Department of Radiology, St. Marianna University School of Medicine, Yokohama City Seibu Hospital, 1197-1 Yasashicho, Asahi-ku, Yokohama, Kanagawa, 241-0811, Japan.
Department of Radiology, Breast and Imaging Center, St. Marianna University School of Medicine, 6-7-2 Mampukuji, Asao-ku, Kawasaki, Kanagawa, 215-0004, Japan.
Jpn J Radiol. 2018 Mar;36(3):200-208. doi: 10.1007/s11604-017-0717-9. Epub 2017 Dec 29.
To analyze the association of breast non-mass enhancement descriptors in the BI-RADS 5th edition with malignancy, and to establish a grading system and categorization of descriptors.
This study was approved by our institutional review board. A total of 213 patients were enrolled. Breast MRI was performed with a 1.5-T MRI scanner using a 16-channel breast radiofrequency coil. Two radiologists determined internal enhancement and distribution of non-mass enhancement by consensus. Corresponding pathologic diagnoses were obtained by either biopsy or surgery. The probability of malignancy by descriptor was analyzed using Fisher's exact test and multivariate logistic regression analysis. The probability of malignancy by category was analyzed using Fisher's exact and multi-group comparison tests.
One hundred seventy-eight lesions were malignant. Multivariate model analysis showed that internal enhancement (homogeneous vs others, p < 0.001, heterogeneous and clumped vs clustered ring, p = 0.003) and distribution (focal and linear vs segmental, p < 0.001) were the significant explanatory variables. The descriptors were classified into three grades of suspicion, and the categorization (3, 4A, 4B, 4C, and 5) by sum-up grades showed an incremental increase in the probability of malignancy (p < 0.0001).
The three-grade criteria and categorization by sum-up grades of descriptors appear valid for non-mass enhancement.
分析乳腺非肿块强化描述符在 BI-RADS 第 5 版中与恶性肿瘤的相关性,并建立一个分级系统和描述符分类。
本研究经机构审查委员会批准。共纳入 213 例患者。使用 1.5-T MRI 扫描仪和 16 通道乳腺射频线圈进行乳腺 MRI。两名放射科医生通过共识确定非肿块强化的内部强化和分布。通过活检或手术获得相应的病理诊断。使用 Fisher 精确检验和多变量逻辑回归分析分析每个描述符的恶性肿瘤概率。使用 Fisher 精确检验和多组比较检验分析每个分类的恶性肿瘤概率。
178 个病变为恶性。多变量模型分析表明,内部强化(均匀与其他,p<0.001,不均匀和簇状与环形簇状,p=0.003)和分布(局灶性和线性与节段性,p<0.001)是显著的解释变量。描述符被分为三个可疑等级,通过等级总和进行的分类(3、4A、4B、4C 和 5)显示恶性肿瘤的概率呈递增趋势(p<0.0001)。
非肿块强化的三级标准和等级总和分类似乎是有效的。