弥散张量成像在中枢神经系统中的应用

在磁共振成像(MRI)研究中，弥散张量成像(DTI)是最近几年提出并迅速发展的一个研究方向，本介绍了弥散张量成像的原理以及国际上主要的研究热点，并结合实际介绍了弥散张量成像在中枢神经系统(CNS)中的应用。     

磁共振弥散张量成像在临床诊疗中的应用

磁共振弥散张量成像(diffusion tensor imaging,DTI)作为一种功能磁共振成像(magnetic resonance imaging,MRI),在临床诊疗中发挥了重要作用.本文先介绍了DTI临床应用的各个领域,重点阐述了其在脑部疾病的应用,后指出临床应用中存在的问题,并对其前景进行了展望.     

正常成人近段坐骨神经的弥散张量成像**

背景：弥散张量成像及神经纤维束示踪的出现为外周神经细微结构的显示及定量分析提供了新的方法。 目的：前瞻性分析健康成人大腿近段坐骨神经纤维束示踪、弥散张量成像的可行性及最佳成像参数。 方法：采用单次激发自旋回波-平面回波技术对28名健康志愿者双侧坐骨神经进行弥散张量成像及神经纤维束示踪,b值分别为1 200,1 400,1 600 s/mm2。 结果与结论：弥散张量成像及神经纤维束示踪成功者26名,成功率93%,神经纤维束示踪图上能清晰显示近段坐骨神经,与T1WI上解剖图像融合较好。两侧坐骨神经具有相同的弥散特征：随着b 值增加,信噪比逐渐减少,b值为1 200 s/mm2,信噪比值最大为142.72±32.25,神经纤维束长度最长,所占体素最大,但不同b值的弥散张量参数无差异(P > 0.05),且两侧坐骨神经弥散张量参数无差异。说明正常成人大腿近段坐骨神经的弥散张量成像及经纤维束示踪是可行的,可清晰显示坐骨神经走行及弥散特征;最佳b值为1 200 s/mm2。 关键词：弥散张量成像;坐骨神经;磁共振成像;神经纤维束示踪术;成年人 doi:10.3969/j.issn.1673-8225.2012.09.030     

弥散张量成像对常规性临床应用的初步建立和实现

根据目前国际上被广泛认可的磁共振弥散张量成像(DT-MRI或DTI)处理和表达方法,自行开发出基于PC机的程序(DTI Toolbox based on MATLAB),有效结合第三方软件,为弥散张量成像在常规性临床诊断初步建立有效和完整的测量与分析处理体系,主要包括数据获取、图像预处理、张量可视化、以及脑神经纤维成像。为DTI进入常规性临床应用和检查提供了初步的方案和测量分析体系。     

大脑锥体束华勒氏变性影像学研究进展

原发性脑损伤可导致病灶远端的锥体束发生华勒氏病变,基于磁共振技术(magnetic resonance imaging,MRI)的弥散加权成像(diffusion weighted imaging,DWI)、弥散张量成像(diffusion tensor imaging,DTI)等成像技术对于华勒氏变性的检测有不同的特点和优势,本文针对华勒氏变性各个阶段不同的影像学表现进行了综述,并对临床检测早期华勒氏变性做出了指导。     

采用偏微分方程的磁共振弥散张量各向异性扩散滤波去噪

弥散张量磁共振成像(DTI)是无创研究大脑白质结构及其他人体纤维状组织结构的主要工具。由于合成DTI数据的弥散加权成像数据(DWI)易受噪声干扰,需要有效去噪以保证DTI数据精度和后续应用的实现。使用各向异性扩散滤波理论,综合考虑各方向通道DWI数据的几何形态和结构特点,重构其特征向量和特征值,获得统一平滑的结构张量,以期在有效去噪的基础上最大程度地保持DTI数据几何结构和特征。利用所提出方法在合成弥散张量数据上进行仿真,并在真实脑部DTI数据上进行实验。仿真和实验结果表明,该方法能有效减少噪声对DTI数据的影响,较之现有的时频分析去噪方法,可更准确地恢复DTI数据,减少主分量方向的偏差和部分各向异性值的误差。     

磁共振弥散张量成像在颅脑疾病诊治中的应用

磁共振弥散张量成像(difusion tensor imaging,DTl)是功能磁共振成像的一个重要组成部分,它利用水分子弥散在不均质组织中具有各向异性的特征,通过改变弥散敏感梯度方向,测得体素内水分子在各个方向上的弥散强度,在三维空间定量分析组织内水分子的弥散运动,利用所得多种参数值成像.DTI主要用于评价组织结构的完整性、病理改变及组织结构和功能的关系.现主要就DTI成像在脑白质显示、发育及神经外科的临床应用等方面作一综述.     

变形磁共振弥散张量图像的三维非线性配准

对于磁共振弥散张量成像的图像变形,采用3D非线性图像配准的方法来纠正.在基准磁共振图像和变形弥散张量图像分割的基础上,以互信息为相似性测度,分别采用单级与双级B样条变换来纠正畸变.弥散张量成像由涡流及组织磁敏感性差异引起的几何畸变得到了明显纠正,且与单级B样条变换相比,双级B样条变换更具有鲁棒性.采用3D非线性图像配准可对变形图像进行纠正,明显提高了图像质量.     

磁共振弥散张量成像的脑白质纤维优化重建

磁共振弥散张量成像(DTI)可对大脑白质纤维束的三维几何结构进行无创研究,其主要方法为DTI纤维追踪成像.研究打破现有DTI纤维追踪成像从初始种子区域逐步追踪增长的框架,提出脑白质的纤维优化重建方法,从全局角度描述追踪纤维,通过其对弥散倾向和几何结构的优化估计,重构最优纤维路径.结果表明,该方法可提供连接两个感兴趣区域(ROI)的有效和对称连接,同时通过全局优化手段消除累积噪声及局部随机噪声,提高长距离成像的可靠性;在人工合成数据集和真实人体数据集中均能较好成像,较之现有纤维追踪成像具有更高的可靠性和可重复性.     

抽动秽语综合征的神经影像学研究

抽动秽语综合征(TS)是神经精神疾病,病程反复,近几年发病率升高,临床缺乏客观指标评价TS及估计预后,最近解剖学和神经影像学研究提示,TS患者较正常人基底节区及额叶、边缘系统神经影像学有改变.笔者就TS患者的MRI体积测量及弥散张量成像研究,介绍了TS患者脑体积及弥散特性改变,阐述TS严重程度及疾病过程,更好地为临床有...     

Prognosis of cervical myelopathy based on diffusion tensor imaging with artificial intelligence methods

Diffusion tensor imaging (DTI) has been proposed for the prognosis of cervical myelopathy (CM), but the manual analysis of DTI features is complicated and time consuming. This study evaluated the potential of artificial intelligence (AI) methods in the analysis of DTI for the prognosis of CM. Seventy‐five patients who underwent surgical treatment for CM were recruited for DTI imaging and were divided into two groups based on their one‐year follow‐up recovery. The DTI features of fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were extracted from DTI maps of all cervical levels. Conventional AI models using logistic regression (LR), k‐nearest neighbors (KNN), and a radial basis function kernel support vector machine (RBF‐SVM) were built using these DTI features. In addition, a deep learning model was applied to the DTI maps. Their performances were compared using 50 repeated 10‐fold cross‐validations. The accuracy of the classifications reached 74.2% ± 1.6% for LR, 85.6% ± 1.4% for KNN, 89.7% ± 1.6% for RBF‐SVM, and 59.2% ± 3.8% for the deep leaning model. The RBF‐SVM algorithm achieved the best accuracy, with sensitivity and specificity of 85.0% ± 3.4% and 92.4% ± 1.9% respectively. This finding indicates that AI methods are feasible and effective for DTI analysis for the prognosis of CM.     

Diffusion tensor imaging of normal and injured developing human brain - a technical review

The application of diffusion tensor imaging (DTI) to the evaluation of developing brain remains an area of active investigation. This review focuses on the changes in DTI parameters which accompany both brain maturation and injury. The two primary pieces of information available from DTI studies-water apparent diffusion coefficient and diffusion anisotropy measures-change dramatically during development, reflecting underlying changes in tissue water content and cytoarchitecture. DTI parameters also change in response to brain injury. In this context, not only does DTI offer the possibility of detecting injury earlier than conventional imaging methods, but also appears more sensitive to disruption of white matter than any other imaging method. DTI offers unique insight into brain injury and maturation, and does so in a fashion that can be readily applied in a clinical setting.     

Diffusion weighted imaging and neuropsychological correlates in adults with mild traumatic brain injury

Diffusion Tensor Imaging (DTI) is increasingly being used as a research tool in mild Traumatic Brain Injury (mTBI). This article reviews the concepts of diffusion tensor imaging, neuropsychological testing and results to date when applied to mTBI in adults. DTI is being used in conjunction with neuropsychological and electrophysiological measures to provide improved structural/functional correlations of mTBI. Future directions and applications of DTI in mTBI research are suggested.     

Shape-Adaptive DCT for Denoising of 3D Scalar and Tensor Valued Images

During the last ten years or so, diffusion tensor imaging has been used in both research and clinical medical applications. To construct the diffusion tensor images, a large set of direction sensitive magnetic resonance image (MRI) acquisitions are required. These acquisitions in general have a lower signal-to-noise ratio than conventional MRI acquisitions. In this paper, we discuss computationally effective algorithms for noise removal for diffusion tensor magnetic resonance imaging (DTI) using the framework of 3-dimensional shape-adaptive discrete cosine transform. We use local polynomial approximations for the selection of homogeneous regions in the DTI data. These regions are transformed to the frequency domain by a modified discrete cosine transform. In the frequency domain, the noise is removed by thresholding. We perform numerical experiments on 3D synthetical MRI and DTI data and real 3D DTI brain data from a healthy volunteer. The experiments indicate good performance compared to current state-of-the-art methods. The proposed method is well suited for parallelization and could thus dramatically improve the computation speed of denoising schemes for large scale 3D MRI and DTI.     

Anatomical analysis of an aye-aye brain (Daubentonia madagascariensis, primates: Prosimii) combining histology, structural magnetic resonance imaging, and diffusion-tensor imaging

This report presents initial results of a multimodal analysis of tissue volume and microstructure in the brain of an aye-aye (Daubentonia madagascariensis). The left hemisphere of an aye-aye brain was scanned using T2-weighted structural magnetic resonance imaging (MRI) and diffusion-tensor imaging (DTI) prior to histological processing and staining for Nissl substance and myelinated fibers. The objectives of the experiment were to estimate the volume of gross brain regions for comparison with published data on other prosimians and to validate DTI data on fiber anisotropy with histological measurements of fiber spread. Measurements of brain structure volumes in the specimen are consistent with those reported in the literature: the aye-aye has a very large brain for its body size, a reduced volume of visual structures (V1 and LGN), and an increased volume of the olfactory lobe. This trade-off between visual and olfactory reliance is likely a reflection of the nocturnal extractive foraging behavior practiced by Daubentonia. Additionally, frontal cortex volume is large in the aye-aye, a feature that may also be related to its complex foraging behavior and sensorimotor demands. Analysis of DTI data in the anterior cingulum bundle demonstrates a strong correlation between fiber spread as measured from histological sections and fiber spread as measured from DTI. These results represent the first quantitative comparison of DTI data and fiber-stained histology in the brain.     

Association between sociability and diffusion tensor imaging in BALB/cJ mice

The purpose of this study was to use high-resolution diffusion tensor imaging (DTI) to investigate the association between DTI metrics and sociability in BALB/c inbred mice. The sociability of prepubescent (30-day-old) BALB/cJ mice was operationally defined as the time that the mice spent sniffing a stimulus mouse in a social choice test. High-resolution ex vivo DTI data on 12 BALB/cJ mouse brains were acquired using a 9.4-T vertical-bore magnet. Regression analysis was conducted to investigate the association between DTI metrics and sociability. Significant positive regression (p < 0.001) between social sniffing time and fractional anisotropy was found in 10 regions located in the thalamic nuclei, zona incerta/substantia nigra, visual/orbital/somatosensory cortices and entorhinal cortex. In addition, significant negative regression (p < 0.001) between social sniffing time and mean diffusivity was found in five areas located in the sensory cortex, motor cortex, external capsule and amygdaloid region. In all regions showing significant regression with either the mean diffusivity or fractional anisotropy, the tertiary eigenvalue correlated negatively with the social sniffing time. This study demonstrates the feasibility of using DTI to detect brain regions associated with sociability in a mouse model system.     

基于扩散张量的脑白质内神经纤维束的可视化技术

介绍了在功能磁共振成像的研究中发展非常快的扩散张量成像技术的基本原理，以及如何利用扩散张量数据来重建脑白质内的神经纤维柬图像。其中主要介绍了白质束成像技术及其优缺点，并且分析了神经纤维束可视化技术的应用前景及其局限性。     

Diffusion tensor imaging in fixed brain tissue at 7.0 T

The purpose of this work is to assess the feasibility of performing quantitative in vitro brain tissue diffusion tensor imaging (DTI) measurements and to examine their comparability to in vivo measurements. DTI of fixed tissue at high field strength is potentially a very valuable investigative tool as very high spatial resolution can be achieved. DTI was applied to human and mouse brain fixed tissue samples as well as in vivo measurements of the mouse brain. T(1) and T(2) relaxography of the fixed tissue samples was also performed to provide further characterization of the tissue. All experiments were performed at 7 T. The fractional anisotropy (FA) of the human fixed brain tissue samples is found to be higher in the corpus callosum than in the occipital white matter region, consistent with in vivo measurements reported in the literature. Our FA measurements of the corpus callosum of a mouse brain are also found to be the same both in vitro and in vivo. This preliminary work supports the use of DTI in both fixed human and fixed animal brain tissue as a valid investigative tool. With the increased availability of brain banks in different brain disorders, DTI in fixed tissue may prove to be a very useful method for the study of white matter abnormalities.     

A Modular Framework for Development and Interlaboratory Sharing and Validation of Diffusion Tensor Tractography Algorithms

This Technical Note describes a novel modular framework for development and interlaboratory distribution and validation of 3D tractography algorithms based on in vivo diffusion tensor imaging (DTI) measurements. The proposed framework allows individual MRI research centers to benefit from new tractography algorithms developed at other independent centers by "plugging" new tractography modules directly into their own custom DTI software tools, such as existing graphical user interfaces (GUI) for visualizing brain white matter pathways. The proposed framework is based on the Java 3D programming platform, which provides an object-oriented programming (OOP) model and independence of computer hardware configuration and operating system. To demonstrate the utility of the proposed approach, a complete GUI for interactive DTI tractography was developed, along with two separate and interchangeable modules that implement two different tractography algorithms. Although the application discussed here relates to DTI tractography, the programming concepts presented here should be of interest to anyone who wishes to develop platform-independent GUI applications for interactive 3D visualization.     

磁共振弥散张量成像的质量控制

磁共振弥散张量成像（DTI）是诊断和分析神经系统疾病的重要方法,但其目前发展受空间分辨率、信噪比及图像质量等限制。本文对近年来MRI系统基础质量保证方法、DTI参数定性测量方法、用于扩散成像的软件方法以及不同纤维跟踪方法等进行综述。