An empirical characterization of the quality of DTI data and the efficacy of dyadic sorting

Metrics calculated from images acquired using the diffusion tensor imaging (DTI) technique possess a systematic bias that depends on signal-to-noise ratio (SNR). Dyadic sorting provides a simple method for remediating some of this bias within a region(s) of interest (ROI). Although this bias and its removal using dyadic sorting have been studied previously within a theoretical framework, one can employ precise geometric knowledge of microstructures to perform an empirical comparison between expected DTI results and those measured with a scanner. In this project, the biasing effect of low SNR (approximately 1-10) on DTI eigenvalues was measured directly using water-filled capillary structures of two different sizes, and the magnitude of the corrective effect of dyadically sorting eigenvector-eigenvalue pairs was characterized. Multiple DTI series were acquired for determining DTI metrics at eight unique SNR values, using T(R) to vary signal intensity via T(1) contrast. Differences between the second and third eigenvalues, which should be equal for prolate geometry, ranged from approximately 23% to 45% and from 19% to 41% for large and small inner diameter capillaries after sorting eigenvalues by magnitude, and ranged from approximately 1% to 18% and from 1% to 4% after dyadic sorting. A high-resolution DTI series was used to observe the effect of ROI size on dyadic sorting. For restriction of diffusion on the scale of the small capillary at SNR approximately 18, an ROI with > or =50 pixels is adequate to determine fractional anisotropy to 99% accuracy, while larger ROI are required to resolve the two smaller eigenvalues to the same accuracy ( approximately 330-390 pixels). At low values of SNR, the iteration of dyadic sorting is suggested to achieve good accuracy. A method for the incorporation of empirical measurements into a bias-correction map, which would be useful for characterizing uncertainty and for reducing systematic bias in DTI data, is introduced.     

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.     

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.     

Voxelwise analysis of diffusion MRI of cervical spinal cord using tract-based spatial statistics

Robust voxelwise analysis using tract-based spatial statistics (TBSS) together with permutation statistical method is standardly used in analyzing diffusion tensor imaging (DTI) of brain. A similar analytical method could be useful when studying DTI of cervical spinal cord.Based on anatomical data of sixty-four healthy volunteers, white (WM) and gray matter (GM) masks were created and subsequently registered into DTI space. Using TBSS, two skeleton types were created (single line and dilated for WM as well as GM). From anatomical data, percentage rates of overlap were calculated for all skeletons in relation to WM and GM masks.Voxelwise analysis of fractional anisotropy values depending on age and sex was conducted. Correlation of fraction anisotropy values with age of subjects was also evaluated. The two WM skeleton types showed a high overlap rate with WM masks (~94%); GM skeletons showed lower rates (56% and 42%, respectively, for single line and dilated). WM and GM areas where fraction anisotropy values differ between sexes were identified (p < .05). Furthermore, using voxelwise analysis such WM voxels were identified where fraction anisotropy values differ depending on age (p < .05) and in these voxels linear dependence of fraction anisotropy and age (r = −0.57, p < .001) was confirmed by regression analysis. This dependence was not proven when using WM anatomical masks (r = −0.21, p = .10).The analytical approach presented shown to be useful for group analysis of DTI data for cervical spinal cord.     

Dependence of the fractional anisotropy in cervical spine from the number of diffusion gradients,repeated acquisition and voxel size

The aim of this study is to investigate the consequences of using different gradient schemes, number of repeated measurements and voxel size on the fractional anisotropy (FA) value in a diffusion tensor imaging (DTI) sequence on the cervical tract of the spinal cord. Twenty healthy volunteers underwent a total of 86 DTI axial acquisitions performed by using different voxel size and number of diffusion gradient directions (NDGDs). Three different diffusion gradient schemes were applied, named 6, 15 and 32 according to the NDGD. Furthermore, some acquisitions were repeated to investigate the effects of image averaging on FA value.     

Development and initial evaluation of 7-T q-ball imaging of the human brain

Diffusion tensor imaging (DTI) noninvasively depicts white matter connectivity in regions where the Gaussian model of diffusion is valid but yields inaccurate results in those where diffusion has a more complex distribution, such as fiber crossings. q-ball imaging (QBI) overcomes this limitation of DTI by more fully characterizing the angular dependence of intravoxel diffusion with larger numbers of diffusion-encoding directional measurements at higher diffusion-weighting factors (b values). However, the former technique results in longer acquisition times and the latter technique results in a lower signal-to-noise ratio (SNR). In this project, we developed specialized 7-T acquisition methods utilizing novel radiofrequency pulses, eight-channel parallel imaging EPI and high-order shimming with a phase-sensitive multichannel B0 field map reconstruction. These methods were applied in initial healthy adult volunteer studies, which demonstrated the feasibility of performing 7-T QBI. Preliminary comparisons of 3 T with 7 T within supratentorial crossing white matter tracts documented a 79.5% SNR increase for b=3000 s/mm2 (P=.0001) and a 38.6% SNR increase for b=6000 s/mm2 (P=.015). With spherical harmonic reconstruction of the q-ball orientation distribution function at b=3000 s/mm2, 7-T QBI allowed for accurate visualization of crossing fiber tracts with fewer diffusion-encoding acquisitions as compared with 3-T QBI. The improvement of 7-T QBI at b factors as high as 6000 s/mm2 resulted in better angular resolution as compared with 3-T QBI for depicting fibers crossing at shallow angles. Although the increased susceptibility effects at 7 T caused problematic distortions near brain-air interfaces at the skull base and posterior fossa, these initial 7-T QBI studies demonstrated excellent quality in much of the supratentorial brain, with significant improvements as compared with 3-T acquisitions in the same individuals.     

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

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

The ellipsoidal area ratio: an alternative anisotropy index for diffusion tensor imaging

In the processing and analysis of diffusion tensor imaging (DTI) data, certain predefined morphological features of diffusion tensors are often represented as simplified scalar indices, termed diffusion anisotropy indices (DAIs). When comparing tensor morphologies across differing voxels of an image, or across corresponding voxels in different images, DAIs are mathematically and statistically more tractable than are the full tensors, which are probabilistic ellipsoids consisting of three orthogonal vectors that each has a direction and an associated scalar magnitude. We have developed a new DAI, the "ellipsoidal area ratio" (EAR), to represent the degree of anisotropy in the morphological features of a diffusion tensor. The EAR is a normalized geometrical measure of surface curvature in the 3D diffusion ellipsoid. Monte Carlo simulations and applications to the study of in vivo human data demonstrate that, at low noise levels, EAR provides a similar contrast-to-noise ratio (CNR) but a higher signal-to-noise ratio (SNR) than does fractional anisotropy (FA), which is currently the most popular anisotropy index in active use. Moreover, at the high noise levels encountered most commonly in real-world DTI datasets, EAR compared with FA is consistently much more robust to perturbations from noise and it provides a higher CNR, features useful for the analysis of DTI data that are inherently noise sensitive.     

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.     

Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study

Diffusion tensor imaging (DTI) studies of human ischemic stroke within 24 h of symptom onset have reported variable findings of changes in diffusion anisotropy. Serial DTI within 24 h may clarify these heterogeneous results. We characterized longitudinal changes of diffusion anisotropy by analyzing discrete ischemic white matter (WM) and gray matter (GM) regions during the hyperacute (2.5-7 h) and acute (21.5-29 h) scanning phases of ischemic stroke onset in 13 patients. Mean diffusivity (MD), fractional anisotropy (FA) and T2-weighted signal intensity were measured for deep and subcortical WM and deep and cortical GM areas in lesions outlined by a > or =30% decrease in MD. Average reductions of approximately 40% in relative (r) MD were observed in all four brain regions during both the hyperacute and acute phases post stroke. Overall, 9 of 13 patients within 7 h post symptom onset showed elevated FA in at least one of the four tissues, and within the same cohort, 11 of 13 patients showed reduced FA in at least one of the ischemic WM and GM regions at 21.5-29 h after stroke. The fractional anisotropy in the lesion relative to the contralateral side (rFA, mean+/-S.D.) was significantly elevated in some patients in the deep WM (1.10+/-0.11, n=4), subcortical WM (1.13+/-0.14, n=4), deep GM (1.07+/-0.06, n=1) and cortical GM (1.22+/-0.13, n=5) hyperacutely (< or =7 h); however, reductions of rFA at approximately 24 h post stroke were more consistent (rFA= 0.85+/-0.12).     

Single-shot fast spin-echo diffusion tensor imaging of the lumbar spine at 1.5 and 3 T

Diffusion tensor imaging (DTI) of the lumbar spine could improve diagnostic specificity. The purpose of this work was to determine the feasibility of and to validate DTI with single-shot fast spin-echo (SSFSE) for lumbar intervertebral discs at 1.5 and 3 T. Six normal volunteers were scanned with DTI-SSFSE using an eight- and a three-b-value protocol at 1.5 and 3 T, respectively. Apparent diffusion coefficient (ADC) values were computed and validated based on those obtained at 1.5 T from corresponding diffusion tensor scans using line scan diffusion imaging (LSDI), a technique that has been previously validated for use in the spine. Pearson correlation coefficients for LSDI and DTI-SSFSE ADC values were .88 and .89 for 1.5 and 3 T, respectively, with good quantitative agreement according to the Bland-Altman method. Results indicate that DTI-SSFSE is a candidate as a clinical sequence for obtaining diffusion tensor images of the lumbar intervertebral discs with scan times shorter than 4 min.     

Principal eigenvector field segmentation for reproducible diffusion tensor tractography of white matter structures

The study was aimed to test the feasibility of utilizing an algorithmically determinable stable fiber mass (SFM) map obtained by an unsupervised principal eigenvector field segmentation (PEVFS) for automatic delineation of 18 white matter (WM) tracts: (1) corpus callosum (CC), (2) tapetum (TP), (3) inferior longitudinal fasciculus (ILF), (4) uncinate fasciculus (UNC), (5) inferior fronto-occipital fasciculus (IFO), (6) optic pathways (OP), (7) superior longitudinal fasciculus (SLF), (8) arcuate fasciculus (AF), (9) fornix (FX), (10) cingulum (CG), (11) anterior thalamic radiation (ATR), (12) superior thalamic radiation (STR), (13) posterior thalamic radiation (PTR), (14) corticospinal/corticopontine tract (CST/CPT), (15) medial lemniscus (ML), (16) superior cerebellar peduncle (SCP), (17) middle cerebellar peduncle (MCP) and (18) inferior cerebellar peduncle (ICP). Diffusion tensor imaging (DTI)-derived fractional anisotropy (FA) and the principal eigenvector field have been used to create the SFM consisting of a collection of linear voxel structures which are grouped together by color-coding them into seven natural classes to provide PEVFS signature segments which greatly facilitate the selection of regions of interest (ROIs) for fiber tractography using just a single mouse click, as compared with a manual drawing of ROIs in the classical approach. All the 18 fiber bundles have been successfully reconstructed, in all the subjects, using the single ROIs provided by the SFM approach, with their reproducibility characterized by the fact that the ROI selection is user independent. The essentially automatic PEVFS method is robust, efficient and compares favorably with the classical ROI methods for diffusion tensor tractography (DTT).     

In vivo diffusion tensor imaging of thoracic and cervical rat spinal cord at 7 T

In vivo diffusion tensor imaging (DTI) of rat cervical and thoracic spinal cord was performed using a three-element phased array coil at 7 T. The magnetic field was shimmed over the spinal cord in real time using an in-house developed automatic algorithm. Echo planar imaging (EPI)-based diffusion-weighted images (DWIs) were acquired with 21 gradient encoding directions. The DWIs were tensor encoded, and diffusion tensor metrics, fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusivity (λ₀) and transverse diffusivity (λ) were determined for both white matter (WM) and gray matter (GM). The results on six normal rats indicated no significant differences in the diffusion tensor metrics between thoracic and cervical regions. However, the DTI-derived metrics in cervical spinal cord from our study are somewhat different from the published results in rats. The possible reasons for these differences are suggested.     

Subject-specific changes in brain white matter on diffusion tensor imaging after sports-related concussion

Background and Purpose

Current approaches to diffusion tensor imaging (DTI) analysis do not permit identification of individual-level changes in DTI indices. We investigated the ability of wild bootstrapping analysis to detect subject-specific changes in brain white matter (WM) before and after sports-related concussion.

Materials and Methods

A prospective cohort study was performed in nine high school athletes engaged in hockey or football and six controls. Subjects underwent DTI pre- and postseason within a 3-month interval. One athlete was diagnosed with concussion (scanned within 72 h), and eight suffered between 26 and 399 subconcussive head blows. Fractional anisotropy (FA) and mean diffusivity (MD) were measured in each WM voxel. Bootstrap samples were generated, and a permuted t test was used to compare voxel-wise FA/MD changes in each subject pre- vs. postseason.

Results

The percentage of WM voxels with significant (p<.05) pre–post FA changes was highest for the concussion subject (3.2%), intermediary for those with subconcussive head blows (mean 1.05%±.15%) and lowest for controls (mean 0.28%±.01%). Similarly, the percentage of WM voxels with significant MD changes was highest for the concussion subject (3.44%), intermediary for those with subconcussive head blows (mean 1.48%±.17%) and lowest for controls (mean 0.48%±.05%). Significantly changed FA and MD voxels colocalized in the concussion subject to the right corona radiata and right inferior longitudinal fasciculus.

Conclusions

Wild bootstrap analysis detected significantly changed WM in a single concussed athlete. Athletes with multiple subconcussive head blows had significant changes in a percentage of their WM that was over three times higher than controls. Efforts to understand the significance of these WM changes and their relationship to head impact forces appear warranted.     

In vivo measurements of multi-component T2 relaxation behaviour in guinea pig brain

Multi-echo Carr-Purcell-Meiboom-Gill (CPMG) imaging sequences were implemented on 1.5 T and 4.0 T imaging systems to test their ability to measure in vivo multi-component T2 relaxation behavior in normal guinea pig brain. The known dependence of accurate T2 measurements on the signal-to-noise ratio (SNR) was explored in vivo by comparing T2 decay data obtained using three methods to increase SNR (improved RF coil design, signal averaging and increased magnetic field strength). Good agreement between T2 values of nickel-doped agarose phantoms was found between imaging and spectroscopic methods. T2 values were determined for gray matter (GM) and white matter (WM) locations from images of guinea pig brain in vivo. T2 measurements of GM were found to be monoexponential at both field strengths. The mean T2 times for GM were 71 ms at 1.5 T, and 53 ms at 4.0T. The highest average SNR was achieved using an improved RF coil at 4.0T. In this case, two peaks were extracted in WM, a "short" T2 peak at approximately 6 ms, and a "medium" T2 peak at approximately 48 ms. T2 values in GM and the major component of WM were significantly decreased at 4.0T compared to 1.5 T. The improved SNR attained with this optimized imaging protocol at 4.0T has allowed for the first time extraction of the myelin-sensitive T2 component of WM in animal brain in vivo.     

Reproducibility and biases in high field brain diffusion MRI: An evaluation of acquisition and analysis variables

Diffusion tensor imaging (DTI) of in-vivo human brain provides insights into white matter anatomical connectivity, but little is known about measurement difference biases and reliability of data obtained with last generation high field scanners (> 3 T) as function of MRI acquisition and analyses variables. Here we assess the impact of acquisition (voxel size: 1.8 × 1.8 × 1.8, 2 × 2 × 2 and 2.5 × 2.5 × 2.5 mm³, b-value: 700, 1000 and 1300 s/mm²) and analysis variables (within-session averaging and co-registration methods) on biases and test-retest reproducibility of some common tensor derived quantities like fractional anisotropy (FA), mean diffusivity (MD), axial and radial diffusivity in a group of healthy subjects at 4 T in three regions: arcuate fasciculus, corpus callosum and cingulum. Averaging effects are also evaluated on a full-brain voxel based approach. The main results are: i) group FA and MD reproducibility errors across scan sessions are on average double of those found in within-session repetitions (≈ 1.3 %), regardless of acquisition protocol and region; ii) within-session averaging of two DTI acquisitions does not improve reproducibility of any of the quantities across sessions at the group level, regardless of acquisition protocol; iii) increasing voxel size biased MD, axial and radial diffusivities to higher values and FA to lower values; iv) increasing b-value biased all quantities to lower values, axial diffusivity showing the strongest effects; v) the two co-registration methods evaluated gave similar bias and reproducibility results. Altogether these results show that reproducibility of FA and MD is comparable to that found at lower fields, not significantly dependent on pre-processing and acquisition protocol manipulations, but that the specific choice of acquisition parameters can significantly bias the group measures of FA, MD, axial and radial diffusivities.     

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.     

Discriminative analysis of multivariate features from structural MRI and diffusion tensor images

Imaging markers derived from magnetic resonance images, together with machine learning techniques allow for the recognition of unique anatomical patterns and further differentiating Alzheimer's disease (AD) from normal states. T1-based imaging markers, especially volumetric patterns have demonstrated their discriminative potential, however, rely on the tissue abnormalities of gray matter alone. White matter abnormalities and their contribution to AD discrimination have been studied by measuring voxel-based intensities in diffusion tensor images (DTI); however, no systematic study has been done on the discriminative power of either region-of-interest (ROI)-based features from DTI or the combined features extracted from both T1 images and DTI. ROI-based analysis could potentially reduce the feature dimensionality of DTI indices, usually from more than 10e + 5, to 10–150 which is almost equal to the order of magnitude with respect to volumetric features from T1. Therefore it allows for straight forward combination of intensity based landmarks of DTI indices and volumetric features of T1. In the present study, the feasibility of tract-based features related to Alzheimer's disease was first evaluated by measuring its discriminative capability using support vector machine on fractional anisotropy (FA) maps collected from 21 subjects with Alzheimer's disease and 15 normal controls. Then the performance of the tract-based FA + gray matter volumes-combined feature was evaluated by cross-validation. The combined feature yielded good classification result with 94.3% accuracy, 95.0% sensitivity, 93.3% specificity, and 0.96 area under the receiver operating characteristic curve. The tract-based FA and the tract-based FA + gray matter volumes-combined features are certified their feasibilities for the recognition of anatomical features and may serve to complement classification methods based on other imaging markers.     

MR spectroscopic imaging of glutathione in the white and gray matter at 7 T with an application to multiple sclerosis

Detection of glutathione (GSH) is technically challenging at clinical field strengths of 1.5 or 3 T due to its low concentration in the human brain coupled with the fact that conventional single-echo acquisitions, typically used for magnetic resonance (MR) spectroscopy acquisitions, cannot be used to resolve GSH given its overlap with other resonances. In this study, an MR spectral editing scheme was used to generate an unobstructed detection of GSH at 7 T. This technique was used to obtain normative white (WM) and gray matter (GM) GSH concentrations over a two-dimensional region. Results indicated that GSH was significantly higher (P<.001) in GM relative to WM in normal subjects. This finding is consistent with previous radionuclide experiments and histochemical staining and validates this 7 T MR spectroscopy technique. To our knowledge, this is the first study to report normative differences in WM and GM glutathione concentrations in the human brain. Glutathione is a biomarker for oxidative status and this non-invasive in vivo measurement of GSH was used to explore its sensitivity to oxidative state in multiple sclerosis (MS) patients. There was a significant reduction (P<.001) of GSH between the GM in MS patients and normal controls. No statistically significant GSH differences were found between the WM in controls and MS patients. Reduced GSH was also observed in a MS WM lesion. This preliminary investigation demonstrates the potential of this marker to probe oxidative state in MS.