Importance of exactb-tensor calculation for quantitative diffusion tensor imaging and tracking of neuronal fiber bundles

Quantitative diffusion tensor imaging (DTI) is a novel method of magnetic resonance (MR) imaging providing information on the brain’s microstructure in vivo. DTI can be effectively measured with modern clinical MR scanners. However, imaging sequence details required for accurateb matrix calculation and for following DTI quantification are normally unknown to the user. In this work, we investigated the accuracy ofb value approximation if theb matrix is calculated without taking into account the effect of imaging gradients. It was found that an error of more than 4% in DTI estimation arises for a quite typical brain imaging protocol. The errors in mean diffusivity and fractional anisotropy index depend on diffusion tensor shape and eigenvectors orientation and exceed noise level in DTI quantification. These errors however have a strong impact on fiber tracking — up to 30% difference was found between the fiber tracks corresponding to exact and approximate calculated DTI data. Since these errors are dependent on imaging parameters and sequence implementation, accurateb matrix calculations are important for adequate comparison between data acquired on different MR scanners and also for data measured with the different imaging protocols.     

Localized high-resolution DTI of the human midbrain using single-shot EPI,parallel imaging,and outer-volume suppression at 7 T

Localized high-resolution diffusion tensor images (DTI) from the midbrain were obtained using reduced field-of-view (rFOV) methods combined with SENSE parallel imaging and single-shot echo planar (EPI) acquisitions at 7 T. This combination aimed to diminish sensitivities of DTI to motion, susceptibility variations, and EPI artifacts at ultra-high field. Outer-volume suppression (OVS) was applied in DTI acquisitions at 2- and 1-mm² resolutions, b = 1000 s/mm², and six diffusion directions, resulting in scans of 7- and 14-min durations. Mean apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured in various fiber tract locations at the two resolutions and compared. Geometric distortion and signal-to-noise ratio (SNR) were additionally measured and compared for reduced-FOV and full-FOV DTI scans. Up to an eight-fold data reduction was achieved using DTI-OVS with SENSE at 1 mm², and geometric distortion was halved. The localization of fiber tracts was improved, enabling targeted FA and ADC measurements. Significant differences in diffusion properties were observed between resolutions for a number of regions suggesting that FA values are impacted by partial volume effects even at a 2-mm² resolution. The combined SENSE DTI-OVS approach allows large reductions in DTI data acquisition and provides improved quality for high-resolution diffusion studies of the human brain.     

DTI at 7 and 3 T: systematic comparison of SNR and its influence on quantitative metrics

Diffusion tensor imaging (DTI) and advanced related methods such as diffusion spectrum and kurtosis imaging are limited by low signal-to-noise ratio (SNR) at conventional field strengths. DTI at 7 T can provide increased SNR; however, B0 and B1 inhomogeneity and shorter T2? still pose formidable challenges. The purpose of this study was to quantify and compare SNR at 7 and 3 T for different parallel imaging reduction factors, R, and TE, and to evaluate SNRs influences on fractional anisotropy (FA) and apparent diffusion coefficient (ADC). We found that R>4 at 7 T and R≥2 at 3 T were needed to reduce geometric distortions due to B0 inhomogeneity. For these R at 7 T, SNR was 70-90 for b=0 s/mm² and 22-28 for b=1000s/mm² in central brain regions. SNR was lower at 3 T (40 for b=0 s/mm² and 15 for b=1000 s/mm²) and in lateral brain regions at 7 T due to B1 inhomogeneity. FA and ADC did not change with MRI field strength, SENSE factor or TE in the tested range. However, the coefficient of variation for FA increased for SNR <15 and for SNR <10 in ADC, consistent with published theoretical studies. Our study demonstrates that 7 T is advantageous for DTI and lays the groundwork for further development. Foremost, future work should further address challenges with B0 and B1 inhomogeneity to take full advantage for the increased SNR at 7 T.     

Minimal gradient encoding for robust estimation of diffusion anisotropy

This study has investigated the relationship between the noise sensitivity of measurement by magnetic resonance imaging (MRI) of the diffusion tensor (D) of water and the number N of diffusion-weighting (DW) gradient directions, using computer simulations of strongly anisotropic fibers with variable orientation. The DW directions uniformly sampled the diffusion ellipsoid surface. It is shown that the variation of the signal-to-noise ratio (SNR) of three ideally rotationally invariant scalars of D due to variable fiber orientation provides an objective quantitative measure for the diffusion ellipsoid sampling efficiency, which is independent of the SNR value of the baseline signal obtained without DW; the SNR variation decreased asymptotically with increasing N. The minimum number N(0) of DW directions, which minimized the SNR variation of the three scalars of D was determined, thereby achieving the most efficient ellipsoid sampling. The resulting time efficient diffusion tensor imaging (DTI) protocols provide robust estimation of diffusion anisotropy in the presence of noise and can improve the repeatability/reliability of DTI experiments when there is high variability in the orientation of similar anisotropic structures, as for example, in studies which require repeated measurement of one individual, intersubject comparisons or multicenter studies.     

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.     

描述人体内水分子扩散各向异性特征的新方法

通过核磁共振扩散张量成像(DTI)得到的特定值域的扩散各向异性指数(DAI) 可用于揭示水分子扩散椭球的形态学特征, 定量反映被成像物体内部水分子扩散的优势方向和强度, 间接得到被成像物体内部的组织结构信息. DAI的可靠性直接影响对DTI数据的分析和理解. 本文基于扩散张量椭球的几何学信息, 提出利用扩散椭球几何比(EGR)定量描述水分子扩散的各向异性程度. 通过蒙特卡罗模拟实验和对人脑DTI数据进行分析, 并与当前广泛应用的水分子扩散各向异性分数(FA)和近期文献提出的扩散椭球面积比(EAR)进行对比. 实验发现EGR在不同级别噪声影响下的对比度效果和抗噪性都优于FA及EAR. 而且EGR 加入了体积修正, 增强了盘形扩散张量情况下的敏感性, 能够更好地鉴别神经纤维束交叉情况, 对于各向异性扩散程度较高的白质深层和相对均质的表层都有较好的量化区分结果. 关键词： 扩散系数 各向异性扩散 扩散张量成像 扩散椭球几何比     

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.     

Diffusion tensor parameters and principal eigenvector coherence: Relation to b-value intervals and field strength

Diffusion-weighted MRI images acquired at b-value greater than 1000 s mm^− 2 measure the diffusion of a restricted pool of water molecules. High b-value images are accompanied by a reduction in signal-to-noise ratio (SNR) due to the application of large diffusion gradients. By fitting the diffusion tensor model to data acquired at incremental b-value intervals, we determined the effect of SNR on tensor parameters in normal human brains, in vivo. In addition, we also investigated the impact of field strength on the diffusion tensor model. Data were acquired at 1.5 and 3 T, at b-values 0, 1000, 2000 and 3000 s mm^− 2 in twenty diffusion-sensitised directions. Fractional anisotropy (FA), mean diffusivity (MD) and principal eigenvector coherence (κ) were calculated from diffusion tensors fitted between datasets with b-values 0–1000, 0–2000, 0–3000, 1000–2000 and 2000–3000 s mm^− 2. Field strength and b-value effects on diffusion parameters were analysed in white and grey matter regions of interest. Decreases in FA, κ and MD were found with increasing b-value in white matter. Univariate analysis showed a significant increase in FA with increasing field strength in highly organised white matter. These results suggest there are significant differences in diffusion parameters at 1.5 and 3 T and that the optimal results, in terms of the highest values of FA in white matter, are obtained at 3 T with a maximum b = 1000 s mm^− 2.     

Region-Specific Susceptibilities to Cuprizone-Induced Demyelination of C57BL/6 Mouse: In vivo T2WI and DTI Studies at 7.0T

The cuprizone (CPZ) mouse model of demyelination was recognized and used to explore multiple sclerosis (MS)-like brain lesions. In this study, we assessed CPZ-treated mice using T₂-weighted imaging and diffusion tensor imaging (DTI). C57BL/6 mice treated with 2 weeks of 0.2 % CPZ-containing diet (n = 10) and regular chow diet (n = 10) were scanned with a 7.0 T MRI scanner (Agilent, USA), respectively, using fast spin-echo and fast spin-echo DTI sequences. The normalized T₂ signal intensity (normalized to the cerebrospinal fluid) was calculated and fractional anisotropy (FA value), mean diffusivity, axial diffusivity and radial diffusivity were measured in the brain region of the cerebral cortex (CTX), caudate putamen (CP), hippocampus (HP) and thalamus (TH). Compared with controls, increased normalized T₂ signal intensities and reduced FA values (p < 0.05) were observed in the CTX, HP and CP (p < 0.01), but not in TH in cuprizone-fed mice. In the regions of reduced FA values, an increase in mean diffusivity (p < 0.05) and radial diffusivity (p < 0.05) was also found. Significant decreased axial diffusivity was only observed in CTX (p < 0.05). DTI is sensitive to detecting cuprizone-induced demyelination of C57BL/6 mice. This study suggests that CTX, HP and CP are more susceptible to cuprizone-induced demyelination than TH. Our results also indicate that the decrease of FA value may be more likely due to increased radial diffusivity.     

Effect of B-value in revealing postinfarct myocardial microstructural remodeling using MR diffusion tensor imaging

Nonmonoexponential diffusion behavior has been previously reported to exist in some biological tissues, making quantification of diffusion tensor imaging (DTI) indices dependent on diffusion sensitivity of b-value. This study aims to investigate the effect of b-value in revealing postinfarct myocardial microstructural remodeling in ex vivo hearts. DTI scans were performed on heart samples 1, 3, 5, and 7 days after infarction induction as well as intact controls with b-values of 500 to 2500 s/mm². DTI indices, including fractional anisotropy (FA), and mean and directional diffusivities, were measured in infarct, adjacent and remote regions with zero and each non-zero b-values respectively using conventional DTI analysis. Experimental results showed that these DTI indices decreased gradually with b-values in all regions and groups. Optimal b-values were found to vary with targeted DTI indices, and could strengthen DTI ability in revealing myocardium degradation with using conventional DTI approach. Specifically, FA showed the most sensitive detection of fiber integrity degradation at moderate b-values (≈ 1500 to 2000 s/mm²), and the greatest ability of mean and directional diffusivities in monitoring diffusivity alteration occurred at relatively small b-values (≤ 1500 s/mm²) during the necrotic and fibrotic phases. These findings may provide useful information for DTI protocol parameter optimization in assessing heart microstructures at other pathological or in vivo states in the future.     

Diffusion tensor imaging of oral carcinoma: Clinical evaluation and comparison with histopathological findings

PurposeThis study aims to assess the usefulness of diffusion tensor imaging (DTI) as a noninvasive method for the evaluation of histological grade and lymph node metastasis in patients with oral carcinoma (OC).Materials and methodsThirty-six consecutive patients with histologically confirmed OC underwent examination by 3-T MRI. DTI was performed using a single-shot echo-planar imaging sequence with b values of 0 and 1000 s/mm² and motion-probing gradients in 12 noncollinear directions. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were compared with histopathological findings. The DTI parameters were correlated with the histological grade of the OCs based on the World Health Organization grading criteria and the presence or absence of lymph node metastasis.ResultsThe FA values (0.275 ± 0.058) of OC were significantly lower than those of normal tongue, muscle, and parotid glands (P < 0.001 for all), and the MD, AD, and RD values (1.220 ± 0.149, 1.434 ± 0.172, and 1.019 ± 0.165 × 10⁻³ mm²/s, respectively) were significantly higher than their respective normal values (P < 0.001 for all). Significant inverse correlations with histological grades were shown for FA, MD, AD, and RD values in OC patients (r = −0.862, r = −0.797, r = −0.747, and r = −0.844, respectively; P < 0.001 for all). In addition, there was a significant difference in the FA values of metastatic and nonmetastatic lymph nodes (0.186 vs. 0.276), MD (0.923 vs. 1.242 × 10⁻³ mm²/s), AD (1.246 vs. 1.621 × 10⁻³ mm²/s), and RD (0.792 vs. 1.100 × 10⁻³ mm²/s; P < 0.001 for all).ConclusionsDTI may be clinically useful for the noninvasive evaluation of histological grade and lymph node metastasis in OC patients.     

White matter maturation in the brains of Long Evans shaker myelin mutant rats by ex-vivo QSI and DTI

The brains of Long Evans shaker (les) rats, a model of dysmyelination, and their age- matched controls were studied by ex-vivo q-space diffusion imaging (QSI) and diffusion tensor imaging (DTI). The QSI and DTI indices were computed from the same acquisition. The les and the control brains were studied at different stages of maturation and disease progression. The mean displacement, the probability for zero displacement and kurtosis were computed from QSI data while the fractional anisotropy (FA) and the eigenvalues were computed from DTI. It was found that all QSI indices detect the les pathology, at all stages of maturation, while only some of the DTI indices could detect the les pathology. The QSI mean displacement was larger in the les group as compared with their age-matched controls while the probability for zero displacement and the kurtosis were both lower all indicating higher degree of restriction in the control brains. Since all the DTI eigenvalues were higher in the les brains as compared to controls, the less efficient DTI measure for discerning the les pathology was found to be the FA. Clearly, the most sensitive DTI parameter to the les pathology is λ₃, i.e. the minimal diffusivity. Since the QSI and DTI data were obtained from the same acquisition, despite the somewhat higher SNR of the QSI data compared to the DTI data, it seems that the higher diagnostic capacity of the QSI data in this experimental model of dysmyelination, originates mainly from the higher diffusing weighting of the QSI data.     

A theoretical study of the effect of experimental noise on the measurement of anisotropy in diffusion imaging

Diffusion tensor imaging (DTI) is a modality known to be highly sensitive to the detrimental effects of experimental noise. Here, using Monte Carlo simulations, we compare and contrast how noise complicates the measurement of diffusion anisotropy in diffusion tensor and conventional diffusion-weighted imaging (DWI). As the signal-to-noise ratio (SNR) decreases below a value of approximately 20, the eigenvalues (λ_i) of the diffusion tensor D are found to diverge rapidly from their true values, with the result that the measured anisotropy can be significantly in error and isotropic structures falsely assigned a high level of anisotropy. The effect of noise on the rotationally variant indices, calculated from a conventional diffusion-weighted imaging experiment, is found to be much less insidious, because the apparent diffusion coefficients (ADCs) diverge only slowly as the signal-to-noise decreases. Thus, although rotationally variant indices almost always underestimate the true diffusion anisotropy, they show only a small susceptibility to experimental noise and hence, are preferred to their rotationally invariant counterparts when the signal-to-noise ratio is small.     

Understanding changes in DTI metrics in patients with different stages of neurocysticercosis

Diffusion tensor imaging (DTI) was performed on 25 patients with neurocysticercosis (NCC). The aim of this study was to investigate the changes in DTI measures during the evolutionary course of NCC lesions from vesicular to calcified stage in the brain. DTI measures were quantified from the NCC lesions of all patients. On the basis of conventional imaging findings, NCC lesions were classified into vesicular, vesicular colloidal, granular nodular and calcified stages. Significant inverse correlation was observed between the evolutionary stage of NCC lesion and mean diffusivity (MD; r=−0.748, P<0.001) and spherical anisotropy (CS; r=−0.585, P<.001) values. Significant direct correlations were observed between evolutionary stages of NCC lesion and mean fractional anisotropy (FA; r=0.575, P<0.001), linear anisotropy (CL; r=0.478, p<0.001) and planar anisotropy (CP; r=0.561, p<0.001) values. Successive decrease in MD values calculated from NCC lesions was observed, moving from vesicular to granular nodular stage. On FA, CL and CP maps, a significant increase in signal intensity value was observed in calcified as compared to other stages. We conclude that DTI measures may indicate the evolutionary changes in NCC from vesicular to calcified stage.     

Comparison of mouse brain DTI maps using K-space average,image-space average,or no average approach

Diffusion tensor imaging (DTI) is achieved by collecting a series of diffusion-weighted images (DWIs). Signal averaging of multiple repetitions can be performed in the k-space (k-avg) or in the image space (m-avg) to improve the image quality. Alternatively, one can treat each acquisition as an independent image and use all of the data to reconstruct the DTI without doing any signal averaging (no-avg). To compare these three approaches, in this study, in vivo DTI data were collected from five normal mice. Noisy data with signal-to-noise ratios (SNR) that varied between five and 30 (before averaging) were then simulated. The DTI indices, including relative anisotropy (RA), trace of diffusion tensor (TR), axial diffusivity (λ║), and radial diffusivity (λ ⊥), derived from the k-avg, m-avg, and no-avg, were then compared in the corpus callosum white matter, cortex gray matter, and the ventricles. We found that k-avg and m-avg enhanced the SNR of DWI with no significant differences. However, k-avg produced lower RA in the white matter and higher RA in the gray matter, compared to the m-avg and no-avg, regardless of SNR. The latter two produced similar DTI quantifications. We concluded that k-avg is less preferred for DTI brain imaging.     

Automated assessment of the quality of diffusion tensor imaging data using color cast of color-encoded fractional anisotropy images

Diffusion tensor imaging (DTI) data often suffer from artifacts caused by motion. These artifacts are especially severe in DTI data from infants, and implementing tight quality controls is therefore imperative for DTI studies of infants. Currently, routine procedures for quality assurance of DTI data involve the slice-wise visual inspection of color-encoded, fractional anisotropy (CFA) images. Such procedures often yield inconsistent results across different data sets, across different operators who are examining those data sets, and sometimes even across time when the same operator inspects the same data set on two different occasions. We propose a more consistent, reliable, and effective method to evaluate the quality of CFA images automatically using their color cast, which is calculated on the distribution statistics of the 2D histogram in the color space as defined by the International Commission on Illumination (CIE) on lightness and a and b (LAB) for the color-opponent dimensions (also known as the CIELAB color space) of the images. Experimental results using DTI data acquired from neonates verified that this proposed method is rapid and accurate. The method thus provides a new tool for real-time quality assurance for DTI data.     

Reduced anisotropy of water diffusion in structural cerebral abnormalities demonstrated with diffusion tensor imaging

We used diffusion tensor imaging (DTI) to investigate the behavior of water diffusion in cerebral structural abnormalities. The fractional anisotropy, a measure of directionality of the molecular motion of water, and the mean diffusivity, a measure of the magnitude of the molecular motion of water, were measured in 18 patients with longstanding partial epilepsy and structural abnormalities on standard magnetic resonance imaging and the results compared with measurements in the white matter of 10 control subjects. Structural abnormalities were brain damage (postsurgical brain damage, nonspecific brain damage, perinatal brain damage, perinatal infarct, ischemic infarct, perinatal hypoxia, traumatic brain damage (n = 3), mitochondrial cytopathy and mesiotemporal sclerosis), dysgenesis (cortical dysplasia (n = 2) and heterotopia) and tumors (meningioma (n = 2), hypothalamic hamartoma and glioma). Anisotropy was reduced in all structural abnormalities. In the majority of abnormalities this was associated with an increased mean diffusivity; however, 30% of all structural abnormalities (some patients with brain damage and dysgenesis) had a normal mean diffusivity in combination with a reduced anisotropy. There was no correlation between fractional anisotropy and mean diffusivity measurements in structural abnormalities (r = -0.1). Our findings suggest that DTI is sensitive for the detection of a variety of structural abnormalities, that a reduced anisotropy is the common denominator in structural cerebral abnormalities of different etiologies and that mean diffusivity and fractional anisotropy may be, in part, independent. Combined measurements of mean diffusivity and fractional anisotropy are likely to increase the specificity of DTI.     

Atlas-based and DTI-guided quantification of human brain cerebral blood flow: Feasibility,quality assurance,spatial heterogeneity and age effects

Accurate and noninvasive quantification of regional cerebral blood perfusion (CBF) of the human brain tissue would advance the study of the complex interplay between human brain structure and function, in both health and disease. Despite the plethora of works on CBF in gray matter, a detailed quantitative white matter perfusion atlas has not been presented on healthy adults using the International Consortium for Brain Mapping atlases. In this study, we present a host of assurance measures such as temporal stability, spatial heterogeneity and age effects of regional and global CBF in selected deep, cortical gray matter and white matter tracts identified and quantified using diffusion tensor imaging (DTI). We utilized whole brain high-resolution DTI combined with arterial spin labeling to quantify regional CBF on 15 healthy adults aged 23.2–57.1 years. We present total brain and regional CBF, corresponding volume, mean diffusivity and fractional anisotropy spatial heterogeneity, and dependence on age as additional quality assurance measures to compare with published trends using both MRI and nuclear medicine methods. Total CBF showed a steady decrease with age in gray matter (r=?0.58; P= .03), whereas total CBF of white matter did not significantly change with age (r= 0.11; P= .7). This quantitative report offers a preliminary baseline of CBF, volume and DTI measurements for the design of future multicenter and clinical studies utilizing noninvasive perfusion and DT-MRI.     

In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T

BackgroundDiffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed.MethodsA multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated.ResultsThe SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above.ConclusionThe single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.     

High spatial and angular resolution diffusion-weighted imaging reveals forniceal damage related to memory impairment

Introduction

Diffusion tensor imaging (DTI) measures in patients with multiple sclerosis (MS), particularly those measures associated with a specific white matter pathway, have consistently shown correlations with function. This study sought to investigate correlations between DTI measures in the fornix and common cognitive deficits in MS patients, including episodic memory, working memory and attention.

Materials and Methods

Patients with MS and group age- and sex-matched controls underwent high-resolution diffusion scanning (1-mm isotropic voxels) and cognitive testing. Manually drawn forniceal regions of interest were applied to individual maps of tensor-derived measures, and mean values of transverse diffusivity (TD), mean diffusivity (MD), longitudinal diffusivity (LD) and fractional anisotropy (FA) were calculated.

Results

In 40 patients with MS [mean age±S.D.= 42.55±9.1 years; Expanded Disability Status Scale (EDSS)=2.0±1.2; Multiple Sclerosis Functional Composite (MSFC) score=0.38±0.46] and 20 healthy controls (mean age±S.D.= 41.35±9.7 years; EDSS=0.0±0; MSFC score=0.74±0.24), we found that FA, MD and TD values in the fornix were significantly different between groups (P< .03), and patient performance on the Brief Visuospatial Memory Test-Revised (BVMT-R) was correlated with DTI measures (P< .03).

Discussion

These results are consistent with findings of axonal degeneration in MS and support the use of DTI as an indicator of disease progression.