探讨Bayes判别分析在食管癌淋巴结转移CT诊断中的价值  

The value of Bayes discriminatory analysis in the diagnosis of lymph node metastasis of esophageal cancer

作　　者：邵华飞[1] 刘剑芳[1] 姚丽波[1] 刘戬[1] 屈东[1] 王铸[1] 

机构地区：[1]北京协和医学院中国医学科学院肿瘤医院影像诊断科,北京100021

出　　处：《放射学实践》2015年第8期835-837,共3页Radiologic Practice

基　　金：国家自然科学基金资助项目(61372192)

摘　　要：目的:利用Bayes判别分析初步建立诊断食管癌淋巴结转移的各种CT征象的联合诊断模型。方法:共搜集胸段食管癌208例,将其分为实验组即训练样本(166例,80%)及检验组即验证样本(42例,20%),实验组用以建立诊断方程,检验组用以验证方程。结果:经计算获得的方程为:Y0=-7.499X1+7.957X2+167.761X3-0.087X4+0.459X5-5.528X6-0.711X7-66.080,Y1=-6.697X1+8.231X2+181.686X3-0.106X4+2.219X5-3.331X6-0.124X7-83.183,其中Y0为非转移组,Y1为转移组,X1为淋巴结最大短径,X2为淋巴结最大长径,X3为横纵比,X4为最大截面积,X5为是否边缘模糊,X6为是否中央低密度,X7为是否成簇分布。利用自身检验法所得诊断模型的符合率为87.7%,误判率为12.3%,交叉检验法与自身检验法所得结果相近。当利用验证样本数据代入方程,所得模型诊断符合率为84.7%,误判率为15.3%。结论:通过Bayes判别分析法所建立的不同CT征象对食管癌淋巴结转移的联合诊断模型具有一定的诊断价值,但诊断模型还有待进一步完善。Objective：To construct mechanism model for the diagnosis of LNs （Lymph nodes metastasis）of esophageal cancer by Bayes discriminatory analysis.Methods：208 thoracic esophageal cancer cases were divided into two groups,inclu-ding training set （166 cases）and test set （42 cases）.Training set was used to construct mechanism model,test set was used to analyze its value of diagnosis.Results：Non-metastatic LNs：Y0 = -7.499X1 ＋7.957X2 ＋167.761X3 -0.087X4 ＋0.459X5-5.528X6-0.711X7-66.080;metastatic LNs：Y1= -6.697X1＋8.231X2＋181.686X3-0.106X4＋2.219X5-3.331X6-0.124X7-83.183.X1= short-axis diameter,X2= long-axis diameter,X3= aspect ratio,X4= cross-sectional area, X5= fuzzy rim,X6= cental low density area,X7= clustered distribution.The accuracy was 87.7%,the P （the probability of false prediction）was 12.3%,with similar result by cross validation.For the test set,the accuracy of Bayesian analysis was 84.7%,the P was 15.3%.Conclusion：It is feasible to use Bayes discriminatory analysis for diagnosis of LNs metastasis of esophageal cancer.

关 键 词：体层摄影术 X线计算机 Bayes判别分析 食管癌 淋巴结转移 

分 类 号：R735.1[医药卫生—肿瘤] R730.44[医药卫生—临床医学]