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基于对比增强磁共振成像的纹理分析可预测乳腺癌新辅助化疗的治疗反应

[Texture analysis based on contrast-enhanced MRI can predict treatment response to neoadjuvant chemotherapy of breast cancer].

作者信息

Sun S H, Zhou C W, Zhao L Y, Zhang R Z, Ouyang H

机构信息

Department of Diagnostic Imaging, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

出版信息

Zhonghua Zhong Liu Za Zhi. 2017 May 23;39(5):344-349. doi: 10.3760/cma.j.issn.0253-3766.2017.05.005.

DOI:10.3760/cma.j.issn.0253-3766.2017.05.005
PMID:28535650
Abstract

To investigate whether texture analysis based on contrast-enhanced MRI can predict pathological complete response of locally advanced breast cancer undergoing neoadjuvant chemotherapy(NAC). Forty-seven patients with breast cancer undergone neoadjuvant chemotherapy from January 2015 to February 2016 were divided into pathological complete response (pCR) group or non-pathological complete response (non-pCR) group based on surgical pathology. Their parameters of texture analysis based on MRI before neoadjuvant chemotherapy and after 2 cycles of treatment were analyzed. Parameters(Energy, Entropy, Inertia, Correlation, Inverse Difference Moment)before and after 2 cycles of NAC between pCR and non-pCR groups were compared using Student t or Wilcoxon rank sum test. The diagnostic performance of different parameters was judged by the receiver-operating characteristic (ROC) curve analysis. The post-NAC value was significantly different from that of pre-NAC (all <0.05). Pre-treatment parameters (Energy, Entropy, Inertia, Correlation, Inverse Difference Moment) were 78.58×10(-5)(55.64×10(-5), 135.23×10(-5)), 10.06 ± 1.02, 7 993.91±2 428.10, (4.76±0.99) ×10(-5) and (18.10±4.13) ×10(-3) in pCR group, and 76.84×10(-5) (48.68×10(-5), 154.15×10(-5)), 10.28±1.26, 7 184.77 (4 938.03, 9 974.04), (5.21±2.01) ×10(-5) and (17.68±5.87) ×10(-3) in non-pCR group. No significant difference was found between both groups. (>0.05 for all). At the end of the second cycle of NAC, parameters(Energy, Entropy, Inertia, Correlation, Inverse Difference Moment) were (542.11±361.04) ×10(-5,) 7.95±1.28, 16 765.08±97 06.56, (0.43±0.07) ×10(-5,) and (12.18±9.82) ×10(-3) in pCR group, and 133.00×10(-5) (79.80×10(-5,) 239.00×10(-5)), 9.29±1.46, 7 916.64(6 418.89, 10 934.40), (0.38±0.08) ×10(-5) and (14.80±5.06) ×10(-3) in non-pCR group. At the end of the second cycle of NAC, there was significant difference in the parameters (Energy, Entropy, Inertia, Correlation) and Δparameters (ΔEnergy, ΔEntropy, ΔInertia, ΔInverse Difference Moment) between both groups (<0.05 for all). The area under curve (AUC) of post-treatment ΔEntropy was 0.81, which was the largest one among parameters. Sensitivity of ΔEntropy for predicting pCR was 75.0% and specificity was 85.7%, respectively. Texture analysis based on dynamic contrast-enhanced MRI can predict early treatment response in primary breast cancer.

摘要

探讨基于对比增强磁共振成像(MRI)的纹理分析能否预测接受新辅助化疗(NAC)的局部晚期乳腺癌的病理完全缓解情况。将2015年1月至2016年2月期间接受新辅助化疗的47例乳腺癌患者根据手术病理分为病理完全缓解(pCR)组和非病理完全缓解(non-pCR)组。分析其新辅助化疗前及2个周期治疗后的MRI纹理分析参数。采用Student t检验或Wilcoxon秩和检验比较pCR组和non-pCR组在NAC 2个周期前后的参数(能量、熵、惯性、相关性、逆差矩)。通过受试者操作特征(ROC)曲线分析判断不同参数的诊断性能。NAC后的值与NAC前的值有显著差异(均<0.05)。pCR组治疗前参数(能量、熵、惯性、相关性、逆差矩)分别为78.58×10⁻⁵(55.64×10⁻⁵,135.23×10⁻⁵)、10.06±1.02、7993.91±2428.10、(4.76±0.99)×10⁻⁵和(18.10±4.13)×10⁻³,non-pCR组分别为76.84×10⁻⁵(48.68×10⁻⁵,154.15×10⁻⁵)、10.28±1.26、7184.77(4938.03,9974.04)、(5.21±2.01)×10⁻⁵和(17.68±5.87)×10⁻³。两组间差异无统计学意义(均>0.05)。在NAC第2周期结束时,pCR组参数(能量、熵、惯性、相关性、逆差矩)分别为(542.11±361.04)×10⁻⁵、7.95±1.28、16765.08±9706.56、(0.43±0.07)×10⁻⁵和(12.18±9.82)×10⁻³,non-pCR组分别为133.00×10⁻⁵(79.80×10⁻⁵,239.00×10⁻⁵)、9.29±1.46、7916.64(6418.89,10934.40)、(0.38±0.08)×10⁻⁵和(14.80±5.06)×10⁻³。在NAC第2周期结束时,两组间参数(能量、熵、惯性、相关性)及参数变化量(Δ能量、Δ熵、Δ惯性、Δ逆差矩)有显著差异(均<0.05)。治疗后Δ熵的曲线下面积(AUC)为0.81,是所有参数中最大的。Δ熵预测pCR的敏感度和特异度分别为75.0%和85.7%。基于动态对比增强MRI的纹理分析可预测原发性乳腺癌的早期治疗反应。

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