Literature DB >> 7732068

Validation of a dose-point kernel convolution technique for internal dosimetry.

H B Giap1, D J Macey, J E Bayouth, A L Boyer.   

Abstract

The objective of this study was to validate a dose-point kernel convolution technique that provides a three-dimensional (3D) distribution of absorbed dose from a 3D distribution of the radionuclide 131I. A dose-point kernel for the penetrating radiations was calculated by a Monte Carlo simulation and cast in a 3D rectangular matrix. This matrix was convolved with the 3D activity map furnished by quantitative single-photon-emission computed tomography (SPECT) to provide a 3D distribution of absorbed dose. The convolution calculation was performed using a 3D fast Fourier transform (FFT) technique, which takes less than 40 s for a 128 x 128 x 16 matrix on an Intel 486 DX2 (66 MHz) personal computer. The calculated photon absorbed dose was compared with values measured by thermoluminescent dosimeters (TLDS) inserted along the diameter of a 22 cm diameter annular source of 131I. The mean and standard deviation of the percentage difference between the measurements and the calculations were equal to -1% and 3.6%, respectively. This convolution method was also used to calculate the 3D dose distribution in an Alderson abdominal phantom containing a liver, a spleen, and a spherical tumour volume loaded with various concentrations of 131I. By averaging the dose calculated throughout the liver, spleen, and tumour the dose-point kernel approach was compared with values derived using the MIRD formalism, and found to agree to better than 15%.

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Year:  1995        PMID: 7732068     DOI: 10.1088/0031-9155/40/3/003

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  8 in total

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Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-09-23       Impact factor: 7.038

2.  Improved tumour response prediction with equivalent uniform dose in pre-clinical study using direct intratumoural infusion of liposome-encapsulated ¹⁸⁶Re radionuclides.

Authors:  Brian A Hrycushko; Steve Ware; Shihong Li; Ande Bao
Journal:  Phys Med Biol       Date:  2011-08-12       Impact factor: 3.609

3.  Impact of PET and MRI threshold-based tumor volume segmentation on patient-specific targeted radionuclide therapy dosimetry using CLR1404.

Authors:  Abigail E Besemer; Benjamin Titz; Joseph J Grudzinski; Jamey P Weichert; John S Kuo; H Ian Robins; Lance T Hall; Bryan P Bednarz
Journal:  Phys Med Biol       Date:  2017-07-06       Impact factor: 3.609

4.  Direct intratumoral infusion of liposome encapsulated rhenium radionuclides for cancer therapy: effects of nonuniform intratumoral dose distribution.

Authors:  Brian A Hrycushko; Shihong Li; Beth Goins; Randal A Otto; Ande Bao
Journal:  Med Phys       Date:  2011-03       Impact factor: 4.071

5.  Pre- and post-treatment image-based dosimetry in90Y-microsphere radioembolization using the TOPAS Monte Carlo toolkit.

Authors:  Alejandro Bertolet; Eric Wehrenberg-Klee; Mislav Bobić; Clemens Grassberger; Joseph Perl; Harald Paganetti; Jan Schuemann
Journal:  Phys Med Biol       Date:  2021-12-29       Impact factor: 3.609

6.  Deep-dose: a voxel dose estimation method using deep convolutional neural network for personalized internal dosimetry.

Authors:  Min Sun Lee; Donghwi Hwang; Joong Hyun Kim; Jae Sung Lee
Journal:  Sci Rep       Date:  2019-07-16       Impact factor: 4.379

7.  BIGDOSE: software for 3D personalized targeted radionuclide therapy dosimetry.

Authors:  Tiantian Li; Licheng Zhu; Zhonglin Lu; Na Song; Ko-Han Lin; Greta S P Mok
Journal:  Quant Imaging Med Surg       Date:  2020-01

8.  Whole-body voxel-based internal dosimetry using deep learning.

Authors:  Azadeh Akhavanallaf; Iscaac Shiri; Hossein Arabi; Habib Zaidi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-09-01       Impact factor: 9.236

  8 in total

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