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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/57956
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dc.creatorLucas Paixão Reispt_BR
dc.creatorBruno Beraldo Oliveirapt_BR
dc.creatorM.A. Oliveirapt_BR
dc.creatorM.H.A. Teixeirapt_BR
dc.creatorTelma Fonsecapt_BR
dc.creatorM.S. Nogueirapt_BR
dc.date.accessioned2023-08-18T23:16:25Z-
dc.date.available2023-08-18T23:16:25Z-
dc.date.issued2016-
dc.citation.volume119pt_BR
dc.citation.spage200pt_BR
dc.citation.epage206pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.radphyschem.2015.10.023pt_BR
dc.identifier.issn0969-806Xpt_BR
dc.identifier.urihttp://hdl.handle.net/1843/57956-
dc.description.resumoMammography is the main radiographic technique used for breast imaging. A major concern with mammographic imaging is the risk of radiation-induced breast cancer due to the high sensitivity of breast tissue. The mean glandular dose (DG) is the dosimetric quantity widely accepted to characterize the risk of radiation induced cancer. Previous studies have concluded that DG depends not only on the breast glandular content but also on the spatial distribution of glandular tissue within the breast. In this work, a new method for generating computational breast models featuring skin composition and glandular tissue distribution from patients undergoing digital mammography is proposed. Such models allow a more accurate way of calculating individualized breast glandular doses taking into consideration the glandular tissue fraction. Sixteen breast models of four patients with different glandularity breasts were simulated and the results were compared with those obtained from recommended DG conversion factors. The results show that the internationally recommended conversion factors may be over estimating the mean glandular dose to less dense breasts and underestimating the mean glandular dose for denser breasts. The methodology described in this work constitutes a powerful tool for breast do simetry, especially for risk studies.pt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentMED - DEPARTAMENTO DE ANATOMIA E IMAGEMpt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofRadiation Physics and Chemistry-
dc.rightsAcesso Restritopt_BR
dc.subjectDigital mammographypt_BR
dc.subjectNormalized mean glandular dosept_BR
dc.subjectMonte Carlo simulationpt_BR
dc.subjectBreast modelspt_BR
dc.subjectBreast dosimetrypt_BR
dc.subject.otherMamografiapt_BR
dc.subject.otherImplantes de Mamapt_BR
dc.titleNew method for generating breast models featuring glandular tissue spatial distributionpt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.sciencedirect.com/science/article/pii/S0969806X15300840?via%3Dihubpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-0579-309Xpt_BR
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