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Title: MO-F-CAMPUS-I-02: Accuracy in Converting the Average Breast Dose Into the Mean Glandular Dose (MGD) Using the F-Factor in Cone Beam Breast CT- a Monte Carlo Study Using Homogeneous and Quasi-Homogeneous Phantoms

Abstract

Purpose: To investigate the accuracy in estimating the mean glandular dose (MGD) for homogeneous breast phantoms by converting from the average breast dose using the F-factor in cone beam breast CT. Methods: EGSnrc-based Monte Carlo codes were used to estimate the MGDs. 13-cm in diameter, 10-cm high hemi-ellipsoids were used to simulate pendant-geometry breasts. Two different types of hemi-ellipsoidal models were employed: voxels in quasi-homogeneous phantoms were designed as either adipose or glandular tissue while voxels in homogeneous phantoms were designed as the mixture of adipose and glandular tissues. Breast compositions of 25% and 50% volume glandular fractions (VGFs), defined as the ratio of glandular tissue voxels to entire breast voxels in the quasi-homogeneous phantoms, were studied. These VGFs were converted into glandular fractions by weight and used to construct the corresponding homogeneous phantoms. 80 kVp x-rays with a mean energy of 47 keV was used in the simulation. A total of 109 photons were used to image the phantoms and the energies deposited in the phantom voxels were tallied. Breast doses in homogeneous phantoms were averaged over all voxels and then used to calculate the MGDs using the F-factors evaluated at the mean energy of the x-rays. The MGDsmore » for quasi-homogeneous phantoms were computed directly by averaging the doses over all glandular tissue voxels. The MGDs estimated for the two types of phantoms were normalized to the free-in-air dose at the iso-center and compared. Results: The normalized MGDs were 0.756 and 0.732 mGy/mGy for the 25% and 50% VGF homogeneous breasts and 0.761 and 0.733 mGy/mGy for the corresponding quasi-homogeneous breasts, respectively. The MGDs estimated for the two types of phantoms were similar within 1% in this study. Conclusion: MGDs for homogeneous breast models may be adequately estimated by converting from the average breast dose using the F-factor.« less

Authors:
; ; ;  [1]
  1. UT MD Anderson Cancer Center, Houston, TX (United States)
Publication Date:
OSTI Identifier:
22562939
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; ANIMAL TISSUES; COMPUTERIZED TOMOGRAPHY; MAMMARY GLANDS; MONTE CARLO METHOD; PHANTOMS; RADIATION DOSES

Citation Formats

Lai, C, Zhong, Y, Wang, T, and Shaw, C. MO-F-CAMPUS-I-02: Accuracy in Converting the Average Breast Dose Into the Mean Glandular Dose (MGD) Using the F-Factor in Cone Beam Breast CT- a Monte Carlo Study Using Homogeneous and Quasi-Homogeneous Phantoms. United States: N. p., 2015. Web. doi:10.1118/1.4925453.
Lai, C, Zhong, Y, Wang, T, & Shaw, C. MO-F-CAMPUS-I-02: Accuracy in Converting the Average Breast Dose Into the Mean Glandular Dose (MGD) Using the F-Factor in Cone Beam Breast CT- a Monte Carlo Study Using Homogeneous and Quasi-Homogeneous Phantoms. United States. doi:10.1118/1.4925453.
Lai, C, Zhong, Y, Wang, T, and Shaw, C. Mon . "MO-F-CAMPUS-I-02: Accuracy in Converting the Average Breast Dose Into the Mean Glandular Dose (MGD) Using the F-Factor in Cone Beam Breast CT- a Monte Carlo Study Using Homogeneous and Quasi-Homogeneous Phantoms". United States. doi:10.1118/1.4925453.
@article{osti_22562939,
title = {MO-F-CAMPUS-I-02: Accuracy in Converting the Average Breast Dose Into the Mean Glandular Dose (MGD) Using the F-Factor in Cone Beam Breast CT- a Monte Carlo Study Using Homogeneous and Quasi-Homogeneous Phantoms},
author = {Lai, C and Zhong, Y and Wang, T and Shaw, C},
abstractNote = {Purpose: To investigate the accuracy in estimating the mean glandular dose (MGD) for homogeneous breast phantoms by converting from the average breast dose using the F-factor in cone beam breast CT. Methods: EGSnrc-based Monte Carlo codes were used to estimate the MGDs. 13-cm in diameter, 10-cm high hemi-ellipsoids were used to simulate pendant-geometry breasts. Two different types of hemi-ellipsoidal models were employed: voxels in quasi-homogeneous phantoms were designed as either adipose or glandular tissue while voxels in homogeneous phantoms were designed as the mixture of adipose and glandular tissues. Breast compositions of 25% and 50% volume glandular fractions (VGFs), defined as the ratio of glandular tissue voxels to entire breast voxels in the quasi-homogeneous phantoms, were studied. These VGFs were converted into glandular fractions by weight and used to construct the corresponding homogeneous phantoms. 80 kVp x-rays with a mean energy of 47 keV was used in the simulation. A total of 109 photons were used to image the phantoms and the energies deposited in the phantom voxels were tallied. Breast doses in homogeneous phantoms were averaged over all voxels and then used to calculate the MGDs using the F-factors evaluated at the mean energy of the x-rays. The MGDs for quasi-homogeneous phantoms were computed directly by averaging the doses over all glandular tissue voxels. The MGDs estimated for the two types of phantoms were normalized to the free-in-air dose at the iso-center and compared. Results: The normalized MGDs were 0.756 and 0.732 mGy/mGy for the 25% and 50% VGF homogeneous breasts and 0.761 and 0.733 mGy/mGy for the corresponding quasi-homogeneous breasts, respectively. The MGDs estimated for the two types of phantoms were similar within 1% in this study. Conclusion: MGDs for homogeneous breast models may be adequately estimated by converting from the average breast dose using the F-factor.},
doi = {10.1118/1.4925453},
journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 42,
place = {United States},
year = {2015},
month = {6}
}