胃间质瘤CT征象与肿瘤危险度分级的关系

发布时间：2018-06-08 08:17

本文选题：胃肠道间质瘤 + 体层摄影术　；参考：《石河子大学》2016年硕士论文

【摘要】：目的:1.探讨胃间质瘤(gastric stromal tumors,GST)的CT征象与肿瘤危险度分级的关系及其价值。2.探讨胃间质瘤(GST)免疫组化指标的表达情况及临床意义。方法:1.回顾性分析106例经CT及病理证实的GST的CT征象,分析内容包括:年龄、性别、瘤体部位、大小、形态、生长方式、边界、密度、实性部分强化程度、有无远处转移。GST的危险度分级标准采用2008版美国国立卫生署(NIH)的危险度分级,将危险度分级分为低危组、中危组和高危组。采用SPSS20.0统计软件,以GST各危险度分级作为因变量(Y),各CT征象为自变量(X)对GST危险度分级进行单因素和多因素Logistic回归分析。先将GST患者的临床资料:年龄、性别,CT征象包括瘤体部位、大小、形态、生长方式、边界、密度、实性部分强化程度、有无远处转移与GST危险度分级进行单因素分析,采用χ2检验,再选择其中有显著意义的因素进行多因素Logistic回归分析。P0.05为差异有统计学意义。2.回顾性分析81例经病理证实的GST病例的常规HE染色切片和Envision二步法免疫组化切片。观察指标包括年龄、性别、瘤体部位、肿瘤大小、核分裂象和免疫组化指标(CD117、CD34、DOG-1、Desmin、Ki-67、S-100和SMA)。GST的危险度分级标准采用2008版美国国立卫生署(NIH)的危险度分级,分为极低危组、低危组、中危组和高危组。采用SPSS20.0统计软件,将GST病例的年龄、性别、瘤体部位、大小、核分裂象和危险度分级与免疫组化指标进行单因素分析,采用χ2检验,P0.05为有统计学意义。结果:1.本组106例GST中,低危组46例,中危组27例,高危组33例。其中,年龄≤50岁21例,51~70岁66例,70岁19例。男性43例,女性63例。发生于胃底40例,胃体52例,胃窦14例。肿瘤大小≤5cm52例,5~10cm43例,10cm11例。形态规则69例,形态分叶37例。腔内生长54例,腔外生长30例,混合生长22例。边界清晰83例,边界模糊23例。密度均匀44例,密度不均62例。实性部分轻度强化33例,中度强化22例,重度强化51例。远处转移8例,腹腔内转移6例,淋巴结转移2例。采用单因素分析,各组GST在肿瘤大小、形态、生长方式、边界、密度、实性部分强化程度、远处转移方面有统计学差异(P0.05),而在年龄、性别、瘤体部位方面无统计学差异(P0.05);采用多分类Logistic回归分析,肿瘤大小、形态和生长方式在预测GST恶性风险方面有统计学差异(P0.05)。2.本组81例GST中,CD117、CD34、DOG-1、Desmin、Ki-67、S-100和SMA的阳性率分别为98.8%、98.7%、91.5%、21.7%、40.3%、25.0%和31.4%。胃间质瘤CD117、CD34、DOG-1、Desmin、S-100和SMA的阳性表达与年龄、性别、瘤体部位、大小、核分裂象、危险度分级之间无统计学差异(P0.05);Ki-67的阳性表达与年龄、性别、瘤体部位之间无统计学差异(P0.05),与大小、核分裂象、危险度分级之间有统计学差异(P0.05)。结论:1.CT作为一种快速、有效的检查方法,在肿瘤大小、形态、生长方式、边界、密度、实性部分强化程度、远处转移方面的征象,有助于评估GST的危险度分级。2.肿瘤大小、形态和生长方式可预测GST的恶性风险,为临床诊断、术前评估、治疗方案制定及预后评价提供一定的帮助。3.CD117,CD34和DOG-1的联合检测对于诊断GST具有重要价值。4.Desmin,S-100和SMA可用于GST的鉴别诊断。5.Ki-67的表达结合GST的大小、核分裂象和危险度分级,有助于评估GST的预后。
[Abstract]:Objective: 1. to explore the relationship between the CT signs of gastric stromal tumors (GST) and the classification of tumor risk and the value of.2. to investigate the expression and clinical significance of the immunohistochemical indexes of gastric stromal tumor (GST). Methods 1. retrospective analysis of the CT signs of GST confirmed by CT and pathology in 106 cases, including age, sex, and tumor site The size, shape, growth mode, boundary, density, solid partial intensification, the risk degree classification of distant metastasis.GST was graded by the 2008 edition of the National Health Department (NIH), and the risk grade was divided into low risk group, middle risk group and high risk group. The SPSS20.0 statistical software was used to classify the risk degree of GST as the dependent variable (Y). A single factor and multiple factor Logistic regression analysis of the GST risk grade were performed for the CT signs (X). First, the clinical data of the GST patients: age, sex, CT signs including the site of the tumor, size, shape, growth mode, boundary, density, solid partial intensification, and a single factor analysis of distant metastasis and GST risk classification. The multiple factor Logistic regression analysis was used by the x 2 test, and the multiple factor Logistic regression analysis was used to analyze.P0.05. The difference was statistically significant. The conventional HE staining section and the Envision two step immunohistochemistry section of 81 cases of pathologically confirmed GST cases were analyzed. The observation indexes included age, sex, tumor size, tumor size, and nuclear division. Image and immunohistochemical markers (CD117, CD34, DOG-1, Desmin, Ki-67, S-100 and SMA) risk grading of.GST was classified by the 2008 edition of the National Health Department (NIH) risk grade, divided into the extremely low risk group, the low risk group, the middle risk group and the high risk group. The SPSS20.0 statistics software was used to use the SPSS20.0 statistics software to make the GST cases age, sex, tumor site, size, mitotic image and danger. A single factor analysis of risk grade and immunohistochemistry, P0.05 was statistically significant by chi 2 test. Results: 1. in 106 cases of GST, 46 in low risk group, 27 in middle risk group and 33 in high risk group. Among them, 21 cases of age 50 years old, 66 cases of 51~70 years old, 70 years 19 cases, male 43 cases, female 63 cases, gastric antrum cases, gastric antral cases. Size less than 5cm52, 5~10cm43 and 10cm11, morphological rules 69 cases, morphological lobulation in 37 cases, 54 cases of intravaginal growth, 30 cases of external growth, 22 cases of mixed growth, 83 cases with clear boundary, 23 cases of boundary blurring. 33 cases of density uniformity, 33 cases of mild strengthening, moderately strengthened 22, severe intensified 51. Metastasis 8 cases, intraperitoneal rotation 6 cases and 2 cases of lymph node metastasis were analyzed by single factor analysis. The size, morphology, growth mode, boundary, density, solid partial enhancement and distant metastasis of GST were statistically different in each group (P0.05), but there was no statistical difference in age, sex, and tumor location (P0.05). Multiple classification Logistic regression analysis, tumor size, and morphology were used. The positive rates of CD117, CD34, DOG-1, Desmin, Ki-67, S-100 and SMA were 98.8%, 98.7%, 91.5%, 21.7%, 40.3%, 25%, and 31.4%. gastric stromal tumors, respectively, in the 81 cases of GST in the prediction of the risk of malignant GST. There was no statistical difference between the division images and the risk grade (P0.05); there was no statistical difference between the positive expression of Ki-67 and the age, sex, and the site of the tumor (P0.05), and there was a statistical difference between the size, the nuclear mitotic image and the risk grade (P0.05). Conclusion: 1.CT is a fast and effective method of examination in the size, shape, growth pattern, and edge of the tumor. The boundary, density, real partial enhancement, and distant metastasis contribute to assessing the size of the GST risk grade.2. tumor, and the morphology and growth patterns can predict the malignant risk of GST, providing some help for clinical diagnosis, preoperative assessment, treatment scheme formulation and prognosis evaluation, and combined detection of CD34 and DOG-1 for the diagnosis of GST. The value of.4.Desmin, S-100 and SMA can be used for the differential diagnosis of GST with the expression of.5.Ki-67, the size of GST, the classification of the mitotic image and the risk degree, which can help to evaluate the prognosis of GST.
【学位授予单位】：石河子大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：R735.2

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