Wengert Georg J, Helbich Thomas H, Leithner Doris, Morris Elizabeth A, Baltzer Pascal A T, Pinker Katja
Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria.
Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany.
Curr Breast Cancer Rep. 2019 Mar;11(1):23-33. doi: 10.1007/s12609-019-0302-6. Epub 2019 Jan 17.
Breast density, or the amount of fibroglandular tissue in the breast, has become a recognized and independent marker for breast cancer risk. Public awareness of breast density as a possible risk factor for breast cancer has resulted in legislation for risk stratification purposes in many US states. This review will provide a comprehensive overview of the currently available imaging modalities for qualitative and quantitative breast density assessment and the current evidence on breast density and breast cancer risk assessment.
To date, breast density assessment is mainly performed with mammography and to some extent with magnetic resonance imaging. Data indicate that computerized, quantitative techniques in comparison with subjective visual estimations are characterized by higher reproducibility and robustness.
Breast density reduces the sensitivity of mammography due to a masking effect and is also a recognized independent risk factor for breast cancer. Standardized breast density assessment using automated volumetric quantitative methods has the potential to be used for risk prediction and stratification and in determining the best screening plan for each woman.
乳腺密度，即乳腺中纤维腺组织的数量，已成为公认的独立乳腺癌风险标志物。公众对乳腺密度作为乳腺癌潜在风险因素的认知，促使美国许多州出台了基于风险分层目的的立法。本综述将全面概述目前可用于定性和定量评估乳腺密度的成像模式，以及当前关于乳腺密度与乳腺癌风险评估的证据。
迄今为止，乳腺密度评估主要通过乳腺X线摄影进行，在一定程度上也借助磁共振成像。数据表明，与主观视觉估计相比，计算机化的定量技术具有更高的可重复性和稳健性。
由于掩盖效应，乳腺密度会降低乳腺X线摄影的敏感性，同时它也是公认的独立乳腺癌风险因素。使用自动容积定量方法进行标准化乳腺密度评估，有可能用于风险预测和分层，并为每位女性确定最佳筛查方案。
