乳腺癌MRI影像组学特征与分子标记物的相关性研究

Correlation between MRI radiomics features and molecular markers in breast cancer

目的:探讨乳腺癌MRI动态增强扫描(DCE-MRI)影像组学特征与病理免疫组化分子标记物的相关性。方法:回顾性分析140例经手术病理证实、行DCE-MRI扫描的乳腺癌患者的病例资料,对所有患者提取乳腺癌病灶的MRI影像组学特征(包括11个形态学特征和13个纹理特征),并采用病理学免疫组化方法检测分子标记物,比较分子标记物表达阳性者与表达阴性者间的形态学特征及纹理特征的差异,对具有组间差异的影像组学特征进行受试者工作特征(ROC)曲线分析。结果:雌激素受体(ER)阳性者的和平均(290.28±28.90)明显高于ER阴性者(266.26±33.76),鉴别病灶是否表达ER时,ROC曲线下面积(AUC)为0.701;孕激素受体(PR)阳性者的圆度(3.99±2.75)明显低于PR阴性者(6.11±4.18),联合圆度、紧致度、实体度这3个影像组学特征鉴别病灶是否表达PR时,AUC为0.678;增殖细胞核抗原(Ki-67)阳性者的和熵(7.76±0.53)明显高于Ki-67阴性者(7.36±0.50),联合和熵、毛刺度、面积、熵这4个影像组学特征鉴别病灶是否表达Ki-67时,AUC为0.767;P53蛋白(P53)阳性者的紧致度(2.56±1.33)明显低于P53阴性者(4.03±2.79),联合紧致度、分形度、实体度、圆度这4个影像组学特征鉴别病灶是否表达P53时,AUC为0.669。结论:乳腺癌MRI影像组学特征与分子标记物的表达具有相关性,可作为临床术前无创性预测乳腺癌分子标记物表达的手段。

Objective:To investigate the correlation between radiomics features of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and pathological immunohistochemical molecular markers in breast cancer.Methods:A total of 140 patients with pathologically confirmed breast cancer were retrospective enrolled in the study.24 radiomics features were extracted from all lesions,including 11 morphologic and 13 texture features.Pathological immunohistochemistry was used to define the molecular markers.The differences in morphological and textural characteristics between the groups with positive and negative expression of molecular markers were compared.The imaging traits with differences between groups were further analyzed by the receiver operating characteristic(ROC)curve.Results:Sum average of ER-positive group(290.28±28.90)were significantly higher than that in ER-negative group(266.26±33.76);the area under the ROC curve(AUC)was 0.701.Circularity of PR-positive group(3.99±2.75)were significantly lower than that in PR-negative group(6.11±4.18).The AUC was 0.678 when combining three imaging features of circularity,compactness and solidity for the classification of PR expression.Sum entropy of Ki-67-positive group(7.76±0.53)were significantly higher than Ki-67-negative group(7.36±0.50).The AUC was 0.767 when combining four imaging features of sum entropy,spiculation,area and entropy for the classification of Ki-67 expression.Compactness of P53-positive group(2.56±1.33)were significantly lower than P53-negative group(4.03±2.79).The AUC was 0.669 when combining four imaging features of compactness,fractal,solidity and circularity for the classification of P53 expression.Conclusion:Radiomics features of breast cancer extracted from DCE-MRI are partly correlated with the expression of molecular markers,which may be useful to non-invasively predict the expression of molecular markers in breast cancer before surgery.