核磁共振水分子扩散张量成像中基于广义Fibonacci数列的扩散敏感梯度磁场方向分布方案

为了准确得到人体内水分子各向异性扩散信息,在核磁共振扩散张量成像及高角分辨率扩散成像实验中,需要在众多空间均匀分布的方向上依次施加扩散敏感梯度磁场,测量水分子在不同方向上的扩散系数.目前方向分布方案的缺点有方向数目不连续、均匀性有待提高及部分方向数据的损坏会影响整个数据集等.本文以广义Fibonacci数列为基础,提出新的可以产生连续方向数目的扩散敏感梯度磁场方向分布方案,整个方案的方向均匀性较好,数据集内的部分数据仍然具有很好的空间均匀性,而且本方案中相邻两个扩散敏感梯度磁场方向接近相反,可以减小快速变化的高强度梯度磁场产生的涡流对结果的影响.     

扩散张量成像的人脑模板构建

扩散张量脑模板包含丰富的大脑白质组织信息,在空间标准化或者脑图谱创建中具有重要价值,然而基于扩散张量模型构建的脑模板精度不高,特别是在脑部复杂的神经元微观结构区域中应用受到限制.针对这一问题,研究者们提出了基于高分辨率扩散成像构建大脑模板的方法.本文对使用扩散张量成像方法进行脑模板构建的研究进展进行了综述,首先介绍了扩散张量脑模板构建的发展进程,阐述了脑模板构建中解决的技术问题及同时存在的局限性;接着详细论述了基于扩散频谱成像及高角度分辨率扩散成像构建脑模板的不同方法间的差异,并总结了这些研究方法取得的重要进展;最后通过分析目前研究进展提出该研究问题中存在的不足以及未来的发展趋势.     

低场MRI系统中线扫描扩散张量成像方法的研究

磁共振扩散张量成像(DTI)是在扩散加权成像(DWI)基础上发展起来的一种新型技术,可以无创伤显示脑白质纤维,诊断脑白质病变. 但是由于各种原因,DTI一般只在超导高场磁共振成像(MRI)仪器上进行,这就限制了这一重要诊断手段临床应用的广泛性. 本文在低场磁共振成像系统上应用线扫描实现了扩散张量成像,并测量了健康志愿者大脑内主要解剖结构的表观扩散系数(ADC)和各项异性分数(FA),得到的数据与高场仪器上的相关数据比较是吻合的. 因此临床上使用在低场强上得到的DTI图像评价脑白质是可行的,而且通常在临床上这也是足够的.     

氧气在梯度磁场中流动及扩散行为研究

氧气是顺磁性气体，氮气是抗磁性气体，其在梯度磁场中具有不同的磁特性。氮气与氧气在受到梯度磁场影响时，其流动及扩散情况会呈现不同的行为特性。本文建立多通道层叠磁体阵列结构试验系统，并根据高纯氮气在多通道层叠磁体阵列结构气流通道中流动时气体中氧含量的变化，进行空气中氧气以及高纯氮气在具有梯度磁场作用时的流动及扩散情况的研究...     

四面体磁梯度张量系统的载体磁干扰补偿方法

针对搭载于水下无人航行器(UUV)的四面体磁梯度张量系统易受载体磁场干扰的问题,提出了一种载体磁干扰补偿方法.该方法在载体磁干扰产生机理的基础上,利用磁梯度张量差分测量算法融合四面体磁梯度张量系统中四个矢量磁力仪的载体磁干扰,建立了磁梯度张量系统载体磁干扰数学模型;然后在此数学模型的基础上提出了磁干扰补偿方法,并根据磁梯度张量9分量的数学关系提出了补偿参数辨识方法;最后通过仿真实验对方法进行了验证,结果表明该补偿方法可以有效补偿磁梯度张量系统95.9%的载体磁干扰.该方法利用补偿参数对磁梯度张量系统的输出值直接进行磁干扰补偿,从理论上解决了磁梯度张量系统中各个矢量磁力仪载体磁干扰的统一补偿问题.     

9.4T下TX模型小鼠脑组织的扩散张量成像研究

本文首次应用9.4 T高场磁共振扩散张量成像（diffusion tensor imaging,DTI）技术,研究了Wilson疾病模型TX（toxic milk）小鼠的脑组织微观结构改变和结构连接情况.基于感兴趣区域（region of interest,ROI）的分析发现,与对照组相比,TX模型组的各向异性比值（fractional anisotropy,FA）在海马、尾状核和苍白球显著下降;平均扩散率（mean diffusivity,MD）则呈现上升趋势,但无统计学意义.纤维束追踪法结果表明TX模型组小鼠的脑结构连接并未受到严重破坏,证明了铜累积对脑组织的损伤具有区域性.     

扩散张量图像的插值方法综述

扩散张量成像能够通过获得组织内水分子的三维位移分布来研究脑部结构，是近年来医学成像技术的研究热点.在采集、转换以及处理张量的进程中，研究者需要进行插值处理来提高图像分辨率或改善可视化效果.如在人脑模板构建、脑白质纤维追踪以及配准等应用中，张量插值是一个具有重要作用的处理步骤.本文对现有的张量插值方法进行综述，首先介绍了插值方法的理论内容，阐明各张量插值方法中所解决的技术问题及存在的局限性，然后介绍了常用的插值方法的评估指标，再利用现有的典型插值方法分别对仿真数据和真实数据进行插值实验和结果分析，最后对张量插值方法的未来发展趋势提出建议.     

由扩散张量导出的各向异性扩散模型的隐式数值模拟

研究了由扩散张量导出的各向异性扩散的图像处理模型,并构造了隐式差分格式,形成了有13条对角线的大型稀疏矩阵.利用代数多重网格法求解了这个线性代数方程组.并进行了数值试验.     

超强边缘磁场梯度场下的磁共振成像:STRAFI 实验

磁共振成像（MRI）是一个能够探测样品内部特性的有效检测手段,已被广泛应用于化学、生物研究,以及医疗诊断领域. 自约40年前发展以来, 成像方法的不断发展使得MRI的成像分辨率、实验效率和成像杂核能力得到了很大的改进. 边缘磁场成像（STRAFI）是一种很具潜力的成像方法之一,它利用了超导磁体本身具有的边缘场的强梯度场. 该综述介绍了STRAFI基础,并概括了成像的基本原理、STRAFI的实验理论和方法及其在实际研究中的应用. 由此将比较STRAFI实验相对于传统MRI方法的所具有的优势和多面可行性.     

L波段三维ESR成像系统的研制(Ⅰ)——L波段ESR成像的磁场及三维梯度磁场系统

研究并实现了L波段电子自旋共振三维成像(3D-EPRI)专用的三维梯度磁场系统, 主磁场及扫描磁场系统以及相应的驱动控制系统. 梯度场线圈采用在铜板上用电切割方法加工的平板式线圈, 避免了用铜导线绕制线圈体积较大的缺点, 从而缩小了主磁场的体积和极间距. 梯度场强度在三维方向上均达到200 mT/m, 驱动电流为20 A. 三维空间线性度均优于5%; 线性区域大于直径42 mm的球形空间. 两磁极间距离为63 mm, 可以容纳通常体积的L波段谐振腔. 主磁场和扫描场线圈固定在同一轭铁架上. 它们可分别产生1.6～96 mT和0.2～16 mT的线性变化磁场. 5组磁场线圈(包括主磁场, 扫描磁场和三维梯度磁场)分别由5台独立的恒流驱动电源控制驱动. 电源通过数据接口由计算机控制. 初步成像实验证明本工作所建立的磁场和梯度磁场系统可以用于EPRI实验.     

Evaluation of diffusion models of fiber tracts using diffusion tensor magnetic resonance imaging

Modeling of water diffusion in white matter is useful for revealing microstructure of the brain tissue and hence diagnosis and evaluation of white matter diseases. Researchers have modeled diffusion in white matter using mathematical and mechanical analysis at the cellular level. However, less work has been devoted to evaluate these models using macroscopic real data such as diffusion tensor magnetic resonance imaging (DTMRI) data. DTMRI is a noninvasive tool for evaluating white matter microstructure by measuring random motion of water molecules referred to as diffusion. It reflects directional information of microscopic structures such as fibers. Thus, it is applicable for evaluation and modification of mathematical models of white matter. Nevertheless, a realistic relation between a fiber model and imaging data does not exist. This work opens a promising avenue for relating DTMRI data to microstructural parameters of white matter. First, we propose a strategy for relating DTMRI and fiber model parameters to evaluate mathematical models in light of real data. The proposed strategy is then applied to evaluate and extend an existing model of white matter based on clinically available DTMRI data. Next, the proposed strategy is used to estimate microstructural characteristics of fiber tracts. We illustrate this approach through its application to approximation of myelin sheath thickness and fraction of volume occupied by fibers. Using sufficiently small imaging voxels, the proposed approach is capable of estimating model parameters with desirable precision.     

Study of myocardial fiber pathway using magnetic resonance diffusion tensor imaging

The purpose of this study was to investigate myocardial fiber pathway distribution in order to provide supplemental information on myocardial fiber architecture and cardiac mechanics. Diffusion tensor imaging (DTI) with medium diffusion resolution (15 directions) was performed on normal canine heart samples (N=6) fixed in formalin. With the use of diffusion tensor fiber tracking, left ventricle (LV) myocardial fiber pathways and helix angles were computed pixel by pixel at short-axis slices from base to apex. Distribution of DTI-tracked fiber pathway length and number was analyzed quantitatively as a function of fiber helix angle in step of 9 degrees . The long fiber pathways were found to have small helix angles. They are mostly distributed in the middle myocardium and run circumferentially. Fiber pathways tracked at the middle and upper LV are generally longer than those near the apex. Majority of fiber pathways have small helix angles between -20 degrees and 20 degrees , dominating the fiber architecture in myocardium. Likely, such myocardial fiber pathway measurement by DTI may reflect the spatial connectiveness or connectivity of elastic myofiber bundles along their preferential pathway of electromechanical activation. The dominance of the long and circumferentially running fiber pathways found in the study may explain the circumferential predominance in left ventricular contraction.     

磁共振成像发展与超高场磁共振成像技术

20世纪70年代磁共振成像技术的发明为生物医学成像开辟了一个极富生命力的领域。随着技术的进步和生命科学研究的深入,磁共振成像技术正向超高场发展。文章将在介绍磁共振成像技术发展的历史后,结合作者的认识,简要介绍超高磁共振成像技术的发展现状和关键技术方面的进展。     

Diffusion tensor magnetic resonance imaging of the normal breast

Purpose

The objective of this study was to evaluate diffusion anisotropy of the breast parenchyma and assess the range and repeatability of diffusion tensor imaging (DTI) parameters in normal breast tissue.

Materials and Methods

The study was approved by our institutional review board and included 12 healthy females (median age, 36 years). Diffusion tensor imaging was performed at 1.5 T using a diffusion-weighted echo planar imaging sequence. Diffusion tensor imaging parameters including tensor eigenvalues (λ₁, λ₂, λ₃), fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were measured for anterior, central and posterior breast regions.

Results

Mean normal breast DTI measures were λ₁=2.51×10⁻³ mm²/s, λ₂=1.89×10⁻³ mm²/s, λ₃=1.39×10⁻³ mm²/s, ADC=1.95±0.24×10⁻³ mm²/s and FA=0.29±0.05 for b=600 s/mm². Significant regional differences were observed for both FA and ADC (P<.05), with higher ADC in the central breast and higher FA in the posterior breast. Comparison of DTI values calculated using b=0, 600 s/mm² vs. b=0, 1000 s/mm², showed significant differences in ADC (P<.001), but not FA. Repeatability assessment produced within-subject coefficient of variations of 4.5% for ADC and 11.4% for FA measures.

Conclusion

This study demonstrates anisotropy of water diffusion in normal breast tissue and establishes a normative range of breast FA values. Attention to the influence of breast region and b value on breast DTI measurements may be important for clinical interpretation and standardization of techniques.     

Effects of random subject rotation on optimised diffusion gradient sampling schemes in diffusion tensor MRI

The choice of the number (N) and orientation of diffusion sampling gradients required to measure accurately the water diffusion tensor remains contentious. Monte Carlo studies have suggested that between 20 and 30 uniformly distributed sampling orientations are required to provide robust estimates of water diffusions parameters. These simulations have not, however, taken into account what effect random subject motion, specifically rotation, might have on optimised gradient schemes, a problem which is especially relevant to clinical diffusion tensor MRI (DT-MRI). Here this question is investigated using Monte Carlo simulations of icosahedral sampling schemes and in vivo data. These polyhedra-based schemes, which have the advantage that large N can be created from optimised subsets of smaller N, appear to be ideal for the study of restless subjects since if scanning needs to be prematurely terminated it should be possible to identify a subset of images that have been acquired with a near optimised sampling scheme. The simulations and in vivo data show that as N increases, the rotational variance of fractional anisotropy (FA) estimates becomes progressively less dependent on the magnitude of subject rotation (), while higher FA values are progressively underestimated as increases. These data indicate that for large subject rotations the B-matrix should be recalculated to provide accurate diffusion anisotropy information.     

A diffusion gradient optimization framework for spinal cord diffusion tensor imaging

The uncertainty in the estimation of diffusion model parameters in diffusion tensor imaging (DTI) can be reduced by optimally selecting the diffusion gradient directions utilizing some prior structural information. This is beneficial for spinal cord DTI, where the magnetic resonance images have low signal-to-noise ratio and thus high uncertainty in diffusion model parameter estimation. Presented is a gradient optimization scheme based on D-optimality, which reduces the overall estimation uncertainty by minimizing the Rician Cramer-Rao lower bound of the variance of the model parameter estimates. The tensor-based diffusion model for DTI is simplified to a four-parameter axisymmetric DTI model where diffusion transverse to the principal eigenvector of the tensor is assumed isotropic. Through simulations and experimental validation, we demonstrate that an optimized gradient scheme based on D-optimality is able to reduce the overall uncertainty in the estimation of diffusion model parameters for the cervical spinal cord and brain stem white matter tracts.     

Effect of a weak static magnetic field on nitrogen-14 quadrupole resonance in the case of an axially symmetric electric field gradient tensor

The application of a weak static B₀ magnetic field (less than 1 mT) may produce a well-defined splitting of the ¹⁴N Quadrupole Resonance line when the electric field gradient tensor at the nitrogen nucleus level is of axial symmetry. It is theoretically shown and experimentally confirmed that the actual splitting (when it exists) as well as the line-shape and the signal intensity depends on three factors: (i) the amplitude of B₀, (ii) the amplitude and pulse duration of the radio-frequency field, B₁, used for detecting the NQR signal, and (iii) the relative orientation of B₀ and B₁. For instance, when B₀ is parallel to B₁ and regardless of the B₀ value, the signal intensity is three times larger than when B₀ is perpendicular to B₁. This point is of some importance in practice since NQR measurements are almost always performed in the earth field. Moreover, in the course of this study, it has been recognized that important pieces of information regarding line-shape are contained in data points at the beginning of the free induction decay (fid) which, in practice, are eliminated for avoiding spurious signals due to probe ringing. It has been found that these data points can generally be retrieved by linear prediction (LP) procedures. As a further LP benefit, the signal intensity loss (by about a factor of three) is regained.     

Keyhole and zero-padding approaches for reduced-encoding diffusion tensor imaging of the mouse brains

Keyhole diffusion tensor imaging (keyhole DTI) was previously proposed in cardiac imaging to reconstruct DTI maps from the reduced phase-encoding images. To evaluate the feasibility of keyhole DTI in brain imaging, keyhole and zero-padding DTI algorithms were employed on in vivo mouse brain. The reduced phase-encoding portion, also termed as the sharing rate, was varied from 50% to 90% of the full k-space. Our data showed that zero-padding DTI resulted in decreased fractional anisotropy (FA) and decreased mean apparent diffusion coefficient (mean ADC) in white matter (WM) regions. Keyhole DTI showed a better edge preservation on mean ADC maps but not on FA maps as compared to the zero-padding DTI. When increasing the sharing rate in keyhole approach, an underestimation of FA and an over- or underestimation of mean ADC were measured in WM depending on the selected reference image. The inconsistency of keyhole DTI may add a challenge for the wide use of this modality. However, with a carefully selected directive diffusion-weighted image to serve as the reference image in the keyhole approach, this study demonstrated that one may obtain DTI indices of reduced-encoding images with high consistency to those derived with full k-space DTI.     

Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.