Department of Radiology, University of Cincinnati Medical Center, 234 Goodman St, ML 772, Cincinnati, OH 45267, USA.
Radiology. 2012 Jul;264(1):51-8. doi: 10.1148/radiol.12110619. Epub 2012 May 15.
To evaluate the positive predictive values (PPVs) of Breast Imaging and Reporting Data Systems (BI-RADS) assessment categories for breast magnetic resonance (MR) imaging and to identify the BI-RADS MR imaging lesion features most predictive of cancer.
This institutional review board-approved HIPAA-compliant prospective multicenter study was performed with written informed consent. Breast MR imaging studies of the contralateral breast in women with a recent diagnosis of breast cancer were prospectively evaluated. Contralateral breast MR imaging BI-RADS assessment categories, morphologic descriptors for foci, masses, non-masslike enhancement (NMLE), and kinetic features were assessed for predictive values for malignancy. PPV of each imaging characteristic of interest was estimated, and logistic regression analysis was used to examine the predictive ability of combinations of characteristics.
Of 969 participants, 71.3% had a BI-RADS category 1 or 2 assessment; 10.9%, a BI-RADS category 3 assessment; 10.0%, a BI-RADS category 4 or 5 assessment; and 7.7%, a BI-RADS category 0 assessment on the basis of initial MR images. Thirty-one cancers were detected with MR imaging. Overall PPV for BI-RADS category 4 and 5 lesions was 0.278, with 17 cancers in patients with a BI-RADS category 4 lesion (PPV, 0.205) and 10 cancers in patients with a BI-RADS category 5 lesion (PPV, 0.714). Of the cancers, one was a focus, 17 were masses, and 13 were NMLEs. For masses, irregular shape, irregular margins, spiculated margins, and marked internal enhancement were most predictive of malignancy. For NMLEs, ductal, clumped, and reticular or dendritic enhancement were the features most frequently seen with malignancy. Kinetic enhancement features were less predictive of malignancy than were morphologic features.
Standardized terminology of the BI-RADS lexicon enables quantification of the likelihood of malignancy for MR imaging-detected lesions through careful evaluation of lesion features. In particular, BI-RADS assessment categories and morphologic descriptors for masses and NMLE were useful in estimating the probability of cancer.
评估乳腺磁共振成像（MRI）的乳腺成像报告和数据系统（BI-RADS）评估类别阳性预测值（PPV），并确定对癌症最具预测性的 BI-RADS MRI 病变特征。
本研究经机构审查委员会批准，符合 HIPAA 规定，为前瞻性多中心研究，患者均签署书面知情同意书。前瞻性评估近期诊断为乳腺癌女性的对侧乳腺 MRI 检查结果。评估对侧乳腺 MRI 的 BI-RADS 评估类别、病灶、肿块、非肿块样强化（NMLE）的形态学描述符和动力学特征的恶性肿瘤预测值。计算每个感兴趣的影像学特征的 PPV，并使用逻辑回归分析检查特征组合的预测能力。
在 969 名参与者中，71.3%的患者 BI-RADS 评估类别为 1 类或 2 类；10.9%的患者 BI-RADS 评估类别为 3 类；10.0%的患者 BI-RADS 评估类别为 4 类或 5 类；7.7%的患者初始 MRI 结果为 BI-RADS 评估类别 0。MRI 共检出 31 例癌症。BI-RADS 4 类和 5 类病变的总体 PPV 为 0.278，其中 BI-RADS 4 类病变患者中 17 例为癌症（PPV 为 0.205），BI-RADS 5 类病变患者中 10 例为癌症（PPV 为 0.714）。在这些癌症中，1 例为病灶，17 例为肿块，13 例为 NMLE。对于肿块，不规则形状、不规则边缘、分叶状边缘和明显内部强化是最具恶性预测性的特征。对于 NMLE，导管状、簇状、网状或树突状强化是最常见的恶性特征。与形态学特征相比，动力学增强特征对恶性肿瘤的预测作用较低。
BI-RADS 词汇表的标准化术语能够通过对病变特征的仔细评估，对 MRI 检测到的病变进行恶性肿瘤可能性的定量评估。特别是，BI-RADS 评估类别和肿块及 NMLE 的形态学描述符可用于估计癌症的概率。
