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Article type: Research Article
Authors: Elshemey, Wael M. a; * | Saif, Refat Abob | Elfiky, Abdo A.b
Affiliations: [a] Physics Department, Faculty of Science, Islamic University of Madinah, Madinah, KSA | [b] Biophysics Department, Faculty of Science, Cairo University, Giza, Egypt
Correspondence: [*] Corresponding author: Wael M. Elshemey, Physics Department, Faculty of Science, Islamic University of Madinah, KSA. E-mail: welshemey@iu.edu.sa.
Abstract: BACKGROUND:Characterization of normal and malignant breast tissues using X-ray scattering techniques has shown promising results and applications. OBJECTIVE:To examine possibility of characterizing normal and malignant breast tissues using the scattered photon distribution of polyenergetic beams of 30 kV X-rays. METHODS:A Monte Carlo simulation is upgraded so that it is capable of simulating input mammographic X-ray spectra from different target-filter combinations, tracing photon transport, and producing the distribution of scattered photons. The target-filter combinations include Mo-Mo, Mo-Al, Mo-Rh, Rh-Rh, Rh-Al, W-Rh, and W-Al. Analysis of obtained scattered photon distribution is carried out by comparing the ratio of count under the peak in the momentum transfer region from 0 to 1.55 nm–1, to that in the region from 1.6 to 9.1 nm–1 (covering the regions of scattering from fat and soft tissue, respectively) for breast samples with different percentages of normal tissue (0–100%). RESULTS:Mo-Mo target-filter combination shows a high linear dependence of the count under peak ratio on the percentage of normal tissue in breast samples (R2 = 0.9513). Despite slightly less linear than Mo-Mo, target-filter combinations other than Rh-Rh, W-Rh, and W-Al produce high linear responses (R2 > 0.9) CONCLUSION:Mo-Mo target-filter combination would probably be the most relevant in characterizing normal and malignant breast tissues from their scattered photon distribution.
Keywords: Monte Carlo simulation, breast tissue, X-ray scattering, tissue characterization, mammography
DOI: 10.3233/XST-221154
Journal: Journal of X-Ray Science and Technology, vol. 30, no. 4, pp. 823-834, 2022
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