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Laboratory designs and validations of a glandularity-adjustable dual-purpose breast tissue phantom
Author(s): Di Wu; Yong Chen; Farid Omoumi; Yuran Guo; Yuhua Li; Bin Zheng; Hong Liu
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Paper Abstract

The objectives of this study were to develop and evaluate a breast tissue equivalent phantom that can be used for dual purposes, conventional x-ray imaging and ultrasonography. This phantom was designed based on the prototype of an intralipid-gel soft tissue mimicking phantom used for laser photothermal therapy. The glandularities and the densities of the phantom can be adjusted by modifying the ratio of intralipid and other ingredients and adding fiber powders. An adipose tissue phantom and a glandular tissue phantom were firstly developed and phantoms of different glandularities were further developed through mixing different weight proportions of adipose and glandular. To validate the properties of the phantom for the applications of x-ray imaging techniques, three methods were employed: (1) the compositions of the elements contained in the phantoms were estimated through calculations; (2) the x-ray mass attenuation coefficients of the phantom were calculated based on the elemental compositions; (3) the x-ray photon energies deposit in the phantoms with different glandularities were simulated using Geant4 Simulation Tool Kit. The results showed high agreements with the real breast tissues at corresponding breast glandularities. For the application in ultrasonography, the elasticity of the phantom was determined by measuring the value of Young’s modulus and the value of 39 ± 10 kPa indicated the satisfactory of the requirement of being used as phantom for ultrasound imaging. Therefore, the phantoms developed in this study potentially provided a solution of dualpurpose breast tissue mimicking phantom in the needs of different level of glandularity.

Paper Details

Date Published: 9 March 2018
PDF: 6 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105735H (9 March 2018); doi: 10.1117/12.2293272
Show Author Affiliations
Di Wu, The Univ. of Oklahoma (United States)
Yong Chen, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Farid Omoumi, The Univ. of Oklahoma (United States)
Yuran Guo, The Univ. of Oklahoma (United States)
Yuhua Li, The Univ. of Oklahoma (United States)
Bin Zheng, The Univ. of Oklahoma (United States)
Hong Liu, The Univ. of Oklahoma (United States)


Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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