Improving relative anisotropy measurement using directional correlation of diffusion tensors.

A method employing directional correlation of the diffusion tensor, directional-correlation weighted relative anisotropy (DRA), was developed to improve the accuracy of estimated relative anisotropy (RA). The intravoxel directional correlation was established on the same voxel between two identically acquired diffusion tensor images, and the correlation coefficient derived from tensor dot product was employed as the weighting factor applied in the calculation of RA. The effect of noise influence was reduced since the random noise between repeated scans is not directionally correlated. The RA and the inter- and intravoxel DRA estimations were examined on rat brains in vivo. The background noise alters the direction of eigenvectors and the magnitude of eigenvalues. The dispersion angle between repeatedly obtained eigenvectors, representing the extent of directional alteration of eigenvectors, depends on the tissue anisotropy as well as the signal-to-noise ratio (SNR) of the source images. Current results demonstrate that the intravoxel DRA improves the accuracy of RA estimation, increases the relative contrast of gray and white matter, and avoids the partial volume effect commonly seen in the intervoxel operations.     

A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions

Purpose

To examine the T₂‐normal appearing spinal cord of patients with multiple sclerosis (MS) using diffusion tensor imaging.

Materials and Methods

Diffusion tensor images of the spinal cord were acquired from 21 healthy subjects, 11 MS patients with spinal cord lesions, and 10 MS patients without spinal cord lesions on the T₂‐weighted MR images. Different diffusion measures were evaluated using both a region of interest (ROI) ‐based and a diffusion tensor tractography‐based segmentation approach.

Results

It was observed that the FA, the transverse diffusivity λ_?, and the ratio of the longitudinal and transverse diffusivities (λ_∥/λ _?) were significantly lower in the spinal cord of MS patients with spinal cord lesions compared with the control subjects using both the ROI method (P = 0.014, P = 0.028, and P = 0.039, respectively) and the tractography‐based approach (P = 0.006, P = 0.037, and P = 0.012, respectively). For both image analysis methods, the FA and the λ _∥/λ _? values were significantly different between the control group and the MS patient group without T₂ spinal cord lesions (P = 0.013).

Conclusion

Our results suggest that the spinal cord may still be affected by MS, even when lesions are not detected on a conventional MR scan. In addition, we demonstrated that diffusion tensor tractography is a robust tool to analyze the spinal cord of MS patients. J. Magn. Reson. Imaging 2009;30:25–34. © 2009 Wiley‐Liss, Inc.

     

Slab scan diffusion imaging.

For maximum robustness of a diffusion-weighted MR imaging sequence, it is desirable to use a single-shot imaging method. This article introduces a new single-shot imaging approach that combines the advantages of multiple spin-echoes with the technique of line scan diffusion imaging. A slab volume, which can be spatially encoded with fewer phase encodes than a regular field of view, is selected with 2D selective pulses. With the shorter echo train, the sensitivity to field inhomogeneities and chemical shift is thus greatly diminished. Further reduction is achieved by interleaving short gradient echo trains with refocusing spin-echo pulses. Optimized slice-selective RF pulses that produce flip angles close to 180 degrees are used to minimize the stimulated echo component. Motion-related phase shifts, which change polarity with each spin-echo excitation, will give rise to artifacts that are avoidable by processing even and odd spin-echoes separately. As with line scan diffusion imaging, the complete field of view is acquired by sequential scanning. Since with each shot several lines of data are collected, a considerable improvement over line scan diffusion imaging in terms of scanning speed is achieved. Diffusion data obtained in phantoms and normal subjects demonstrate the feasibility of this novel approach.     

Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging.

A new method for mapping diffusivity profiles in tissue is presented. The Bloch-Torrey equation is modified to include a diffusion term with an arbitrary rank Cartesian tensor. This equation is solved to give the expression for the generalized Stejskal-Tanner formula quantifying diffusive attenuation in complicated geometries. This makes it possible to calculate the components of higher-rank tensors without using the computationally-difficult spherical harmonic transform. General theoretical relations between the diffusion tensor (DT) components measured by traditional (rank-2) DT imaging (DTI) and 3D distribution of diffusivities, as measured by high angular resolution diffusion imaging (HARDI) methods, are derived. Also, the spherical tensor components from HARDI are related to the rank-2 DT. The relationships between higher- and lower-rank Cartesian DTs are also presented. The inadequacy of the traditional rank-2 tensor model is demonstrated with simulations, and the method is applied to excised rat brain data collected in a spin-echo HARDI experiment.     

Minimum detectable difference of MR diffusion maps in acute ischemic stroke

PURPOSE: To determine the minimum detectable difference (MDD) and investigate variability of region-of-interest (ROI) analysis of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in acute ischemic stroke. MATERIALS AND METHODS: Ten patients with acute stroke (<24 hours) and moderate-to-large infarcts were imaged using a fast diffusion tensor technique. Four observers repeated three trials, during which each of two ROI types (free-hand polygon and ellipse) were drawn in white and gray matter (WM and GM) on FA and ADC maps. Analysis-of-variance techniques examined tissue and ROI type effects as well as inter- and intraobserver variability. F-tests examined the variability differences between ROI types. RESULTS: The MDD for ADC was 0.160 x 10(-3) mm(2) s(-1) in WM and 0.212 x 10(-3) mm(2) s(-1) in GM. The FA MDD was 0.19 in WM and 0.10 in GM. Tissue but not ROI type affected the mean values for both ADC and FA maps. Intraobserver reliability was substantial, while interobserver reliability was poor-to-moderate. No variability differences were found by ROI types. CONCLUSION: The MDD for WM and GM in normal and ischemic tissue were calculated. Inter- and intraobserver variability and tissue type affect ROI analysis of ADC and FA maps.     

Biexponential diffusion tensor analysis of human brain diffusion data.

Several studies have shown that in tissues over an extended range of b-factors, the signal decay deviates significantly from the basic monoexponential model. The true nature of this departure has to date not been identified. For the current study, line scan diffusion images of brain suitable for biexponential diffusion tensor analysis were acquired in normal subjects on a clinical MR system. For each of six noncollinear directions, 32 images with b-factors ranging from 5 to 5000 s/mm2 were collected. Biexponential fits yielded parameter maps for a fast and a slow diffusion component. A subset of the diffusion data, consisting of the images obtained at the conventional range of b-factors between 5 and 972 s/mm2, was used for monoexponential diffusion tensor analysis. Fractional anisotropy (FA) of the fast-diffusion component and the monoexponential fit exhibited no significant difference. FA of the slow-diffusion biexponential component was significantly higher, particularly in areas of lower fiber density. The principal diffusion directions for the two biexponential components and the monoexponential solution were largely the same and in agreement with known fiber tracts. The second and third diffusion eigenvector directions also appeared to be aligned, but they exhibited significant deviations in localized areas.     

Investigation of anomalous estimates of tensor-derived quantities in diffusion tensor imaging.

The diffusion tensor is typically assumed to be positive definite. However, noise in the measurements may cause the eigenvalues of the tensor estimate to be negative, thereby violating this assumption. Negative eigenvalues in diffusion tensor imaging (DTI) data occur predominately in regions of high anisotropy and may cause the fractional anisotropy (FA) to exceed unity. Two constrained least squares methods for eliminating negative eigenvalues are explored. These methods, the constrained linear least squares method (CLLS) and the constrained nonlinear least squares method (CNLS), are compared with other commonly used algebraic constrained methods. The CLLS tensor estimator can be shown to be equivalent to the linear least squares (LLS) tensor estimator when the LLS tensor estimate is positive definite. Similarly, the CNLS tensor estimator can be shown to be equivalent to the nonlinear least squares (NLS) tensor estimator when the NLS tensor estimate is positive definite. The constrained least squares methods for eliminating negative eigenvalues are evaluated with both simulations and in vivo human brain DTI data. Simulation results show that the CNLS method is, in terms of mean squared error for estimating trace and FA, the most effective method for correcting negative eigenvalues.     

Characterizing non-Gaussian diffusion by using generalized diffusion tensors.

Diffusion tensor imaging (DTI) is known to have a limited capability of resolving multiple fiber orientations within one voxel. This is mainly because the probability density function (PDF) for random spin displacement is non-Gaussian in the confining environment of biological tissues and, thus, the modeling of self-diffusion by a second-order tensor breaks down. The statistical property of a non-Gaussian diffusion process is characterized via the higher-order tensor (HOT) coefficients by reconstructing the PDF of the random spin displacement. Those HOT coefficients can be determined by combining a series of complex diffusion-weighted measurements. The signal equation for an MR diffusion experiment was investigated theoretically by generalizing Fick's law to a higher-order partial differential equation (PDE) obtained via Kramers-Moyal expansion. A relationship has been derived between the HOT coefficients of the PDE and the higher-order cumulants of the random spin displacement. Monte-Carlo simulations of diffusion in a restricted environment with different geometrical shapes were performed, and the strengths and weaknesses of both HOT and established diffusion analysis techniques were investigated. The generalized diffusion tensor formalism is capable of accurately resolving the underlying spin displacement for complex geometrical structures, of which neither conventional DTI nor diffusion-weighted imaging at high angular resolution (HARD) is capable. The HOT method helps illuminate some of the restrictions that are characteristic of these other methods. Furthermore, a direct relationship between HOT and q-space is also established.     

Using diffusion tensor imaging and immunofluorescent assay to evaluate the pathology of multiple sclerosis

Purpose:

To determine the ability of the principal diffusion tensor imaging (DTI) indices to predict the underlying histopathology evaluated with immunofluorescent assay (IFA).

Materials and Methods:

Conventional T2 and 3D multishot‐diffusion weighted echoplanar imaging (3D ms‐DWEPI) was performed on a fixed, ex vivo human cervical spinal cord (CSC) from a patient with a history of multiple sclerosis (MS). In all, 170 regions of interest (ROIs) were selected within the white matter and categorized as a high intensity lesion (HIL), low intensity lesion (LIL), and normal‐appearing white matter (NAWM). The longitudinal diffusivity (λl), radial diffusivity (λr), and fractional anisotropy (FA) were obtained from each ROI. The underlying histopathology was then evaluated using immunofluorescent assay with antibodies directed to myelin and neurofilament staining.

Results:

The mean values for λl and λr were significantly elevated within HIL relative to NAWM and LIL. IFA analysis of HIL demonstrated significant demyelination, without significant if any axon loss. The FA values were significantly reduced in HIL and LILs. FA values were also reduced in lesions with increased λl and λr values relative to normal.

Conclusion:

Aberrant λl, λr, and FA relative to normal values are strong indicators of demyelination. DTI indices are not specific for axon loss. IFA analysis is a reliable method to demonstrate myelin and axon pathology within the ex vivo setting. J. Magn. Reson. Imaging 2011;33:557–564. © 2011 Wiley‐Liss, Inc.     

Effects of cord motion on diffusion imaging of the spinal cord.

Measurement of diffusion and its dependence on direction has become an important tool for clinical and research studies of the brain. Diffusion imaging of the spinal cord may likewise prove useful as an indicator of tissue damage and axonal integrity; however, it is more challenging to perform diffusion imaging in the cord than in the brain. Here we report a study of the effects of motion on single-shot fast spin echo (FSE) diffusion tensor imaging (DTI) of the spinal cord. Diffusion imaging was performed at four different times in the cardiac cycle both without and with velocity compensation of the diffusion gradients. Uncompensated diffusion images demonstrated substantial signal loss artifacts in the cord that were strongly dependent on the delay after the pulse-oximeter trigger. Quantitative diffusion analysis was also strongly affected by this motion artifact. The use of flow-compensated gradients helped to restore normal signal in the cord, especially at particular trigger delays. Theoretical arguments suggest that improved spatial resolution may help eliminate this signal loss. Even with higher spatial resolution, motion-related signal attenuation may still occur in diffusion imaging of pathologies that alter the motion of the cord. However, this same cord motion may contain diagnostically valuable information when probed using appropriate diffusion imaging approaches.     

快速 DTI 在急性颈髓损伤的临床应用

目的：研究扩散张量成像(DTI)在急性颈髓损伤(CSCI)的成像特点,评估其临床应用价值。方法本组8例 CSCI 患者(发病72 h 内)均采用3.0T 磁共振仪进行快速颈髓 DTI 扫描,并在工作站进行扩散张量纤维束成像(DTT)。同时,在工作站分别测量并计算颈髓病变区及上下相对正常区的各向异性(FA)值和表观扩散系数(ADC)值,之后进行统计学组间配对 t 检验分析(SPSS 13.0)。结果急性 CSCI 以 C5~C6节段(占4/8)和 C4~C5节段(占3/8)多见,且快速 DTI 均获得了较好的图像质量。急性 CSCI 时病变区 FA 值和 ADC 值均明显低于相对正常区域数值(P <0.01),相应在 FA 图和 ADC 图均表现为低信号,而上下相对正常区 FA 值和 ADC 值间无明显区别;同时,DTT 有利于显示刀刺伤导致的颈髓纤维束断裂,颈髓闭合伤则主要表现为脊髓纤维束紊乱等。结论3.0T 快速 DTI 序列可以在2 min 扫描时间内获得临床较为满意的诊断图像,并通过 FA 值和 ADC 值更敏感地反映急性 CSCI 后髓鞘损伤导致的 FA 改变及细胞毒性水肿和血管源性水肿导致的水分子扩散的变化。     

Utilizing the diffusion-to-noise ratio to optimize magnetic resonance diffusion tensor acquisition strategies for improving measurements of diffusion anisotropy.

It is well known that quantitative anisotropy measurements derived from the diffusion tensor are extremely sensitive to noise contamination. The level of noise in the diffusion tensor imaging (DTI) experiment is usually measured from some estimate of the signal-to-noise ratio (SNR) in the component diffusion-weighted (DW) images. This measure is, however, highly dependent on experimental parameters, such as the diffusion attenuation b-value and the diffusion coefficient of the subject. Conversely, the diffusion-to-noise ratio (DNR), defined as the SNR of the calculated diffusion tensor trace map, provides a reliable estimate of noise contamination, which is largely independent of such parameters. In this work it is demonstrated how reliable anisotropy measurements can be obtained using an image acquisition strategy that optimizes the DNR of the DTI experiment. This acquisition scheme is shown to provide noise-independent measurements of typical diffusion anisotropy values found in the human brain.     

创伤性脑白质损伤的扩散张量成像研究

目的:评价扩散张量成像(DTI)在创伤性脑白质损伤(WMI)中的应用价值。方法:16例创伤性脑外伤后经临床诊断有WMI的患者通过Philips 1.5TIntera Achieva MR扫描仪行常规MRI和DTI。后处理获得部分各向异性指数(FA)、表观弥散系数(ADC)和纤维示踪成像三维图。根据T2WI及T2快速场回波图像,分别于WMI区域、同侧同名或对侧同名纤维束正常区域取感兴趣区,测量FA值和ADC值并进行比较。结果:脑外伤患者损伤脑白质中挫伤和出血、仅挫伤和仅出血区域三者之间的FA值(F=0.68,P>0.05)和ADC值(F=0.53,P>0.05)均未见明显不同。除仅出血区域的ADC值与对照区域相比差异无统计学意义(t=1.36,P>0.05),挫伤和出血(t=9.72,P<0.05)、仅挫伤(t=8.28,P<0.05)和仅出血(t=5.44,P<0.05)区域的FA值较正常对照区域明显降低,挫伤和出血(t=4.71,P<0.05)、仅挫伤(t=4.81,P<0.05)的ADC值较正常对照明显增高,纤维示踪成像显示损伤区域脑白质较正常区域稀疏、分离、缺失。结论:DTI技术能够显示患者WMI区域的异常改变,但ADC值对出血的判断有局限性。     

Classification and quantification of neuronal fiber pathways using diffusion tensor MRI.

Quantitative characterization of neuronal fiber pathways in vivo is of significant neurological and clinical interest. Using the capability of MR diffusion tensor imaging to determine the local orientations of neuronal fibers, novel algorithms were developed to bundle neuronal fiber pathways reconstructed in vivo with diffusion tensor images and to quantify various physical and geometric properties of fiber bundles. The reliability of the algorithms was examined with reproducibility tests. Illustrative results show that consistent physical and geometric measurements of novel properties of neuronal tissue can be obtained, which offer considerable potential for the quantitative study of fiber pathways in vivo.     

In vivo diffusion tensor imaging of the human prostate.

This study demonstrates the feasibility of in vivo prostate diffusion tensor imaging (DTI) in human subjects. We implemented an EPI-based diffusion-weighted (DW) sequence with seven-direction diffusion gradient sensitization, and acquired DT images from six subjects using cardiac gating with a phased-array prostate surface coil operating in a linear mode. We calculated two indices to quantify diffusion anisotropy. The direction of the eigenvector corresponding to the leading eigenvalue was displayed by means of a color-coding scheme. The average diffusion values of the prostate peripheral zone (PZ) and central gland (CG) were 1.95 +/- 0.08 x 10(-3) mm2 s and 1.53 +/- 0.34 x 10(-3) mm2 s, respectively. The average fractional anisotropy (FA) values for the PZ and CG were 0.46 +/- 0.04 and 0.40 +/- 0.08, respectively. The diffusion ellipsoid in prostate tissue was anisotropic and approximated a prolate model, as shown in the color maps of the anisotropy. Consistent with the tissue architecture, the prostate fiber orientations were predominantly in the superior-inferior (SI) direction for both the PZ and CG. This study shows the feasibility of in vivo DTI and establishes normative DT values for six subjects.     

PROPELLER EPI: an MRI technique suitable for diffusion tensor imaging at high field strength with reduced geometric distortions.

A technique suitable for diffusion tensor imaging (DTI) at high field strengths is presented in this work. The method is based on a periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) k-space trajectory using EPI as the signal readout module, and hence is dubbed PROPELLER EPI. The implementation of PROPELLER EPI included a series of correction schemes to reduce possible errors associated with the intrinsically higher sensitivity of EPI to off-resonance effects. Experimental results on a 3.0 Tesla MR system showed that the PROPELLER EPI images exhibit substantially reduced geometric distortions compared with single-shot EPI, at a much lower RF specific absorption rate (SAR) than the original version of the PROPELLER fast spin-echo (FSE) technique. For DTI, the self-navigated phase-correction capability of the PROPELLER EPI sequence was shown to be effective for in vivo imaging. A higher signal-to-noise ratio (SNR) compared to single-shot EPI at an identical total scan time was achieved, which is advantageous for routine DTI applications in clinical practice.     

Selecting an appropriate anisotropy index for displaying diffusion tensor imaging data with improved contrast and sensitivity.

A review of the behavior of different diffusion anisotropy indices (DAIs) to changes in diffusion anisotropy was undertaken and the limitations of several previously proposed DAIs are discussed. A mathematical representation of anisotropy sensitivity was used to enable image contrast and sensitivity to noise to be predicted. This technique was utilized to devise a new DAI, the gamma-variate anisotropy, which has a low sensitivity to noise and an improved contrast range for human brain imaging. This index can be easily modified for other applications, in that the range of anisotropy values to which it is highly sensitive can be altered. Magn Reson Med 44:117-121, 2000.