背景 根据动态对比增强（DCE）磁共振成像扫描自动识别定量乳腺实质增强特征，可以增加对极度密集乳房女性乳腺癌风险评估的价值。目的 在基线DCE MRI扫描中自动识别乳腺实质的定量特性，并评估其与极度密集乳房女性乳腺癌发生的关联。材料与方法 本研究代表密集组织和早期乳腺肿瘤筛查试验的次要分析。MRI在2011年12月至2016年1月期间在八家医院进行。在分割纤维腺组织后，从基线MRI扫描中提取乳腺实质的定量特征（包括体积密度，体积形态和增强特性）。使用主成分分析识别具有最大方差的乳腺实质测量。应用多变量Cox比例风险回归评估乳腺癌发生与乳腺实质定量特征之间的关联，然后将显著特征分层为三分位数。结果共纳入了4553名极度密集乳房女性（平均年龄55.7岁±6 [SD]），其中122名（3％）被诊断出乳腺癌。鉴定出五个解释96％方差的主成分，而解释最大的独立方差（42％）的成分包括与增强乳腺实质体积有关的MRI特征。多变量分析显示，增强乳腺实质体积与乳腺癌发生有关（风险比[HR]，1.09；95％CI：1.01，1.18；P = .02）。此外，体积增强乳腺实质的高三分位数女性患乳腺癌的发生率是低三分位数女性的两倍（HR，2.09；95％CI：1.25，3.61；P = .005）。结论在极度密集乳房女性中，基线DCE MRI扫描中增强乳腺实质的高体积与低体积相比，与乳腺癌的发生率增加有关。© RSNA，2023 本文提供了附加材料。此外，本期的Grimm社论也可参考。

Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. MRI was performed in eight hospitals between December 2011 and January 2016. After segmentation of fibroglandular tissue, quantitative features (including volumetric density, volumetric morphology, and enhancement characteristics) of the parenchyma were extracted from baseline MRI scans. Principal component analysis was used to identify parenchymal measures with the greatest variance. Multivariable Cox proportional hazards regression was applied to assess the association between breast cancer occurrence and quantitative parenchymal features, followed by stratification of significant features into tertiles. Results A total of 4553 women (mean age, 55.7 years ± 6 [SD]) with extremely dense breasts were included; of these women, 122 (3%) were diagnosed with breast cancer. Five principal components representing 96% of the variance were identified, and the component explaining the greatest independent variance (42%) consisted of MRI features relating to volume of enhancing parenchyma. Multivariable analysis showed that volume of enhancing parenchyma was associated with breast cancer occurrence (hazard ratio [HR], 1.09; 95% CI: 1.01, 1.18; P = .02). Additionally, women in the high tertile of volume of enhancing parenchyma showed a breast cancer occurrence twice that of women in the low tertile (HR, 2.09; 95% CI: 1.25, 3.61; P = .005). Conclusion In women with extremely dense breasts, a high volume of enhancing parenchyma on baseline DCE MRI scans was associated with increased occurrence of breast cancer as compared with a low volume of enhancing parenchyma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grimm in this issue.