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Cognitive impairment (CI) is a major manifestation of multiple sclerosis (MS) and is responsible for extensively hindering patient quality of life. Cortical gray matter (cGM) damage is a significant contributor to CI, but is poorly characterized by conventional MRI let alone with quantitative MRI, such as quantitative magnetization transfer (qMT). Here we employed high-resolution qMT at 7T via the selective inversion recovery (SIR) method, which provides tissue-specific indices of tissue macromolecular content, such as the pool size ratio (PSR) and the rate of MT exchange (kmf). These indices could represent expected demyelination that occurs in the presence of gray matter damage. We utilized selective inversion recovery (SIR) qMT which provides a low SAR estimate of macromolecular-bulk water interactions using a tailored, B1 and B0 robust inversion recovery (IR) sequence acquired at multiple inversion times (TI) at 7T and fit to a two-pool model of magnetization exchange. Using this sequence, we evaluated qMT indices across relapsing-remitting multiple sclerosis patients (N = 19) and healthy volunteers (N = 37) and derived related associations with neuropsychological measures of cognitive impairment. We found a significant reduction in k in cGM of MS patients (15.5%, p = 0.002), unique association with EDSS (ρ = -0.922, p = 0.0001), and strong correlation with cognitive performance (ρ = -0.602, p = 0.0082). Together these findings indicate that the rate of MT exchange (k) may be a significant biomarker of cGM damage relating to CI in MS.
Copyright © 2019 Elsevier Inc. All rights reserved.
Functional MRI (fMRI) signals are robustly detectable in white matter (WM) but they have been largely ignored in the fMRI literature. Their nature, interpretation, and relevance as potential indicators of brain function remain under explored and even controversial. Blood oxygenation level dependent (BOLD) contrast has for over 25 years been exploited for detecting localized neural activity in the cortex using fMRI. While BOLD signals have been reliably detected in grey matter (GM) in a very large number of studies, such signals have rarely been reported from WM. However, it is clear from our own and other studies that although BOLD effects are weaker in WM, using appropriate detection and analysis methods they are robustly detectable both in response to stimuli and in a resting state. BOLD fluctuations in a resting state exhibit similar temporal and spectral profiles in both GM and WM, and their relative low frequency (0.01-0.1 Hz) signal powers are comparable. They also vary with baseline neural activity e.g. as induced by different levels of anesthesia, and alter in response to a stimulus. In previous work we reported that BOLD signals in WM in a resting state exhibit anisotropic temporal correlations with neighboring voxels. On the basis of these findings, we derived functional correlation tensors that quantify the correlational anisotropy in WM BOLD signals. We found that, along many WM tracts, the directional preferences of these functional correlation tensors in a resting state are grossly consistent with those revealed by diffusion tensors, and that external stimuli tend to enhance visualization of specific and relevant fiber pathways. These findings support the proposition that variations in WM BOLD signals represent tract-specific responses to neural activity. We have more recently shown that sensory stimulations induce explicit BOLD responses along parts of the projection fiber pathways, and that task-related BOLD changes in WM occur synchronously with the temporal pattern of stimuli. WM tracts also show a transient signal response following short stimuli analogous to but different from the hemodynamic response function (HRF) characteristic of GM. Thus there is converging and compelling evidence that WM exhibits both resting state fluctuations and stimulus-evoked BOLD signals very similar (albeit weaker) to those in GM. A number of studies from other laboratories have also reported reliable observations of WM activations. Detection of BOLD signals in WM has been enhanced by using specialized tasks or modified data analysis methods. In this mini-review we report summaries of some of our recent studies that provide evidence that BOLD signals in WM are related to brain functional activity and deserve greater attention by the neuroimaging community.
Copyright © 2019 Elsevier Inc. All rights reserved.
Because the white matter of the cerebral cortex contains axons that connect distant neurons in the cortical gray matter, the relationship between the volumes of the 2 cortical compartments is key for information transmission in the brain. It has been suggested that the volume of the white matter scales universally as a function of the volume of the gray matter across mammalian species, as would be expected if a global principle of wiring minimization applied. Using a systematic analysis across several mammalian clades, here we show that the volume of the white matter does not scale universally with the volume of the gray matter across mammals and is not optimized for wiring minimization. Instead, the ratio between volumes of gray and white matter is universally predicted by the same equation that predicts the degree of folding of the cerebral cortex, given the clade-specific scaling of cortical thickness, such that the volume of the gray matter (or the ratio of gray to total cortical volumes) divided by the square root of cortical thickness is a universal function of total cortical volume, regardless of the number of cortical neurons. Thus, the very mechanism that we propose to generate cortical folding also results in compactness of the white matter to a predictable degree across a wide variety of mammalian species.
Neuroimaging often involves acquiring high-resolution anatomical images along with other low-resolution image modalities, like diffusion and functional magnetic resonance imaging. Performing gray matter statistics with low-resolution image modalities is a challenge due to registration artifacts and partial volume effects. Gray matter surface based spatial statistics (GS-BSS) has been shown to provide higher sensitivity using gray matter surfaces compared to that of skeletonization approach of gray matter based spatial statistics which is adapted from tract based spatial statistics in diffusion studies. In this study, we improve upon GS-BSS incorporating neurite orientation dispersion and density imaging (NODDI) based search (denoted N-GSBSS) by 1) enhancing metrics mapping from native space, 2) incorporating maximum orientation dispersion index (ODI) search along surface normal, and 3) proposing applicability to other modalities, such as functional MRI (fMRI). We evaluated the performance of N-GSBSS against three baseline pipelines: volume-based registration, FreeSurfer's surface registration and ciftify pipeline for fMRI and simulation studies. First, qualitative mean ODI results are shown for N-GSBSS with and without NODDI based search in comparison with ciftify pipeline. Second, we conducted one-sample t-tests on working memory activations in fMRI to show that the proposed method can aid in the analysis of low resolution fMRI data. Finally we performed a sensitivity test in a simulation study by varying percentage change of intensity values within a region of interest in gray matter probability maps. N-GSBSS showed higher sensitivity in the simulation test compared to the other methods capturing difference between the groups starting at 10% change in the intensity values. The computational time of N-GSBSS is 68 times faster than that of traditional surface-based or 86 times faster than that of ciftify pipeline analysis.
Copyright © 2019 Elsevier Inc. All rights reserved.
PURPOSE - To measure the transverse relaxation time T* in healthy human cervical spinal cord gray matter (GM) and white matter (WM) at 3T.
METHODS - Thirty healthy volunteers were recruited. Axial images were acquired using an averaged multi-echo gradient-echo (mFFE) T*-weighted sequence with 5 echoes. We used the signal equation for an mFFE sequence with constant dephasing gradients after each echo to jointly estimate the spin density and T* for each voxel.
RESULTS - No global difference in T* was observed between all GM (41.3 ± 5.6 ms) and all WM (39.8 ± 5.4 ms). No significant differences were observed between left (43.2 ± 6.8 ms) and right (43.4 ± 5.5 ms) ventral GM, left (38.3 ± 6.1 ms) and right (38.6 ± 6.5 ms) dorsal GM, and left (39.4 ± 5.8 ms) and right (40.3 ± 5.8 ms) lateral WM. However, significant regional differences were observed between ventral (43.4 ± 5.7 ms) and dorsal (38.4 ± 6.0 ms) GM (p < 0.05), as well as between ventral (42.9 ± 6.5 ms) and dorsal (37.9 ± 6.2 ms) WM (p < 0.05). In analyses across slices, inferior T* was longer than superior T* in GM (44.7 ms vs. 40.1 ms; p < 0.01) and in WM (41.8 ms vs. 35.9 ms; p < 0.01).
CONCLUSIONS - Significant differences in T* are observed between ventral and dorsal GM, ventral and dorsal WM, and superior and inferior GM and WM. There is no evidence for bilateral asymmetry in T* in the healthy cord. These values of T* in the spinal cord are notably lower than most reported values of T* in the cortex.
© 2019 International Society for Magnetic Resonance in Medicine.
Accurate estimates of the BOLD hemodynamic response function (HRF) are crucial for the interpretation and analysis of event-related functional MRI data. To date, however, there have been no comprehensive measurements of the HRF in white matter (WM) despite increasing evidence that BOLD signals in WM change after a stimulus. We performed an event-related cognitive task (Stroop color-word interference) to measure the HRF in selected human WM pathways. The task was chosen in order to produce robust, distributed centers of activity throughout the cortex. To measure the HRF in WM, fiber tracts were reconstructed between each pair of activated cortical areas. We observed clear task-specific HRFs with reduced magnitudes, delayed onsets and prolonged initial dips in WM tracts compared with activated grey matter, thus calling for significant changes to current standard models for accurately characterizing the HRFs in WM and for modifications of standard methods of analysis of functional imaging data.
Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.
© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: email@example.com.
BACKGROUND - Cognitive impairment (CI) profoundly impacts quality of life for patients with multiple sclerosis (MS). Dysfunctional regulation of glutamate in gray matter (GM) has been implicated in the pathogenesis of MS by post-mortem pathological studies and in CI by in vivo magnetic resonance spectroscopy, yet GM pathology is subtle and difficult to detect using conventional T- and T-weighted magnetic resonance imaging (MRI). There is a need for high-resolution, clinically accessible imaging techniques that probe molecular changes in GM.
OBJECTIVE - To study cortical GM pathology related to CI in MS using glutamate-sensitive chemical exchange saturation transfer (GluCEST) MRI at 7.0 Tesla (7T).
METHODS - A total of 20 patients with relapsing-remitting MS and 20 healthy controls underwent cognitive testing, anatomical imaging, and GluCEST imaging. Glutamate-sensitive image contrast was quantified for cortical GM, compared between cohorts, and correlated with clinical measures of CI.
RESULTS AND CONCLUSION - Glutamate-sensitive contrast was significantly increased in the prefrontal cortex of MS patients with accumulated disability ( < 0.05). In addition, glutamate-sensitive contrast in the prefrontal cortex was significantly correlated with symbol digit modality test ( = -0.814) and choice reaction time ( = 0.772) scores in patients ( < 0.05), suggesting that GluCEST MRI may have utility as a marker for GM pathology and CI.
Numerous studies have used functional magnetic resonance imaging (fMRI) to characterize functional connectivity between cortical regions by analyzing correlations in blood oxygenation level dependent (BOLD) signals in a resting state. However, to date, there have been only a handful of studies reporting resting state BOLD signals in white matter. Nonetheless, a growing number of reports has emerged in recent years suggesting white matter BOLD signals can be reliably detected, though their biophysical origins remain unclear. Moreover, recent studies have identified robust correlations in a resting state between signals from cortex and specific white matter tracts. In order to further validate and interpret these findings, we studied a non-human primate model to investigate resting-state connectivity patterns between parcellated cortical volumes and specific white matter bundles. Our results show that resting-state connectivity patterns between white and gray matter structures are not randomly distributed but share notable similarities with diffusion- and histology-derived anatomic connectivities. This suggests that resting-state BOLD correlations between white matter fiber tracts and the gray matter regions to which they connect are directly related to the anatomic arrangement and density of WM fibers. We also measured how different levels of baseline neural activity, induced by varying levels of anesthesia, modulate these patterns. As anesthesia levels were raised, we observed weakened correlation coefficients between specific white matter tracts and gray matter regions while key features of the connectivity pattern remained similar. Overall, results from this study provide further evidence that neural activity is detectable by BOLD fMRI in both gray and white matter throughout the resting brain. The combined use of gray and white matter functional connectivity could also offer refined full-scale functional parcellation of the entire brain to characterize its functional architecture.
Published by Elsevier Inc.
Functional magnetic resonance imaging (fMRI) depicts neural activity in the brain indirectly by measuring blood oxygenation level dependent (BOLD) signals. The majority of fMRI studies have focused on detecting cortical activity in gray matter (GM), but whether functional BOLD signal changes also arise in white matter (WM), and whether neural activities trigger hemodynamic changes in WM similarly to GM, remain controversial, particularly in light of the much lower vascular density in WM. However, BOLD effects in WM are readily detected under hypercapnic challenges, and the number of reports supporting reliable detections of stimulus-induced activations in WM continues to grow. Rather than assume a particular hemodynamic response function, we used a voxel-by-voxel analysis of frequency spectra in WM to detect WM activations under visual stimulation, whose locations were validated with fiber tractography using diffusion tensor imaging (DTI). We demonstrate that specific WM regions are robustly activated in response to visual stimulation, and that regional distributions of WM activation are consistent with fiber pathways reconstructed using DTI. We further examined the variation in the concordance between WM activation and fiber density in groups of different sample sizes, and compared the signal profiles of BOLD time series between resting state and visual stimulation conditions in activated GM as well as activated and non-activated WM regions. Our findings confirm that BOLD signal variations in WM are modulated by neural activity and are detectable with conventional fMRI using appropriate methods, thus offering the potential of expanding functional connectivity measurements throughout the brain.
Copyright © 2018 Elsevier Inc. All rights reserved.