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MRI影像学特征预测乳腺癌新辅助化疗疗效的可行性 被引量:12

Feasibility of MRI Features in Predicting Efficacy of Neoadjuvant Chemotherapy for Breast Cancer
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摘要 目的探讨MRI特征用于预测局部进展期乳腺癌新辅助化疗(NAC)疗效的可行性。资料与方法纳入经诊治并行MR动态增强检查的乳腺癌患者66例,行NAC 8个周期结束后手术切除病灶,并根据Miller-Payne病理评级分为组织学显著反应组与非显著反应组。对治疗前及分别行NAC 2个周期和4个周期的3次MR图像提取灰度、形态、纹理3种影像学特征,并研究其用于预测NAC疗效的可行性。结果66例患者中,20例(30.3%)呈现病理组织学显著反应。病理组织学显著反应组与非显著反应组间NAC 4个周期后的影像学特征差异有统计学意义(P<0.05)。LASSO回归分析显示,NAC 4个周期后的影像学特征对NAC疗效预测价值较好(ROC曲线下面积为0.701)。结论NAC 4个周期后的MRI特征可用于预测局部进展期乳腺癌患者NAC的疗效。 Purpose To investigate the feasibility of MRI features in predicting the efficacy of neoadjuvant chemotherapy(NAC)for patients with breast cancer in locally advanced phase.Materials and Methods Sixty-six patients with breast cancer who received diagnosis and treatment and dynamic MRI enhanced examination were included.After 8 cycles of NAC,lesions were surgically resected and the patients were divided into major histological response and non-major histological response group in line with Miller-Payne pathology grading.Three imaging characteristics namely gray level,morphology and texture were extracted before surgery and two as well as 4 cycles NAC,and its feasibility to predict NAC efficacy was also analyzed.Results Among the 66 patients,20 cases(30.3%)were represented by major responses of pathologic histology.Difference of imaging characteristics after 4 cycles NAC between major response and non-major response group was of statistical significance(P<0.05).LASSO regression analysis showed that imaging characteristics after 4 cycles NAC were of predictive value to NAC efficacy(area under the curve of ROC was 0.701).Conclusion MRI characteristics after 4 cycles NAC could be used to predict NAC efficacy in patients with breast cancer in locally advanced phase.
作者 单慧明 周靖宇 谢婷婷 黄嵘 石桥 冯飞 成官迅 SHAN Huiming;ZHOU Jingyu;XIE Tingting;HUANG Rong;SHI Qiao;FENG Fei;CHENG Guanxun(Department of Radiology,Peking University Shenzhen Hospital,Shenzhen 518000,China)
出处 《中国医学影像学杂志》 CSCD 北大核心 2019年第12期905-909,913,共6页 Chinese Journal of Medical Imaging
基金 北京大学深圳医院科研项目(LCYJ2017006)
关键词 乳腺肿瘤 磁共振成像 化学疗法 辅助 治疗结果 Breast neoplasms Magnetic resonance imaging Chemotherapy,adjuvant Treatment outcome
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