诊断学理论与实践2017，Vol.16Issue(6)：601-606,6.DOI:10.16150/j.1671-2870.2017.06.008
MRI图像纹理分析在胰腺神经内分泌肿瘤病理分级中的应用研究
Application of texture analysis of MR imagings in grading of pancreatic neuroendocrine neoplasms
摘要
Abstract
Objective:To investigate the application of texture analysis derived from MR imaging in grading of pancreatic neuroendocrine neoplasms (PNENs).Methods:MR imagings of 64 patients with pathologically confirmed PNENs admitted to Ruijin Hospital were enrolled.Texture features were extracted from manually drawn ROIs by using MaZda software,and were selected according to the pathological grade by the feature selection methods.Statistical methods including Fisher coefficient(Fisher),classification error probability combined with average correlation coefficients(POE+ACC),mutual information (MI),and combination of above three methods (FPM) were used to classify the pathological grading of PNENs.The results were shown by misclassification rate.Results:For feature selection methods,FPM had the lowest misclassification rate.Among the statistical methods,the misclassification of NDA was lower than those of RDA,PCA,and LDA.Among the MRI sequences,the ADC map obtained the lowest misclassification rate of 9.38％(6/64),but there was no significant difference between sequences.Conclusions:Texture analysis of MR imaging can be used as an assistant tool for preoperative grading of pancreatic neuroendocrine neoplasms,and when it comes to statistical methods,FPM has the lowest misclassification rate.关键词
胰腺神经内分泌肿瘤/磁共振成像/纹理分析/特征选择/病理分级Key words
Pancreatic neuroendocrine neoplasms/MRI/Texture analysis/Feature selection/Tumor grade分类
医药卫生引用本文复制引用
李旭东,林晓珠,房炜桓,谢环环,陈楠,柴维敏,严福华,陈克敏..MRI图像纹理分析在胰腺神经内分泌肿瘤病理分级中的应用研究[J].诊断学理论与实践,2017,16(6):601-606,6.基金项目
国家自然科学基金资助项目(81201145) （81201145）
