摘要
目的探讨CT常规特征及纹理特征预测胰腺神经内分泌肿瘤(PNET)病理分级的应用价值。方法回顾性分析经手术病理证实的102例PNET患者的CT常规特征及纹理特征。观察测量肿瘤的最大径、钙化、囊变坏死、胰管扩张、强化方式及CT值等常规特征并进行相关计算,再采用ITK-SNAP软件勾画感兴趣区,A.K.软件提取纹理特征,并筛选出动、静脉期纹理特征。应用独立样本t检验及卡方检验等比较低级别组与高级别组患者CT特征的差异。采用二元Logistic回归筛选独立预测因素,绘制受试者工作特征曲线(ROC)比较两种特征预测病理分级的效能。结果本组102例,其中低级别组(G1)41例,高级别组(G2、G3)61例。不同组别间常规特征中最大径、强化方式、囊变及钙化的差异有统计学意义(P<0.05);静脉期相对强化程度值(PVP)及CT比值(VCR)差别有统计学意义(P<0.05)。纹理特征中动脉期的频率大小、协方差、体素数,静脉期的平均偏差、最小强度、协方差、频率大小、体素数、体素灰度值和,2组间差别有统计学意义(P<0.05)。二元Logistic回归分析表明,肿瘤最大径(P<0.05)为独立预测因素。基于CT常规特征的模型(模型1),曲线下面积(AUC)为0.797,敏感度为61%,特异度为92.5%;基于纹理特征的模型(模型2),AUC值为0.784,敏感度为61%,特异度为90%;联合模型1+2,AUC值为0.917,敏感度为83.1%,特异度为90%。结论肿瘤最大径为预测PNET病理分级的独立预测因素。CT常规特征及纹理特征都可用于预测PNET的病理分级,联合两种特征共同分析可提高诊断效能。
Objective To evaluate the accuracy of conventional and texture features to predict the pathological grades of pancreatic neuroendocrine tumors(PNET).Methods 102 cases of pancreatic neuroendocrine tumors,confirmed by postoperative pathology,were retrospectively enrolled in our study.Conventional imaging features including maximum diameter,calcification,cystic necrosis,pancreatic duct dilatation,enhancement pattern,CT values were measured and calculated.The region of interest(ROI)were manually drawn by using ITK Snap software and A.K.software was used for texture extraction in the arterial phase and the venous phase.Independent sample t-test and chi-square test were used to compare the CT features between the low-grade group and the high-grade group.Binary Logistic regression was used to screen independent assessment factors.ROC curve was drawn to compare the efficacy of the two characteristics in predicting the pathological classification.Results There were 41 cases of pancreatic neuroendocrine tumor in the low-grade group and 61 cases of pancreatic neuroendocrine carcinoma in the high-grade group.The differences of conventional characteristics between the two groups including maximum diameter,enhancement pattern,cystic degeneration,calcification showed statistical significance(P<0.05).There were statistically significant differences(P<0.05)in Relative venous phase(PVP)and venous CT ratio(VCR).The texture parameters including frequency size,variance and value count in arterial phase and mean deviation,min intensity,variance,frequency size,volume count,voxel value sum in venous phase were significantly different between the two groups(P<0.05).Binary logistic regression analysis showed that the maximum tumor diameter(P<0.05)was an independent predictor.In the model 1 based on the conventional CT characteristics,the AUC value was 0.797,the sensitivity was 61%,and the specificity was 92.5%.In the model 2 based on texture features,the AUC value was 0.784,the sensitivity was 61%,and the specificity was 90%.Combined analysis of model 1 and 2 showed that AUC value was 0.917,sensitivity was 83.1%,and specificity was 90%.Conclusion Maximum tumor size was an independent predictor of pathologic grade of pancreatic neuroendocrine tumors.Conventional CT features and texture features can be used to predict the pathological classification of pancreatic neuroendocrine tumors.Conjoint analysis of the two features can improve the diagnostic efficacy and provide imaging evidence in order to provide options for clinical therapy.
作者
刘群
单海荣
史红媛
徐青
LIU Qun;SHAN Hairong;SHI Hongyuan(Department of Medical Imaging,the First Affiliated Hospital Of Nanjing Medical University/Jiangsu Province Hospital,Nanjing 210029,P.R.China)
出处
《临床放射学杂志》
CSCD
北大核心
2020年第11期2232-2237,共6页
Journal of Clinical Radiology
作者简介
通讯作者:徐青
