Fast and accurate initialization of the free‐water imaging model parameters from multi‐shell diffusion MRI

Cerebrospinal fluid partial volume effect is a known bias in the estimation of Diffusion Tensor Imaging (DTI) parameters from diffusion MRI data. The Free‐Water Imaging model for diffusion MRI data adds a second compartment to the DTI model, which explicitly accounts for the signal contribution of extracellular free‐water, such as cerebrospinal fluid. As a result the DTI parameters obtained through the free‐water model are corrected for partial volume effects, and thus better represent tissue microstructure. In addition, the model estimates the fractional volume of free‐water, and can be used to monitor changes in the extracellular space. Under certain assumptions, the model can be estimated from single‐shell diffusion MRI data. However, by using data from multi‐shell diffusion acquisitions, these assumptions can be relaxed, and the fit becomes more robust. Nevertheless, fitting the model to multi‐shell data requires high computational cost, with a non‐linear iterative minimization, which has to be initialized close enough to the global minimum to avoid local minima and to robustly estimate the model parameters. Here we investigate the properties of the main initialization approaches that are currently being used, and suggest new fast approaches to improve the initial estimates of the model parameters. We show that our proposed approaches provide a fast and accurate initial approximation of the model parameters, which is very close to the final solution. We demonstrate that the proposed initializations improve the final outcome of non‐linear model fitting.     

High‐resolution diffusion tensor imaging in cervical spondylotic myelopathy: a preliminary follow‐up study

Diffusion imaging is a promising technique as it can provide microstructural tissue information and thus potentially show viable changes in spinal cord. However, the traditional single‐shot imaging method is limited as a result of various image artifacts. In order to improve measurement accuracy, we used a newly developed, multi‐shot, high‐resolution, diffusion tensor imaging (DTI) method to investigate diffusion metric changes and compare them with T₂‐weighted (T2W) images before and after decompressive surgery for cervical spondylotic myelopathy (CSM). T2W imaging, single‐shot DTI and multi‐shot DTI were employed to scan seven patients with CSM before and 3 months after decompressive surgery. High signal intensities were scored using the T2 W images. DTI metrics, including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD), were quantified and compared pre‐ and post‐surgery. In addition, the relationship between imaging metrics and neurological assessments was examined. The reproducibility of multi‐shot DTI was also assessed in 10 healthy volunteers. Post‐surgery, the mean grade of cervical canal stenosis was reduced from grade 3 to normal after 3 months. Compared with single‐shot DTI, multi‐shot DTI provided better images with lower artifact levels, especially following surgery, as a result of reduced artifacts from metal implants. The new method also showed acceptable reproducibility. Both FA and RD values from the new acquisition showed significant differences post‐surgery (FA, p = 0.026; RD, p = 0.048). These changes were consistent with neurological assessments. In contrast, T2W images did not show significant changes before and after surgery. Multi‐shot diffusion imaging showed improved image quality over single‐shot DWI, and presented superior performance in diagnosis and recovery monitoring for patients with CSM compared with T2W imaging. DTI metrics can reflect the pathological conditions of spondylotic spinal cord quantitatively and may serve as a sensitive biomarker for potential CSM management.     

Analysis of errors in diffusion kurtosis imaging caused by slice crosstalk in simultaneous multi‐slice imaging

Simultaneous multi‐slice (SMS) imaging techniques accelerate diffusion MRI data acquisition. However, slice separation is imperfect and results in residual signal leakage between the simultaneously excited slices. The resulting consistent bias may adversely affect diffusion model parameter estimation. Although this bias is usually small and might not affect the simplified diffusion tensor model significantly, higher order diffusion models such as kurtosis are likely to be more susceptible to such effects. In this work, two SMS reconstruction techniques and an alternative acquisition approach were tested to quantify the effects of slice crosstalk on diffusion kurtosis parameters. In reconstruction, two popular slice separation algorithms, slice GRAPPA and split‐slice GRAPPA, are evaluated to determine the effect of slice leakage on diffusion kurtosis metrics. For the alternative acquisition, the slice pairings were varied across diffusion weighted images such that the signal leakage does not come from the same overlapped slice for all diffusion encodings. Simulation results demonstrated the potential benefits of randomizing the slice pairings. However, various experimental factors confounded the advantages of slice pair randomization. In volunteer experiments, region‐of‐interest analyses found high metric errors with each of the SMS acquisitions and reconstructions in the brain white matter.     

MRI quantification of non‐Gaussian water diffusion in normal human kidney: a diffusional kurtosis imaging study

Our aim was to prospectively evaluate the feasibility of diffusional kurtosis imaging (DKI) in normal human kidney and to report preliminary DKI measurements. Institutional review board approval and informed consent were obtained. Forty‐two healthy volunteers underwent diffusion‐weighted imaging (DWI) scans with a 3‐T MR scanner. b values of 0, 500 and 1000 s/mm² were adopted. Maps of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (D_⊥), axial diffusivity (D_||), mean kurtosis (MK), radial kurtosis (K_⊥) and axial kurtosis (K_||) were produced. Three representative axial slices in the upper pole, mid‐zone and lower pole were selected in the left and right kidney. On each selected slice, three regions of interest were drawn on the renal cortex and another three on the medulla. Statistical comparison was performed with t‐test and analysis of variance. Thirty‐seven volunteers successfully completed the scans. No statistically significant differences were observed between the left and right kidney for all metrics (p values in the cortex: FA, 0.114; MD, 0.531; D_⊥, 0.576; D_||, 0.691; MK, 0.934; K_⊥, 0.722; K_||, 0.891; p values in the medulla: FA, 0.348; MD, 0.732; D_⊥, 0.470; D_||, 0.289; MK, 0.959; K_⊥, 0.780; K_||, 0.287). Kurtosis metrics (MK, K_||, K_⊥) obtained in the renal medulla were significantly (p <0.001) higher than those in the cortex (0.552 ± 0.04, 0.637 ± 0.07 and 0.530 ± 0.08 in the medulla and 0.373 ± 0.04, 0.492 ± 0.06 and 0.295 ± 0.06 in the cortex, respectively). For the diffusivity measures, FA of the medulla (0.356 ± 0.03) was higher than that of the cortex (0.179 ± 0.03), whereas MD, D_⊥ and D_|| (mm²/ms) were lower in the medulla than in the cortex (3.88 ± 0.09, 3.50 ± 0.23 and 4.65 ± 0.29 in the cortex and 2.88 ± 0.11, 2.32 ± 0.20 and 3.47 ± 0.31 in the medulla, respectively). Our results indicate that DKI is feasible in the human kidney. We have reported the preliminary DKI measurements of normal human kidney that demonstrate well the non‐Gaussian behavior of water diffusion, especially in the renal medulla. Copyright © 2014 John Wiley & Sons, Ltd.     

A model‐based reconstruction for undersampled radial spin‐echo DTI with variational penalties on the diffusion tensor

Radial spin‐echo diffusion imaging allows motion‐robust imaging of tissues with very low T₂ values like articular cartilage with high spatial resolution and signal‐to‐noise ratio (SNR). However, in vivo measurements are challenging, due to the significantly slower data acquisition speed of spin‐echo sequences and the less efficient k‐space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled diffusion‐tensor imaging (DTI). A model‐based reconstruction implicitly exploits redundancies in the diffusion‐weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a total variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (three and two volunteers, respectively). Evaluation of the new approach was conducted by comparing the results with reconstructions performed with gridding, combined parallel imaging and compressed sensing and a recently proposed model‐based approach. The experiments demonstrated improvements in terms of reduction of noise and streaking artifacts in the quantitative parameter maps, as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin‐echo diffusion‐tensor imaging without degrading parameter quantification and/or SNR. Copyright © 2015 John Wiley & Sons, Ltd.     

Improvement of accuracy of diffusion MRI using real‐time self‐gated data acquisition

Diffusion‐weighted and diffusion tensor MR imaging (DWI, DTI) techniques are generally performed with signal averaging of multiple measurements to improve the signal‐to‐noise ratio (SNR) and the accuracy of the diffusion measurement. Any discrepancy in the images between different averages causes errors which reduce the accuracy of the diffusion MRI measurements. In this report, a motion artifact reduction scheme with a real‐time self‐gated (RTSG) data acquisition for diffusion MRI using two‐dimensional echo planar imaging (2D EPI) is described. A subject's translational and rotational motions during application of the diffusion gradients induce an additional phase term and a shift of the echo‐peak position in the k‐space, respectively. These motions also reduce the magnitude of the echo‐peak. Based on these properties, we present a new scheme which monitors the position and the magnitude of the largest echo‐peak in the k‐space. The position and the magnitude of each average is compared to those of early averaging shot to determine if the differences are within or beyond the given threshold values. Motion corrupted data are reacquired in real time. Our preliminary results using RTSG indicate an improvement of both SNR and the accuracy of diffusion MRI measurements. Copyright © 2009 John Wiley & Sons, Ltd.     

High‐resolution diffusion tensor imaging of the human kidneys using a free‐breathing,multi‐slice,targeted field of view approach

Fractional anisotropy (FA) obtained by diffusion tensor imaging (DTI) can be used to image the kidneys without any contrast media. FA of the medulla has been shown to correlate with kidney function. It is expected that higher spatial resolution would improve the depiction of small structures within the kidney. However, the achievement of high spatial resolution in renal DTI remains challenging as a result of respiratory motion and susceptibility to diffusion imaging artefacts. In this study, a targeted field of view (TFOV) method was used to obtain high‐resolution FA maps and colour‐coded diffusion tensor orientations, together with measures of the medullary and cortical FA, in 12 healthy subjects. Subjects were scanned with two implementations (dual and single kidney) of a TFOV DTI method. DTI scans were performed during free breathing with a navigator‐triggered sequence. Results showed high consistency in the greyscale FA, colour‐coded FA and diffusion tensors across subjects and between dual‐ and single‐kidney scans, which have in‐plane voxel sizes of 2 × 2 mm² and 1.2 × 1.2 mm², respectively. The ability to acquire multiple contiguous slices allowed the medulla and cortical FA to be quantified over the entire kidney volume. The mean medulla and cortical FA values were 0.38 ± 0.017 and 0.21 ± 0.019, respectively, for the dual‐kidney scan, and 0.35 ± 0.032 and 0.20 ± 0.014, respectively, for the single‐kidney scan. The mean FA between the medulla and cortex was significantly different (p < 0.001) for both dual‐ and single‐kidney implementations. High‐spatial‐resolution DTI shows promise for improving the characterization and non‐invasive assessment of kidney function. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.     

User‐independent diffusion tensor imaging analysis pipelines in a rat model presenting ventriculomegalia: A comparison study

Automated analysis of diffusion tensor imaging (DTI) data is an appealing way to process large datasets in an unbiased manner. However, automation can sometimes be linked to a lack of interpretability. Two whole‐brain, automated and voxelwise methods exist: voxel‐based analysis (VBA) and tract‐based spatial statistics (TBSS). In VBA, the amount of smoothing has been shown to influence the results. TBSS is free of this step, but a projection procedure is introduced to correct for residual misalignments. This projection assigns the local highest fractional anisotropy (FA) value to the mean FA skeleton, which represents white matter tract centers. For both methods, the normalization procedure has a major impact. These issues are well documented in humans but, to our knowledge, not in rodents. In this study, we assessed the quality of three different registration algorithms (ANTs SyN, DTI‐TK and FNIRT) using study‐specific templates and their impact on automated analysis methods (VBA and TBSS) in a rat pup model of diffuse white matter injury presenting large unilateral deformations. VBA and TBSS results were stable and anatomically coherent across the three pipelines. For VBA, in regions around the large deformations, interpretability was limited because of the increased partial volume effect. With TBSS, two of the three pipelines found a significant decrease in axial diffusivity (AD) at the known injury site. These results demonstrate that automated voxelwise analyses can be used in an animal model with large deformations.     

DTI of human skeletal muscle: the effects of diffusion encoding parameters,signal‐to‐noise ratio and T2 on tensor indices and fiber tracts

In this study, we have performed simulations to address the effects of diffusion encoding parameters, signal‐to‐noise ratio (SNR) and T₂ on skeletal muscle diffusion tensor indices and fiber tracts. Where appropriate, simulations were corroborated and validated by in vivo diffusion tensor imaging (DTI) of human skeletal muscle. Specifically, we have addressed: (i) the accuracy and precision of the diffusion parameters and eigenvectors at different SNR levels; (ii) the effects of the diffusion gradient direction encoding scheme; (iii) the optimal b value for diffusion tensor estimation; (iv) the effects of changes in skeletal muscle T₂; and, finally, the influence of SNR on fiber tractography and derived (v) fiber lengths, (vi) pennation angles and (vii) fiber curvatures. We conclude that accurate DTI of skeletal muscle requires an SNR of at least 25, a b value of between 400 and 500 s/mm², and data acquired with at least 12 diffusion gradient directions homogeneously distributed on half a sphere. Furthermore, for DTI studies focusing on skeletal muscle injury or pathology, apparent changes in the diffusion parameters need to be interpreted with great care in view of the confounding effects of T₂, particularly for moderate to low SNR values. Copyright © 2013 John Wiley & Sons, Ltd.     

Reproducibility of tract‐specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3 tesla

Damage to specific white matter tracts within the spinal cord can often result in the particular neurological syndromes that characterize myelopathies such as traumatic spinal cord injury. Noninvasive visualization of these tracts with imaging techniques that are sensitive to microstructural integrity is an important clinical goal. Diffusion tensor imaging (DTI)‐ and magnetization transfer (MT)‐derived quantities have shown promise in assessing tissue health in the central nervous system. In this paper, we demonstrate that DTI of the cervical spinal cord can reliably discriminate sensory (dorsal) and motor (lateral) columns. From data derived from nine healthy volunteers, two raters quantified column‐specific parallel (λ_||) and perpendicular (λ_?) diffusivity, fractional anisotropy (FA), mean diffusivity (MD), and MT‐weighted signal intensity relative to cerebrospinal fluid (MTCSF) over two time‐points separated by more than 1 week. Cross‐sectional means and standard deviations of these measures in the lateral and dorsal columns were as follows: λ_||: 2.13 ± 0.14 and 2.14 ± 0.11 μm²/ms; λ_?: 0.67 ± 0.16 and 0.61 ± 0.09 μm²/ms; MD: 1.15 ± 0.15 and 1.12 ± 0.08 μm²/ms; FA: 0.68 ± 0.06 and 0.68 ± 0.05; MTCSF: 0.52 ± 0.05 and 0.50 ± 0.05. We examined the variability and interrater and test‐retest reliability for each metric. These column‐specific MR measurements are expected to enhance understanding of the intimate structure‐function relationship in the cervical spinal cord and may be useful for the assessment of disease progression. Copyright © 2009 John Wiley & Sons, Ltd.     

Leading non‐Gaussian corrections for diffusion orientation distribution function

An analytical representation of the leading non‐Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed from the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model‐independent non‐Gaussian diffusion effects, it improves on the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI‐based white matter fiber tractography, which has potential advantages over conventional DTI‐based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra‐voxel fiber crossings. The formula is illustrated with numerical simulations for a two‐compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non‐Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. Copyright © 2013 John Wiley & Sons, Ltd.     

纤维跟踪技术在模拟显示人脑联络纤维中的应用

目的：应用弥散张量（DTI）纤维跟踪技术来模拟显示脑的联络纤维，探讨结果与经典解剖学知识的一致性。方法：对1个志愿者行单次激发回波平面弥散张量成像，利用纤维跟踪技术来模拟显示其联络纤维，并观察与经典解剖学知识的一致性。结果：通过选择恰当的感兴趣区，各向异性阈值、角度阈值、步长和体素内采样数目等参数，利用弥散张量纤维跟踪技术可模拟显示扣带、上枕额束、下枕额束、钩束、下纵束等联络纤维。结论：利用弥散张量纤维跟踪技术可模拟显示人脑联络纤维，且与经典解剖学有高度一致性，是在活体中研究人脑联络纤维的一种新方法。     

Investigation of field and diffusion time dependence of the diffusion‐weighted signal at ultrahigh magnetic fields

Over the last decade, there has been a significant increase in the number of high‐magnetic‐field MRI magnets. However, the exact effect of a high magnetic field strength (B₀) on diffusion‐weighted MR signals is not yet fully understood. The goal of this study was to investigate the influence of different high magnetic field strengths (9.4 T and 14.1 T) and diffusion times (9, 11, 13, 15, 17 and 24 ms) on the diffusion‐weighted signal in rat brain white matter. At a short diffusion time (9 ms), fractional anisotropy values were found to be lower at 14.1 T than at 9.4 T, but this difference disappeared at longer diffusion times. A simple two‐pool model was used to explain these findings. The model describes the white matter as a first hindered compartment (often associated with the extra‐axonal space), characterized by a faster orthogonal diffusion and a lower fractional anisotropy, and a second restricted compartment (often associated with the intra‐axonal space), characterized by a slower orthogonal diffusion (i.e. orthogonal to the axon direction) and a higher fractional anisotropy. Apparent T₂ relaxation time measurements of the hindered and restricted pools were performed. The shortening of the pseudo‐T₂ value from the restricted compartment with B₀ is likely to be more pronounced than the apparent T₂ changes in the hindered compartment. This study suggests that the observed differences in diffusion tensor imaging parameters between the two magnetic field strengths at short diffusion time may be related to differences in the apparent T₂ values between the pools. Copyright © 2013 John Wiley & Sons, Ltd.     

Diffusion in Polymer Solutions: Molecular Weight Distribution by PFG‐NMR and Relation to SEC

Quantification of diffusion coefficient distribution (DCD) and correlation with molecular weight distribution (MWD) of polymers is still an issue in pulsed field‐gradient nuclear magnetic resonance (PFG‐NMR). The conventional scaling law utilized so far to relate diffusion coefficient and molecular weight only holds true for the determination of MWD at sufficiently low concentrations. To extend measurement limits and to get a good signal‐to‐noise ratio, an exponential correlation is introduced to describe the effect of polymer concentration on diffusion in PFG‐NMR. Two model polymers (polystyrene and poly(methyl methacrylate)) dissolved in deuterated chloroform are studied at different concentrations in the range of 0.16–8 wt%. The DCDs are determined by modeling the measured signal attenuation with three methods (gamma distribution, log normal distribution, and tailored norm regularization). It is shown that the proposed method applies to the PFG‐NMR measurements on polymer solutions over a wide concentration range, providing almost the same MWDs as those obtained at low concentrations. The MWDs retrieved from NMR experiments agree well with those by size exclusion chromatography.

     

Detection of acute nervous system injury with advanced diffusion‐weighted MRI: a simulation and sensitivity analysis

Diffusion‐weighted imaging (DWI) is a powerful tool to investigate the microscopic structure of the central nervous system (CNS). Diffusion tensor imaging (DTI), a common model of the DWI signal, has a demonstrated sensitivity to detect microscopic changes as a result of injury or disease. However, DTI and other similar models have inherent limitations that reduce their specificity for certain pathological features, particularly in tissues with complex fiber arrangements. Methods such as double pulsed field gradient (dPFG) and q‐vector magic angle spinning (qMAS) have been proposed to specifically probe the underlying microscopic anisotropy without interference from the macroscopic tissue organization. This is particularly important for the study of acute injury, where abrupt changes in the microscopic morphology of axons and dendrites manifest as focal enlargements known as beading. The purpose of this work was to assess the relative sensitivity of DWI measures to beading in the context of macroscopic fiber organization and edema. Computational simulations of DWI experiments in normal and beaded axons demonstrated that, although DWI models can be highly specific for the simulated pathologies of beading and volume fraction changes in coherent fiber pathways, their sensitivity to a single idealized pathology is considerably reduced in crossing and dispersed fibers. However, dPFG and qMAS have a high sensitivity for beading, even in complex fiber tracts. Moreover, in tissues with coherent arrangements, such as the spinal cord or nerve fibers in which tract orientation is known a priori, a specific dPFG sequence variant decreases the effects of edema and improves specificity for beading. Collectively, the simulation results demonstrate that advanced DWI methods, particularly those which sample diffusion along multiple directions within a single acquisition, have improved sensitivity to acute axonal injury over conventional DTI metrics and hold promise for more informative clinical diagnostic use in CNS injury evaluation. Copyright © 2015 John Wiley & Sons, Ltd.     

Fast low‐angle shot diffusion tensor imaging with stimulated echo encoding in the muscle of rabbit shank

In the past, spin‐echo (SE) echo planar imaging(EPI)‐based diffusion tensor imaging (DTI) has been widely used to study the fiber structure of skeletal muscles in vivo. However, this sequence has several shortcomings when measuring restricted diffusion in small animals, such as its sensitivity to susceptibility‐related distortions and a relatively short applicable diffusion time. To address these limitations, in the current work, a stimulated echo acquisition mode (STEAM) MRI technique, in combination with fast low‐angle shot (FLASH) readout (turbo‐STEAM MRI), was implemented and adjusted for DTI in skeletal muscles. Signal preparation using stimulated echoes enables longer effective diffusion times, and thus the detection of restricted diffusion within muscular tissue with intracellular distances up to 100 µm. Furthermore, it has a reduced penalty for fast T₂ muscle signal decay, but at the expense of 50% signal loss compared with a SE preparation. Turbo‐STEAM MRI facilitates high‐resolution DTI of skeletal muscle without introducing susceptibility‐related distortions. To demonstrate its applicability, we carried out rabbit in vivo measurements on a human whole‐body 3 T scanner. DTI parameters of the shank muscles were extracted, including the apparent diffusion coefficient, fractional anisotropy, eigenvalues and eigenvectors. Eigenvectors were used to calculate maps of structural parameters, such as the planar index and the polar coordinates θ and ? of the largest eigenvector. These parameters were compared between three muscles. θ and ? showed clear differences between the three muscles, reflecting different pennation angles of the underlying fiber structures. Fiber tractography was performed to visualize and analyze the architecture of skeletal pennate muscles. Optimization of tracking parameters and utilization of T₂‐weighted images for improved muscle boundary detection enabled the determination of additional parameters, such as the mean fiber length. The presented results support the applicability of turbo‐STEAM MRI as a promising method for quantitative DTI analysis and fiber tractography in skeletal muscles. Copyright © 2013 John Wiley & Sons, Ltd.     

Improved Assessment of Ex Vivo Brainstem Neuroanatomy With High‐Resolution MRI and DTI at 7 Tesla

The aim of the present work was to provide the topography of the main gray nuclei and white matter tracts of the human brainstem at 7 Tesla (7 T) high‐field magnetic resonance imaging (MRI) using structural imaging (T1) and diffusion tensor imaging (DTI). Both imaging techniques represent a new field of increasing interest for its potential neuroanatomic and neuropathologic value. Brainstems were obtained postmortem from human donors, fixated by intracarotid perfusion of 10% neutral buffered formalin, and scanned in a Bruker BioSpec 7 T horizontal scanner. 3D‐data sets were acquired using the modified driven equilibrium Fourier transform (MDEFT) sequence and Spin Echo‐DTI (SE‐DTI) sequence was used for DTI acquisition. High‐resolution structural MRI and DTI of the human brainstem acquired postmortem reveals its basic cyto‐ and myeloar‐chitectonic organization, only visualized to this moment by histological techniques and higher magnetic field strengths. Brainstem structures that are usually not observed with lower magnetic fields were now topographically identified at midbrain, pons, and medullar levels. The application of high‐resolution structural MRI will contribute to precisely determine the extension and topography of brain lesions. Indeed, the current findings will be useful to interpret future high‐resolution in vivo MRI studies in living humans. Anat Rec, 2011. © 2011 Wiley‐Liss, Inc.     

Assessment of the diagnostic value of diffusion tensor imaging in patients with spinal cord compression: a meta-analysis

We investigated the diagnostic value of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of magnetic resonance diffusion tensor imaging (DTI) in patients with spinal cord compression (SCC) using a meta-analysis framework. Multiple scientific literature databases were exhaustively searched to identify articles relevant to this study. Mean values and standardized mean differences (SMDs) were calculated for the ADC and FA in normal and diseased tissues. The STATA version 12.0 software was used for statistical analysis. Of the 41 articles initially retrieved through database searches, 11 case-control studies were eligible for the meta-analysis and contained a combined total of 645 human subjects (394 patients with SCC and 251 healthy controls). All 11 studies reported data on FA, and 9 contained data related to the ADC. The combined SMDs of the ADC and FA showed that the ADC was significantly higher and the FA was lower in patients with SCC than in healthy controls. Subgroup analysis based on the b value showed higher ADCs in patients with SCC than in healthy controls at b values of both ≤500 and >500 s/mm². In summary, the main findings of this meta-analysis revealed an increased ADC and decreased FA in patients with SCC, indicating that DTI is an important diagnostic imaging tool to assess patients suspected to have SCC.     

Spatiotemporal microstructural white matter changes in diffusion tensor imaging after transient focal ischemic stroke in rats

Structural reorganization in white matter (WM) after stroke is a potential contributor to substitute or to newly establish the functional field on the injured brain in nature. Diffusion tensor imaging (DTI) is an imaging modality that can be used to evaluate damage and recovery within the brain. This method of imaging allows for in vivo assessment of the restricted movements of water molecules in WM and provides a detailed look at structural connectivity in the brain. For longitudinal DTI studies after a stroke, the conventional region of interest method and voxel‐based analysis are highly dependent on the user‐hypothesis and parameter settings for implementation. In contrast, tract‐based spatial statistics (TBSS) allows for reliable voxel‐wise analysis via the projection of diffusion‐derived parameters onto an alignment‐invariant WM skeleton. In this study, spatiotemporal WM changes were examined with DTI‐derived parameters (fractional anisotropy, FA; mean diffusivity, MD; axial diffusivity, DA; radial diffusivity, RD) using TBSS 2 h to 6 weeks after experimental focal ischemic stroke in rats (N = 6). FA values remained unchanged 2–4 h after the stroke, followed by a continuous decrease in the ipsilesional hemisphere from 24 h to 2 weeks post‐stroke and gradual recovery from the ipsilesional corpus callosum to the external capsule until 6 weeks post‐stroke. In particular, the fibers in these areas were extended toward the striatum of the ischemic boundary region at 6 weeks on tractography. The alterations of the other parameters in the ipsilesional hemisphere showed patterns of a decrease at the early stage, a subsequent pseudo‐normalization of MD and DA, a rapid reduction of RD, and a progressive increase in MD, DA and RD with a decreased extent in the injured area at later stages. The findings of this study may reflect the ongoing processes on tissue damage and spontaneous recovery after stroke.     

Intravoxel water diffusion heterogeneity imaging of human high‐grade gliomas

This study aimed to determine the potential value of intravoxel water diffusion heterogeneity imaging for brain tumor characterization and evaluation of high‐grade gliomas, by comparing an established heterogeneity index (α value) measured in human high‐grade gliomas to those of normal appearing white and grey matter landmarks. Twenty patients with high‐grade gliomas prospectively underwent diffusion‐weighted magnetic resonance imaging using multiple b‐values. The stretched‐exponential model was used to generate α and distributed diffusion coefficient (DDC) maps. The α values and DDCs of the tumor and contralateral anatomic landmarks were measured in each patient. Differences between α values of tumors and landmark tissues were assessed using paired t‐tests. Correlation between tumor α and tumor DDC was assessed using Pearson's correlation coefficient. Mean α of tumors was significantly lower than that of contralateral frontal white matter (p = 0.0249), basal ganglia (p < 0.0001), cortical grey matter (p < 0.0001), and centrum semiovale (p = 0.0497). Correlation between tumor α and tumor DDC was strongly negative (Pearson correlation coefficient, ?0.8493; p < 0.0001). The heterogeneity index α of human high‐grade gliomas is significantly different from those of normal brain structures, which potentially offers a new method for evaluating brain tumors. The observed negative correlation between tumor α and tumor DDC requires further investigation. Copyright © 2009 John Wiley & Sons, Ltd.