Vol. 10, 2025

Medical Physics

EXAMINING LESION VISIBILITY OF THICK COMPRESSED BREASTS UNDER DIFFERENT IONIZING RADIATION EXPOSURE CONDITIONS BY USING A MAMMOGRAPHIC MATHEMATICAL PHANTOM

Spyridoula Katsanevaki, Nektarios Kalyvas, Christos Michail, Ioannis Valais, George Fountos, Ioannis Kandarakis

Pages: 21-27

DOI: 10.37392/RapProc.2025.05

Mammography is an X-ray imaging application used for breast diagnosis. Its high importance is denoted by the routinely mammographic examinations suggested for women above a certain age. In the era of digital mammography, various dedicated detector designs have been considered for possible use in a mammographic system. Despite, the detector characteristics the image of thick or dense breasts is a challenge since the amount of radiation transmitted through the breast and incident at the detector surface is a function of the ionizing radiation energy and exposure. In addition, possible breast lesions may be visible or not depending upon their size and composition. In general, a large size and high atomic number lesion has higher visibility than a small size and low atomic number one. A simple mathematical breast phantom was designed which was comprised from breast tissue as a background material and areas corresponding to a) blood for low atomic number material and b) Ca for a high atomic number material like microcalcifications. The phantom dimensions were 1000×1000 pixels, while the lesions were constructed as squares ranging from 2x2 pixels up to 50×50 pixels and lines. The breast thicknesses considered were 5.2 cm and 6 cm for the phantom. For the Ca the thicknesses ranged from 0.0008 cm up to 0.01 cm and for the blood lesions from 0.08 cm up to 0.5 cm. Simulations of the irradiated with 22 keV and 28 keV X-ray photons for different photon fluences, which after transmission from the phantom they have been assumed to impinge a Dexela mammographic detector, have been performed. It was found that at 22 keV and 6 cm breast thickness the 0.003 cm, 10×10 Ca lesion could be observed as well as the 20×20 blood lesion of 0.2 cm thickness. The increase of photon fluence improved the derived image due to the decrease of the image noise levels. The 5.2 cm thickness irradiation conditions produced less noisy images due to the higher number of photons impinging on the detector surface.
  1. W. Ren, M. Chen, Y. Qiao, F. Zhao. “Global guidelines for breast cancer screening: A systematic review,” Breast, vol. 64, pp. 85 – 99, Aug. 2022.
    DOI: 10.1016/j.breast.2022.04.003
    PMid: 35636342
    PMCid: PMC9142711
  2. H. Aichinger, J. Dierker, S. Joite-Barfuß, M. Säbel, “Principles of X-Ray Imaging,” in Radiation Exposure and Image Quality in X-ray Diagnostic Radiology: Physical Principles and Clinical Applications, 2nd ed., Berlin Heidelberg, Germany: Springer-Verlag, 2012, ch. 1, pp. 3 – 7.
    DOI: 10.1007/978-3-642-11241-6_1
  3. K. Bliznakova “The advent of anthropomorphic three-dimensional breast phantoms for X-ray imaging,” Phys. Med., vol. 79, pp. 145 – 161, Nov. 2020.
    DOI: 10.1016/j.ejmp.2020.11.025
    PMid: 33321469
  4. N. Kalyvas et al., “A Novel Method to Model Image Creation Based on Mammographic Sensors Performance Parameters: A Theoretical Study,” Sensors, vol. 23, no. 4, 2335, Feb. 2023.
    DOI: 10.3390/s23042335
    PMid: 36850937
    PMCid: PMC9968010
  5. A. C. Konstantinidis, M. B. Szafraniec, R. D. Speller, A. Olivo “The Dexela 2923 CMOS X-ray detector: A flat panel detector based on CMOS active pixel sensors for medical imaging applications,” Nucl. Instrum. Methods in Phys. Res. Sec. A, vol. 689, pp. 12 – 21, Oct. 2012.
    DOI: 10.1016/j.nima.2012.06.024
  6. MATLAB version 9.12, MathWorks, Natick (MA), USA, 2022.
    Retrieved from: https://www.mathworks.com
    Retrieved on: Jun. 30, 2025
  7. R. Nowotny, XMuDat: Photon attenuation data on PC version 1.0.1, IAEA Nuclear Data Section, Vienna, Austria, 1998.
    Retrieved from: https://www-nds.iaea.org/publications/iaea-nds/iaea-nds-0195.htm
    Retrieved on: Jun. 30, 2025
  8. S. Katsanevaki, “Mathematical creation of a phantom to study the effect of exposure on mammography,” Diploma Thesis, University of West Attica, Athens, Greece, 2024.
    DOI: 10.26265/polynoe-5930
  9. W. Rasband, ImageJ version 1.47h, National Institutes of Health, Bethesda (MD), USA, 2012.
    Retrieved from: https://imagej.net/ij/
    Retrieved on: Jun. 30, 2025
  10. F. Stossi, P. K. Singh, “Basic Image Analysis and Manipulation in ImageJ/Fiji,” Curr. Protoc., vol. 3, no. 7, e849, Jul. 2023.
    DOI: 10.1002/cpz1.849
    PMid: 37498127