Human Brain White Matter Research Articles

Empirical validation of gradient field models for an accurate ADC measured on clinical 3T MR systems in body oncologic applications.

To empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations. Spatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients. To illustrate spatial impact of GNL on ADC, diffusion weighted imaging using three orthogonal gradient directions was performed on a volunteer brain positioned at isocenter (as a reference) and offset superiorly by 10-17cm (>10% predicted GNL bias). The SPH tensor-based GNL correction was applied to individual DWI gradient directions, and derived ADC was compared with low-bias reference for human brain white matter (WM) ROIs. Empiric and predicted GNL errors were comparable for all three studied 3T MR systems, with <1.0% differences in the median and width of spatial histograms for individual GNL tensor elements. Median (±width) of ADC (10-3mm2/s) histograms measured at isocenter in WM reference ROIs from three MR systems were: 0.73±0.11, 0.71±0.14, 0.74±0.17, and at off-isocenters (before versus after GNL correction) were respectively 0.63±0.14 versus 0.72±0.11, 0.53±0.16 versus 0.74±0.18, and 0.65±0.16 versus 0.76±0.18. The phantom-based spatial distortion measurements validated vendor-provided gradient fields, and accurate WM ADC was recovered regardless of spatial locations and clinical MR platforms using system-specific tensor-based GNL correction for routine DWI.

Compartmental diffusion and microstructural properties of human brain gray and white matter studied with double diffusion encoding magnetic resonance spectroscopy of metabolites and water

Double diffusion encoding (DDE) of the water signal offers a unique ability to separate the effect of microscopic anisotropic diffusion in structural units of tissue from the overall macroscopic orientational distribution of cells. However, the specificity in detected microscopic anisotropy is limited as the signal is averaged over different cell types and across tissue compartments. Performing side-by-side water and metabolite DDE spectroscopic (DDES) experiments provides complementary measures from which intracellular and extracellular microscopic fractional anisotropies (μFA) and diffusivities can be estimated. Metabolites are largely confined to the intracellular space and therefore provide a benchmark for intracellular μFA and diffusivities of specific cell types. By contrast, water DDES measurements allow examination of the separate contributions to water μFA and diffusivity from the intra- and extracellular spaces, by using a wide range of b values to gradually eliminate the extracellular contribution. Here, we aimed to estimate tissue and compartment specific human brain microstructure by combining water and metabolites DDES experiments. We performed our DDES measurements in two brain regions that contain widely different amounts of white matter (WM) and gray matter (GM): parietal white matter (PWM) and occipital gray matter (OGM) in a total of 20 healthy volunteers at 7 Tesla. Metabolite DDES measurements were performed at b = 7199 s/mm2, while water DDES measurements were performed with a range of b values from 918 to 7199 s/mm2. The experimental framework we employed here resulted in a set of insights pertaining to the morphology of the intracellular and extracellular spaces in both gray and white matter. Results of the metabolite DDES experiments in both PWM and OGM suggest a highly anisotropic intracellular space within neurons and glia, with the possible exception of gray matter glia. The water μFA obtained from the DDES results at high b values in both regions converged with that of the metabolite DDES, suggesting that the signal from the extracellular space is indeed effectively suppressed at the highest b value. The μFA measured in the OGM significantly decreased at lower b values, suggesting a considerably lower anisotropy of the extracellular space in GM compared to WM. In PWM, the water μFA remained high even at the lowest b value, indicating a high degree of organization in the interstitial space in WM. Tortuosity values in the cytoplasm for water and tNAA, obtained with correlation analysis of microscopic parallel diffusivity with respect to GM/WM tissue fraction in the volume of interest, are remarkably similar for both molecules, while exhibiting a clear difference between gray and white matter, suggesting a more crowded cytoplasm and more complex cytomorphology of neuronal cell bodies and dendrites in GM than those found in long-range axons in WM.

Estimates of brain age for gray matter and white matter in younger and older adults: Insights into human intelligence

Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.

A comparison of cerebral small vessel disease severity between autopsy cohorts in the northeast of England and Sacramento County in California, USA

AbstractBackgroundCerebral small vessel disease (SVD) encompasses progressive fibrosis/hyalinosis of the small arteries and arterioles of the white matter (WM) resulting in ischemic WM damage. Few studies have compared SVD between different cohorts. Using a sclerotic index (SI) measurement, we quantitatively assessed vessel wall fibrosis in the frontal and parietal WM of human brains donated to brain banks in the UK and the USA.Method64 cases from the University of California Davis (UCD) Alzheimer’s Disease Centre Biorepository and 55 cases from the Newcastle Brain and Tissue resource (NBTR) were included. Cases were neuropathological diagnosed as controls (UCD n=18; NBTR n=25), intermediate Alzheimer’s disease (AD) neuropathologic change (UCD n=13; NBTR n=4), and definite AD (UCD n=33; NBTR n = 26). In the UCD cohort, 49 identified racially as White, 9 as Black African American, 3 as Chinese and 1 as Indian Asian. All cases from the NBTR identified racially as White. Using H&amp;E sections, images of approximately eight arteries/arterioles from the frontal and parietal WM were captured and SI assessment performed. Mean SI score was calculated per region, per cases.ResultNo intergroup differences in age were observed and age was not associated with SI score in either cohort. In the UCD cohort, race was not associated with neuropathological diagnosis (Chi‐sq = 8.39, p&gt;0.211) and no differences were seen in SI scores between White and Black African Americans (p&gt;0.69). Intergroup comparisons revealed that SI scores in both WM regions were significantly higher in the overall UCD cohort compared to the overall NBTR cohort (p&gt;0.006) and this was consistent across controls (frontal p=0.0001; parietal p=0.045), intermediate AD neuropathological change (p=0.001), and AD (frontal p=0.001) cases.ConclusionSVD‐associated vessel occlusion is more severe in the USA cohort from Sacramento compared to the UK cohort from Newcastle. This may reflect differences in cardiovascular disease and lifestyle of individuals enrolled in the two brain donation programmes.

Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across four time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis

The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.

White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction

The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the ‘FA fine’ metric of the RSI model and ‘orientation dispersion’ (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.

Visco-hyperelastic characterization of human brain white matter micro-level constituents in different strain rates.

In this study, we propose a computational characterization technique for obtaining the material properties of axons and extracellular matrix (ECM) in human brain white matter. To account for the dynamic behavior of the brain tissue, data from time-dependent relaxation tests of human brain white matter in different strain rates are extracted and formulated by a visco-hyperelastic constitutive model consisting of the Ogden hyperelastic model and the Prony series expansion. Through micromechanical finite element simulation, a derivative-free optimization framework designed to minimize the difference between the numerical and experimental data is used to identify the material properties of the axons and ECM. The Prony series expansion parameters of axons and ECM are found to be highly affected by the Prony series expansion coefficients of the brain white matter. The optimal parameters of axons and ECM are verified through micromechanical simulation by comparing the averaged numerical response with that of the experimental data. Moreover, the initial shear modulus and the reduced shear modulus of the axons are found for different strain rates of 0.0001, 0.01, and 1s-1. Consequently, first- and second-order regressions are used to find relations for the prediction of the shear modulus at the intermediate strain rates. Graphical Abstract The applied procedure for characterization of brain white matter micro-level constituents. The macro-level experimental data in different strain rates are used in the context of simulation-based optimization to obtain the properties of axons and extracellular matrix material.

A time-dependent diffusion MRI signature of axon caliber variations and beading

MRI provides a unique non-invasive window into the brain, yet is limited to millimeter resolution, orders of magnitude coarser than cell dimensions. Here, we show that diffusion MRI is sensitive to the micrometer-scale variations in axon caliber or pathological beading, by identifying a signature power-law diffusion time-dependence of the along-fiber diffusion coefficient. We observe this signature in human brain white matter and identify its origins by Monte Carlo simulations in realistic substrates from 3-dimensional electron microscopy of mouse corpus callosum. Simulations reveal that the time-dependence originates from axon caliber variation, rather than from mitochondria or axonal undulations. We report a decreased amplitude of time-dependence in multiple sclerosis lesions, illustrating the potential sensitivity of our method to axonal beading in a plethora of neurodegenerative disorders. This specificity to microstructure offers an exciting possibility of bridging across scales to image cellular-level pathology with a clinically feasible MRI technique.

Evidence for wakefulness-related changes to extracellular space in human brain white matter from diffusion-weighted MRI

Recently, several magnetic resonance imaging (MRI) studies have reported time-of-day effects on brain structure and function. Due to the possibility that time-of-day effects reflect mechanisms of circadian regulation, the aim of this prospective study was to assess these effects while under strict experimental control of variables that might influence biological clocks, such as caffeine intake and exposure to blue-emitting light. In addition, the current study assessed whether time-of-day effects were driven by changes to extracellular space, by including estimations of non-Gaussian diffusion metrics obtained from diffusion kurtosis imaging, white matter tract integrity and the spherical mean technique, in addition to conventional diffusion tensor imaging -derived parameters. Participants were 47 healthy adults who underwent diffusion-weighted imaging in the morning and evening of the same day. Morning and evening scans were compared using voxel-wise tract based spatial statistics and permutation testing. A day of wakefulness was associated with widespread increases in fractional anisotropy, indices of kurtosis and indices of the axonal water fraction. In addition, wakefulness was associated with widespread decreases in radial diffusivity, both in the single compartment and in extra-axonal space. These results suggest that an increase in the intra-axonal space relative to the extra-axonal volume underlies time-of-day effects in human white matter, which is in line with activity-induced reductions to the extracellular volume. These findings provide important insight into possible mechanisms driving time-of-day effects in MRI.

Center-out EPI (COEPI): A fast single-shot imaging technique with a short TE.

To develop a center-out echo planar imaging (COEPI) acquisition technique to increase SNR through minimizing the TE. In single-shot COEPI, the phase-encoding starts from the center (ky = 0) toward both sides of k-space to substantially shorten the TE compared to the conventional single-shot EPI. The phase-encoding gradient waveform is partially overlapped with the frequency-encoding gradient waveform to keep the echo spacing constant during the echo train readout. A reconstruction pipeline was developed to correct for phase and off-resonance errors in COEPI. Gradient-recalled echo (GRE), spin echo (SE), and DWI COEPI were obtained in phantoms and healthy brains at 1.5 tesla (T) and 3.0T. The SNR in COEPI and single-shot partial ky EPI was compared. Acquisition matrix of 128 × 80 (16 overscan lines) was obtained in both COEPI and EPI. At 1.5T/3.0T, a minimum TE of 3 ms/4 ms in GRE-COEPI, 11 ms/12 ms in SE-COEPI, and 40 ms in DWI-COEPI (3.0T only, maximum b value = 2000 s/mm2 ) was achieved, compared to a minimum TE of 18 ms/16 ms in GRE-EPI, 37 ms/34 ms in SE-EPI, and 66 ms in DWI-EPI, respectively. Image blurring and Nyquist ghost appear in COEPI and were substantially reduced after corrections. At 1.5T/3.0T, a SNR increase of 27.7% ± 6.9%/20.7% ± 7.0% in GRE-COEPI and 37.7% ± 5.7%/28.2% ± 1.3% in SE-COEPI was observed in white matter of human brains, compared to GRE-EPI and SE-EPI, respectively. At 3.0T, a SNR increase of 41.2% ± 4.1% in DWI-COEPI was observed in white matter of 5 subjects at 5 b values (0~2000 s/mm2 ), compared to DWI-EPI. The feasibility of COEPI and its SNR benefit were demonstrated in this study.

NI-18 INVASIONS OF WHITE MATTER AS A PROGNOSTIC FACTOR IN LOW GRADE GLIOMAS

INTRODUCTIONGliomatosis cerebri (GC), which was characterized by widespread infiltration of the brain involving three lobes, was deleted in the 2016 WHO classification. However, it is known that gliomas with GC growth pattern have a poor prognosis even in low histological grading. In this study, we focused on tumor invasion into white matter fibers. We analyzed the MRI findings focusing on white matter fibers and compared in patients with histologically proven low grade gliomas (LGGs) with GC pattern and localized LGGs.METHODThe patients can be classified into four groups according to the range of tumor invasion in T2-weighted image as follows: group 1, more than 3 lobes (n=6); group 2, 1 or 2 lobes infiltrate the basal ganglia (n=5); group 3, multicentric (n=2) and group 4 (n=12), localized. In reference to the human brain white matter atlas, the infiltration to the major white matter fibers (uncinate fasciculus, genu &splenium of corpus callosum, inferior fronto-occipital fasciculus, superior& inferior longitudinal fasciculus) was examined.RESULTSTwenty-five patients (median 39.5 years) were included in the study. Of these, 20 patients were histologically diagnosed with diffuse astrocytomas, and 5 patients with oligodendrogliomas. The infiltrations into ifo, slf, and ilf of white matter fibers were a poor prognostic factor. The number of infiltrating white matter fibers correlated significantly with the Kaplan-Meier survival curve.CONCLUSIONSThe 2016 WHO classification defines diagnostic entities by combining molecular and histological information and remove GC as a distinct glioma entity. LGGs with GC pattern should be considered to be detected in different types of histologically and molecularly defined gliomas. As the patient numbers analyzed here were small, and larger series reproducing these results would be desirable. MRI findings particularly focusing on infiltration of LGGs into white matter fibers might be important to estimate the prognosis of patients.

White Matter by Diffusion MRI Following Methylphenidate Treatment: A Randomized Control Trial in Males with Attention-Deficit/Hyperactivity Disorder.

BackgroundMethylphenidate (MPH) is highly effective in treating attention-deficit/hyperactivity disorder (ADHD). However, not much is known about its effect on the development of human brain white matter (WM).PurposeTo determine whether MPH modulates WM microstructure in an age-dependent fashion in a randomized double-blind placebo-controlled trial (Effects of Psychotropic Medication on Brain Development-Methylphenidate, or ePOD-MPH) among ADHD referral centers between October 13, 2011, and June 15, 2015, by using diffusion-tensor imaging (DTI).Materials and MethodsIn this prospective study (NTR3103 and NL34509.000.10), 50 stimulant treatment-naive boys and 49 young adult men diagnosed with ADHD (all types) according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition criteria were randomized to undergo treatment with MPH or placebo for 16 weeks. Before and 1 week after treatment cessation, study participants underwent MRI, including DTI. The outcome measure was change in fractional anisotropy (FA), which was assessed in three regions of interest (ROIs), as well as in a voxel-based analysis in brain WM. Data were analyzed by using intention-to-treat linear mixed models for ROI analysis and a permutation-based method for voxel-based analysis with family-wise error correction.ResultsFifty boys (n = 25 MPH group, n = 25 placebo group; age range, 10-12 years) and 48 men (n = 24 MPH group, n = 24 placebo group; age range, 23-40 years) were included. ROI analysis of FA yielded no main effect of time in any of the conditions. However, voxel-based analysis revealed significant (P < .05) time-by-medication-by-age interaction effects in several association tracts of the left hemisphere, as well as in the lateral aspect of the truncus of the corpus callosum, due to greater increase in FA (standardized effect size, 5.25) in MPH-treated boys. Similar changes were not present in boys receiving a placebo, nor in adult men.ConclusionFour months of treatment with methylphenidate affects specific tracts in brain white matter in boys with attention-deficit/hyperactivity disorder. These effects seem to be age dependent, because they were not observed in adults treated with methylphenidate.© RSNA, 2019Online supplemental material is available for this article.

MEDUSA: A GPU-based tool to create realistic phantoms of the brain microstructure using tiny spheres

A GPU-based tool to generate realistic phantoms of the brain microstructure is presented. Using a spherical meshing technique which decomposes each microstructural item into a set of overlapping spheres, the phantom construction is made very fast while reliably avoiding the collisions between items in the scene. This novel method is applied to the construction of human brain white matter microstructural components, namely axonal fibers, oligodendrocytes and astrocytes. The algorithm reaches high values of packing density and angular dispersion for the axonal fibers, even in the case of multiple white matter fiber populations and enables the construction of complex biomimicking geometries including myelinated axons, beaded axons, and glial cells. The method can be readily adapted to model gray matter microstructure.

Real-Time Ex-Vivo Magnetic Resonance Image—Guided Dissection of Human Brain White Matter: A Proof-of-Principle Study

Modern neuroanatomic education should be based on interdisciplinary methods that allow an understanding of the cerebral circuitry, which is at the base of the structural connectivity. Ex-vivo MRI-guided dissection is an essential method for developing and refining the knowledge of complex 3-dimensional brain anatomy and the mutual relationships between structures and architecture of the white matter bundles. The aim of this technical note is to present a new and innovative method of studying human brain white matter. Four adult human cerebral hemispheres were prepared according to the Klinger's method. T1-weighted and T2-weighted and fluid attenuated inversion recovery images were obtained with a 3T magnetic resonance machine. The dissection was performed in a dedicated neurosurgical laboratory equipped with a microscope and an electromagnetic neuronavigation system that guided the whole white matter dissection. Gyri and sulci morphology were studied in detail. The relations between superficial and inner structures were observed before and after the dissection. Gray matter was carefully removed with blunt dissectors, and the U-fibers were exposed. Afterwards, deeper association and projection fibers, such as the arcuate fasciculus, superior and inferior longitudinal fasciculus, corona radiata, extreme and external capsule, claustrum, anterior commissure, and internal capsule were visualized under high magnification. The neuronavigation system was crucial for continuously checking the whole dissection procedure to avoid any accidental excision of fibers. Image-guided neuronavigated dissection can significantly improve the quality of white matter dissection and represents a valid tool for learning the 3-dimensional anatomy of the human brain tracts.

Electrical stimulation of the left IFG improves category fluency in primary progressive aphasia: far-transfer effects and their neural mechanisms

Electrical stimulation of the left IFG improves category fluency in primary progressive aphasia: far-transfer effects and their neural mechanisms

On the scaling behavior of water diffusion in human brain white matter

Development of therapies for neurological disorders depends on our ability to non-invasively diagnose and monitor the progression of underlying pathologies at the cellular level. Physics and physiology limit the resolution of human MRI to be orders of magnitude coarser than cell dimensions. Here we identify and quantify the MRI signal coming from within micrometer-thin axons in human white matter tracts in vivo, by utilizing the sensitivity of diffusion MRI to Brownian motion of water molecules restricted by cell walls. We study a specific power-law scaling of the diffusion MRI signal with the diffusion weighting, predicted for water confined to narrow axons, and quantify axonal water fraction and orientation dispersion.

Population-averaged atlas of the macroscale human structural connectome and its network topology

A comprehensive map of the structural connectome in the human brain has been a coveted resource for understanding macroscopic brain networks. Here we report an expert-vetted, population-averaged atlas of the structural connectome derived from diffusion MRI data (N = 842). This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate 550,000 trajectories of representative white matter fascicles annotated by 80 anatomical labels. The trajectories were subsequently clustered and labeled by a team of experienced neuroanatomists in order to conform to prior neuroanatomical knowledge. A multi-level network topology was then described using whole-brain connectograms, with subdivisions of the association pathways showing small-worldness in intra-hemisphere connections, projection pathways showing hub structures at thalamus, putamen, and brainstem, and commissural pathways showing bridges connecting cerebral hemispheres to provide global efficiency. This atlas of the structural connectome provides representative organization of human brain white matter, complementary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectome studies.

Microstructural correlates of 3D steady-state inhomogeneous magnetization transfer (ihMT) in the human brain white matter assessed by myelin water imaging and diffusion tensor imaging.

To compare the recently introduced inhomogeneous magnetization transfer (ihMT) technique with more established MRI techniques including myelin water imaging (MWI) and diffusion tensor imaging (DTI), and to evaluate the microstructural attributes correlating with this new contrast method in the human brain white matter. Eight adult healthy volunteers underwent T1 -weighted, ihMT, MWI, and DTI imaging on a 3T human scanner. The ihMT ratio (ihMTR), myelin water fraction (MWF), fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) values were calculated from different white matter tracts. The angle ( ) between the directions of the principal eigenvector, as measured by DTI, and the main magnetic field was calculated for all voxels from various fiber tracts. The ihMTR was correlated with MWF and DTI metrics. A strong correlation was found between ihMTR and MWF (ρ = 0.77, P < 0.0001). This was followed by moderate to weak correlations between ihMTR and DTI metrics: RD (ρ = -0.30, P < 0.0001), FA (ρ = 0.20, P < 0.0001), MD (ρ = -0.19, P < 0.0001), AD (ρ = 0.02, P < 0.0001). A strong correlation was found between ihMTR and (ρ = -0.541, P < 0.0001). The strong correlation with myelin water imaging and its low coefficient of variation suggest that ihMT has the potential to become a new structural imaging marker of myelin. The substantial orientational dependence of ihMT should be taken into account when evaluating and quantitatively interpreting ihMT results.

Miniature pig model of human adolescent brain white matter development

BackgroundNeuroscience research in brain development and disorders can benefit from an in vivo animal model that portrays normal white matter (WM) development trajectories and has a sufficiently large cerebrum for imaging with human MRI scanners and protocols. New methodTwelve three-month-old Sinclair™ miniature pigs (Sus scrofa domestica) were longitudinally evaluated during adolescent development using advanced diffusion weighted imaging (DWI) focused on cerebral WM. Animals had three MRI scans every 23.95 ± 3.73 days using a 3-T scanner. The DWI imaging protocol closely modeled advanced human structural protocols and consisted of fifteen b-shells (b = 0–3500 s/mm2) with 32-directions/shell. DWI data were analyzed using diffusion kurtosis and bi-exponential modeling that provided measurements that included fractional anisotropy (FA), radial kurtosis, kurtosis anisotropy (KA), axial kurtosis, tortuosity, and permeability-diffusivity index (PDI). ResultsSignificant longitudinal effects of brain development were observed for whole-brain average FA, KA, and PDI (all p < 0.001). There were expected regional differences in trends, with corpus callosum fibers showing the highest rate of change. Comparison with existing method(s)Pigs have a large, gyrencephalic brain that can be studied using clinical MRI scanners/protocols. Pigs are less complex than non-human primates thus satisfying the “replacement” principle of animal research. ConclusionsLongitudinal effects were observed for whole-brain and regional diffusion measurements. The changes in diffusion measurements were interepreted as evidence for ongoing myelination and maturation of cerebral WM. Corpus callosum and superficial cortical WM showed the expected higher rates of change, mirroring results in humans.