摘要
目的探讨CT检查三段公式法判断食管胃结合部腺癌(AEG)Siewert分型的临床价值。方法采用回顾性描述性研究方法。收集2019年1月至2021年1月国内2家医学中心收治的62例(北京大学肿瘤医院33例、陆军军医大学第一附属医院29例)AEG患者的临床病理资料;男53例,女9例;年龄为(66±9)岁。患者行CT检查获取冠状位和轴位图像,确定肿瘤上下缘及食管胃结合部3个层面,导入公式进行Siewert分型。观察指标:(1)CT检查和病理学检查结果。(2)医师间CT检查结果一致性判断。(3)CT检查结果与病理学检查结果一致性判断。病理学检查结果为大体病理学检查和术后组织病理学检查结果。正态分布的计量资料以x±s表示,计数资料以绝对数或构成百分比表示。一致性系数Kappa(κ)评价阅读者间诊断的一致性,κ≥0.75为一致性非常好,0.40<κ<0.75为一致性良好,κ≤0.40为一致性差。Wilcoxon秩和检验评价CT检查三段公式法与病理学检查结果之间是否具有统计学差异,以组织病理学检查结果为标准,计算CT检查三段公式法诊断的灵敏度、特异度和准确率及其95%可信区间。结果(1)CT检查和病理学检查结果:62例患者均顺利进行CT检查,获得冠状位和轴位图像确定肿瘤上下缘及食管胃结合部层面并进行Siewert分型。62例患者经北京大学肿瘤医院判定SiewertⅠ型3例,Ⅱ型47例,Ⅲ型12例;经陆军军医大学第一附属医院判定SiewertⅠ型3例,Ⅱ型49例,Ⅲ型10例;仲裁后CT检查三段公式法判定SiewertⅠ型2例,Ⅱ型48例,Ⅲ型12例。病理学T分期:T1期7例,T2期10例,T3期24例,T4a期14例,T4b期7例。62例患者病理学检查结果为SiewertⅠ型2例,Ⅱ型48例,Ⅲ型12例。(2)医师间CT检查结果一致性判断:2位医师运用CT检查三段公式法判定Siewert分型一致性良好(κ=0.74,P<0.001)。(3)CT检查结果与病理学检查结果一致性判断:以病理学检查的Siewert分型为参照,CT检查三段公式法判断Siewert分型准确率为90.3%,一致性良好(κ=0.73,P<0.001)。CT检查三段公式法判断SiewertⅠ型的灵敏度为66.7%(95%可信区间为20.8%~93.9%),特异度为100.0%(95%可信区间为93.9%~100.0%);判断SiewertⅡ型的灵敏度为97.7%(95%可信区间为88.2%~99.6%),特异度为72.2%(95%可信区间为49.1%~87.5%);判断SiewertⅢ型的灵敏度为73.3%(95%可信区间为48.0%~89.1%),特异度为97.9%(95%可信区间为88.9%~99.9%)。结论CT检查三段公式法可用于判断AEG的Siewert分型,具有较高准确率。
Objective To investigate the clinical value of computer tomography(CT)-based three-section formula in identification of Siewert types of adenocarcinoma of esophagogastric junction(AEG).Methods The retrospective and descriptive study was conducted.The clinicopatho-logical data of 62 AEG patients who were admitted to two medical centers,including 33 patients from Peking University Cancer Hospital and 29 patients from the First Affiliated Hospital of Amy Medical University,between January 2019 and January 2021 were collected.There were 53 males and 9 females,aged(66±9)years.All patients underwent CT examination to obtain the coronal and axial images and determine the upper and lower edges of the tumor and the esophagogastric junction,which were imported into the formula for Siewert classification.Observation indicators:(1)results of CT examination and pathological examination;(2)consistence of judgements for CT examination between doctors;(3)consistence of judgements between CT examination and patholo-gical examination.Results of pathological examination came from intraoperative surgical observa-tion and postoperative histopathological examination.Measurement data with normal distribution were represented as Mean±SD,and count data were described as absolute numbers or percentages.The consistency coefficient Kappa(κ)was used to evaluate the consistency of diagnosis between resear-chers.Theκ≥0.75 was regarded as excellent consistency,0.40<κ<0.75 as good consistency,κ≤0.40 as poor consistency.Wilcoxon rank sum test was used to evaluate the statistical difference between results of the CT-based three-section formula method and the pathological examination.Taking the results of histopathological examination as standard,the sensitivity,specifi-city,accuracy and 95%confidence interval of the CT-based three-section formula method were calculated.Results(1)Results of CT examination and pathological examination:all the 62 patients underwent CT examination successfully to obtain the coronal and axial images and determine the upper and lower edges of the tumor and the esophagogastric junction,which were used for Siewert classifica-tion.There were 3 cases with AEG of Siewert typeⅠ,47 cases with AEG of Siewert typeⅡand 12 cases with AEG of Siewert typeⅢaccording to doctor's judgement from the Peking University Cancer Hospital,and there were 3 cases with AEG of Siewert typeⅠ,49 cases with AEG of Siewert typeⅡand 10 cases with AEG of Siewert typeⅢaccording to doctor's judgement from the First Affiliated Hospital of Amy Medical University,respectively.After arbitration,there were 2 cases with AEG of Siewert typeⅠ,48 cases with AEG of Siewert typeⅡand 12 cases with AEG of Siewert typeⅢdetermined by the CT based three-section formula.There were 7 cases of stage T1,10 cases of stage T2,24 cases of stage T3,14 of stage T4a and 7 cases of stage T4b of pathological T staging.There were 2 cases with AEG of Siewert typeⅠ,48 cases with AEG of Siewert typeⅡand 12 cases with AEG of Siewert typeⅢdetermined by pathological examination.(2)Consistence of judgements for CT examination between doctors:the consistency of Siewert classification determined by CT-based three-section formula between 2 doctors was good(κ=0.74,P<0.001).(3)Consistence of judgements between pathological examination and CT examination:with Siewert classification determined by pathological examination as reference,the accuracy of Siewert classification determined by CT based three-section formula was 90.3%(κ=0.73,P<0.001).The sensitivity and specificity of CT-based three-section formula were 66.7%(95%confidence interval as 20.8%-93.9%)and 100.0%(95%confidence interval as 93.9%-100.0%)for AEG of Siewert typeⅠ,97.7%(95%confidence interval as 88.2%-99.6%)and 72.2%(95%confidence interval as 49.1%-87.5%)for AEG of Siewert typeⅡ,73.3%(95%confidence interval as 48.0%-89.1%)and 97.9%(95%confidence interval as 88.9%-99.9%)for AEG of Siewert typeⅢ,respectively.Conclusion The CT-based three-section formula can be used for identification of Siewert types of AEG,with a high accuracy.
作者
刘一婷
李晓明
李晓婷
李佳铮
何蒙
陕飞
蔡萍
李子禹
唐磊
Liu Yiting;Li Xiaoming;Li Xiaoting;Li Jiazheng;He Meng;Shan Fei;Cai Ping;Li Ziyu;Tang Lei(Department of Radiology,Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education),Peking University Cancer Hospital&Institute,Beijing 100142,China;Department of Radio-logy,the First Affiliated Hospital of Amy Medical University,Chongqing 400038,China;Gastrointestinal Cancer Center,Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education),Peking University Cancer Hospital&Institute,Beijing 100142,China)
出处
《中华消化外科杂志》
CAS
CSCD
北大核心
2022年第1期135-142,共8页
Chinese Journal of Digestive Surgery
基金
北大百度基金(2020BD027)
北京市自然科学基金(Z180001,Z200015)
北京市属医学科研院所公益发展改革试点项目(2019-1)。
关键词
食管肿瘤
胃肿瘤
食管胃结合部
腺癌
多排螺旋CT检查
多平面重建
Siewert分型
Esophageal neoplasms
Stomach neoplasms
Esophagogastric junction
Adenocarcinoma
Multi-detector computed tomography
Multiplanar recon-struction
Siewert classification