue Volumes of organs (cm3) 133Xe Differences of SAF for voxel thorax model and ORNL phantom (%) 99mTc Differences of SAF for voxel thorax model and ORNL phantom (%) 81mKr Differences of SAF for voxel thorax model and ORNL phantom (%) Adipose tissue 3930.5 1.72 · 10−2 1.78 · 10−2 1.85 · 10−2 Skin 235.8 0.96 · 10−2 9.82 0.96 · 10−2 14.96 1.01 · 10−2 16.4 Lungs 3564.2 5.59 · 10−2 −24.3 5.09 · 10−2 −16.89 5.18 · 10−2 −15.9 Bones 1465.7 5.01 · 10−2 12.4 2.90 · 10−2 6.86 2.29 · 10−2 8.0 Heart 404.8 3.63 · 10−2 2.43 3.05 · 10−2 7.56 3.01 · 10−2 9.0 Spinal cord 41.3 2.35 · 10−2 2.42 · 10−2 2.48 · 10−2 Aorta 141.9 4.53 · 10−2 3.92 · 10−2 3.90 · 10−2 Muscle 3449 1.89 · 10−2 −16.5 1.76 · 10−2 −7.07 1.78 · 10−2 −4.5 Table 3. Results of SAF (kg−1) for the ORNL phantom for 133Xe, 99mTc and 81mKr. Organs/tissue Volumes of organs (cm3) 133Xe 99mTc 81mKr Skin 371 8.72 · 10−3 8.39 · 10−3 8.66 · 10−3 Lungs 2200 7.38 · 10−2 6.12 · 10−2 6.16 · 10−2 Esophagus 25.6 2.62 · 10−2 2.17 · 10−2 2.11 · 10−2 Clavicles 41.6 1.93 · 10−2 1.04 · 10−2 8.18 · 10−3 Scapulae 154 4.48 · 10−2 2.26 · 10−2 1.79 · 10−2 Rib cage 401.8 5.73 · 10−2 2.68 · 10−2 2.09 · 10−2 Spine 325 5.65 · 10−2 3.15 · 10−2 2.49 · 10−2 Thymus 27.3 1.89 · 10−2 1.53 · 10−2 1.47 · 10−2 Heart 230.8 3.54 · 10−2 2.84 · 10−2 2.76 · 10−2 Trunk 8380 2.26 · 10−2 1.89 · 10−2 1.86 · 10−2 Breasts 347 1.39 · 10−2 1.21 · 10−2 1.21 · 10−2 Organs/tissue Volumes of organs (cm3) 133Xe 99mTc 81mKr Skin 371 8.72 · 10−3 8.39 · 10−3 8.66 · 10−3 Lungs 2200 7.38 · 10−2 6.12 · 10−2 6.16 · 10−2 Esophagus 25.6 2.62 · 10−2 2.17 · 10−2 2.11 · 10−2 Clavicles 41.6 1.93 · 10−2 1.04 · 10−2 8.18 · 10−3 Scapulae 154 4.48 · 10−2 2.26 · 10−2 1.79 · 10−2 Rib cage 401.8 5.73 · 10−2 2.68 · 10−2 2.09 · 10−2 Spine 325 5.65 · 10−2 3.15 · 10−2 2.49 · 10−2 Thymus 27.3 1.89 · 10−2 1.53 · 10−2 1.47 · 10−2 Heart 230.8 3.54 · 10−2 2.84 · 10−2 2.76 · 10−2 Trunk 8380 2.26 · 10−2 1.89 · 10−2 1.86 · 10−2 Breasts 347 1.39 · 10−2 1.21 · 10−2 1.21 · 10−2 SAF values for lungs using the voxel thorax model, shown in Table 3, are 5.59 · 10−2, 5.09 · 10−2 and 5.18·10−2 kg−1 for 133Xe, 99 mTc and 81 mKr, respectively. Discrepancy between SAFs values for the same considered organs, obtained using ORNL and voxel thorax models, are in the range from 2.43 to 24.3%. The values given in Table 2 are the differences in respect to the ORNL phantom. Comparison results of SAF with literature data A comparison with literature data for SAFS obtained with MCNPX software is shown in Table 4. Table 4. Comparison of SAF (kg−1) obtained in this work with literature data. Lungs ← Lungs SAF (kg−1) Energy (MeV) Hadid et al.(19) Patni et al.(21) Villoing et al.(24) This work ORNL Voxel 0.05 1.26 · 10−1 1.04 · 10−1 1.38 · 10−1 1.45 · 10−1 9.15 · 10−2 0.08 7.73 · 10−2 7.76 · 10−2 5.62 · 10−2 0.081 7.38 · 10−2 5.59 · 10−2 0.1 7.13 · 10−2 5.95 · 10−2 7.80 · 10−2 6.78 · 10−2 5.19 · 10−2 0.141 6.12 · 10−2 5.09 · 10−2 1.190 6.16 · 10−2 5.18 · 10−2 0.2 5.78 · 10−2 6.33 · 10−2 5.20 · 10−2 Lungs ← Lungs SAF (kg−1) Energy (MeV) Hadid et al.(19) Patni et al.(21) Villoing et al.(24) This work ORNL Voxel 0.05 1.26 · 10−1 1.04 · 10−1 1.38 · 10−1 1.45 · 10−1 9.15 · 10−2 0.08 7.73 · 10−2 7.76 · 10−2 5.62 · 10−2 0.081 7.38 · 10−2 5.59 · 10−2 0.1 7.13 · 10−2 5.95 · 10−2 7.80 · 10−2 6.78 · 10−2 5.19 · 10−2 0.141 6.12 · 10−2 5.09 · 10−2 1.190 6.16 · 10−2 5.18 · 10−2 0.2 5.78 · 10−2 6.33 · 10−2 5.20 · 10−2 In the article by Hadid et al.(19) Adult Male Reference Computational Phantom (RCP-AM) and Adult Female Reference Computational Phantom (RCP-AF) were applied, and electrons and photons with energies from 10 keV up to 10 MeV were considered. The following organs were considered: lungs, thyroid and the liver. Results obtained for RCP-AM and RCP-AF phantoms were given in Annex A. In order to compare with the presented work, the lungs were treated as the source and as a target for energies 0.08, 0.1 and 0.3 MeV. The obtained values are 7.78·10−2 and 7.13·10−2 kg−1 for 0.08 and 0.1 MeV, respectively, while in the presented work we got 7.38·10−2 kg−1 for 0.081 MeV (131Xe) which is a good agreement. SAF in lungs, as the source organ, were taken from a article by Patni et al.(21) where the ICRP reference voxel thorax model were used: SAFs were 5.95·10−2 kg−1 for monoenergetic gamma radiation of 100 keV and 5.78·10−2 for 200 keV. In the presented work calculations were done for 81 keV (133Xe) and 190 keV (for 81mKr). Since the energies are relatively close, for the calculated SAF of 5.59·10−2 kg−1 for Xe, and 5.18·10−2 kg−1 for Kr are in good agreement with the results of the cited paper. In this work, computer software FLUKA was applied which is also based on the Monte Carlo method. In the article by Villoing et al.(24) computer programs GATE and MCNPX were applied to calculate dosimetry quantities (AF, SAF and S-values) for monoenergetic photons and electrons, as well as for fluorine-18, lutetium-117, iodine-131 and yttrium-90. Comparable results were again obtained for lungs as a source and as a target, with 7.80·10−2 kg−1 for 0.1 MeV. In order to estimate the interpolation error, and to make comparison with other authors feasible, additional computations were performed for discrete energies of 0.05, 0.08, 0.1 and 0.2 MeV. Data about SAF are presented in Table 4. Interpolation errors for Xe and Kr were between 3 and 5% for both phantoms. Certain discrepancies between authors originated from the application of different software and considered phantoms. The differences between computed SAF values using the voxel thorax model and those obtained from the ORNL model, are due to the more realistic shape, size and positioning of organs characterizing the voxel thorax model. The results of the absorbed dose per source particle obtained for the two models, are presented in Figure 4. In both cases the doses increase with energy of gamma radiation. Figure 4. View largeDownload slide Results of absorbed dose (fGy per photon) for ORNL and voxel thorax models for 81 keV (133Xe), 141 keV (99mTc) and 190 keV (81mKr). Figure 4. View largeDownload slide Results of absorbed dose (fGy per photon) for ORNL and voxel thorax models for 81 keV (133Xe), 141 keV (99mTc) and 190 keV (81mKr). In Figure 5 the SAF are presented normalized to the SAF in the lungs allowing a more direct comparison between the two models: as a matter of fact, employing the same calculation methodology, differences can only derive from the ‘geometrical’ difference between the voxel thorax model and the analytical model. The value for bone for the ORNL phantom was obtained by weighting according to mass for separate parts of bones. As can be seen the curves trend are well preserved for 99mTc and 81mKr and, in a minor way, for 133Xe but ratios are, as expected, different. They are generally higher for the voxel thorax model and this is due, mainly, to the relative reciprocal distances within organs, as a matter of fact for technical construction reasons, as in the MIRD type phantom(37) there is a larger absorption due to the soft ‘soft tissue’ separating the investigated organs. This effect is particularly evident for 133Xe that emits lower energy photons. Figure 5. View largeDownload slide Results of organ SAF (kg−1) divided by lungs SAF (kg−1) value for 133Xe, 99mTc and 81mKr. Figure 5. View largeDownload slide Results of organ SAF (kg−1) divided by lungs SAF (kg−1) value for 133Xe, 99mTc and 81mKr. CONCLUSIONS In the present study CT scans were used to create a voxel thorax model of a thorax to be employed in calculating SAFs in different organs/tissue, when 81mKr, 99mTc and 133Xe, were incorporated into the lungs during scintigraphy examinations. The work is intended as a preliminary study and the three radionuclides were used to test the phantom. For this reason a benchmark with other numerical models is presented. Discrepancy between SAFs obtained using the voxel thorax model and ORNL mathematical phantom is presented in Tables 2 and 3. This difference is due to the fact that the voxel thorax model is a representation of a real human person which is surely different than the ORNL phantom. The differences are from 2.43 to 24.3%. It should be pointed out that a mathematical model is an average representation of a large population of individuals, while a voxel model represents a specific person and not a whole population(1, 2). Inherent limitations in CT imaging, as spatial resolution, motion artefacts, could also contribute to the differences. However comparisons with the new ICRP reference model are satisfactory. The presented data could be used in the future for dose calculation and radiation protection purposes in nuclear medicine. Further developments will be done in the near future aimed at increasing the number of organs and tissues contained in the voxel model and the available SAF. ACKNOWLEDGMENTS The author (Z.J.) would like to thank EURADOS (M. Zankl for organizing the voxel school), Christelle Huet and David Broggio for kindly providing the data sets. FUNDING The present work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia, under the Projects nos. 171021 and 43011. REFERENCES 1 Wang, H., Maurea, S., Mainolfi, C., Fiore, F., Gravina, A., Panico, M. R., Bazzicalupo, L. and Salvatore, M. Tc-99m MIBI scintigraphy in patients with lung cancer. Comparison with CT and fluorine-18 FDG PET imaging. Clin. Nucl. Med. 22, 243– 249 ( 1997). Google Scholar CrossRef Search ADS PubMed 2 Yoriyaz, H., Stabin, G. M. and Santos, A. Monte Carlo MCNP-4B–based absorbed dose distribution estimates for patient-specific dosimetry. J. Nucl. Med. 42, 662– 669 ( 2001). Google Scholar PubMed 3 International Commission on Radiological Protection (ICRP). Radiation dose to patients from radiopharmaceuticals (Addendum 3 to ICRP Publication 53). ICRP Publication 106. Ann. ICRP 38 (1–2) Elsevier ( 2008) 4 Uhrhan, K., Drzezga, A. and Sudbrock, F. The patients as a radioactive source: an intercomparison of survey meters for measurements in nuclear medicine. Radiat. Prot. Dosim. 162, 101– 104 ( 2014). Google Scholar CrossRef Search ADS 5 United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). Sources and effects of ionizing radiation. Report to the General Assembly with Scientific Annexes. Volume I; United Nations, New York ( 2008). 6 Ponto, J. A. Radiopharmaceutical considerations for using Tc-99m MAA in lung transplant patients. J. Am. Pharm. Assoc. 50, 419– 423 ( 2010). Google Scholar CrossRef Search ADS 7 Gardumi, A., Farah, J. and Desbre´e, A. Creation of ORNL NURBS-based phantoms: evaluation of the voxel effect on absorbed doses from radiopharmaceuticals. Radiat. Prot. Dosim. 153, 273– 281 ( 2013). Google Scholar CrossRef Search ADS 8 Ciofetta, G., Piepsz, A., Roca, I., Fisher, S., Hahn, K., Sixt, R., Biassoni, L., De Palma, D. and Zucchetta, P. Guidelines for lung scintigraphy in children. Eur. J. Nucl. Med. Mol. Imaging 34, 1518– 1526 ( 2007). Google Scholar CrossRef Search ADS PubMed 9 Lin, J., Qiu, L., Cheng, W., Luo, S., Xue, L. and Zhang, S. Development of superior bone scintigraphic agent from a series of 99mTc-labeled zoledronic acid derivatives. Appl. Radiat. Isot. 70, 848– 855 ( 2012). Google Scholar CrossRef Search ADS PubMed 10 Parker, A. J., Coleman, R. E., Grady, E., Royal, D. H., Siegel, A. B., Stabin, G. M., Sostman, H. D. and Hilson, J. W. A. SNM practice guideline for lung scintigraphy 4.0. J. Nucl. Med. Technol. 40, 57– 65 ( 2012). Google Scholar CrossRef Search ADS PubMed 11 Lobov, A. S., King, W. D., Knox, J. K., Senden, J. T. and Stephens, W. R. Cationised radiolabelled nanoparticles for perfusion imaging of the lungs. Biomaterials 34, 1732– 1738 ( 2013). Google Scholar CrossRef Search ADS PubMed 12 International Commission on Radiological Protection (ICRP). Radiation dose to patients from radiopharmaceuticals: a compendium of current information related to frequently used substances. ICRP Publication 128. Ann. ICRP 44 (2S) ( 2015). 13 Bajc, M., Neilly, J. B., Miniati, M., Schuemichen, C., Meignan, M. and Jonson, B. EANM guidelines for ventilation/perfusion scintigraphy, Part 1. Pulmonary imaging with ventilation/perfusion single photon emission tomography. Eur. J. Nucl. Med. Mol. Imaging 36, 1356– 1370 ( 2009). Google Scholar CrossRef Search ADS PubMed 14 International Commission on Radiological Protection (ICRP). Adult reference computational phantoms. Realistic reference phantoms: an ICRP/ICRU joint effort. ICRP Publication 110. Ann. ICRP 39 (3–5) Elsevier ( 2009). 15 International Commission on Radiological Protection (ICRP). Occupational intakes of radionuclides: Part 1. ICRP Publication 130. Ann. ICRP 44(2) Elsevier ( 2015). 16 International Commission on Radiological Protection (ICRP). The ICRP computational framework for internal dose assessment for reference adults: specific absorbed fractions. ICRP Publication 133. Ann. ICRP 45(2) ( 2016). 17 Stabin, M. G. MIRDOSE: personal computer software for internal dose assessment in nuclear medicine. J. Nucl. Med. 37, 538– 546 ( 1996). Google Scholar PubMed 18 Stabin, M. G., Sparks, R. B. and Crowe, E. OLINDA/EXM: the second-generation personal computer software for internal dose assessment in nuclear medicine. J. Nucl. Med. 46, 1023– 1027 ( 2005). Google Scholar PubMed 19 Hadid, L., Desbr´ee, A., Schlattl, H., Franck, D., Blanchardon, E. and Zankl, M. Application of the ICRP/ICRU reference computational phantoms to internal dosimetry: calculation of specific absorbed fractions of energy for photons and electrons. Phys. Med. Biol. 55, 3631– 3641 ( 2010). Google Scholar CrossRef Search ADS PubMed 20 Lamart, S., Bouville, A., Simon, L. S., Eckerman, F. K., Melo, D. and Lee, C. Comparison of internal dosimetry factors for three classes of adult computational phantoms with emphasis on I-131 in the thyroid. Phys. Med. Biol. 56( 22), 7317– 7335 ( 2011). Google Scholar CrossRef Search ADS PubMed 21 Patni, H. K., Akar, D. K., Nadar, M. Y., Ghare, V. P., Rao, D. D. and Sarkar, P. K. Estimation of Specific Absorbed Fractions for selected organs due to photons emitted by activity deposited in the human respiratory tract using ICRP/ICRU male voxel phantom in FLUKA. Radiat. Prot. Dosim. 153, 32– 46 ( 2013). Google Scholar CrossRef Search ADS 22 Díaz-Londoño, G., García-Pareja, S., Salvat, F. and Lallena, A. M. Monte Carlo calculation of specific absorbed fractions: variance reduction techniques. Phys. Med. Biol. 60, 2625– 2644 ( 2015). Google Scholar CrossRef Search ADS PubMed 23 Lamart, S., Simon, L. S., Bouville, A., Moroz, E. B. and Lee, C. S values for 131I based on the ICRP adult voxel phantoms. Radiat. Prot. Dosim. 168( 1), 92– 110 ( 2016). Google Scholar CrossRef Search ADS 24 Villoing, D., Marcatili, S., Garcia, M.-P. and Bardiès, M. Internal dosimetry with the Monte Carlo code GATE: validation using the ICRP/ICRU female reference computational model. Phys. Med. Biol. 62, 1885– 1904 ( 2017). Google Scholar CrossRef Search ADS PubMed 25 Kramer, R., Vieira, J. W., Khoury, H. J., Lima, F. R. A. and Fnelle, D. All about MAX: a male adult voxel phantom for Monte Carlo calculations in radiation protection dosimetry. Phys. Med. Biol. 48, 1239– 1262 ( 2003). Google Scholar CrossRef Search ADS PubMed 26 Caon, M. Voxel-based computational models of real human anatomy: a review. Radiat. Environ. Biophys. 42, 229– 235 ( 2004). Google Scholar CrossRef Search ADS PubMed 27 Lee, C., Lodwick, D., Hurtado, J., Pafundi, D., Jonathan, L., Williams, J. L. and Bolch, E. W. The UF family of reference hybrid phantoms for computational radiation dosimetry. Phys. Med. Biol. 55( 2), 339– 363 ( 2010). Google Scholar CrossRef Search ADS PubMed 28 Hurtado, L. J., Lee, C., Lodwick, D., Goede, T., Williams, J. L. and Bolch, E. W. Hybrid computational phantoms representing the reference adult male and adult female: construction and applications for retrospective dosimetry. Health Phys. 102, 292– 304 ( 2012). Google Scholar CrossRef Search ADS PubMed 29 ImageJ (https://imagej.nih.gov/ij/) 30 Burger, W. and Burge, M. J. Digital Image Processing: An Algorithmic Introduction Using Java. Springer-Verlag London ( 2016). 31 AEGIS04-KG Cluster Information. http://www.aegis.rs/infrastructure/ 32 European Grid Initiative-EGI. http://www.egi.eu/ 33 MCNP—a general Monte Carlo N-Particle Transport Code (X-5 Monte Carlo Team, Version 5). Vol. I: Overview and Theory. Los Alamos, NM: Los Alamos National Laboratory; LA- UR-03–1987 ( 2003). 34 International Commission on Radiological Protection (ICRP). Basic anatomical and physiological data for use in radiological protection reference values. ICRP Publication 89. Ann. ICRP 32 (3–4) Elsevier ( 2002). 35 Eckerman, K. F., Cristy, M. and Ryman, J. C. The ORNL mathematical phantom series. Oak Ridge National Laboratory Report. Oak Ridge, TN, USA ( 1996). 36 Krstic, D. and Nikezic, D. Input files with ORNL—mathematical phantoms of the human body for MCNP-4B. Comput. Phys. Commun. 176, 33– 37 ( 2007). Google Scholar CrossRef Search ADS 37 Ferrari, P. and Gualdrini, G. MCNPX internal dosimetry studies based on the NORMAN-05 voxel model. Radiat. Prot. Dosim. 127( 1–4), 209– 213 ( 2007). Google Scholar CrossRef Search ADS © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: firstname.lastname@example.org
Radiation Protection Dosimetry – Oxford University Press
Published: Mar 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera