磁共振弥散峰度成像在胶质瘤分级及肿瘤微观结构评估中的应用研究

发布时间：2018-02-01 00:08

本文关键词： 胶质瘤弥散峰度成像病理分级微观结构　出处：《山东大学》2017年硕士论文　论文类型：学位论文

【摘要】：目的:探讨磁共振弥散峰度成像(diffusional kurtosis imaging,DKI)在脑胶质瘤分级中的应用价值,以及弥散峰度参数与肿瘤病理组织学参数的相关性,以明确DKI是否可以评估脑胶质瘤微观结构的变化。方法:本研究使用3.0 T MR扫描仪,对37名经病理证实为脑胶质瘤的患者(男性23例,女性14例,年龄23岁-66岁,平均年龄47岁)行MRI常规序列及DKI序列扫描。经后处理软件得到各项异性分数(fractional anisotropy,FA)、平均扩散系数(mean diffusivity,MD)以及平均扩散峰度(mean kurtosis,MK)参数图,由一名经验丰富的磁共振诊断医师分别在瘤体、瘤周及对侧正常脑白质(contralateral normal appearing white matter,NAWMc)色画感兴趣区.(region of interest,ROI),以NAWMc为参照对瘤体及瘤周的各参数值进行标准化处理,最终得到标准化参数(nFA、nMD和nMK)。应用独立样本t检验比较标准化参数在高低级别胶质瘤瘤体中的差异。应用受试者工作特性曲线(receiver operating characteristic,ROC)分析标准化参数在鉴别高-低级别胶质瘤中的敏感性及特异性。采用配对t检验比较标准化参数在瘤体及瘤周中的差异。术中神经外科医生根据常规MRI定位分别切取对应的瘤体及瘤周组织,并对其分别进行单克隆Ki-67、CD34 和微管相关蛋白(microtubule-associated protein 2,MAP2)抗体的免疫组化染色。采用Pearson相关分析检测标准化DKI参数值(nFA、nMD及nMK)与病理组织学参数(肿瘤细胞密度,微血管总面积(total vascular area,TVA)以及Ki-67标记指数(labe1ingindex,LI))的相关性。结果:1.高级别胶质瘤瘤体nFA和nMK参数值明显高于低级别胶质瘤(P=0.02和P0.001),而nMD参数值明显低于低级别胶质瘤(P=0.001)。2.在鉴别高低级别胶质瘤ROC曲线分析中,nMK具有最大的曲线下面积(area underthecurve,AUC)(0.889),最高的灵敏度(80%)和特异度(100%),差异具有统计学意义(P值均0.05)。3.nFA和nMD参数值在胶质瘤瘤体及瘤周中有显著性差异(P0.001和P=0.006),nMK参数值在两者间无显著性差异(P=0.28),然而,在低级别胶质瘤中,瘤体nMK值显著低于瘤周(P0.001),在高级别胶质瘤中,瘤体nMK值显著高于瘤周(P=0.002)。4.胶质瘤肿瘤实质nMK值与肿瘤细胞密度(r = 0.596,P=0.006)、TVA(r = 0.764,P0.001)以及Ki-67 LI(r = 0.766,P0.001)均存在显著的正相关关系,然而nFA值仅与肿瘤细胞密度这一个指标存在显著的正相关关系(r = 0.534,P=0.01),nMD 仅与肿瘤细胞密度(r =-0.467,P=0.03)和 Ki-67LI(r =-0.630,P=0.003)存在显著的负相关关系。结论:1.DKI尤其是MK参数在高低级别胶质瘤中存在显著性差异,而且具有较高的特异度和敏感度,与传统的扩散成像参数(FA及MD)相比,可以更好地鉴别高-低级别胶质瘤。2.DKI尤其是MK参数与胶质瘤细胞的增殖活性、肿瘤内微血管密度和形态以及肿瘤细胞密度密切相关,可以作为无创性MRI技术来评估胶质瘤微观结构的变化。
[Abstract]:Objective: to evaluate the value of diffusional kurtosis imaging (DKI) in the classification of gliomas. And the correlation between diffusion kurtosis parameters and tumor histopathological parameters to determine whether DKI can be used to evaluate the microstructural changes of gliomas. Methods: 3. 0 T Mr scanner was used in this study. Thirty-seven patients (23 males and 14 females, aged 23 to 66 years) with pathologically confirmed gliomas were enrolled. The average age was 47 years). MRI routine sequence and DKI sequence scanning were performed. After the post-processing software, the fractional anisotropic fractions were obtained. Mean diffusion coefficient and mean diffusion kurtosis mean kurtosism (MK). By an experienced magnetic resonance diagnostic physician in the tumor. Contralateral normal appearing white matter. The region of interest is drawn by NAW McC. The parameters of the tumor and its circumference are standardized with NAWMc as the reference. Finally, the standardized parameters (nFA) were obtained. NMD and nMK. The differences of standardized parameters in high and low grade gliomas were compared using independent sample t test. Receiver operating characteristic. Rock). The sensitivity and specificity of standardized parameters in differentiating high and low grade gliomas were analyzed. The difference of standardized parameters in tumor and surrounding tumor was compared by paired t test. Neurosurgeon's localization was based on conventional MRI during operation. The corresponding tumor and peri-tumor tissue were removed respectively. The monoclonal Ki-67mCD34 and microtubule-associated protein 2 were used respectively. Pearson correlation analysis was used to detect the normalized DKI parameters, nFA-nMD and nMK) and histopathological parameters (tumor cell density). Total vascular area (TVA) and Ki-67 labeling index (labe1ing index). Results the parameters of nFA and nMK in high grade gliomas were significantly higher than those in low grade gliomas (P 0. 02 and P 0. 001). NMD parameters were significantly lower than those of low grade gliomas (P < 0. 001). In the analysis of ROC curve for differentiating high and low grade gliomas. NMK has a maximum area under the curve (0.889), with the highest sensitivity (80) and specificity (100). The difference was statistically significant (P = 0.05nFA, P = 0.05nFA, P < 0.05) and nMD parameters were significantly different (P 0.001 and P ~ (0.006)) in glioma tumor and its peritumour (P ~ (0.001) and P ~ (0.006)). There was no significant difference in nMK parameter between the two groups. However, in the low grade glioma, the nMK value of the tumor was significantly lower than that of the surrounding tumor (P 0.001), and in the high grade glioma. The nMK value of the tumor was significantly higher than that of the surrounding tumor. The nMK value of the tumor parenchyma and the density of the tumor cell were significantly higher than that of the surrounding tumor (r = 0. 596 P0. 006). TVA(r = 0.764P0.001) and Ki-67 LI(r = 0.766P0.001). However, there was only a significant positive correlation between nFA value and tumor cell density (r = 0.534P0. 01). NMD was only associated with tumor cell density (r = -0.467) and Ki-67LI(r ~ (-0.630). Conclusion: 1. DKI, especially MK parameters, have significant differences in high and low grade gliomas, and have high specificity and sensitivity. Compared with the conventional diffusion imaging parameters (FA and MDD), DKI and MK parameters can be used to identify the proliferation of glioma cells. 2. DKI, especially MK parameters, can be used to differentiate glioma cells from high to low grade gliomas. 2. Microvessel density (MVD), morphology and tumor cell density are closely related to tumor cell density, and can be used as a noninvasive MRI technique to evaluate the microstructural changes of gliomas.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R445.2;R739.41

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