Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA.
Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA.
Semin Ultrasound CT MR. 2023 Feb;44(1):35-45. doi: 10.1053/j.sult.2022.11.001. Epub 2022 Nov 4.
Mammographic breast density is widely accepted as an independent risk factor for the development of breast cancer. In addition, because dense breast tissue may mask breast malignancies, breast density is inversely related to the sensitivity of screening mammography. Given the risks associated with breast density, as well as ongoing efforts to stratify individual risk and personalize breast cancer screening and prevention, numerous studies have sought to better understand the factors that impact breast density, and to develop and implement reproducible, quantitative methods to assess mammographic density. Breast density assessments have been incorporated into risk assessment models to improve risk stratification. Recently, novel techniques for analyzing mammographic parenchymal complexity, or texture, have been explored as potential means of refining mammographic tissue-based risk assessment beyond breast density.
乳腺密度被广泛认为是乳腺癌发展的一个独立危险因素。此外，由于致密的乳腺组织可能掩盖乳腺恶性肿瘤，乳腺密度与筛查性乳房 X 线摄影的灵敏度呈负相关。鉴于乳腺密度相关的风险，以及不断努力对个体风险进行分层和对乳腺癌筛查和预防进行个体化，许多研究都试图更好地了解影响乳腺密度的因素，并开发和实施可重复、定量的方法来评估乳房 X 线摄影密度。乳腺密度评估已被纳入风险评估模型，以改善风险分层。最近，分析乳腺实质复杂性或纹理的新技术已被探索作为潜在手段，以在乳腺密度之外完善基于乳腺组织的乳房 X 线摄影风险评估。
