摘要
目的:利用数字乳腺断层摄影(digital breast tomosynthesis,DBT)评估病变边缘方面的优势,探讨DBT图像的毛刺征象与Ki-67增殖指数的关系。方法:回顾并纳入2022年3月—2023年4月于郑州大学第一附属医院就诊的99例浸润性乳腺癌患者的DBT影像学资料,所有患者在DBT图像中均表现为毛刺型肿块。对99例乳腺毛刺型肿块的肿块大小、毛刺的长度和宽度、肿瘤边缘毛刺的覆盖情况及毛刺的数量进行分析,并收集患者的一般临床资料,比较各参数在Ki-67增殖指数之间的差异。采用多因素logistic回归分析Ki-67增殖指数的独立预测因素,并采用受试者工作特征曲线评价其诊断效能。结果:Ki-67增殖指数高低患者之间DBT图像毛刺特征,包括毛刺长度与毛刺宽度比较差异均有统计学意义(P<0.05),而毛刺数量、患者年龄、绝经状态及肿块大小差异无统计学意义(P=0.060,P=0.175,P=0.507,P=0.050)。多因素logistic回归模型分析显示,毛刺长度(OR=0.036,P<0.001)、毛刺宽度(OR=8.829,P<0.001)为Ki-67增殖指数的独立预测因素。将毛刺长度与毛刺宽度联合后,诊断效能最好,AUC为0.897。结论:乳腺癌DBT图像中的毛刺征分析可作为一种无创预测恶性肿瘤增殖活性的方法,从而判断患者的预后。
Objective:To utilize the advantages of digital breast tomosynthesis(DBT)in assessing lesion margins and to explore the relationship between the burr sign of DBT images and Ki-67 proliferation index.Methods:DBT imaging data of 99 patients with invasive breast cancer who in the First Affiliated Hospital of Zhengzhou University from March 2022 to April 2023 were retrospectively included,and all of the patients showed a burr-type mass in DBT images.Lump size,length and width of the burr,coverage of the burr at the tumor margin,and number of burrs were analyzed in 99 cases of breast burr-type lumps,and general clinical data of the patients were collected to compare the differences of each parameter between the Ki-67 proliferation index expression states.Independent predictors of Ki-67 proliferation index were analyzed using multifactorial logistic regression,and the diagnostic efficacy was evaluated using subject working curves.Results:The differences in DBT image burr characteristics including burr length and burr width were statistically significant when comparing Ki-67 proliferation index high patients and low patients(P<0.05),whereas the differences in the number of burrs,age of patients,menopausal status,and size of the mass were not statistically significant(P=0.060,P=0.175,P=0.507,and P=0.050,respectively).Multifactorial logistic regression model analysis showed that burr length(OR=0.036,P<0.001)and burr width(OR=8.829,P<0.001)were independent predictors of Ki-67 proliferation index.The best diagnostic efficacy was achieved when combining burr length with burr width,with an AUC of 0.897.Conclusion:Burr sign analysis in DBT images of breast cancer can be used as a noninvasive predictor of the proliferative activity of malignant tumors to determine patient prognosis.
作者
刘思腾
于湛
王洁洁
LIU Siteng;YU Zhan;WANG Jiejie(Department of Radiology,The First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,Henan Province,China)
出处
《肿瘤影像学》
2024年第4期412-417,共6页
Oncoradiology
