摘要目的 探讨增强CT征象联合纹理分析参数鉴别胰头肿块型胰腺炎与胰头癌的价值.方法 回顾性收集2014年1月至2017年12月间南京中医药大学附属医院及皖南医学院第一附属医院经手术或活检病理证实的21例胰头肿块型胰腺炎与47例胰头导管腺癌患者.统计患者的性别、年龄等一般资料和CT征象,选择胰实质期进行纹理分析.对纹理参数进行最小绝对收缩和选择算子(LASSO)法进行降维处理.根据Shapiro-Wilks正态性检验结果,对连续型变量采用两独立样本t检验或Mann-Whitney U检验.分类变量采用x2或Fisher精确概率检验.运用多因素回归分析,建立CT征象、CT纹理分析、CT征象加纹理分析预测模型.受试者工作特征(ROC)曲线用于评价单个指标和各预测模型的诊断效能,Delong检验用于比较各模型的曲线下面积(AUC)值差异是否有统计学意义.结果 CT征象预测模型由胰实质期病灶CT值和胰管贯穿征组成,纹理分析预测模型由均方根和135°方向低灰度游程优势(low grey level run emphasis_angle 135)组成,二者的AUC值差异无统计学意义(Z=0.150,P＞0.05).CT征象和纹理分析联合的预测模型诊断效能最高(AUC值0.944,敏感度83.0％,特异度95.2％,阳性似然比17.43,阴性似然比0.18),同CT征象预测模型(Z=2.008,P＜0.05)和纹理分析预测模型(Z=2.236,P＜0.05)差异均有统计学意义.结论 CT征象模型和纹理分析模型对胰头肿块型胰腺炎和胰头癌具有一定的鉴别诊断价值,增强CT联合纹理分析模型具有最好的诊断效能,可以进一步提高鉴别诊断能力.

abstractsObjective To explore the value of contrast-enhanced CT combined with texture analysis in differentiating pancreatic cancer from mass-forming pancreatitis in pancreatic head.Methods A retrospective study collected 21 patients with pancreatic head mass-forming pancreatitis confirmed by surgery or biopsy and 47 patients with pancreatic ductal adenocarcinoma confirmed by surgery.The patients visited the Affiliated Hospital of Nanjing University of Chinese Medicine and the First Affiliated Hospital of Wannan Medical College between January 2014 and December 2017.Gender,age and CT findings were collected.The parenchymal phase was selected for texture analysis.The minimum absolute shrinkage and selection operator (LASSO) method was applied for dimensionality reduction.Two independent sample t-tests or Mann-Whitney U test were used for continuous variables based on the Shapiro-Wilks normality test results.Categorical variables were tested by Chi-square or Fisher test.By multivariable regression analysis,CT findings,CT texture analysis,CT findings combined with texture analysis prediction models were established.The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of individual indicators and each prediction model.The Delong test was used to compare the area under the curve (AUC) of each model.Results The CT findings prediction model consisted of CT value of lesion on pancreatic parenchymal phase and pancreatic duct penetrating sign.The texture analysis prediction model consists of root mean square and low grey level run emphasis_angle135.The AUC of them were not statistically different (Z=0.150,P＞0.05).The combined predictive model had the better diagnostic performance (AUC 0.944,sensitivity 83.0％,specificity 95.2％,+ LR 17.43,-LR 0.18) than CT sign prediction model (Z=2.008,P＜0.05) and texture analysis prediction model(Z=2.236,P＜0.05) were significantly different.Conclusions The CT findings model and the texture analysis model have equivalent diagnostic performance in the differentiation of mass-forming pancreatitis and pancreatic cancer.The enhanced CT combined with texture analysis model has the best diagnostic efficiency and can further improve the diagnostic ability.