CT检查三段公式法判断食管胃结合部腺癌Siewert分型的临床价值

Clinical value of CT‐based three‐section formula in identification of Siewert types of adeno‐ carcinoma of esophagogastric junction

  • 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 Siewert Ⅰ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Siewert Ⅰ型 3 例,Ⅱ型 49例,Ⅲ型 10例;仲裁后 CT检查三段公式法判定 Siewert Ⅰ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Siewert Ⅰ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 Siewert Ⅰ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 Siewert Ⅱ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 Siewert Ⅲ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。

     

    Abstract: 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 clinicopathological 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 pathological examination. Results of pathological examination came from intraoperative surgical observation 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. The κ≥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 classification. There were 3 cases with AEG of Siewert type Ⅰ, 47 cases with AEG of Siewert type Ⅱ and 12 cases with AEG of Siewert type Ⅲ according to doctor's judgement from the Peking University Cancer Hospital, and there were 3 cases with AEG of Siewert type Ⅰ, 49 cases with AEG of Siewert type Ⅱ and 10 cases with AEG of Siewert type Ⅲ according to doctor's judgement from the First Affiliated Hospital of Amy Medical University, respectively. After arbitration, there were 2 cases with AEG of Siewert type Ⅰ, 48 cases with AEG of Siewert type Ⅱ and 12 cases with AEG of Siewert type Ⅲ determined 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 type Ⅰ, 48 cases with AEG of Siewert type Ⅱ and 12 cases with AEG of Siewert type Ⅲ determined 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 type Ⅰ, 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 type Ⅱ, 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 type Ⅲ, respectively. Conclusion The CT-based three-section formula can be used for identification of Siewert types of AEG, with a high accuracy.

     

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