Mamografia Digital: estudos dosimétricos e de qualidade da imagem por simulação Monte Carlo
DOI:
https://doi.org/10.29384/rbfm.2019.v13.n1.p154-161Keywords:
mamografia digital, método Monte Carlo, dosimetriaAbstract
Por meio do código Monte Carlo (MC) modificado PENELOPE (v. 2014) + penEasy (v. 2015), a contribuição do corpo do paciente na dose glandular média (DGM), além da contribuição dos fótons por tipos de interação e da geração da partícula, foi estudada. Diferentes métodos de ponderação da DGM foram comparados. A razão contraste-ruído (CNR) foi quantificada para diferentes tamanhos e tipos de lesões (calcificação e tumor), na ausência e presença de grades antiespalhamento (ideal, linear e celular). Em mamografia, o corpo do paciente contribui com menos de 1% para o aumento da DGM. O efeito fotoelétrico é a interação que mais contribui para a DGM (até aproximadamente 50 keV), enquanto a contribuição da radiação espalhada aumenta com a energia e espessura da mama. Ponderar a DGM de maneira retrospectiva pode subestimar em até 6%, para mamas espessas e de baixa glandularidade em 60 keV, sendo negligenciável em mamografia digital. A CNR pode ser superestimada em até 27(2)% na ausência de grade, dependendo da área da lesão, indicando que seu tamanho deve ser considerado nos estudos de qualidade da imagem.
Downloads
References
INCA. Etimativa 2018 - Incidência de Câncer no Brasil. Rio de Janeiro: Ministério da Saúde; 2017.
Stewart BW, Wild CP. World Cancer Report 2014. Lyon: IARC; 2014.
European Society of Radiology. Screening & Beyond: Medical Imaging in the Detection, Diagnoses and Management of Breast Diseases. Vienna: ESR; 2016.
Dance DR, Sechopoulos I. Dosimetry in x-ray-based breast imaging. Phys Med Biol. 2016;61(19):R271–304.
Wu X, Barnes GT, Tucker DM. Spectral dependence of glandular tissue dose in screen-film mammography. Radiology. 1991;179(1):143–8.
Boone JM. Normalized glandular dose (DgN) coefficients for arbitrary x-ray spectra in mammography: Computer-fit values of Monte Carlo derived data. Med Phys. 2002;29(5):869–75.
Cunha DM, Tomal A, Poletti ME. Evaluation of scatter-to-primary ratio, grid performance and normalized average glandular dose in mammography by Monte Carlo simulation including interference and energy broadening effects. Phys Med Biol. 2010;55(15):4335–59.
Sarno A, Mettivier G, Di Lillo F, Russo P. Monte Carlo Evaluation of Normalized Glandular Dose Coefficients in Mammography. In: Proceedings of the 13th International Workshop on Breast Imaging - Volume 9699. Springer-Verlag; 2016. p. 190–6.
Sarno A, Mettivier G, Di Lillo F, Russo P. A Monte Carlo study of monoenergetic and polyenergetic normalized glandular dose (DgN) coefficients in mammography. Phys Med Biol. 2017;62(1):306–25.
Wilkinson L, Heggie JCP. Glandular breast dose: potential errors. Radiology. 2001;213(1).
Myronakis ME, Zvelebil M, Darambara DG. Normalized mean glandular dose computation from mammography using GATE: a validation study. Phys Med Biol. 2013;58(7):2247–65.
Boone JM. Glandular Breast Dose for Monoenergetic and High-Energy X-ray Beams: Monte Carlo Assessment. Radiology. 1999;213(1):23–37.
Massera RT, Tomal A. Skin models and their impact on mean glandular dose in mammography. Phys Med. 2018;51:38-47.
Nykänen K, Siltanen S. X-ray scattering in full-field digital mammography. Med Phys. 2003;30(7):1864–73.
Cunha DM, Tomal A, Poletti ME. Optimization of x-ray spectra in digital mammography through Monte Carlo simulations. Phys Med Biol. 2012;57(7):1919–35.
Dance DR, Thilander AK, Sandborg M, Skinner CL, Castellano IA, Carlsson GA. Influence of anode/filter material and tube potential on contrast, signal-to-noise ratio and average absorbed dose in mammography: a Monte Carlo study. Br J Radiol. 2000;73(874):1056–67.
Chen H, Danielsson M, Xu C, Cederström B. On image quality metrics and the usefulness of grids in digital mammography. J Med imaging (Bellingham, Wash). 2015;2(1):013501.
Salvat F. PENELOPE-2014: A Code System for Monte Carlo Simulation of Electron and Photon Transport. NEA/NSC/DOC(2015); 2015.
Sempau J, Badal A, Brualla L. A PENELOPE -based system for the automated Monte Carlo simulation of clinacs and voxelized geometries-application to far-from-axis fields. Med Phys. 2011;38(11):5887–95.
Sechopoulos I, Rogers DWO, Bazalova-Carter M, Bolch WE, Heath EC, McNitt-Gray MF, et al. RECORDS: improved Reporting of montE CarlO RaDiation transport Studies: Report of the AAPM Research Committee Task Group 268. Med Phys. 2018;45(1):e1–5.
Badal A, Sempau J. A package of Linux scripts for the parallelization of Monte Carlo simulations. Comput Phys Commun. 2006;175(6):440–50.
Sechopoulos I, Ali ESM, Badal A, Badano A, Boone JM, Kyprianou IS, et al. Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195. Med Phys. 2015;42(10):5679–91.
Yaffe MJ, Boone JM, Packard N, Alonzo-Proulx O, Huang S-Y, Peressotti CL, et al. The myth of the 50-50 breast. Med Phys. 2009;36(12):5437–43.
Shi L, Vedantham S, Karellas A, O’Connell AM. Technical Note: Skin thickness measurements using high-resolution flat-panel cone-beam dedicated breast CTa). Med Phys. 2013;40(3):031913.
Huang S-Y, Boone JM, Yang K, Kwan ALC, Packard NJ. The effect of skin thickness determined using breast CT on mammographic dosimetry. Med Phys. 2008;35(4):1199–206.
Day GJ, Dance DR. X-ray transmission formula for antiscatter grids. Phys Med Biol. 1983;28(12):1429–33.
Sarno A, Mettivier G, Di Lillo F, Tucciariello RM, Bliznakova K, Russo P. Normalized glandular dose coefficients in mammography, digital breast tomosynthesis and dedicated breast CT. Phys Med. 2018;55:142-48.
Hammerstein RG, Miller DW, White DR, Masterson ME, Woodard HQ, Laughlin JS. Absorbed Radiation Dose in Mammography. Radiology. 1979;130(2):485–91.
Hubbell J H, Seltzer S M. Tables of X-Ray Mass Attenuation Coefficients and Mass Energy-Absorption Coefficients from 1 keV to 20 MeV for Elements Z = 1 to 92 and 48 Additional Substances of Dosimetric Interest. 2004.
Hernandez AM, Seibert JA, Nosratieh A, Boone JM. Generation and analysis of clinically relevant breast imaging x-ray spectra. Med Phys. 2017;44(6):2148–60.
Nosratieh A, Hernandez A, Shen SZ, Yaffe MJ, Seibert JA, Boone JM. Mean glandular dose coefficients (D(g)N) for x-ray spectra used in contemporary breast imaging systems. Phys Med Biol. 2015;60(18):7179–90.
Massera RT. Otimização dos parâmetros de exposição em mamografia digital: estudos experimentais e por simulação Monte Carlo. Universidade Estadual de Campinas; 2018.
Zhou A, Yin Y, White GL, Davidson R. A new solution for radiation transmission in anti-scatter grids. Biomed Phys Eng Express. 2016;2(5):055011.
Downloads
Published
How to Cite
Issue
Section
License
The submission of original articles to the Brazilian Journal of Medical Physics implies the transfer, by the authors, of the rights of print and digital publication. Copyright for published articles remains with the author, with journal rights on first publication. Authors may only use the same results in other publications by clearly indicating this journal as the original publisher. As we are an open access journal, free use of articles in educational, scientific, non-commercial applications is allowed, as long as the source is cited.
The Brazilian Journal of Medical Physics is under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
