Literature DB >> 34130221

Biological effects induced by doses of mammographic screening.

Leslie Pereira1, Marcella T Ferreira2, Antonio Gilcler F Lima2, Camila Salata3, Samara C Ferreira-Machado4, I Lima5, Verônica Morandi6, Luís A G Magalhães7.   

Abstract

PURPOSE: Mammography is the diagnostic imaging practice used in screening to detect early lesions suspected of malignancy. It uses a low energy X-ray beam in which a low dose in the order of 2-3 mGy is delivered to patient breast cells. However, it has been speculated that it could lead to significant cell damage, when compared to conventional X-ray. We investigated the biological effects of low doses, with mean glandular doses (MGDs) of 2.5 mGy and 2.5 + 2.5 mGy, on mammary cells in vitro.
METHODS: We used the non-tumorigenic cell line (MCF-10A) and two tumor cells lines (MCF-7 and MDA-MB-231). Colony formation, apoptosis, and double-strand DNA breaks (DSBs) were quantified.
RESULTS: The selected MGD regimens did not alter the formation of colonies by any of the cell lines. MCF-7 cells exhibited a markedly increase in apoptosis, 24 h after the single-dose protocol; MCF-10A cells underwent apoptosis only after 72 h, with both irradiation regimens, while MDA-MB-231 cells (highly invasive and metastatic) were not susceptible to apoptosis. The detection of γH2AX histone in the nuclei of irradiated cells showed that the double-dose resulted in increase of DSBs, especially in tumor cell lines.
CONCLUSIONS: Although the health benefits of early breast screening remain indisputable, our future perspective is to better understand the biological basis for the effects of low dose radiation on breast cells and to investigate if and under what conditions there would be a risky situation in repeated mammography screening, in both asymptomatic and symptomatic women.
Copyright © 2021 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Apoptosis; Breast cell; Mammography; γH2AX

Mesh:

Year:  2021        PMID: 34130221     DOI: 10.1016/j.ejmp.2021.06.002

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


  1 in total

1.  Regression-based neural network for improving image reconstruction in diffuse optical tomography.

Authors:  Ganesh M Balasubramaniam; Shlomi Arnon
Journal:  Biomed Opt Express       Date:  2022-03-11       Impact factor: 3.562

  1 in total

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