Abstract:

 Objective　To explore the value of "cloud sign" on coronal plane of automated breast volume scanner (ABVS) for the differential diagnosis and prognosis evaluation of breast lesions. Methods　It was a cross-sectional study. In total, we collected 154 cases of breast lesions with Breast Imaging Reporting and Data System (BI-RADS) grade 3 and above which were confirmed by ABVS and surgical pathology in The Third Affiliated Hospital of Guangzhou Medical University from January 2020 to January 2021. The "cloud sign" and "convergence sign" were studied retrospectively, then the correlations between "cloud sign" and patient age, tumor size, benign or malignant tumor, invasion, and lymph node metastasis were analyzed. χ² test was used. The sensitivity, specificity, and accuracy of the "cloud sign" and "convergence sign" on coronal plane in the diagnosis of breast lesions were compared. Results　A total of 154 breast lesions were included in this study, including 42 benign lesions, with an age of (40.5±10.9) years old and a diameter of (26.7±13.7) mm, and 112 malignant lesions, with an age of (55.4±11.4) years old and a diameter of (17.9±11.5) mm. There were statistically significant differences in the occurrence rate of "cloud sign" among different age groups and different tumor diameter groups (P<0.001, P=0.013). The occurrence rate of "cloud sign" was significantly different between the benign and malignant tumor groups [14.3% (6/42) vs. 75.0% (84/112)] (P<0.001). The sensitivity, specificity, and accuracy of "cloud sign" for the diagnosis of benign and malignant tumors were 85.7%, 75.0%, and 77.9%. The occurrence of "cloud sign" was correlated with the positive expressions of estrogen and progesterone receptors (ER and PR) (P=0.049 and 0.005), but had no significant correlation with Ki-67, Cerb-B2, or lymph node metastasis (P=0.649, 1.000, and 0.064). The sensitivity, specificity, and accuracy of "convergence sign" in the diagnosis of breast cancer were 43.8%, 90.5%, and 56.4%. Conclusion　The "cloud sign" on coronal plane of ABVS has definite value in the diagnosis of breast lesions and prediction of ER and PR expressions.

Key words:

Breast lesions, ABVS, Cloud sign, Convergence sign

摘要：

目的　本研究通过分析乳腺肿物的自动乳腺全容积扫描（automated breast volume scanner，ABVS）冠状面声像图特点，初步探讨ABVS冠状面征象“云雾征”对乳腺占位性病变的鉴别诊断及预后评估价值。方法　本文为横断面研究。收集2020年1月至2021年1月在广州医科大学附属第三医院就诊的经ABVS扫查，乳腺影像报告和数据系统（BI-RADS）分类在3类以上，且经过手术病理证实的乳腺肿物共154例。通过回顾性分析乳腺肿物是否出现“云雾征”及“汇聚征”，分别比较“云雾征”与患者年龄、肿物大小、肿物良恶性、是否为浸润性及淋巴结转移之间的相关性，使用χ²检验进行统计分析，对比冠状面“云雾征”及“汇聚征”对乳腺占位性病变诊断的灵敏度、特异度、准确度。结果　本研究一共纳入乳腺肿物154个，包括良性病变42个，年龄（40.5±10.9）岁，肿物长径（26.7±13.7）mm；恶性病变112个，年龄（55.4±11.4）岁，肿物长径（17.9±11.5）mm。“云雾征”出现率在不同年龄组、不同肿物长径组间差异均有统计学意义（P<0.001、P=0.013）；“云雾征”出现率在良性肿物组和恶性肿物组之间差异有统计学意义［14.3%（6/42）比75.0%（84/112）］（P<0.001）。“云雾征”对肿物良恶性诊断的灵敏度、特异度、准确度分为85.7%、75.0%、77.9%。“云雾征”的出现与雌、孕激素受体（ER、PR）表达阳性与否存在相关（P=0.049、0.005），但与Ki-67、Cerb-B2及淋巴结转移没有明显相关性（P=0.649、1.000、0.064）。本组“汇聚征”诊断乳腺癌的灵敏度、特异度、准确度为43.8%、90.5%、56.4%。结论　“云雾征”对乳腺占位性病变的良恶性鉴别及预测ER、PR表达的判断具有一定价值。

关键词:

乳腺肿物, ABVS, 云雾征, 汇聚征