
Screening Algorithms in Dense Breasts: AJR Expert Panel Narrative Review
Author(s) -
Wendie A. Berg,
Elizabeth A. Rafferty,
Sarah M. Friedewald,
Carrie B. Hruska,
Habib Rahbar
Publication year - 2021
Publication title -
american journal of roentgenology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.294
H-Index - 196
eISSN - 1546-3141
pISSN - 0361-803X
DOI - 10.2214/ajr.20.24436
Subject(s) - medicine , narrative review , narrative , algorithm , medical physics , radiology , linguistics , intensive care medicine , computer science , philosophy
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.