非增强CT纹理特征对超急性期脑梗死溶栓后出血转化的预测价值

Predictive value of non-contrast CT texture analysis for hemorrhage transformation after thrombolysis in hyperacute cerebral infarction

目的:探讨非增强CT(NCCT)纹理参数对超急性期脑梗死溶栓患者出血转化的预测价值。方法:收集行NCCT、DWI,并接受静脉溶栓治疗的超急性期脑梗死患者83例,分为无出血组60例和出血转化组23例。在ADC图上手动勾画ROI,并复制至处理后的NCCT图像上,提取纹理参数。采用Fisher、最小分类误差联合最小平均系数(POE+ACC)、交互信息测度法(MI)和MI+PA+F方法实现降维筛选,绘制ROC曲线获得最强纹理参数。另用B11模块原始分析(RDA)、主成分分析(PCA)、线性分析(LDA)和非线性分析(NDA)计算分类误判率,对最强纹理参数和误判率最低模型降维筛选的纹理参数进行标准化,分别代入MaZda人工神经网络(ANN)分类器进行训练和分类,通过5倍交叉验证评估预测模型性能。结果:10个纹理参数AUC值>0.70。10个最强纹理参数ANN 1-class模型的平均误判率为15.86%。POE+ACC与NDA组合模型误判率最低,为9.64%;POE+ACC降维筛选的ANN 1-class模型的平均误判率为17.11%。结论:NCCT纹理分析有助于早期识别超急性期脑梗死溶栓后发生出血转化的风险人群,基于10个最强纹理参数建立的ANN模型对出血转化具有较高的预测价值。

Objective:To explore the predictive value of non-contrast CT(NCCT)texture parameters for hemorrhage transformation(HT)after thrombolysis in hyperacute cerebral infarction.Methods:Eighty-three patients with hyperacute cerebral infarction who underwent NCCT and DWI scanning and received intravenous thrombolytic therapy were collected.60 cases were divided into non-HT group and 23 cases were divided into HT group.In each group,ROI in ADC map was sketched and replicated to the same layer of NCCT image.Relevant texture parameters were extracted and dimension reduction was achieved by Fisher,POE+ACC,MI,MI+PA+F.The optimal texture parameters were screened and ROC curves were drawn to analyze the prediction efficiency of HT.B11 module RDA,PCA,LDA and NDA were used to analyze the two optimal texture feature subsets.A total of 83 patients were divided into 5 groups,including 4 as training sets and 1 as test set.ANN 1-class and ANN N-class classification training was used to evaluate the performance of the classifier combined with 5-fold cross validation.Results:AUC values of 10 texture parameters were greater than 0.70,showing good prediction effect.The average misjudgement rate of ANN 1-class model based on the best 10 texture parameters was 15.86%.The combination of POE+ACC and NDA had the lowest misjudgment rate(9.64%).The average misjudgement rate of ANN 1-class model based on POE+ACC was 17.11%.Conclusions:NCCT texture analysis is helpful for early identification of people at risk of HT after thrombolytic therapy,and ANN model based on the best 10 texture parameters has better prediction effect on HT.