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乳腺癌DBT征象与不同分子亚型之间的相关性
引用本文:宁艳云,崔曹哲,武慧慧,张鹏丽,马彦云.乳腺癌DBT征象与不同分子亚型之间的相关性[J].影像诊断与介入放射学,2020(1):54-59.
作者姓名:宁艳云  崔曹哲  武慧慧  张鹏丽  马彦云
作者单位:山西医科大学医学影像学院;山西医科大学第一医院放射科
基金项目:山西省科技厅重点研发计划基金项目(201803D31100);山西省卫计委科研基金项目(2017042);山西医科大学科技创新基金项目(01201514)
摘    要:目的探讨乳腺癌数字乳腺断层摄影(DBT)征象与不同分子亚型相关性。方法回顾性分析经病理证实的260例乳腺癌患者的资料。采用单因素和多因素Logistic回归分析,以评估乳腺癌DBT征象与其分子亚型的关联。结果Luminal A、B型多表现为不规则的毛刺状肿块,毛刺与Luminal A型(OR 3.77,P<0.001)关系密切;肿块边缘清楚、形态规则高度提示三阴型(OR 12.53,P<0.001);HER-2型(OR 2.42,P=0.015)、Luminal B型(OR 1.69,P=0.047)与微钙化相关,其中单纯钙化多见于HER-2型(P=0.005),肿块伴钙化多见于Luminal B型(P=0.017);不同亚型间钙化形态有统计学差异(P=0.027),Luminal A型(12,52.2%)多表现为无定形钙化,HER-2型(10,55.6%)多表现为细小多形性钙化。结论乳腺癌某些DBT征象可用于预测特定的亚型,并帮助指导临床治疗策略。

关 键 词:数字乳腺断层摄影  乳腺癌  分子亚型

Association between digital breast tomosynthesis characteristics and different molecular subtypes of breast cancer
NING Yan-yun,CUI Cao-zhe,WU Hui-hui,ZHANG Peng-li,MA Yan-yun.Association between digital breast tomosynthesis characteristics and different molecular subtypes of breast cancer[J].Journal of Diagnostic Imaging & Interventional Radiology,2020(1):54-59.
Authors:NING Yan-yun  CUI Cao-zhe  WU Hui-hui  ZHANG Peng-li  MA Yan-yun
Affiliation:(Department of Medical Imaging,Shanxi Medical University,Shanxi 030001,China)
Abstract:Objective To investigate the correlation between digital breast tomosynthesis (DBT) features of breast cancer with molecular subtypes. Methods A total of 260 patients with breast cancer confirmed by surgical biopsy were analyzed retrospectively. Univariate and multivariate logistic regression analyses were performed to assess the association between DBT features and the subtypes. Results The most common DBT findings were irregular spiculated masses for luminal A and B subtype. Spiculated masses were strongly associated with the luminal A subtype (OR 3.77, P<0.001). Regular masses with circumscribed margins were highly suggestive of the triple-negative subtype (OR 12.53, P<0.001). Microcalcifications were associated with HER-2 overexpression (OR 2.42, P=0.015) and luminal B (OR 1.69, P=0.047) subtype including calcifications alone for HER-2 overexpression subtype (P=0.005) and masses with calcifications for luminal B subtype (P=0.017). Statistical significance was found in calcification morphology (P=0.027) with amorphous calcifications in the luminal A subtype (12, 52.2%), fine pleomorphic calcifications in the HER-2 overexpression subtype (10, 55.6%). Conclusion Certain DBT features in breast cancer can be used to predict the molecular subtypes and guide treatment planning.
Keywords:Digital breast tomosynthesis  Breast cancer  Molecular subtype
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