基于全肿瘤MRI筛选胰腺导管腺癌SMAD4表达影像-生物学标志物

Imaging biomarkers of SMAD4 expression in pancreatic ductal adenocarcinoma:a preliminary study with whole-tumor MRI evaluation

目的利用包括影像组学特征在内的全肿瘤MRI评价,结合组织病理学和SMAD4表达分析,寻找预测胰腺导管腺癌(pancreatic ductal adenocarcinoma,PDAC)SMAD4表达的影像-生物学标志物。方法纳入2012年1月至2017年9月复旦大学附属中山医院收治的60例经手术病理证实的PDAC患者。患者术前均用同一台1.5T MRI进行腹部平扫及动态增强检查,并对PDAC进行包括主观评价和影像组学分析的全肿瘤影像学评价。对PDAC进行病理评价,分析SMAD4表达。用最大相关最小冗余(maximum relevance minimum redundancy,mRMR)算法筛选影像组学特征并进行多因素融合建模,获取可能预测SMAD4表达的影像-生物学标志物。结果SMAD4阳性表达者11例(18.3%)、阴性表达者49例(81.7%)。不同SMAD4表达组间性别差异有统计学意义(P=0.012),余临床资料及常规影像学评价指标差异均无统计学意义;SMAD4阴性表达组男性比例明显高于女性(71.4%vs 28.6%)。经基于SMAD4表达的全肿瘤影像组学特征单因素筛选,6个影像组学特征进入多因素影像组学特征融合模型。所得最佳子集模型为门脉期_wavelet-HHL_NGTDM_Contrast+T1WI_wavelet-HHL_GLDM_HighGrayLevelEmphasis,BIC值为33.4,ROC曲线下面积为0.92(P<0.001),预测灵敏度为90.9%、特异度为81.6%,组内预测准确度为83.3%。结论通过包括影像组学特征的全肿瘤MRI评价有望无创获取PDAC病灶SMAD4表达的影像-生物学标志物,具有较好的诊断效能。

Objective To investigate the relationship between imaging features from whole-tumor evaluation with MRI as well as radiomics and SMAD4 expression in pancreatic ductal adenocarcinoma(PDAC)and to determine imaging biomarkers of SMAD4.Methods A total of 60 patients with pathologically confirmed PDAC in Zhongshan Hospital,Fudan University from January 2012 to September 2017 were included.All the patients received abdominal contrast-enhanced MRI examination with the same equipment before surgery.Whole-tumor evaluation including subjective evaluation and radiomics analysis was performed.Sections of specimens were reviewed and SMAD4 expression was evaluated.Univariate analysis,as well as the radiomics were screened by maximum relevance minimum redundancy(mRMR)method,and multi-factor fusion modeling was contracted to find the imaging biomarkers that could predict SMAD4 expression.Results The positive and negative expressions of SMAD4 were found in 11(18.3%)and 49(81.7%)patients,respectively.Only the gender had statistically significant difference between the two groups(P=0.012).There was no significant difference in qualitative features and whole-tumor quantitative features.The proportion of males was significantly higher than that of females in the negative expression group(71.4%vs 28.6%).After single-factor screening of whole-tumor radiomic features basing on SMAD4 expression,6 features entered into multi-factor fusion models.Portal phase_wavelet-HHL_NGTDM_Contrast+T1WI_wavelet-HHL_GLDM_HighGrayLevelEmphasis were enrolled as the best subset model,with the BIC of 33.4,and the area under ROC curve was 0.92(P<0.001)for predicting the expression of SMAD4.The prediction sensitivity and specificity was 90.9%and 81.6%,with the intra-group prediction accuracy of 83.3%.Conclusion Through whole-tumor MRI evaluation with radiomics analysis is expected to noninvasively obtain the imaging-biological markers of SMAD4 expression in PDAC,with good performance.