From the Department of Radiology, Kameda Kyobashi Clinic, Tokyo Square Garden 4F, 3-1-1 Kyobashi, Chuo City, Tokyo, Japan 104-0031 (Y.M., M.T., T.Y.); and Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan (A.S.).
Radiology. 2015 Sep;276(3):686-94. doi: 10.1148/radiol.2015141775. Epub 2015 Apr 15.
To compare positive predictive values (PPVs) of linearly distributed nonmass enhancement (NME) with linear and branching patterns and to identify imaging characteristics of NME that would enable classification as Breast Imaging Reporting and Data System category 3 lesions.
The institutional review board approved this retrospective study and waived the requirement to obtain informed consent. Reports of breast magnetic resonance (MR) examinations (n = 9453) that described NME were reviewed from examinations performed at the study institution from January 2008 to December 2011. NME with linear distribution was allocated to one of two subtypes: linear pattern (arrayed in a line) or branching pattern (with branches). The χ(2) test, Fisher exact test, or Student t test was performed for univariate analyses. Factors that showed a significant association with outcome at univariate analyses were assessed with multivariate analyses by using a logistic regression model. Interobserver agreement of the two subtypes between initial interpretation and the interpretation by two additional radiologists who were blinded to any clinical or pathologic information was evaluated with κ analysis.
Within the 156 linearly distributed NME lesions, the PPV of the branching pattern (71 of 95 lesions [75%]; 95% confidence interval [CI]: 66%, 84%) was significantly higher than that of the linear pattern (five of 61 lesions [8%]; 95% CI: 1%, 15%) (P < .0001). The PPV of linear pattern lesions smaller than 1 cm was 0% (0 of 30 lesions; 95% CI: 0%, 0%). At multivariate analysis, branching pattern and NME lesion size of 1 cm or greater were significant predictors of malignancy (P < .0001 [odds ratio: 21.6; 95% CI: 7.5, 62.2] and P = .015 [odds ratio: 5.8; 95% CI: 1.4, 24.0], respectively). Substantial interobserver agreement was obtained for differentiating the two subtypes, with κ values of 0.64 (95% CI: 0.51, 0.76), 0.70 (95% CI: 0.59, 0.82), and 0.64 (95% CI: 0.51, 0.76) between the initial interpreter and reviewer 1, the initial interpreter and reviewer 2, and reviewer 1 and reviewer 2, respectively.
The branching pattern was a significantly stronger predictor of malignancy than was the linear pattern. NME lesions with a linear pattern that are smaller than 1 cm can be managed with follow-up.
比较线性分布非肿块强化(NME)呈线性和分支模式的阳性预测值(PPV),并确定能够将 NME 分类为乳腺影像报告和数据系统(BI-RADS)类别 3 病变的成像特征。
本回顾性研究经机构审查委员会批准,且豁免了获得知情同意的要求。对 2008 年 1 月至 2011 年 12 月在本研究机构进行的乳腺磁共振(MR)检查报告进行了回顾性分析,这些报告描述了 NME。线性分布的 NME 被分配到两种亚型之一:线性模式(呈线状排列)或分支模式(具有分支)。使用卡方检验、Fisher 确切检验或学生 t 检验进行单变量分析。单变量分析中具有显著相关性的因素,使用 logistic 回归模型进行多变量分析。最初的解释者和另外两名对任何临床或病理信息均不知情的放射科医生对两种亚型之间的两种亚型进行了评估,并通过κ分析进行了评估。
在 156 个线性分布的 NME 病变中,分支模式的 PPV(71/95 个病变[75%];95%置信区间[CI]:66%,84%)明显高于线性模式(61/5 个病变[8%];95%CI:1%,15%)(P<.0001)。小于 1cm 的线性模式病变的 PPV 为 0%(30/30 个病变;95%CI:0%,0%)。多变量分析显示,分支模式和 1cm 或更大的 NME 病变大小是恶性肿瘤的显著预测因素(P<.0001[比值比:21.6;95%CI:7.5,62.2]和 P=0.015[比值比:5.8;95%CI:1.4,24.0])。最初的解释者和审阅者 1、最初的解释者和审阅者 2 以及审阅者 1 和审阅者 2 之间,分别获得了区分这两种亚型的适度观察者间一致性,κ 值分别为 0.64(95%CI:0.51,0.76)、0.70(95%CI:0.59,0.82)和 0.64(95%CI:0.51,0.76)。
分支模式是比线性模式更强的恶性肿瘤预测因子。小于 1cm 的具有线性模式的 NME 病变可以通过随访进行管理。