Exploratory voxel-based analysis of diffusion indices and hemispheric asymmetry in normal aging

Age-related microstructural changes in brain white matter can be studied by utilizing indices derived from diffusion tensor imaging (DTI): apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The objective of this study is to examine alterations in FA and ADC by employing exploratory voxel-based analysis (VBA) and region(s) of interest (ROI)-based analysis. A highly nonlinear registration algorithm was used to align the ADC and FA image volumes of different subjects to perform accurate voxel-level statistics for two age groups, as well as for hemispheric asymmetry for both age groups. VBA shows significant age-related decline in FA with frontal predominance (frontal white matter, and genu and anterior body of the corpus callosum), superior portions of a splenium and highly oriented fibers of the posterior limb of the internal capsule and the anterior and posterior limbs of the external capsule. Hemispheric asymmetry of FA, as assessed by VBA, showed that for the young-age group, significant right-greater-than-left asymmetry exists in the genu, splenium and body of the corpus callosum and that left-greater-than-right asymmetry exists in the anterior limb of the external capsule and in the posterior limb of the internal capsule, thalamus, cerebral peduncle and temporal-parietal regions. VBA of the hemispheric asymmetry of the middle-age group revealed much less asymmetry. Regions showing age-related changes and hemispheric asymmetry from VBA were, for a majority of the findings, in conformance with ROI analysis and with the known pattern of development and age-related degradation of fiber tracks. The study shows the feasibility of the VBA of DTI indices for exploratory investigations of subtle differences in population cohorts, especially when findings are not localized and/or known a priori.     

Sex differences in the relationship between white matter microstructure and impulsivity in adolescents

Rapid maturational brain changes occur during adolescence--a time associated with risk-taking behaviors and improvements in cognition. The present study examined the relationship between white matter (WM) microstructure, impulsive behavior and response inhibition in female and male adolescents. Twenty-one healthy adolescents underwent diffusion tensor imaging using a 3.0-T magnetic resonance imaging system. Impulse control was assessed using the Bar-On Emotional Quotient Inventory, Youth Version. Response inhibition was assessed using the Stroop Color-Word Interference Test. Fractional anisotropy (FA), a measure of WM coherence, and trace, a measure of overall diffusivity, were determined from voxels manually placed in the midline and in the left and right forward-projecting arms of the genu and the splenium of the corpus callosum. Sex-specific differences were observed for the relationship between FA and impulsive behavior in the right anterior callosum for males and in the splenium for females. Males, compared to females, displayed significantly higher FA in the left WM region. Although trace was not associated with impulse control, trace in the genu (for females) and splenium (males and females) was associated with Stroop performance. Regional differences in trace also were evident, with lower values in the splenium observed than in all other regions. Although the latter significantly improved with age, no sex differences in impulse control or in Stroop performance were detected. The present findings provide supporting evidence for sex-related differences in the development of WM microstructure during adolescence. These data further suggest a neurobiological mechanism underlying some of the emotional and cognitive changes commonly observed in males versus females during the adolescent period.     

Effects of interpolation methods in spatial normalization of diffusion tensor imaging data on group comparison of fractional anisotropy

This study investigated the effects on the measurement of fractional anisotropy (FA) during interpolation of diffusion tensor images in spatial normalization, which is required for voxel-based statistics. Diffusion tensor imaging data were obtained from nine male patients with attention deficit/hyperactivity disorder and nine age-matched control subjects. Regions of interest were selected from the genu of corpus callosum (GCC) and the right anterior corona radiata (RACR), with FA values measured before and after spatial normalization using two interpolation algorithms: linear and rotationally linear. Computer simulations were performed to verify the experimental findings. Between-group difference in FA was observed in the GCC and RACR before spatial normalization (P<.00001). Interpolation reduced the measured FA values significantly (P<.00001 for both algorithms) but did not affect the group difference in the GCC. For the RACR, the between-group difference vanished (P=.968) after linear interpolation but was relatively unaffected by using rotationally linear interpolation (P=.00001). FA histogram analysis and computer simulations confirmed these findings. This work suggests that caution should be exercised in voxel-based group comparisons as spatial normalization may affect the FA value in nonnegligible degrees, particularly in brain areas with predominantly crossing fibers.     

Is diffusion anisotropy an accurate monitor of myelination?: Correlation of multicomponent T2 relaxation and diffusion tensor anisotropy in human brain

We compare T2-relaxation and diffusion tensor data from normal human brain. The relationships between myelin-water fraction (MWF) and various diffusion tensor measures [e.g., fractional anisotropy (FA), perpendicular diffusivity (ADC perpendicular) and mean diffusivity ] in white matter (WM) and gray matter (GM) structures in the brain were examined in 16 normal volunteers at 1.5 T and 6 normal subjects at 3.0 T and mean diffusivity. We found some degree of linear correlation between these measurements, but by using region of interest (ROI)-based analysis, we also observed several structures which seemed to deviate significantly from a linear relationship. From all investigated relationships between various diffusion tensor measures and myelin-water content, FA and ADC perpendicular yielded the highest correlation coefficients with MWF. However, diffusion anisotropy was also significantly influenced by factors other than myelin-water content. The less operator-dependent voxel-based analysis (VBA) between myelin-water and diffusional anisotropy measures is proposed as an innovative alternative to ROI-based analysis. We confirmed that WM structures, in general, have higher diffusional anisotropy than GM structures and also have higher myelin-water content. However, our findings suggest that in the highly organized fibre arrangement of compact WM structures such as the genu of the corpus callosum, elevated degrees of diffusional anisotropies are measured, which do not necessarily correspond to an elevated myelin content but more likely reflect the highly organized directionality of fibre bundles in these areas (low microscopic and macroscopic tortuosity) as well as strongly restricted diffusion in the interstitial space between the myelinated axons. Conversely, in structures with disorganized fibre bundles and multiple fibre crossings, such as the minor and major forceps, low FA values were measured, which does not necessarily reflect a decrease myelin-water content.     

Tics are caused by alterations in prefrontal areas, thalamus and putamen, while changes in the cingulate gyrus reflect secondary compensatory mechanisms

Background

Despite strong evidence that the pathophysiology of Tourette syndrome (TS) involves structural and functional disturbances of the basal ganglia and cortical frontal areas, findings from in vivo imaging studies have provided conflicting results. In this study we used whole brain diffusion tensor imaging (DTI) to investigate the microstructural integrity of white matter pathways and brain tissue in 19 unmedicated, adult, male patients with TS “only” (without comorbid psychiatric disorders) and 20 age- and sex-matched control subjects.

Results

Compared to normal controls, TS patients showed a decrease in the fractional anisotropy index (FA) bilaterally in the medial frontal gyrus, the pars opercularis of the left inferior frontal gyrus, the middle occipital gyrus, the right cingulate gyrus, and the medial premotor cortex. Increased apparent diffusion coefficient (ADC) maps were detected in the left cingulate gyrus, prefrontal areas, left precentral gyrus, and left putamen. There was a negative correlation between tic severity and FA values in the left superior frontal gyrus, medial frontal gyrus bilaterally, cingulate gyrus bilaterally, and ventral posterior lateral nucleus of the right thalamus, and a positive correlation in the body of the corpus callosum, left thalamus, right superior temporal gyrus, and left parahippocampal gyrus. There was also a positive correlation between regional ADC values and tic severity in the left cingulate gyrus, putamen bilaterally, medial frontal gyrus bilaterally, left precentral gyrus, and ventral anterior nucleus of the left thalamus.

Conclusions

Our results confirm prior studies suggesting that tics are caused by alterations in prefrontal areas, thalamus and putamen, while changes in the cingulate gyrus seem to reflect secondary compensatory mechanisms. Due to the study design, influences from comorbidities, gender, medication and age can be excluded.     

Constrained spherical deconvolution-based tractography to depict and characterize a case of “hyperplastic fornix dorsalis”

The authors report the relevance of Constrained Spherical Deconvolution (CSD)-based tractography in demonstrating and quantitatively assessing a complex midline structure malformation in a 9-year-old girl with moderate intellectual disability and thickening of corpus callosum (CC) body discovered through conventional MRI (cMRI). Color-encoded fractional anisotropy (FA) maps clearly demonstrated what the cMRI showed as a thicknening of CC: a green, longitudinal bundle running dorsally to the body of CC. A more complex midline maldevelopmental disorder was suspected. CSD-based tractography was performed to virtually dissect the anomalous supracallosal longitudinal bundle (SLB), CC, fornix, anterior commissure (AC) and cingula. In addition, DTI-derived metrics were calculated for each virtually dissected fiber tract.     

A framework for quality control and parameter optimization in diffusion tensor imaging: theoretical analysis and validation

In this communication, a theoretical framework for quality control and parameter optimization in diffusion tensor imaging (DTI) is presented and validated. The approach is based on the analytical error propagation of the mean diffusivity (D(av)) obtained directly from the diffusion-weighted data acquired using rotationally invariant and uniformly distributed icosahedral encoding schemes. The error propagation of a recently described and validated cylindrical tensor model is further extrapolated to the spherical tensor case (diffusion anisotropy approximately 0) to relate analytically the precision error in fractional tensor anisotropy (FA) with the mean diffusion-to-noise ratio (DNR). The approach provided simple analytical and empirical quality control measures for optimization of diffusion parameter space in an isotropic medium that can be tested using widely available water phantoms.     

Validation of the anisotropy index ellipsoidal area ratio in diffusion tensor imaging

A new diffusion anisotropy index, ellipsoidal area ratio (EAR), was described recently and proved to be less noise-sensitive than fractional anisotropy (FA) by theory and simulation. Here we show that EAR has higher signal-to-noise ratios than FA in average diffusion tensor imaging data from 40 normal subjects. EAR was also more sensitive than FA in detecting white matter abnormalities in a patient with widespread diffuse axonal injury. Monte Carlo simulation showed that EAR's mean values are more biased by noise than FA when anisotropy is small, both for single fiber tracts and when fiber tracts cross. However, the improved signal-to-noise ratio of EAR relative to FA suggests that EAR may be a superior measure of anisotropy both in quantifying both deep white matter with relatively uniform fiber tracts and pericortical white matter structure with relatively low anisotropy and fiber crossings.     

On the down-sampling of diffusion MRI data along the angular dimension

BackgroundIt has been established that the diffusion gradient directions in diffusion MRI should be uniformly distributed in 3D spherical space, so that orientation-dependent diffusion properties (e.g., fractional anisotropy or FA) can be properly quantified. Sometimes the acquired data need to be down-sampled along the angular dimension before computing diffusion properties (e.g., to exclude data points corrupted by motion artifact; to harmonize data obtained with different protocols). It is important to quantitatively assess the impact of data down-sampling on measurement of diffusion properties.Materials and methodsHere we report 1) a numerical procedure for down-sampling diffusion MRI (e.g., for data harmonization), and 2) a spatial uniformity index of diffusion directions, aiming to predict the quality of the chosen down-sampling schemes (e.g., from data harmonization; or rejection of motion corrupted data points). We quantitatively evaluated human diffusion MRI data, which were down-sampled from 64 or 60 diffusion gradient directions to 30 directions, in terms of their 1) FA value accuracy (using fully-sampled data as the ground truth), 2) FA fitting residuals, and 3) spatial uniformity indices.ResultsOur experimental data show that the proposed spatial uniformity index is correlated with errors in FA obtained from down-sampled diffusion MRI data. The FA fitting residuals that are typically used to assess diffusion MRI quality are not correlated with either FA errors or spatial uniformity index.ConclusionsThese results suggest that the spatial uniformity index could be more valuable in assessing quality of down-sampled diffusion MRI data, as compared with FA fitting residual measures. We expect that our implemented software procedure should prove valuable for 1) guiding data harmonization for multi-site diffusion MRI studies, and 2) assessing the impact of rejecting motion corrupted data points on the accuracy of diffusion measures.     

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.     

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.     

Role of diffusion tensor imaging metrics and in vivo proton magnetic resonance spectroscopy in the differential diagnosis of cystic intracranial mass lesions

The purpose of this study was to determine whether proton magnetic resonance spectroscopy (PMRS) and diffusion tensor imaging (DTI) indices, fractional anisotropy (FA) and mean diffusivity (MD) can be used to distinguish brain abscess from cystic brain tumors, which are difficult to distinguish by conventional magnetic resonance imaging (MRI). Fifty-three patients with intracranial cystic mass lesions and 10 normal controls were studied. Conventional MRI, PMRS and DTI of all the patients were performed on a 1.5-T GE scanner. Forty patients were with brain abscess and 13 with cystic tumors. Cytosolic amino acids (AAs) were present in 32 of 40 brain abscess patients. Out of 13 patients with cystic tumors, lactate and choline were seen in 3 and only lactate was present in 10 patients on PMRS. All 40 cases of abscess had high FA, while all 13 cases of tumor cysts had high MD values. We conclude that FA measurements are more sensitive in predicting the abscess, while PMRS and MD are more specific in differentiating abscess from cystic tumors. We suggest that PMRS should be combined with DTI rather than with diffusion-weighted imaging as FA can be used as an additional parameter for separation of abscess from other cystic intracranial mass lesions.     

Insights into brain microstructure from the T2 distribution

T2 weighting is particularly sensitive, but notoriously unspecific, to a wide range of brain pathologies. However, careful measurement and analysis of the T2 decay curve from brain tissue promise to provide much improved pathological specificity. In vivo T2 measurement requires accurate 180 pulses and appropriate manipulation of stimulated echoes; the most common approach is to acquire multiple echoes from a single slice. The T2 distribution, a plot of component amplitude as a function of T2, can be estimated using an algorithm capable of fitting a multi-exponential T2 decay with no a priori assumptions about the number of exponential components. T2 distributions from normal brain show peaks from myelin water, intra/extracellular water and cerebral spinal fluid; they can be used to provide estimates of total water content (total area under the T2 distribution) and myelin water fraction (MWF, fractional area under the myelin water peak), a measure believed to be related to myelin content. Experiments on bovine brain suggest that magnetization exchange between water pools plays a minor role in the T2 distribution. Different white matter structures have different MWFs. In normal white matter (NWM), MWF is not correlated with the magnetization transfer ratio (MTR) or the diffusion tensor fractional anisotropy (FA); hence it provides unique information about brain microstructure. Normal-appearing white matter (NAWM) in multiple sclerosis (MS) brain possesses a higher water content and lower MWF than controls, consistent with histopathological findings. Multiple sclerosis lesions demonstrate great heterogeneity in MWF, presumably due to varying myelin contents of these focal regions of pathology. Subjects with schizophrenia were found to have significantly reduced MWF in the minor forceps and genu of the corpus callosum when compared to controls, suggesting that reduced frontal lobe myelination plays a role in schizophrenia. In normal controls, frontal lobe myelination was positively correlated with both age and education; this result was not observed in subjects with schizophrenia. A strong correlation between MWF and the optical density from the luxol fast blue histological stain for myelin was observed in formalin-fixed brain, supporting the use of the MWF as an in vivo myelin marker.     

Evaluation of Disease Stage of Radiation-Induced Brain Injury: a DTI Study with Pathological Correlation

The aim of this study is to evaluate if diffusion tensor imaging (DTI) can distinguish the disease process of radiation-induced brain injury when combined with apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values. Twenty-one rabbits received irradiation of 100 Gy in the right brain hemisphere. Twelve rabbits were screened with magnetic resonance imaging (MRI) and DTI before radiation, and imaged at every week until week 9 following radiation. The rabbits that had MRI were euthanized at week 9 for histologic evaluation, while other nine rabbits without MRI were randomly killed for histologic evaluation at weeks 2, 4 and 6, respectively. From the DTI, the ADC and FA values were measured, and rADC and rFA were calculated. After radiation, the trend of the ADC value can be divided into three stages. In the first stage, the ADC value of the target tissues gradually decreased. In the second stage, the ADC value of white matter in the target tissues showed a recovery trend, back to the initial level similar to that in contralateral. In the third stage, the ADC value of white matter in the target tissue continues to increase over the ADC value of baseline and contralateral white matter. The FA value of radiation-targeted area showed continuous decreasing tendency. Pathological evaluation showed the different features in three stages. DTI can distinguish the different disease stages when combined with the ADC and FA values.     

Quantitative assessment of intracranial tumor response to dexamethasone using diffusion, perfusion and permeability magnetic resonance imaging

There is increasing interest in obtaining quantitative imaging parameters to aid in the assessment of tumor responses to treatment. In this study, the feasibility of performing integrated diffusion, perfusion and permeability magnetic resonance imaging (MRI) for characterizing responses to dexamethasone in intracranial tumors was assessed. Eight patients with glioblastoma, five with meningioma and three with metastatic carcinoma underwent MRI prior to and 48-72 h following dexamethasone administration. The MRI protocol enabled quantification of the volume transfer constant (K(trans)), extracellular space volume fraction (nu(e)), plasma volume fraction (nu(p)), regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), longitudinal relaxation time (T(1)) and mean diffusivity (D(av)). All subjects successfully completed the imaging protocol for the presteroid and poststeroid scans. Significant reductions were observed after the treatment for K(trans), nu(e) and nu(p) in enhancing tumor as well as for T(1) and D(av) in the edematous brain in glioblastoma; on the other hand, for meningioma, significant differences were seen only in edematous brain T(1) and D(av). No significant difference was observed for any parameter in metastatic carcinoma, most likely due to the small sample size. In addition, no significant difference was observed for enhancing tumor rCBF and rCBV in any of the tumor types, although the general trend was for rCBV to be reduced and for rCBF to be more variable. The yielded parameters provide a wealth of physiologic information and contribute to the understanding of dexamethasone actions on different types of intracranial tumors.     

Reproducibility and variation of diffusion measures in the squirrel monkey brain,in vivo and ex vivo

PurposeAnimal models are needed to better understand the relationship between diffusion MRI (dMRI) and the underlying tissue microstructure. One promising model for validation studies is the common squirrel monkey, Saimiri sciureus. This study aims to determine (1) the reproducibility of in vivo diffusion measures both within and between subjects; (2) the agreement between in vivo and ex vivo data acquired from the same specimen and (3) normal diffusion values and their variation across brain regions.MethodsData were acquired from three healthy squirrel monkeys, each imaged twice in vivo and once ex vivo. Reproducibility of fractional anisotropy (FA), mean diffusivity (MD), and principal eigenvector (PEV) was assessed, and normal values were determined both in vivo and ex vivo.ResultsThe calculated coefficients of variation (CVs) for both intra-subject and inter-subject MD were below 10% (low variability) while FA had a wider range of CVs, 2–14% intra-subject (moderate variability), and 3–31% inter-subject (high variability). MD in ex vivo tissue was lower than in vivo (30%–50% decrease), while FA values increased in all regions (30–39% increase). The mode of angular differences between in vivo and ex vivo PEVs was 12 degrees.ConclusionThis study characterizes the diffusion properties of the squirrel monkey brain and serves as the groundwork for using the squirrel monkey, both in vivo and ex vivo, as a model for diffusion MRI studies.     

Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation

Water diffusion anisotropy in the human brain is affected by disease, trauma, and development. Microscopic fractional anisotropy (μFA) is a diffusion MRI (dMRI) metric that can quantify water diffusion anisotropy independent of neuron fiber orientation dispersion. However, there are several different techniques to estimate μFA and few have demonstrated full brain imaging capabilities within clinically viable scan times and resolutions. Here, we present an optimized spherical tensor encoding (STE) technique to acquire μFA directly from the 2nd order cumulant expansion of the powder averaged dMRI signal obtained from direct linear regression (i.e. diffusion kurtosis) which requires fewer powder-averaged signals than other STE fitting techniques and can be rapidly computed. We found that the optimal dMRI parameters for white matter μFA imaging were a maximum b-value of 2000 s/mm² and a ratio of STE to LTE tensor encoded acquisitions of 1.7 for our system specifications. We then compared two implementations of the direct regression approach to the well-established gamma model in 4 healthy volunteers on a 3 Tesla system. One implementation used mean diffusivity (D) obtained from a 2nd order fit of the cumulant expansion, while the other used a linear estimation of D from the low b-values. Both implementations of the direct regression approach showed strong linear correlations with the gamma model (ρ = 0.97 and ρ = 0.90) but mean biases of −0.11 and − 0.02 relative to the gamma model were also observed, respectively. All three μFA measurements showed good test-retest reliability (ρ ≥ 0.79 and bias = 0). To demonstrate the potential scan time advantage of the direct approach, 2 mm isotropic resolution μFA was demonstrated over a 10 cm slab using a subsampled data set with fewer powder-averaged signals that would correspond to a 3.3-min scan. Accordingly, our results introduce an optimization procedure that has enabled nearly full brain μFA in only several minutes.     

Novel diffusion tensor imaging methodology to detect and quantify injured regions and affected brain pathways in traumatic brain injury

Purpose

To develop and apply diffusion tensor imaging (DTI)-based normalization methodology for the detection and quantification of sites of traumatic brain injury (TBI) and the impact of injury along specific brain pathways in (a) individual TBI subjects and (b) a TBI group.

Materials and Methods

Normalized DTI tractography was conducted in the native space of 12 TBI and 10 age-matched control subjects using the same number of seeds in each subject, distributed at anatomically equivalent locations. Whole-brain tracts from the control group were mapped onto the head of each TBI subject. Differences in the fractional anisotropy (FA) maps between each TBI subject and the control group were computed in a common space using a t test, transformed back to the individual TBI subject's head space, and thresholded to form regions of interest (ROIs) that were used to sort tracts from the control group and the individual TBI subject. Tract counts for a given ROI in each TBI subject were compared to group mean for the same ROI to quantify the impact of injury along affected pathways. The same procedure was used to compare the TBI group to the control group in a common space.

Results

Sites of injury within individual TBI subjects and affected pathways included hippocampal/fornix, inferior fronto-occipital, inferior longitudinal fasciculus, corpus callosum (genu and splenium), cortico-spinal tracts and the uncinate fasciculus. Most of these regions were also detected in the group study.

Conclusions

The DTI normalization methodology presented here enables automatic delineation of ROIs within the heads of individual subjects (or in a group). These ROIs not only localize and quantify the extent of injury, but also quantify the impact of injury on affected pathways in an individual or in a group of TBI subjects.     

Diffusional kurtosis imaging of cingulate fibers in Parkinson disease: Comparison with conventional diffusion tensor imaging

Objective

The pathological changes in Parkinson disease begin in the brainstem; reach the limbic system and ultimately spread to the cerebral cortex. In Parkinson disease (PD) patients, we evaluated the alteration of cingulate fibers, which comprise part of the limbic system, by using diffusional kurtosis imaging (DKI).

Methods

Seventeen patients with PD and 15 age-matched healthy controls underwent DKI with a 3-T MR imager. Diffusion tensor tractography images of the anterior and posterior cingulum were generated. The mean kurtosis (MK) and conventional diffusion tensor parameters measured along the images in the anterior and posterior cingulum were compared between the groups. Receiver operating characteristic (ROC) analysis was also performed to compare the diagnostic abilities of the MK and conventional diffusion tensor parameters.

Results

The MK and fractional anisotropy (FA) in the anterior cingulum were significantly lower in PD patients than in healthy controls. The area under the ROC curve was 0.912 for MK and 0.747 for FA in the anterior cingulum. MK in the anterior cingulum had the best diagnostic performance (mean cutoff, 0.967; sensitivity, 0.87; specificity, 0.94).

Conclusions

DKI can detect alterations of the anterior cingulum in PD patients more sensitively than can conventional diffusion tensor imaging. Use of DKI can be expected to improve the ability to diagnose PD.     

Anisotropic diffusion of metabolites in peripheral nerve using diffusion weighted magnetic resonance spectroscopy at ultra-high field

Although the diffusivity and anisotropy of water has been investigated thoroughly in ordered axonal systems (i.e., nervous tissue), there have been very few studies on the directional dependence of diffusion of metabolites. In this study, the mean apparent diffusion coefficient (Trace/3 ADC) and fractional anisotropy (FA) values of the intracellular metabolites N-acetyl aspartate (NAA), creatine and phosphocreatine (tCr), choline (Cho), taurine (Tau), and glutamate and glutamine (Glx) were measured parallel and perpendicular to the length of excised frog sciatic nerve using a water suppressed, diffusion-weighted, spin-echo pulse sequence at 18.8T. The degree of anisotropy (FA) of NAA (0.41+/-0.09) was determined to be less than tCr (0.59+/-0.07) and Cho (0.61+/-0.11), which is consistent with previously reported human studies of white matter. In contrast, Glx diffusion was found to be almost isotropic with an FA value of 0.20+/-0.06. The differences of FA between the metabolites is most likely due to their differing micro-environments and could be beneficial as an indicator of compartment specific changes with disease, information not readily available with water diffusion.