功能磁共振和脑电神经成像技术与大脑刺激相结合的研究进展

随着对神经机制问题阐述水平的迅速提高,所应用的神经成像技术、方法及各种工具的复杂程度也在不断提高．一方面是神经成像技术本身的不断发展,另一方面则是大脑直接刺激与神经成像技术同步记录方法的发展．经颅磁刺激-功能磁共振成像同步技术(TMS-fMRI)和经颅磁刺激-脑电技术(TMS-EEG)能为研究大脑网络的功能和有效连通性提供技术手段,该技术在多种认知领域的发展和应用,为神经科学、认知心理学、神经信息学等学科的研究者对人脑的研究开启了多条通道,更加有利于深入地理解人类大脑的工作机制．     

功能磁共振视网膜皮层映射成像在视觉系统研究中的应用

功能磁共振视网膜皮层映射成像能提供关于视觉皮层的丰富信息,是研究生理及病理状态下视觉皮层定位以及功能特性的强有力工具。本文就该成像技术的原理、应用及前景作一综述。     

磁共振扩散加权成像在肺癌中的临床应用

影像学检查在肺癌的诊断和分期中起到了至关重要的作用,目前电子计算机体层成像(CT)和正电子发射断层成像技术以及磁共振成像(MRI)已经被广泛的应用于肺癌的分期和疗效评估。其中MRI不仅能提供形态学信息,近年来发展起来的磁共振功能成像能提供更多的功能信息。磁共振扩散加权成像(Diffusion-weighted imaging,DWI)是最常应用于临床的磁共振功能成像序列。最初主要应用在神经系统,随着磁共振成像序列的不断发展以及软硬件的开发应用,其在腹部和盆腔的应用也日趋广泛,然而胸部DWI成像仍待普及和更多认识。本文就肺部DWI成像在良恶性病变鉴别、恶性肿瘤的筛查、分期、以及治疗疗效评估方面进行综述。     

MRI的临床应用进展

磁共振成像(magnatic resonance imaging,MRI)是现代影像医学的重要组成部分之一。随着硬件和软件方面的不断改进和发展,MRI日益得到广泛的临床应用。MRI的临床应用主要有五个方面：磁共振水成像、磁共振血管成像、磁共振功能成像、磁共振波谱以及磁共振造影介入技术。MRI可提供病变组织在形态学改变和生理功能方面的信息,因此MRI已成为进行疾病诊断和鉴别诊断的重要工具,亦是介入技术导引的手段。由于MRI具有无创性和信息容量多等点,使其能在生物学医学领域内作深入的研究。MRI将提供生物化学的信息。总之,MRI是现代医学的新领域,代表着影像医学的发展方向。     

光纤记录系统在神经科学研究中的应用

近年来,光纤记录系统作为一种记录自由活动动物大脑特定核团神经元活动的技术,在神经科学领域研究中广受欢迎,是研究动物神经元活动与行为关系的重要技术手段.本文综述了单通道光纤记录系统、多通道光纤记录系统及多色光纤记录系统在认知、行为学、心理学等神经科学基础及神经疾病中的应用,并简述了光纤记录系统与功能磁共振成像技术结合、光...     

脑功能磁共振成像的研究现状

脑功能磁共振成像是近年来磁共振成像技术的一项新发展,为从单一形态学研究到形态与功能相结合的系统研究开辟了一条崭新的道路。本文主要介绍了人脑的功能活动磁共振成像的概念、原理、试验设计、临床的研究现状。     

多功能磁共振造影剂研究进展

磁共振成像技术因对人体无创、任意方向断层扫描三维图像且分辨率较高、提供形态与功能两方面诊断评价等突出优点,成为了临床上用于疾病诊断的重要手段之一。临床上使用磁共振造影剂可以提高成像的分辨率和灵敏度,提高图像质量,增强对比度和可读性。但是,各种成像技术由于实现原理不同,具有各自的优势和缺陷,靠传统单一的诊断模式无法提供疾病的全面信息,因而在对各种复杂疾病进行诊断时会受到一定的限制。因此,将磁共振成像与其他成像技术如CT成像、超声成像等联合起来使用,则可以达到优势互补的效果,能为疾病的临床诊断提供更快捷精确的信息,同时可将磁共振成像与各种治疗方式结合在一起,即开发基于磁共振成像的诊断治疗一体化试剂,以实现对疾病的即时治疗和实时监控。本文主要介绍了磁共振成像造影剂的原理和种类,并且综述了目前国内外在基于磁共振成像的多功能造影剂/诊疗制剂这一领域的研究进展,最后就未来可能的研究方向进行了展望。     

高时空分辨的脑功能光学成像研究进展

脑功能成像技术对深入分析脑的信息加工过程,揭示脑的高级功能至关重要,是目前国际研究热点,已经在神经科学研究和神经系统疾病的临床诊断方面取得了很大的进展.已有脑功能成像技术如:功能磁共振成像(fMRI)、正电子断层成像(PET)、脑电图(EEG)、脑磁图(MEG)等等,虽然已被成功用于脑功能研究,但是目前这些方法也存在着时间或空间分辨率不够的局限.比较而言,光学成像方法表现出其独特魅力.激光散斑衬比成像和内源信号光学成像由于能提供空间取样、时间分辨率及空间分辨率三者的最佳组合和不需加入外源性标记物等特点,与其他脑功能成像技术相比其优势可能更为突出.具有较高的时间和空间分辨率的这两种脑功能光学成像技术及其应用都取得了重大发展,成为研究脑皮层功能构筑和脑病理生理的有力工具.但是目前这两种成像方法也面临着一些挑战.     

研究报告: 小动物高分辨扩散磁共振成像数据分析方法

扩散磁共振成像(dMRI)是一种非侵入性的、能提供生物体内水分子扩散运动相关信息的成像技术,可用于检测神经纤维微观结构的变化．dMRI的出现为大脑结构与功能研究提供了全新的检测手段．过去的20年中,dMRI在实验方法和临床应用上均取得了重大进展．然而dMRI应用在基于动物模型的临床前脑成像研究中却并不常见．本文针对dMRI在临床前脑成像研究中的应用,建立了系列针对小动物高分辨dMRI数据的分析方法：a．构建了大鼠高分辨dMRI图像模板;b．实现了适用于小动物研究的基于体素的统计分析(VBA)方法与基于纤维束的空间统计分析(TBSS)方法;c．实现了小动物脑白质纤维束的确定性与概率性跟踪．这些方法的实现不仅能为小动物脑dMRI研究提供统一的图像模板与完善的计算方法,还将大大促进dMRI技术在小动物脑成像研究中的应用．     

编者按: 脑成像与脑网络

揭示脑的奥秘是人类面临的最大挑战之一。神经元是构成神经系统结构与功能的基本单位。神经元与神经元之间通过突触实现信息交互,并构成神经环路或神经网络。神经环路有局部的,也有跨脑区或长程的,甚至全脑尺度的。神经环路则是脑实现神经信息处理的基本单元。若干神经环路构成脑网络。脑网络研究已经成为脑功能与脑疾病研究领域的热点。 在国家自然科学基金委员会和科技部“973计划”等项目的支持下,我国科学家在这一领域已经开展了卓有成效的工作。2011年第393次香山科学会议“脑网络组及其临床应用的前沿科学问题”曾对此进行过比较深入的研讨。为促进对该领域现状及发展的了解,本期汇集了2篇述评和2篇研究论文,作为脑成像与脑网络专题发表,以飨读者。 利用9.4T功能磁共振成像(fMRI)获得轻度麻醉状态下大鼠静息状态及刺激激活的数据,通过互相关分析构建节点之间的相关系数矩阵并计算相应的网络参数,赖永秀等人报道了大鼠感觉运动系统静息态脑网络的研究成果,发现感觉运动系统在静息态时的脑网络具有小世界属性。 扩散磁共振成像(dMRI)的出现为大脑结构与功能研究提供了全新的检测手段,雷皓等报道了小动物高分辨扩散磁共振成像数据分析方法,为小动物脑dMRI研究提供了统一图像模板与完善的计算方法,对于检测神经纤维微观结构的变化,以及临床诊断,将具有极其重要的意义。 神经环路功能变化的实时在体监测是研究脑网络不可或缺的手段,曾绍群等评述了基于声光偏转器的快速无惯性随机扫描双光子显微成像技术的研究进展及发展趋势,指出该技术的进一步发展将为神经活动观测提供一种全新的方法,从而极大地推动脑科学研究的发展。 针对哺乳动物全脑的神经元网络成像,龚辉等从空间分辨率、探测范围、数据配准和成像速度等方面评述了光学显微水平全脑成像方法的研究进展,并讨论所面临的挑战。他们指出,要在全脑尺度获取突起水平分辨率的结构与功能数据,光学成像方法最为成熟。华中科技大学研制的MOST系统,率先获得了一系列高分辨率的完整大脑解剖数据集,该成果将在神经元网络的构建和脑功能与疾病研究中发挥重要作用。 我们期待更多、更好的有关脑成像与脑网络的论文发表,以更广泛和深入地促进我国脑科学研究领域的学术交流。     

使用非侵入的神经影像方法解码人类思维

随着神经影像技术的发展,“读脑机器”在不久的将来可能会变成现实。在众多实现“读脑机器”的技术中,使用基于血氧水平依赖的脑功能磁共振技术的神经解码方法则是非常有希望的一种技术。在本报告中,我们结合我们实验室最近开展的两个研究工作,说明了使用功能磁共振技术进行神经解码的一般方法及其应用。本领域的发展很快,所有的这些工作让我们对发明“读脑机器”充满了期待。但是,与此同时,我们也应该看到目前还存在着很多技术的局限和挑战。本报告的最后,我们也对这些局限和挑战进行了一些讨论。     

Integration of Diffusion Magnetic Resonance Tractography into tomotherapy radiation treatment planning for high-grade gliomas

IntroductionFractionated radiotherapy in brain tumors is commonly associated with several detrimental effects, largely related to the higher radiosensitivity of the white matter (WM) with respect to gray matter. However, no dose constraints are applied to preserve WM structures at present. Magnetic Resonance (MR) Tractography is the only technique that allows to visualize in vivo the course of WM eloquent tracts in the brain. In this study, the feasibility of integrating MR Tractography in tomotherapy treatment planning has been investigated, with the aim to spare eloquent WM regions from the dose delivered during treatment.MethodsNineteen high grade glioma patients treated with fractionated radiotherapy were enrolled. All the patients underwent pre-treatment MR imaging protocol including Diffusion Tensor Imaging (DTI) acquisitions for MR Tractography analysis. Bilateral tracts involved in several motor, language, cognitive functions were reconstructed and these fiber bundles were integrated into the Tomotherapy Treatment planning system. The original plans without tracts were compared with the optimized plans incorporating the fibers, to evaluate doses to WM structures in the two differently optimized plans.ResultsNo significant differences were found between plans in terms of planning target volume (PTV) coverage between the original plans and the optimized plans incorporating fiber tracts. Comparing the mean as well as the maximal dose (Dmean and Dmax), a significant dose reduction was found for most of the tracts. The dose sparing was more relevant for contralateral tracts (P < 0.0001).ConclusionThe integration of MR Tractography into radiotherapy planning is feasible and beneficial to preserve important WM structures without reducing the clinical goal of radiation treatment.     

Atlas-Guided Cluster Analysis of Large Tractography Datasets

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.     

Deep White Matter in Huntington's Disease

White matter (WM) abnormalities have already been shown in presymptomatic (Pre-HD) and symptomatic HD subjects using Magnetic Resonance Imaging (MRI). In the present study, we examined the microstructure of the long-range large deep WM tracts by applying two different MRI approaches: Diffusion Tensor Imaging (DTI) -based tractography, and T2*weighted (iron sensitive) imaging. We collected Pre-HD subjects (n = 25), HD patients (n = 25) and healthy control subjects (n = 50). Results revealed increased axial (AD) and radial diffusivity (RD) and iron levels in Pre-HD subjects compared to controls. Fractional anisotropy decreased between the Pre-HD and HD phase and AD/RD increased and although impairment was pervasive in HD, degeneration occurred in a pattern in Pre-HD. Furthermore, iron levels dropped for HD patients. As increased iron levels are associated with remyelination, the data suggests that Pre-HD subjects attempt to repair damaged deep WM years before symptoms occur but this process fails with disease progression.     

Spatio-Temporal Correlation Tensors Reveal Functional Structure in Human Brain

Resting state functional magnetic resonance imaging (fMRI) has been commonly used to measure functional connectivity between cortical regions, while diffusion tensor imaging (DTI) can be used to characterize structural connectivity of white matter tracts. In principle combining resting state fMRI and DTI data could allow characterization of structure-function relations of distributed neural networks. However, due to differences in the biophysical origins of their signals and in the tissues to which they apply, there has been no direct integration of these techniques to date. We demonstrate that MRI signal variations and power spectra in a resting state are largely comparable between gray matter and white matter, that there are temporal correlations of fMRI signals that persist over long distances within distinct white matter structures, and that neighboring intervoxel correlations of low frequency resting state signals showed distinct anisotropy in many regions. These observations suggest that MRI signal variations from within white matter in a resting state may convey similar information as their corresponding fluctuations of MRI signals in gray matter. We thus derive a local spatio-temporal correlation tensor which captures directional variations of resting-state correlations and which reveals distinct structures in both white and gray matter. This novel concept is illustrated with in vivo experiments in a resting state, which demonstrate the potential of the technique for mapping the functional structure of neural networks and for direct integration of structure-function relations in the human brain.     

Diffusion signal in magnetic resonance imaging: origin and interpretation in neurosciences

Diffusion Magnetic Resonance Imaging provides images of unquestionable diagnostic value. It is commonly used in the assessment of stroke and in white matter fiber tracking, among other applications. The diffusion coefficient has been shown to depend on cell concentration, membrane permeability, and cell orientation in the case of white matter or muscle fiber tracking; yet a clear relation between diffusion measurements and known physiological parameters is not established. The aim of this paper is to review hypotheses and actual knowledge on diffusion signal origin to provide assistance in the interpretation of diffusion MR images. Focus will be set on brain images, as most common applications of diffusion MRI are found in neuroradiology. Diffusion signal does not come from two intra- or extracellular compartments, as was first assumed. Restriction of water displacement due to membranes, hindrance in the extracellular space, and tissue heterogeneity are important factors. Unanswered questions remain on how to deal with tissue heterogeneity, and how to retrieve parameters less troublesome to work with from biological and clinical points of view. Diffusion quantification should be done with care, as many variables can lead to variation in measurements.     

White Matter Changes of Neurite Density and Fiber Orientation Dispersion during Human Brain Maturation

Diffusion tensor imaging (DTI) studies of human brain development have consistently shown widespread, but nonlinear increases in white matter anisotropy through childhood, adolescence, and into adulthood. However, despite its sensitivity to changes in tissue microstructure, DTI lacks the specificity to disentangle distinct microstructural features of white and gray matter. Neurite orientation dispersion and density imaging (NODDI) is a recently proposed multi-compartment biophysical model of brain microstructure that can estimate non-collinear properties of white matter, such as neurite orientation dispersion index (ODI) and neurite density index (NDI). In this study, we apply NODDI to 66 healthy controls aged 7–63 years to investigate changes of ODI and NDI with brain maturation, with comparison to standard DTI metrics. Using both region-of-interest and voxel-wise analyses, we find that NDI exhibits striking increases over the studied age range following a logarithmic growth pattern, while ODI rises following an exponential growth pattern. This novel finding is consistent with well-established age-related changes of FA over the lifespan that show growth during childhood and adolescence, plateau during early adulthood, and accelerating decay after the fourth decade of life. Our results suggest that the rise of FA during the first two decades of life is dominated by increasing NDI, while the fall in FA after the fourth decade is driven by the exponential rise of ODI that overcomes the slower increases of NDI. Using partial least squares regression, we further demonstrate that NODDI better predicts chronological age than DTI. Finally, we show excellent test—retest reliability of NODDI metrics, with coefficients of variation below 5% in all measured regions of interest. Our results support the conclusion that NODDI reveals biologically specific characteristics of brain development that are more closely linked to the microstructural features of white matter than are the empirical metrics provided by DTI.     

Neuroimaging Evidence of Major Morpho-Anatomical and Functional Abnormalities in the BTBR T+TF/J Mouse Model of Autism

BTBR T+tf/J (BTBR) mice display prominent behavioural deficits analogous to the defining symptoms of autism, a feature that has prompted a widespread use of the model in preclinical autism research. Because neuro-behavioural traits are described with respect to reference populations, multiple investigators have examined and described the behaviour of BTBR mice against that exhibited by C57BL/6J (B6), a mouse line characterised by high sociability and low self-grooming. In an attempt to probe the translational relevance of this comparison for autism research, we used Magnetic Resonance Imaging (MRI) to map in both strain multiple morpho-anatomical and functional neuroimaging readouts that have been extensively used in patient populations. Diffusion tensor tractography confirmed previous reports of callosal agenesis and lack of hippocampal commissure in BTBR mice, and revealed a concomitant rostro-caudal reorganisation of major cortical white matter bundles. Intact inter-hemispheric tracts were found in the anterior commissure, ventro-medial thalamus, and in a strain-specific white matter formation located above the third ventricle. BTBR also exhibited decreased fronto-cortical, occipital and thalamic gray matter volume and widespread reductions in cortical thickness with respect to control B6 mice. Foci of increased gray matter volume and thickness were observed in the medial prefrontal and insular cortex. Mapping of resting-state brain activity using cerebral blood volume weighted fMRI revealed reduced cortico-thalamic function together with foci of increased activity in the hypothalamus and dorsal hippocampus of BTBR mice. Collectively, our results show pronounced functional and structural abnormalities in the brain of BTBR mice with respect to control B6 mice. The large and widespread white and gray matter abnormalities observed do not appear to be representative of the neuroanatomical alterations typically observed in autistic patients. The presence of reduced fronto-cortical metabolism is of potential translational relevance, as this feature recapitulates previously-reported clinical observations.     

Diffusion Tensor Imaging in brain tumors: A study on gliomas and metastases

PurposeTo explore the role of Diffusion Tensor Imaging in preoperative glioma grading, as well as in differentiation between gliomas and metastatic brain tumors. We measured diffusion tensor variables in enhancement and edema regions, which were compared between the different subject groups.Materials and methodsWe performed DTI in 48 patients (11 Low Grade Gliomas, 27 High Grade Gliomas, 10 Single Metastatic brain tumors). We measured FA, λ1, λ2, λ3, ADC, Cl, Cp, Cs, RA, and VR in enhancing portions of tumors and edema regions. Additionally, ratios of enhancement to edema values were created for each variable.ResultsIn peritumoral edema, Cl and RA were proven to be significantly different in pair-wise comparisons, in addition to ADC, Cp, Cs and VR in enhancement regions. Enhancement to edema values were significantly different as well.ConclusionDiffusion tensor indices could be used for the differentiation between low and high grade gliomas, as well as for distinction between gliomas and metastases.     

Structural Integrity of the Contralesional Hemisphere Predicts Cognitive Impairment in Ischemic Stroke at Three Months

After stroke, white matter integrity can be affected both locally and distally to the primary lesion location. It has been shown that tract disruption in mirror’s regions of the contralateral hemisphere is associated with degree of functional impairment. Fourteen patients suffering right hemispheric focal stroke (S) and eighteen healthy controls (HC) underwent Diffusion Weighted Imaging (DWI) and neuropsychological assessment. The stroke patient group was divided into poor (SP; n = 8) and good (SG; n = 6) cognitive recovery groups according to their cognitive improvement from the acute phase (72 hours after stroke) to the subacute phase (3 months post-stroke). Whole-brain DWI data analysis was performed by computing Diffusion Tensor Imaging (DTI) followed by Tract Based Spatial Statistics (TBSS). Assessment of effects was obtained computing the correlation of the projections on TBSS skeleton of Fractional Anisotropy (FA) and Radial Diffusivity (RD) with cognitive test results. Significant decrease of FA was found only in right brain anatomical areas for the S group when compared to the HC group. Analyzed separately, stroke patients with poor cognitive recovery showed additional significant FA decrease in several left hemisphere regions; whereas SG patients showed significant decrease only in the left genu of corpus callosum when compared to the HC. For the SG group, whole brain analysis revealed significant correlation between the performance in the Semantic Fluency test and the FA in the right hemisphere as well as between the performance in the Grooved Pegboard Test (GPT) and theTrail Making Test-part A and the FA in the left hemisphere. For the SP group, correlation analysis revealed significant correlation between the performance in the GPT and the FA in the right hemisphere.