摘要
目的探讨动态增强磁共振成像(DCE-MRI)预测乳癌新辅助化疗(NAC)后病理完全缓解(pCR)的价值。方法回顾性选取2020年1月—2022年10月于我院接受NAC的乳癌病人108例,病人于NAC前和第2~3周期后各进行1次乳腺MR增强检查。根据术后Miller-Payne病理反应分级,将病人分为pCR组(36例)和non-pCR组(72例),比较两组临床病理资料及影像学特征。采用多因素Logistic回归分析筛选预测pCR的独立影响因素,并构建预测模型。采用受试者工作特征曲线的曲线下面积(AUC)评估模型预测pCR的效能。结果pCR组与non-pCR组比较,雌激素受体、孕激素受体、人表皮生长因子受体2(HER2)、组织学分级、肿瘤强化方式、肿瘤退缩方式、肿瘤最大径变化率(△D%)差异均有显著意义(χ^(2)=-3.12~29.79,t=6.09,P<0.05)。多因素Logistic回归分析显示,△D%(OR=1.046,95%CI=1.019~1.075,P<0.001)和HER2表达状态(OR=0.171,95%CI=0.038~0.758,P=0.020)是pCR的独立预测因素。其中△D%预测pCR的AUC最高(0.813),其次为HER2表达状态(0.660),二者联合诊断的AUC为0.854,灵敏度为80.6%,特异度为80.6%。结论乳癌NAC早期阶段DCE-MRI病灶△D%和HER2表达是预测NAC后pCR的重要指标,可以为临床治疗方案制定提供重要依据。
Objective To evaluate the application of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)in prediction of pathological complete response(pCR)in breast cancer patients treated with neoadjuvant chemotherapy(NAC).Methods A retrospective analysis was performed in 108 breast cancer patients who received NAC in our hospital from January 2020 to October 2022.DCE-MRI examination was performed before and after 2-3 cycles of NAC.The patients were divided into pCR group(36 patients)and non-pCR group(72 patients)according to the postoperative Miller-Payne pathological response gra-ding.The clinicopathological data and imaging characteristics were compared between the two groups.Multivariate logistic regression was used to screen for independent influencing factors for predicting pCR and a prediction model was constructed.The area under receiver operating characteristic curve(AUC)was used to assess the efficacy of the model in pCR prediction.Results Statistically significant differences were found between the pCR and non-pCR groups in estrogen receptor,progesterone receptor,human epidermal growth factor receptor 2(HER2),histological grading,tumor intensification mode,tumor regression mode,and maximum tumor diameter change(△D%)(χ^(2)=-3.12 to 29.79,t=6.09,P<0.05).The multivariate logistic regression analysis showed that△D%(OR=1.046,95%CI=1.019-1.075,P<0.001)and HER2 expression(OR=0.171,95%CI=0.038-0.758,P=0.020)were independent predictors of pCR.The AUC was higher for△D%(0.813)than for HER2 expression(0.660),and their combination had the highest AUC value of 0.854,with a sensitivity of 80.6%and a specificity of 80.6%.Conclusion The△D%and HER2 expression in DCE-MRI are important parameters in pCR prediction at the early stage of NAC for breast cancer,which can provide an important basis for clinical treatment planning.
作者
张琦
林青
王海波
崔春晓
边甜甜
苏晓慧
ZHANG Qi;LIN Qing;WANG Haibo;CUI Chunxiao;BIAN Tiantian;SU Xiaohui(Department of Radiology,The Affiliated Hospital of Qingdao University,Qingdao 266003,China)
出处
《青岛大学学报（医学版）》
CAS
2023年第6期840-844,共5页
Journal of Qingdao University(Medical Sciences)
基金
国家重点研发计划课题(2016YFC1303004)。
关键词
乳腺肿瘤
化学疗法
辅助
磁共振成像
预测
病理完全缓解
breast neoplasms
chemotherapy,adjuvant
magnetic resonance imaging
forecasting
pathologic complete response
