Journal article
The Impact of Tissue Type and Density on Dose Point Kernels for Patient-Specific Voxel-Wise Dosimetry: A Monte Carlo Investigation
Radiation research, Vol.193(6), pp.531-542
06/01/2020
DOI: 10.1667/RR15563.1
PMID: 32315249
Abstract
We report the generation of dose point kernels for clinically-relevant radionuclide beta decays and monoenergetic electrons in various tissues to understand the impact of tissue type on dose point kernels. Currently available voxelwise dosimetry approaches using dose point kernels ignore tissue composition and density heterogeneities. Therefore, the study on the impact of tissue type on dose point kernels is warranted. Simulations were performed using the GATE Monte Carlo toolkit, which encapsulates GEANT4 libraries. Dose point kernels were simulated in phantoms of water, compact bone, lung, adipose tissue, blood and red marrow for radionuclides Y-90, Re-188,Sr-89, P-32 ,Re-186, Sm-153 and Lu-177 and monoenergetic electrons (0.015-10 MeV). All simulations were performed by assuming an isotropic point source of electrons at the center of a homogeneous spherical phantom. Tissue-specific differences between kernels were investigated by normalizing kernels for effective pathlength. Transport of 20 million particles was found to provide sufficient statistical precision in all simulated kernels. The simulated dose point kernels demonstrate excellent agreement with other Monte Carlo packages. Deviation from kernels reported in the literature did not exceed a 10% global difference, which is consistent with the variability among published results. There are no significant differences between the dose point kernel in water and kernels in other tissues that have been scaled to account for density; however, tissue density predictably demonstrated itself to be a significant variable in dose point kernel distribution. (C) 2020 by Radiation Research Society
Details
- Title: Subtitle
- The Impact of Tissue Type and Density on Dose Point Kernels for Patient-Specific Voxel-Wise Dosimetry: A Monte Carlo Investigation
- Creators
- Ashok Tiwari - University of IowaStephen A. Graves - University of IowaJohn Sunderland - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Radiation research, Vol.193(6), pp.531-542
- Publisher
- Radiation Research Soc
- DOI
- 10.1667/RR15563.1
- PMID
- 32315249
- ISSN
- 0033-7587
- eISSN
- 1938-5404
- Number of pages
- 12
- Language
- English
- Date published
- 06/01/2020
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Physics and Astronomy; Radiation Oncology
- Record Identifier
- 9984313859402771
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