Purpose: To apply a series of Whole‐Body Phantoms Representing An Average Adult Male and Female Using Surface‐Geometry Methods to the study of external radiation dosimetry. Method and Materials: Boundary reprentation was used to deform the original organs automatically into two sets of standard RPI Adult Male/Female phantoms with volume/mass matched with those of the ICRP. To finally define the phantom geometries in Monte Carlo codes for dose calculations, we developed a software to convert the finished surface phantoms into the voxel phantoms at any desired voxel size. The voxelization used the parity count method together with the method of ray stabbing on polygon surface. The corresponding Monte Carlo input file was derived automatically by our program “Phantom Processor”. Average absorbed doses to organs were obtained by MCNPX. Results: The volume/mass data of the standard RPI Adult Male/Female phantoms match with those of the ICRP. After mesh voxelization, the volume/mass data of the voxel phantoms have the relative error less than 0.5%. The voxel resolutions of the Male/Female are 3.2 mm and 3.0 mm respectively. The average absorbed doses of internal organs were calculated using the 6 external neutron irradiation geometries. All results were normalized by the unit source fluence in accordance with the standard usage in radiation protection dosimetry for reporting fluence to absorbed dose conversion coefficients. Typically, 107 histories were simulated and the uncertainties were better than about 1% for most of the target organs. Conclusion: A series of RPI Adult Male/Female phantoms have been developed. Using our software we have developed additional registration and deformation algorithms that allow a mesh‐based phantom to “morph” into a different individual. This series of phantoms were voxelized and implanted into MCNPX. The results suggest that Monte Carlo calculations can be performed for various internal and external exposures to ionizing radiation.
Purpose: Whole‐body patient models of various sizes and postures are needed for the assessment of organ doses in CT imaging, internal nuclear medicine and external‐beam radiation treatment procedures. This paper discusses a deformable mesh‐based modeling method to create patient‐specific phantoms that are morphed by changing to 5th‐ to 95th‐percentiles of body height and weight, as well as internal organ volume and masse. Method and Materials: The mesh‐based reference adult male and female phantoms were deformed by mainly two different percentile data: 1) the whole‐body size percentile data which were defined by the anthropometric parameters such as height and weight from the National Health and Nutrition Examination Survey (NHANES). 2) individual internal organ percentile data which were derived by the cumulative pattern analysis based on the International Commission on Radiological Protection (ICRP) 23 and 89 references. These mesh‐based percentile phantoms were converted into the voxel‐based phantoms. The final step is to link the voxel phantom with correct tissue density and elemental composition, so that radiation transport through the human‐body phantom was modeled correctly in a Monte Carlo code. Results: The whole‐body size percentile models have been created by the NHANES anthropometric data and the details of organ percentiles derived from ICRP references. The deformability of the RPI reference adult phantoms has been shown through the demonstration of percentiles‐ and postures‐specific adult models. Conclusion: A next generation deformable patient modeling method has been demonstrated. With the mesh deformation algorithms, the individual organs are able to be deformed to match the volumes and masses with desired organ percentiles. The flexible modeling allows patients to be represented in various sizes and postures for the purpose of Monte Carlo dose calculations. This study also identified the need for further research to develop method to run Monte Carlo calculations in mesh geometry directly.
Purpose: Whole‐body patient models are needed for the assessment of organ doses in various CT imaging and external‐beam radiation treatment procedures. The Boundary REPresentation (BPRE) type of geometry offers greater control over the anatomical shapes and tissue/organ surfaces could be flexibly deformed. Currently tedious and time‐consuming manual adjustment is necessary. This paper discusses an automatic modeling method recently developed to create two adjustable adult male and female mesh models with dynamically deformable organs. Method and Materials: The algorithm for the development of the deformable RPI Adult Male/Female phantoms was implemented by MATLAB® 7.4. The anatomical mesh models were based the Anatomium™ 3D models whose organ geometries were morphed to agree within 0.5% with the ICRP reference male and female organ volume/mass data. These mesh morphing algorithms were used to automatically pre‐modify the dataset to have unique mesh information in each of organ boundaries and deform the whole meshes based on the ICRP volume/mass reference without unwanted surface overlapping through the special mesh overlap avoiding process. After the deformations, the RPI Adult Male/Female mesh models were transformed to the solid geometries through the voxelization process with 3.2 mm and 3.0 mm, respectively. Results: These phantoms have been used by transforming the solid geometries into the voxel domain that is compatible with well‐validated Monte Carlo radiation transport simulations such as MCNP, EGSnrc and GEANT4codes. Through these mesh deformation algorithms, complicated bone (cavity, spongiosa, and cortical bones) and muscle structures have been described in the RPI Adult Male/Female mesh models. Conclusion: This study has demonstrated the feasibility to create deformable RPI Adult Male/Female phantoms. These phantoms will be applied to various applications of including person specific adjustments depended on age, weight, and height changes.
Purpose: To demonstrate the feasibility of deformable patient modeling for the virtual calibration of detectors used to measure inhaled radioactivity in a female patient's lungs for internal dose assessment. Materials and Methods: We have developed the ability to deform a mesh‐based phantom that consists of 140 highly detailed organs or tissues. The phantom can be adjusted to match a desired patient. A software was developed to deform the breasts of this phantom to create new models representing female patients with different breast cup sizes (ranging from AA to G) and breast glandularities. The geometries of these phantoms and a Phoswhich detector system were defined in a Monte Carlo code for virtual in‐vivo lung counting simulations involving various photon emitting radionuclides. The counting efficiencies for each of the virtual patients were calculated and compared. Results: The counting efficiency was found to decrease with increasing breast size and mass because of greater attenuation in the patient. For low energy emitting radionuclides such as Am‐241, roughly a 50% drop in counting efficiency was observed for the model with G cup size as compared to the smaller breasted AA model. Higher breast glandularities resulted in lower counting efficiencies; however, this effect was small. For the E breast cup size model, the counting efficiency for low energy emitters decreased by roughly 2% as the glandularity increased from 7% to 40%. Conclusions: In order to obtain accurate internal dosimetry estimates for female patients, the in‐vivo measurements of the activity in the lungs should account for breast size. The effect of breast glandularity can be ignored because it is negligibly small compared to other sources of experimental uncertainty.
Purpose: To apply an anatomically detailed motion‐simulating virtual patient model to the study of external beam treatment planning. Method and Materials: Breathing induced organ motion modeling may be classified broadly into (a) geometry‐based and (b) physics‐based methods. We have been developing a 4D motion‐simulating chest model from a 3D tomographic model of the Visible Human images by varying the shape, size and location of the organs. Anatomical features where from the VIP‐Man model that contains 80 segmented organs and tissues. The Non‐Uniform Rational B‐Splines (NURBS) surfaces of the organs were reconstructed to deform the organs by changing the control points. Clinically measured motion patterns were used to guide the deformation and motion. Four‐field conformal photon beams were simulated for the treatment of a lung tumor case. The energy of the beam was assumed to be 6 MeV and the 4‐field irradiation geometry was assumed to be AP, PA, RLAT, and LLAT. The lesion was simulated in the left lung and the PTV is designed as a sphere of 5‐mm radius. The motion‐simulating model is implemented into the EGSnrc code to calculate the absorbed doses using various non‐registration registration methods. Results: The results showed that the dose to tumor could be up to 40% differences from phase to phase. DVH for this calculation showed less homogeneity for the whole breathing cycle. However, if the beam was gated to one phase, the result showed better homogeneity for target. Conclusion: A 4D chest motion‐simulating model has been developed using the segmented Visible Human images. This study summarized procedures to develop a 4D motion‐simulating chest model and demonstrated the usefulness of the model for Monte Carlo calculations. Possible ways to improve the motion simulation using physics‐based tissue properties available from surgical simulation community are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.