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Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool.

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Tucker, Lorraine 
Young, Ken C 


Breast screening with full-field digital mammography (FFDM) fails to detect 15-30% of cancers. This figure is higher for women with dense breasts. A new tomographic technique in mammography has been developed--digital breast tomosynthesis (DBT)--which allows images to be viewed in sections through the breast and has the potential to improve cancer detection rates. Results from retrospective reading studies comparing DBT with FFDM have been largely favourable with improvement in sensitivity and specificity. Increases in diagnostic accuracy have been reported as being independent of breast density; however there are mixed reports regarding the detection of microcalcification. Prospective screening studies using DBT with FFDM have demonstrated increased rates in cancer detection compared with FFDM alone. A reduction in false-positive recall rates has also been shown. Screening with the addition of DBT would approximately double radiation dose; however a simulated FFDM image can be generated from a DBT scan. The combination of simulated FFDM images and DBT is being evaluated within several studies and some positive results have been published. Interval cancer rates for the UK National Health Service Breast Screening Programme (NHSBSP) demonstrate the limited sensitivity of FFDM in cancer detection. DBT has the potential to increase sensitivity and decrease false-positive recall rates. It has approval for screening and diagnostics in several countries; however, there are issues with DBT as a screening tool including additional reading time, IT storage and connectivity, over-diagnosis, and cost effectiveness. Feasibility and cost-effectiveness trials are needed before the implementation of DBT in NHSBSP can be considered.



Breast Neoplasms, Early Detection of Cancer, Female, Humans, Mammography, Mass Screening, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Sensitivity and Specificity

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Clin Radiol

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Elsevier BV
Department of Health (via National Institute for Health Research (NIHR)) (09/22/182)
Cambridge University Hospitals NHS Foundation Trust (CUH) (3819/1415/ 19)