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Selective inversion recovery (SIR) is a quantitative magnetization transfer (qMT) method that provides estimates of parameters related to myelin content in white matter, namely the macromolecular pool-size-ratio (PSR) and the spin-lattice relaxation rate of the free pool (R), without the need for independent estimates of ∆B, B, and T. Although the feasibility of performing SIR in the human brain has been demonstrated, the scan times reported previously were too long for whole-brain applications. In this work, we combined optimized, short-TR acquisitions, SENSE/partial-Fourier accelerations, and efficient 3D readouts (turbo spin-echo, SIR-TSE; echo-planar imaging, SIR-EPI; and turbo field echo, SIR-TFE) to obtain whole-brain data in 18, 10, and 7 min for SIR-TSE, SIR-EPI, SIR-TFE, respectively. Based on numerical simulations, all schemes provided accurate parameter estimates in large, homogenous regions; however, the shorter SIR-TFE scans underestimated focal changes in smaller lesions due to blurring. Experimental studies in healthy subjects (n = 8) yielded parameters that were consistent with literature values and repeatable across scans (coefficient of variation: PSR = 2.2-6.4%, R = 0.6-1.4%) for all readouts. Overall, SIR-TFE parameters exhibited the lowest variability, while SIR-EPI parameters were adversely affected by susceptibility-related image distortions. In patients with relapsing remitting multiple sclerosis (n = 2), focal changes in SIR parameters were observed in lesions using all three readouts; however, contrast was reduced in smaller lesions for SIR-TFE, which was consistent with the numerical simulations. Together, these findings demonstrate that efficient, accurate, and repeatable whole-brain SIR can be performed using 3D TFE, EPI, or TSE readouts; however, the appropriate readout should be tailored to the application.
Copyright © 2020 Elsevier Inc. All rights reserved.
PURPOSE - This study aims to systematically evaluate the accuracy and precision of pool size ratio (PSR) measurements from quantitative magnetization transfer (qMT) acquisitions using simplified models in the context of assessing injury-associated spatiotemporal changes in spinal cords of non-human primates. This study also aims to characterize changes in the spinal tissue pathology in individual subjects, both regionally and longitudinally, in order to demonstrate the relationship between regional tissue compositional changes and sensorimotor behavioral recovery after cervical spinal cord injury (SCI).
METHODS - MRI scans were recorded on anesthetized monkeys at 9.4 T, before and serially after a unilateral section of the dorsal column tract. Images were acquired following saturating RF pulses at different offset frequencies. Models incorporating two pools of protons but with differing numbers of variable parameters were used to fit the data to derive qMT parameters. The results using different amounts of measured data and assuming different numbers of variable model parameters were compared. Behavioral impairments and recovery were assessed by a food grasping-retrieving task. Histological sections were obtained post mortem for validation of the injury.
RESULTS - QMT fitting provided maps of pool size ratio (PSR), the relative amounts of immobilized protons exchanging magnetization compared to the "free" water. All the selected modeling approaches detected a lesion/cyst at the site of injury as significant reductions in PSR values. The regional contrasts in the PSR maps obtained using the different fittings varied, but the 2-parameter fitting results showed strong positive correlations with results from 5-parameter modeling. 2-parameter fitting results with modest (>3) RF offsets showed comparable sensitivity for detecting demyelination in white matter and loss of macromolecules in gray matter around lesion sites compared to 5-parameter fitting with fully-sampled data acquisitions. Histology confirmed that decreases of PSR corresponded to regional demyelination around lesion sites, especially when demyelination occurred along the dorsal column on the injury side. Longitudinally, PSR values of injured dorsal column tract and gray matter horns exhibited remarkable recovery that associated with behavioral improvement.
CONCLUSION - Simplified qMT modeling approaches provide efficient and sensitive means to detect and characterize injury-associated demyelination in white matter tracts and loss of macromolecules in gray matter and to monitor its recovery over time.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.
OBJECTS - The diffusion-based spherical mean technique (SMT) provides a novel model to relate multi-b-value diffusion magnetic resonance imaging (MRI) data to features of tissue microstructure. We propose the first clinical application of SMT to image the brain of patients with multiple sclerosis (MS) and investigate clinical feasibility and translation.
METHODS - Eighteen MS patients and nine age- and sex-matched healthy controls (HCs) underwent a 3.0 Tesla scan inclusive of clinical sequences and SMT images (isotropic resolution of 2 mm). Axial diffusivity (AD), apparent axonal volume fraction (V ), and effective neural diffusivity (D ) parametric maps were fitted. Differences in AD, V , and D between anatomically matched regions reflecting different tissues types were estimated using generalized linear mixed models for binary outcomes.
RESULTS - Differences were seen in all SMT-derived parameters between chronic black holes (cBHs) and T2-lesions (P ≤ 0.0016), in V and AD between T2-lesions and normal appearing white matter (NAWM) (P < 0.0001), but not between the NAWM and normal WM in HCs. Inverse correlations were seen between V and AD in cBHs (r = -0.750, P = 0.02); in T2-lesions D values were associated with V (r = 0.824, P < 0.0001) and AD (r = 0.570, P = 0.014).
INTERPRETATIONS - SMT-derived metrics are sensitive to pathological changes and hold potential for clinical application in MS patients.
© 2019 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.
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.
Early life stress (ELS) is a risk factor for the development of depression in adolescence; the mediating neurobiological mechanisms, however, are unknown. In this study, we examined in early pubertal youth the associations among ELS, cortisol stress responsivity, and white matter microstructure of the uncinate fasciculus and the fornix, two key frontolimbic tracts; we also tested whether and how these variables predicted depressive symptoms in later puberty. A total of 208 participants (117 females; M age = 11.37 years; M Tanner stage = 2.03) provided data across two or more assessment modalities: ELS; salivary cortisol levels during a psychosocial stress task; diffusion magnetic resonance imaging; and depressive symptoms. In early puberty there were significant associations between higher ELS and decreased cortisol production, and between decreased cortisol production and increased fractional anisotropy in the uncinate fasciculus. Further, increased fractional anisotropy in the uncinate fasciculus predicted higher depressive symptoms in later puberty, above and beyond earlier symptoms. In post hoc analyses, we found that sex moderated several additional associations. We discuss these findings within a broader conceptual model linking ELS, emotion dysregulation, and depression across the transition through puberty, and contend that brain circuits implicated in the control of hypothalamic-pituitary-adrenal axis function should be a focus of continued research.
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.
Understanding the relationship between the diffusion-weighted MRI signal and the arrangement of white matter fibers is fundamental for accurate voxel-wise reconstruction of the fiber orientation distribution (FOD) and subsequent fiber tractography. Spherical deconvolution reconstruction techniques model the diffusion signal as the convolution of the FOD with a response function that represents the signal profile of a single fiber orientation. Thus, given the signal and a fiber response function, the FOD can be estimated in every imaging voxel by deconvolution. However, the selection of the appropriate response function remains relatively under-studied, and requires further validation. In this work, using 3D histologically defined FODs and the corresponding diffusion signal from three ex vivo squirrel monkey brains, we derive the ground truth response functions. We find that the histologically derived response functions differ from those conventionally used. Next, we find that response functions statistically vary across brain regions, which suggests that the practice of using the same kernel throughout the brain is not optimal. We show that different kernels lead to different FOD reconstructions, which in turn can lead to different tractography results depending on algorithmic parameters, with large variations in the accuracy of resulting reconstructions. Together, these results suggest there is room for improvement in estimating and understanding the relationship between the diffusion signal and the underlying FOD.
© 2019 John Wiley & Sons, Ltd.