Systematic Review of the Effectiveness of Mammography and Alternative Screening Methods in Breast Cancer Programs
DOI:
https://doi.org/10.56294/mw2024533Keywords:
Mammography, Breast Cancer Screening, Ultrasound, Digital Breast Tomosynthesis, MRI (Magnetic Resonance Imaging)Abstract
Breast cancer is still one of the main reasons women get sick and die, which has brought a lot of attention to screening programs that try to find the disease early and increase survival rates. For a long time, mammography has been the usual way to check for breast cancer. However, it has some problems, like giving fake positives and negatives and not working as well in women with thick breast tissue. These problems have led to the search for other screening methods. This study looks at how well mammography and newer alternative screening methods find breast cancer. It looks at their pros and cons and how they might be able to improve current screening methods. Mammography is widely used, but it has been criticized for not being sensitive enough, especially in younger women and women with thicker breast tissue, where it may miss cancers or give false results that lead to tests that aren't needed. Even with these problems, mammography has been shown to lower the death rate from breast cancer in older women through regular screening, and it is still the gold standard in many national breast cancer programs. New options like ultrasound, MRI, DBT, and CEM show promise in making sensitivity and precision better. Ultrasound, especially when used with mammograms, can help find breast cancer in women with thick breasts, but the accuracy depends on how skilled the expert is. MRI is better at finding breast cancer, especially in people who are at a high risk, but it is more expensive and doesn't find as many cancers. This means that more false positives and needless treatments happen. Digital breast tomosynthesis (DBT) gives three-dimensional images, which compared to regular mammography increases the number of cancers found while decreasing the number of false positives and the need for follow-up images. Contrast-enhanced mammography (CEM), which combines the benefits of mammography with contrast agents, may help doctors make more accurate diagnoses, especially for women whose breast tissue is thick.
References
nto, A.; Conti, A.; Mauriello, A.; Guerrisi, M.; Toschi, N. Deep computational pathology in breast cancer. Semin. Cancer Biol. 2021, 72, 226–237.
Ding, K.; Zhou, M.; Wang, H.; Gevaert, O.; Metaxas, D.; Zhang, S. A large-scale synthetic pathologicalHuang, J.; Chan, P.S.; Lok, V.; Chen, X.; Ding, H.; Jin, Y.; Yuan, J.; Lao, X.Q.; Zheng, Z.J.; Wong, M.C. Global incidence and mortality of breast cancer: A trend analysis. Aging 2021, 13, 5748–5803.
Dugge dataset for deep learning-enabled segmentation of breast cancer. Sci. Data 2023, 10, 231.
Qu, H.; Zhou, M.; Yan, Z.; Wang, H.; Rustgi, V.K.; Zhang, S.; Gevaert, O.; Metaxas, D.N. Genetic mutation and biological pathway prediction based on whole slide images in breast carcinoma using deep learning. NPJ Precis. Oncol. 2021, 5, 87.
Ibrahim, A.; Gamble, P.; Jaroensri, R.; Abdelsamea, M.M.; Mermel, C.H.; Chen, P.-H.C.; Rakha, E.A. Artificial intelligence in digital breast pathology: Techniques and applications. Breast 2020, 49, 267–273.
Bhushan, A.; Gonsalves, A.; Menon, J.U. Current state of breast cancer diagnosis, treatment, and theranostics. Pharmaceutics 2021, 13, 723.
Moy, L.; Heller, S.L.; Bailey, L.; D’Orsi, C.; DiFlorio, R.M.; Green, E.D.; Holbrook, A.I.; Lee, S.J.; Lourenco, A.P.; Mainiero, M.B.; et al. ACR Appropriateness Criteria(®) Palpable Breast Masses. J. Am. Coll. Radiol. 2017, 14, S203–S224.
Nikolova, N.K. Microwave imaging for breast cancer. IEEE Microw. Mag. 2011, 12, 78–94.
Løberg, M.; Lousdal, M.L.; Bretthauer, M.; Kalager, M. Benefits and harms of mammography screening. Breast Cancer Res. 2015, 17, 63.
Dibden, A.; Offman, J.; Duffy, S.W.; Gabe, R. Worldwide review and meta-analysis of cohort studies measuring the effect of mammography screening programmes on incidence-based breast cancer mortality. Cancers 2020, 12, 976.
Hendrick, R.E. Radiation Doses and Risks in Breast Screening. J. Breast Imaging 2020, 2, 188–200.
Zeeshan, M.; Salam, B.; Khalid, Q.S.B.; Alam, S.; Sayani, R. Diagnostic accuracy of digital mammography in the detection of breast cancer. Cureus 2018, 10, e2448.
He, Z.; Chen, Z.; Tan, M.; Elingarami, S.; Liu, Y.; Li, T.; Deng, Y.; He, N.; Li, S.; Fu, J. A review on methods for diagnosis of breast cancer cells and tissues. Cell Prolif. 2020, 53, e12822.
R. Golchha, P. Khobragade and A. Talekar, "Design of an Efficient Model for Health Status Prediction Using LSTM, Transformer, and Bayesian Neural Networks," 2024 International Conference on Innovations and Challenges in Emerging Technologies (ICICET), Nagpur, India, 2024, pp. 1-5, doi: 10.1109/ICICET59348.2024.10616353.
Song, S.Y.; Park, B.; Hong, S.; Kim, M.J.; Lee, E.H.; Jun, J.K. Comparison of Digital and Screen-Film Mammography for Breast-Cancer Screening: A Systematic Review and Meta-Analysis. J. Breast Cancer 2019, 22, 311–325.
Farber, R.; Houssami, N.; Wortley, S.; Jacklyn, G.; Marinovich, M.L.; McGeechan, K.; Barratt, A.; Bell, K. Impact of Full-Field Digital Mammography Versus Film-Screen Mammography in Population Screening: A Meta-Analysis. JNCI J. Natl. Cancer Inst. 2020, 113, 16–26. Posso, M.; Louro, J.; Sánchez, M.; Román, M.; Vidal, C.; Sala, M.; Baré, M.; Castells, X.; Group, B.S. Mammographic breast density: How it affects performance indicators in screening programmes? Eur. J. Radiol. 2019, 110, 81–87.
Kerlikowske, K.; Hubbard, R.A.; Miglioretti, D.L.; Geller, B.M.; Yankaskas, B.C.; Lehman, C.D.; Taplin, S.H.; Sickles, E.A.; Consortium, B.C.S. Comparative effectiveness of digital versus film-screen mammography in community practice in the United States: A cohort study. Ann. Intern. Med. 2011, 155, 493–502.
Korhonen, K.E.; Weinstein, S.P.; McDonald, E.S.; Conant, E.F. Strategies to increase cancer detection: Review of true-positive and false-negative results at digital breast tomosynthesis screening. Radiographics 2016, 36, 1954.
Baker, J.A.; Lo, J.Y. Breast tomosynthesis: State-of-the-art and review of the literature. Acad. Radiol. 2011, 18, 1298–1310.
Gennaro, G.; Bernardi, D.; Houssami, N. Radiation dose with digital breast tomosynthesis compared to digital mammography: Per-view analysis. Eur. Radiol. 2018, 28, 573–581.
Georgian-Smith, D.; Obuchowski, N.A.; Lo, J.Y.; Brem, R.F.; Baker, J.A.; Fisher, P.R.; Rim, A.; Zhao, W.; Fajardo, L.L.; Mertelmeier, T. Can Digital Breast Tomosynthesis Replace Full-Field Digital Mammography? A Multireader, Multicase Study of Wide-Angle Tomosynthesis. Am. J. Roentgenol. 2019, 212, 1393–1399.
Ali, E.A.; Adel, L. Study of role of digital breast tomosynthesis over digital mammography in the assessment of BIRADS 3 breast lesions. Egypt. J. Radiol. Nucl. Med. 2019, 50, 48.
Østerås, B.H.; Martinsen, A.C.T.; Gullien, R.; Skaane, P. Digital Mammography versus Breast Tomosynthesis: Impact of Breast Density on Diagnostic Performance in Population-based Screening. Radiology 2019, 293, 60–68.
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Copyright (c) 2024 Anbazhagan. S, Vivek Saraswat, Satya Sundar Gajendra Mohapatra, Joginder, Jamuna.K.V, Kanchana. A, Swarna Swetha Kolaventi (Author)

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