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DOI 10.2214/ajr.20.24436

Медицинская библиотека · AJR. American journal of roentgenology · 2020

Screening Algorithms in Dense Breasts: AJR Expert Panel Narrative Review.

Berg Wendie A, Rafferty Elizabeth A, Friedewald Sarah M, Hruska Carrie B, Rahbar Habib

СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАОбзорПеревод пока не подготовлен

Аннотация

Screening mammography reduces breast cancer mortality; however, when used to examine women with dense breasts, its performance and resulting benefits are reduced. Increased breast density is an independent risk factor for breast cancer. Digital breast tomosynthesis (DBT), ultrasound (US), molecular breast imaging (MBI), MRI, and contrast-enhanced mammography (CEM) each have shown improved cancer detection in dense breasts when compared with 2D digital mammography (DM). DBT is the preferred mammographic technique for producing a simultaneous reduction in recalls (i.e., additional imaging). US further increases cancer detection after DM or DBT and reduces interval cancers (cancers detected in the interval between recommended screening examinations), but it also produces substantial additional false-positive findings. MBI improves cancer detection with an effective radiation dose that is approximately fourfold that of DM or DBT but is still within accepted limits. MRI provides the greatest increase in cancer detection and reduces interval cancers and late-stage disease; abbreviated techniques will reduce cost and improve availability. CEM appears to offer performance similar to that of MRI, but further validation is needed. Dense breast notification will soon be a national standard; therefore, understanding the performance of mammography and supplemental modalities is necessary to optimize screening for women with dense breasts.

Для цитирования: Berg Wendie A, Rafferty Elizabeth A, Friedewald Sarah M, Hruska Carrie B, Rahbar Habib. Screening Algorithms in Dense Breasts: AJR Expert Panel Narrative Review.. AJR. American journal of roentgenology. 2020. DOI: 10.2214/ajr.20.24436.

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