DTI量化分析研究及其临床应用

发布时间：2018-11-27 16:31

【摘要】：弥散张量成像(Diffusion Tensor Imaging,DTI)技术要求从多个方向连续施加弥散梯度编码,既可以度量弥散的大小,又可以考察弥散的方向性,比单幅弥散加权图像更全面地反映出成像体素内弥散的变化情况,可以从微观角度反映脑组织结构的连通性和完整性。DTI技术已在多种中枢神经系统疾病的病灶病理分析中表现出极大的研究价值,可为临床治疗及预后评估提供重要的参考依据,因此越来越受到广泛关注。然而,DTI技术目前尚主要停留在对脑神经科学的研究阶段,其临床化进程主要受到量化分析的瓶颈制约。已有的DTI量化分析方法存在各自的应用局限性,为了建立较为准确又合理的DTI量化分析模型,为疾病提供可靠的病理诊断依据,开展了本论文的研究工作,论文的研究内容主要如下:一方面,对当前广泛研究、普遍认可的一种DTI量化分析方法,即基于体素的全脑分析方法(Voxel-based analysis,VBA),进行算法分析及流程实现,并针对其平滑步骤中的各向同性高斯核尺寸无统一标准而对分析结果产生很大影响的问题,提出了一种适用于DTI图像去噪,又有效保留纤维束特征的各向异性滤波算法,并将其与普通各向异性滤波方法处理的结果进行比较,从主观和客观两个角度,利用图像间的均方根误差值、峰值信噪比、结构相似性指标等多个图像质量评估参数验证了所提出的算法的优越性。另一方面,对近年来逐渐流行的基于纤维束空间统计(Tract-based spatial statistics,TBSS)的DTI量化分析方法进行了研究和实现,并联合基于所提出的各向异性滤波器的VBA方法,建立DTI量化分析融合模型,依据相同的DTI图像预处理过程及相同的图像配准模板,综合两种方法分析结果各自的优势,既可以较为准确地定位脑白质纤维束DTI参数值显著变化的位置,又可以分析病变区域的相关解剖结构变化。基于这一融合量化分析模型,针对多发性硬化症临床DTI数据进行了分析,取得了较为准确合理的分析结果,并发现了视神经纤维束出现的DTI参数显著性变化,说明视神经束可能出现髓鞘微损伤或轴突损伤,符合病人普遍视力减弱的临床症状表现,而这样的病灶在MRI影像上无法看到,这对多发性硬化的早期评估及临床诊断具有十分重要的意义。
[Abstract]:Diffusion Zhang Liang imaging (Diffusion Tensor Imaging,DTI) technology requires continuous application of diffusion gradient coding from multiple directions, which can measure the size of dispersion and investigate its directionality. Compared with a single diffusion-weighted image, it reflects the dispersion in the voxel more comprehensively. It can reflect the connectivity and integrity of brain tissue structure from the microscopic angle. DTI technique has shown great research value in pathological analysis of various central nervous system diseases. It can provide important reference for clinical treatment and prognosis evaluation, so it has attracted more and more attention. However, DTI technology is still mainly in the research stage of brain neuroscience, and its clinical process is mainly restricted by the bottleneck of quantitative analysis. The existing quantitative analysis methods of DTI have their own application limitations. In order to establish a more accurate and reasonable quantitative analysis model of DTI and provide reliable pathological diagnosis basis for diseases, the research work of this paper has been carried out. The main contents of this paper are as follows: on the one hand, an DTI quantitative analysis method based on voxel (Voxel-based analysis,VBA), which is widely studied and widely accepted at present, is used to analyze the algorithm and implement the flow chart. Aiming at the problem that the isotropic Gao Si kernel size in the smoothing step has no uniform standard and has a great influence on the analysis results, an anisotropic filtering algorithm is proposed, which is suitable for denoising DTI images and effectively preserves the characteristics of fiber bundles. The results are compared with those obtained by the conventional anisotropic filtering method. From the subjective and objective aspects, the root mean square error (RMS) and peak signal-to-noise ratio (PSNR) between images are used. Several image quality evaluation parameters, such as structural similarity index, verify the superiority of the proposed algorithm. On the other hand, the DTI quantitative analysis method based on fiber bundle spatial statistics (Tract-based spatial statistics,TBSS) is studied and implemented in recent years, and the VBA method based on the proposed anisotropic filter is combined. The fusion model of DTI quantitative analysis is established. According to the same DTI image preprocessing process and the same image registration template, the advantages of the two methods are synthesised. Not only can the location of the DTI parameters of the white matter bundle change significantly, but also the related anatomical changes in the diseased areas can be analyzed. Based on this fusion quantitative analysis model, the clinical DTI data of multiple sclerosis were analyzed, the results were more accurate and reasonable, and the significant changes of DTI parameters of optic nerve fiber bundle were found. It is suggested that the optic nerve bundle may have myelin microinjury or axonal injury, which is consistent with the clinical symptoms of the general impaired visual acuity of the patient, but such lesions cannot be seen on MRI images. This is of great significance for the early evaluation and clinical diagnosis of multiple sclerosis.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R445.2

【相似文献】