Tensor-valued diffusion MRI of human acute stroke.

PURPOSE: Tensor-valued diffusion encoding can disentangle orientation dispersion and subvoxel anisotropy, potentially offering insight into microstructural changes after cerebral ischemia. The purpose was to evaluate tensor-valued diffusion MRI in human acute ischemic stroke, assess potential confounders from diffusion time dependencies, and compare to Monte Carlo diffusion simulations of axon beading. METHODS: Linear (LTE) and spherical (STE) b-tensor encoding with inherently different effective diffusion times were acquired in 21 acute ischemic stroke patients between 3 and 57 h post-onset at 3 T in 2.5 min. In an additional 10 patients, STE with 2 LTE yielding different effective diffusion times were acquired for comparison. Diffusional variance decomposition (DIVIDE) was used to estimate microscopic anisotropy (µFA), as well as anisotropic, isotropic, and total diffusional variance (MKA , MKI , MKT ). DIVIDE parameters, and diffusion tensor imaging (DTI)-derived mean diffusivity and fractional anisotropy (FA) were compared in lesion versus contralateral white matter. Monte Carlo diffusion simulations of various cylindrical geometries for all b-tensor protocols were used to interpret parameter measurements. RESULTS: MD was ˜40% lower in lesions for all LTE/STE protocols. The DIVIDE parameters varied with effective diffusion time: higher µFA and MKA in lesion versus contralateral white matter for STE with longer effective diffusion time LTE, whereas the shorter effective diffusion time LTE protocol yielded lower µFA and MKA in lesions. Both protocols, regardless of diffusion time, were consistent with simulations of greater beading amplitude and intracellular volume fraction. CONCLUSION: DIVIDE parameters depend on diffusion time in acute stroke but consistently indicate neurite beading and larger intracellular volume fraction.

Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling.

Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.

Automatic deep learning segmentation of the hippocampus on high-resolution diffusion magnetic resonance imaging and its application to the healthy lifespan.

Diffusion tensor imaging (DTI) can provide unique contrast and insight into microstructural changes with age or disease of the hippocampus, although it is difficult to measure the hippocampus because of its comparatively small size, location, and shape. This has been markedly improved by the advent of a clinically feasible 1-mm isotropic resolution 6-min DTI protocol at 3 T of the hippocampus with limited brain coverage of 20 axial-oblique slices aligned along its long axis. However, manual segmentation is too laborious for large population studies, and it cannot be automatically segmented directly on the diffusion images using traditional T1 or T2 image-based methods because of the limited brain coverage and different contrast. An automatic method is proposed here that segments the hippocampus directly on high-resolution diffusion images based on an extension of well-known deep learning architectures like UNet and UNet++ by including additional dense residual connections. The method was trained on 100 healthy participants with previously performed manual segmentation on the 1-mm DTI, then evaluated on typical healthy participants (n = 53), yielding an excellent voxel overlap with a Dice score of ~ 0.90 with manual segmentation; notably, this was comparable with the inter-rater reliability of manually delineating the hippocampus on diffusion magnetic resonance imaging (MRI) (Dice score of 0.86). This method also generalized to a different DTI protocol with 36% fewer acquisitions. It was further validated by showing similar age trajectories of volumes, fractional anisotropy, and mean diffusivity from manual segmentations in one cohort (n = 153, age 5-74 years) with automatic segmentations from a second cohort without manual segmentations (n = 354, age 5-90 years). Automated high-resolution diffusion MRI segmentation of the hippocampus will facilitate large cohort analyses and, in future research, needs to be evaluated on patient groups.

Reference Values for Water-Specific T1 of the Liver at 3 T: T2*-Compensation and the Confounding Effects of Fat.

BACKGROUND: T1 mapping of the liver is confounded by the presence of fat. Multiparametric T1 mapping combines fat-water separation with T1-weighting to enable imaging of water-specific T1 (T1Water), proton density fat fraction (PDFF), and T2* values. However, normative T1Water values in the liver and its dependence on age/sex is unknown. PURPOSE: Determine normative values for T1Water in the liver with comparison to MOLLI and evaluate a T2*-compensation approach to reduce T1 variability. STUDY TYPE: Prospective observational; phantoms. POPULATIONS: One hundred twenty-four controls (56 male, 18-75 years), 50 patients at-risk for liver disease (18 male, 30-76 years). FIELD STRENGTH/SEQUENCE: 2.89 T; Saturation-recovery chemical-shift encoded T1 Mapping (SR-CSE); MOLLI. ASSESSMENT: SR-CSE provided T1Water measurements, PDFF and T2* values in the liver across three slices in 6 seconds. These were compared with MOLLI T1 values. A new T2*-compensation approach to reduce T1 variability was evaluated test/re-test reproducibility. STATISTICAL TESTS: Linear regression, ANCOVA, t-test, Bland and Altman, intraclass correlation coefficient (ICC). P < 0.05 was considered statistically significant. RESULTS: Liver T1 values were significantly higher in healthy females (F) than males (M) for both SR-CSE (F-973 ± 78 msec, M-930 ± 72 msec) and MOLLI (F-802 ± 55 msec, M-759 ± 69 msec). T1 values were negatively correlated with age, with similar sex- and age-dependencies observed in T2*. The T2*-compensation model reduced the variability of T1 values by half and removed sex- and age-differences (SR-CSE: F-946 ± 36 msec, M-941 ± 43 msec; MOLLI: F-775 ± 35 msec, M-770 ± 35 msec). At-risk participants had elevated PDFF and T1 values, which became more distinct from the healthy cohort after T2*-compensation. MOLLI systematically underestimated liver T1 values by ~170 msec with an additional positive T1-bias from fat content (~11 msec/1% in PDFF). Reproducibility ICC values were ≥0.96 for all parameters. DATA CONCLUSION: Liver T1Water values were lower in males and decreased with age, as observed for SR-CSE and MOLLI acquisitions. MOLLI underestimated liver T1 with an additional large positive fat-modulated T1 bias. T2*-compensation removed sex- and age-dependence in liver T1, reduced the range of healthy values and increased T1 group differences between healthy and at-risk groups. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

High-resolution diffusion tensor imaging and T2 mapping detect regional changes within the hippocampus in multiple sclerosis.

Hippocampus demyelinating lesions in multiple sclerosis (MS) have been frequently observed in ex vivo histopathological studies; however, they are difficult to image and quantify in vivo. Diffusion tensor imaging (DTI) and T2 mapping could potentially detect such regional in vivo changes if acquired with sufficient spatial resolution. The goal here was to evaluate whether there are focal hippocampal abnormalities in 43 MS patients (35 relapsing-remitting, eight secondary progressive) with and without cognitive impairment (CI) versus 43 controls using high-resolution 1 mm isotropic DTI, as well as complementary methods of T2-weighted and T2 mapping at 3 T. Abnormal hippocampus regions were identified voxel-by-voxel by using mean diffusivity (MD)/T2 thresholds and avoiding voxels attributed to cerebrospinal fluid. When compared with controls, averaged left/right whole hippocampus MD was higher in both MS groups, while lower fractional anisotropy (FA) and volume, and higher T2 relaxometry and T2-weighted signal values, were only significant in CI MS. The hippocampal MD and T2 images/maps were not uniformly affected and focal regions of elevated MD/T2 were evident in MS patients. Both CI and not CI MS groups showed greater proportional areas of the hippocampus with elevated MD, whereas only the CI group showed a greater proportional area of elevated T2 relaxation times or T2-weighted signal. Higher T2 relaxometry and T2-weighted signal values of elevated regions correlated with greater disability and whole hippocampus FA negatively correlated with physical fatigue. High-resolution hippocampus DTI and T2 mapping with less partial volume effects showed whole hippocampus abnormalities with regional elevations of MD/T2 in MS, which could be interpreted as potentially from demyelination, neuron loss, and/or inflammation, and which overall were more extensive in the hippocampus of patients with larger total brain lesion volumes and CI.

Motor cortex functional connectivity is associated with underlying neurochemistry in ALS.

OBJECTIVE: To identify structural and neurochemical properties that underlie functional connectivity impairments of the primary motor cortex (PMC) and how these relate to clinical findings in amyotrophic lateral sclerosis (ALS). METHODS: 52 patients with ALS and 52 healthy controls, matched for age and sex, were enrolled from 5 centres across Canada for the Canadian ALS Neuroimaging Consortium study. Resting-state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy data were acquired. Functional connectivity maps, diffusion metrics and neurometabolite ratios were obtained from the analyses of the acquired multimodal data. A clinical assessment of foot tapping (frequency) was performed to examine upper motor neuron function in all participants. RESULTS: Compared with healthy controls, the primary motor cortex in ALS showed reduced functional connectivity with sensory (T=5.21), frontal (T=3.70), temporal (T=3.80), putaminal (T=4.03) and adjacent motor (T=4.60) regions. In the primary motor cortex, N-acetyl aspartate (NAA, a neuronal marker) ratios and diffusion metrics (mean, axial and radial diffusivity, fractional anisotropy (FA)) were altered. Within the ALS cohort, foot tapping frequency correlated with NAA (r=0.347) and white matter FA (r=0.537). NAA levels showed associations with disturbed functional connectivity of the motor cortex. CONCLUSION: In vivo neurochemistry may represent an effective imaging marker of impaired motor cortex functional connectivity in ALS.

A Normative Brain MRI Database of Neurotypical Participants from 5 to 90 Years of Age.

Brain magnetic resonance imaging (MRI) studies of clinical populations often require comparison to a normative 'control' cohort, usually of similar age/sex, scanned with the same protocol. The goal here was to create a normative brain MRI database of common quantitative methods to be used in comparisons with a variety of neurological disorders across the lifespan. 378 neurotypical controls (aged 5-90 years; median 31 years; 216 females, 162 males) completed brain MRI, cognitive testing, clinical assessment, and a demographics questionnaire. In addition, this large normative sample will yield novel insight into healthy brain development and aging.

Quantitative Susceptibility Mapping Changes Relate to Gait Issues in Parkinson's Disease.

BACKGROUND: Quantitative susceptibility mapping (QSM) demonstrates elevated iron content in Parkinson's disease (PD) patients within the basal ganglia, though it has infrequently been studied in relation to gait difficulties including freezing of gait (FOG). Our purpose was to relate QSM of basal ganglia and extra-basal ganglia structures with qualitative and quantitative gait measures in PD. METHODS: This case-control study included PD and cognitively unimpaired (CU) participants from the Comprehensive Assessment of Neurodegeneration and Dementia study. Whole brain QSM was acquired at 3T. Region of interests (ROIs) were drawn blinded manually in the caudate nucleus, putamen, globus pallidus, pulvinar nucleus of the thalamus, red nucleus, substantia nigra, and dentate nucleus. Susceptibilities of ROIs were compared between PD and CU. Items from the FOG questionnaire and quantitative gait measures from PD participants were compared to susceptibilities. RESULTS: Twenty-nine participants with PD and 27 CU participants were included. There was no difference in susceptibility values in any ROI when comparing CU versus PD (p > 0.05 for all). PD participants with gait impairment (n = 23) had significantly higher susceptibility in the putamen (p = 0.008), red nucleus (p = 0.01), and caudate nucleus (p = 0.03) compared to those without gait impairment (n = 6). PD participants with FOG (n = 12) had significantly higher susceptibility in the globus pallidus (p = 0.03) compared to those without FOG (n = 17). Among quantitative gait measures, only stride time variability was significantly different between those with and without FOG (p = 0.04). CONCLUSION: Susceptibilities in basal ganglia and extra-basal ganglia structures are related to qualitative measures of gait impairment and FOG in PD.

Diffusion imaging of fornix and interconnected limbic deep grey matter is linked to cognitive impairment in multiple sclerosis.

Diffusion tensor imaging (DTI) and volumetric magnetic resonance imaging (MRI) have shown white matter (WM) and deep grey matter (GM) abnormalities in the limbic system of multiple sclerosis (MS) participants. Structures like the fornix have been associated with cognitive impairment (CI) in MS, but the diffusion metrics are often biased by partial volume effects from cerebrospinal fluid (CSF) due to its small bundle size and intraventricular location. These errors in DTI parameter estimation worsen with atrophy in MS. The goal here was to evaluate DTI parameters and volumes of the fornix, as well as associated deep GM structures like the thalamus and hippocampus, with high-resolution fluid-attenuated inversion recovery (FLAIR)-DTI at 3T in 43 MS patients, with and without CI, versus 43 controls. The fornix, thalamus and hippocampus displayed atrophy and/or abnormal diffusion metrics, with the fornix showing the most extensive changes within the structures studied here, mainly in CI MS. The affected fornix volumes and diffusion metrics were associated with thalamic atrophy and atypical diffusion metrics in interconnected limbic GM, larger total lesion volume and global brain atrophy. Lower fractional anisotropy (FA) and higher mean and radial diffusivity in the fornix, lower hippocampus FA and lower thalamus volume were strongly correlated with CI in MS. Hippocampus FA and thalamus atrophy were negatively correlated with fatigue and longer time since MS symptoms onset, respectively. FLAIR-DTI and volumetric analyses provided methodologically superior evidence for microstructural abnormalities and extensive atrophy of the fornix and interconnected deep GM in MS that were associated with cognitive deficits.

Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: An A-CAP study.

In the largest sample studied to date, white matter microstructural trajectories and their relation to persistent symptoms were examined after pediatric mild traumatic brain injury (mTBI). This prospective, longitudinal cohort study recruited children aged 8-16.99 years with mTBI or mild orthopedic injury (OI) from five pediatric emergency departments. Children's pre-injury and 1-month post-injury symptom ratings were used to classify mTBI with or without persistent symptoms. Children completed diffusion-weighted imaging at post-acute (2-33 days post-injury) and chronic (3 or 6 months via random assignment) post-injury assessments. Mean diffusivity (MD) and fractional anisotropy (FA) were derived for 18 white matter tracts in 560 children (362 mTBI/198 OI), 407 with longitudinal data. Superior longitudinal fasciculus FA was higher in mTBI without persistent symptoms relative to OI, d (95% confidence interval) = 0.31 to 0.37 (0.02, 0.68), across time. In younger children, MD of the anterior thalamic radiations was higher in mTBI with persistent symptoms relative to both mTBI without persistent symptoms, 1.43 (0.59, 2.27), and OI, 1.94 (1.07, 2.81). MD of the arcuate fasciculus, -0.58 (-1.04, -0.11), and superior longitudinal fasciculus, -0.49 (-0.90, -0.09) was lower in mTBI without persistent symptoms relative to OI at 6 months post-injury. White matter microstructural changes suggesting neuroinflammation and axonal swelling occurred chronically and continued 6 months post injury in children with mTBI, especially in younger children with persistent symptoms, relative to OI. White matter microstructure appears more organized in children without persistent symptoms, consistent with their better clinical outcomes.

Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis.

Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T0 ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T0 and Tmax (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at Tmax than at T0 . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.

Characterization of B1+ field variation in brain at 3 T using 385 healthy individuals across the lifespan.

PURPOSE: The transmit field B1+ at 3 T in brain affects the spatial uniformity and contrast of most image acquisitions. Here, B1+ spatial variation in brain at 3 T is characterized in a large healthy population. METHODS: Bloch-Siegert B1+ maps were acquired at 3 T from 385 healthy subjects aged 5-90 years on a single MRI system. After transforming all B1+ maps to a standard brain atlas space, region-of-interest analysis was performed, and intersubject voxel-wise coefficient of variation was calculated across the whole brain. The B1+ variability due to age and brain size was studied separately in males and females, along with B1+ variability due to nonideal transmit calibration. RESULTS: The voxel-based mean coefficient of variation was 4.0% across all subjects, and the difference in B1+ between central (left thalamus) and outer regions (left frontal gray matter) was 24.2% ± 2.3%. The least intersubject variability occurred in central regions, whereas regions toward brain edges increased markedly in variation. The B1+ variability with age was mostly attributed to lifespan changes in CSF volume (which alters brain conductivity) and head orientation. Larger brain size correlated with more B1+ inhomogeneity (p < .001). Varying head position and anatomy resulted in an inaccurate transmit calibration. CONCLUSION: In standard atlas space, intersubject B1+ variability at 3 T was relatively small in a large population aged 5-90 years. The B1+ varied with age-related changes of CSF volume and head orientation, as well as differences in brain size and transmit calibration.

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads.

Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2 *) mapping from multiecho T2 *-weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R2 * reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross-site variability through postprocessing approaches. Twenty-four healthy subjects traveled between three sites and were scanned twice at each site. Scan-rescan measurements from seven deep gray matter regions were used for assessing within-site and cross-site reproducibility using intraclass correlation coefficient (ICC) and within-subject standard deviation (SDw) measures. In addition, multiple QSM and R2 * postprocessing options were investigated with the aim to minimize cross-site sequence-related variations, including: mask generation approach, echo-timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same-subject cross-site region of interest measurements for QSM and R2 * were highly correlated (R2 ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R2 *, respectively). The mean cross-site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s-1 for R2 *. For within-site measurements of QSM and R2 *, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s-1 , respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross-site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.

High-resolution diffusion tensor imaging identifies hippocampal volume loss without diffusion changes in individuals with prenatal alcohol exposure.

BACKGROUND: Magnetic resonance imaging (MRI) studies of prenatal alcohol exposure (PAE) commonly report reduced hippocampal volumes, which animal models suggest may result from microstructural changes that include cell loss and altered myelination. Diffusion tensor imaging (DTI) is sensitive to microstructural changes but has not yet been used to study the hippocampus in PAE. METHODS: Thirty-six healthy controls (19 females; 8 to 24 years) and 19 participants with PAE (8 females; 8 to 23 years) underwent high-resolution (1 mm isotropic) DTI, anatomical T1-weighted imaging, and cognitive testing. Whole-hippocampus, head, body, and tail subregions were manually segmented to yield DTI metrics (mean, axial, and radial diffusivities-MD, AD, and RD; fractional anisotropy-FA), volumes, and qualitative assessments of hippocampal morphology and digitations. Automated segmentation of T1-weighted images was used to corroborate manual whole-hippocampus volumes. RESULTS: Gross morphology and digitation counts were similar in both groups. Whole-hippocampus volumes were 18% smaller in the PAE than the control group on manually traced diffusion images, but automated T1-weighted image segmentations were not significantly different. Subregion segmentation on DTI revealed reduced volumes of the body and tail, but not the head. There were no significant differences in diffusion metrics between groups for any hippocampal region. Correlations between age and volume were not significant in either group, whereas negative correlations between age and whole-hippocampus MD/AD/RD, and head/body (but not tail) MD/AD/RD were significant in both groups. There were no significant effects of sex, group by age, or group by sex for any hippocampal metric. In controls, seven positive linear correlations were found between hippocampal volume and cognition; five of these were left lateralized and included episodic and working memory, and two were right lateralized and included working memory and processing speed. In PAE, left tail MD positively correlated with executive functioning, and right head MD negatively correlated with episodic memory. CONCLUSIONS: Reductions of hippocampal volumes and altered relationships with memory suggest disrupted hippocampal development in PAE.

Frontoparietal and temporal white matter diffusion MRI in children and youth with prenatal alcohol exposure.

BACKGROUND: Prenatal alcohol exposure (PAE) is associated with brain alterations and neurocognitive deficits, but relationships between brain alterations and neurocognitive deficits remain unclear. METHODS: Diffusion tensor imaging (DTI) data were obtained from 31 participants with PAE and 31 unexposed controls aged 7-15 years. Mean diffusivity (MD) and fractional anisotropy (FA) were derived from the genu, body, and splenium of the corpus callosum (CC), bilateral cingulum, and inferior and superior longitudinal fasciculus (ILF, SLF). Participants completed language subtests from the NEPSY-II. Executive functioning was measured using the Behavior Rating Inventory of Executive Functioning (BRIEF-PR) and verbal learning was assessed using the California Verbal Learning Test-Children's Version (CVLT-C) only in children with PAE. Group differences in diffusion metrics and cognitive scores were tested. Principal component analysis was used to reduce redundancy in cognitive and behavior variables; associations between components and brain measures were then assessed. RESULTS: Children with PAE had lower MD in the right SLF compared with unexposed controls. FA was positively related to age in 6 of 9 tracts and MD negatively related to age in all tracts; there were no significant age-by-group interactions. Participants with PAE scored lower than unexposed peers on the NEPSY-II Comprehension of Instructions and Phonological Processing and above population norms (indicating worse performance) on the BRIEF-PR. Children with PAE had a negative association between a principal component closely associated with Speeded Naming and FA in the left SLF (PAE: p = 0.002) and left ILF (PAE: p = 0.002); unexposed controls showed no significant associations. CONCLUSION: We found widespread cognitive difficulties in children with PAE, but relatively limited differences in brain metrics and associations with age. Different brain-cognitive relationships were found in children with PAE compared with controls. Overall, the results provide additional evidence that PAE may lead to cognitive difficulties and disrupt typical brain-function relationships.

Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy.

To extract Diffusion Tensor Imaging (DTI) parameters from the human cortex, the inner and outer boundaries of the cortex are usually defined on 3D-T1-weighted images and then applied to the co-registered DTI. However, this analysis requires the acquisition of an additional high-resolution structural image that may not be practical in various imaging studies. Here an automatic cortical boundary segmentation method was developed to work directly only on the native DTI images by using fractional anisotropy (FA) maps and mean diffusion weighted images (DWI), the latter with acceptable gray-white matter image contrast. This new method was compared to the conventional cortical segmentations generated from high-resolution T1 structural images in 5 participants. In addition, the proposed method was applied to 15 healthy young adults (10 cross-sectional, 5 test-retest) to measure FA, MD, and radiality of the primary eigenvector across the cortex on whole-brain 1.5 mm isotropic images acquired in 3.5 min at 3T. The proposed method generated reasonable segmentations of the cortical boundaries for all individuals and large proportions of the proposed method segmentations (more than 85%) were within ±1 mm from those generated with the conventional approach on higher resolution T1 structural images. Both FA (~0.15) and MD (~0.77 × 10-3 mm2/s) extracted halfway between the cortical boundaries were relatively stable across the cortex, although focal regions such as the posterior bank of the central sulcus, anterior insula, and medial temporal lobe showed higher FA. The primary eigenvectors were primarily oriented radially to the middle cortical surface, but there were tangential orientations in the sulcal fundi as well as in the posterior bank of the central sulcus. The proposed method demonstrates the feasibility and accuracy of cortical analysis in native DTI space while avoiding the acquisition of other imaging contrasts like 3D T1-weighted scans.

A simple estimate of axon size with diffusion MRI.

Noninvasive estimation of mean axon diameter presents a new opportunity to explore white matter plasticity, development, and pathology. Several diffusion-weighted MRI (DW-MRI) methods have been proposed to measure the average axon diameter in white matter, but they typically require many diffusion encoding measurements and complicated mathematical models to fit the signal to multiple tissue compartments, including intra- and extra-axonal spaces. Here, Monte Carlo simulations uncovered a straightforward DW-MRI metric of axon diameter: the change in radial apparent diffusion coefficient estimated at different effective diffusion times, ΔD⊥. Simulations indicated that this metric increases monotonically within a relevant range of effective mean axon diameter while being insensitive to changes in extra-axonal volume fraction, axon diameter distribution, g-ratio, and influence of myelin water. Also, a monotonic relationship was found to exist for signals coming from both intra- and extra-axonal compartments. The slope in ΔD⊥ with effective axon diameter increased with the difference in diffusion time of both oscillating and pulsed gradient diffusion sequences.

High resolution diffusion tensor imaging of the hippocampus across the healthy lifespan.

The human hippocampus is difficult to image given its small size, location, shape, and complex internal architecture. Structural magnetic resonance imaging (MRI) has shown age-related hippocampal volume changes that vary along the anterior-posterior axis. Diffusion tensor imaging (DTI) provides complementary measures related to microstructure, but there are few hippocampus DTI studies investigating change with age in healthy participants, and all have been limited by low spatial resolution. The current study uses high resolution 1 mm isotropic DTI of 153 healthy volunteers aged 5-74 years to investigate diffusion and volume trajectories of the hippocampus (whole, head, body, and tail) and correlations with memory. Hippocampal volume showed age-related changes that differed between head (peaking at midlife), body (no changes), and tail (decreasing across the age span). Fractional anisotropy (FA) and mean, axial, and radial diffusivities (MD, AD, RD) yielded peaks or minima, respectively, at ~30-35 years in all three subregions of the hippocampus. Greater magnitude changes were observed during development than in aging. Age trajectories for both volume and DTI were similar between males and females. Correlations between tests of memory and FA and/or volume were significant in younger subjects (5-17 years), but not in 18-49 year olds or 50-74 year olds. MD was significantly correlated with memory performance in 18-49 year olds, but not in other age groups. Given the diffusion-weighted image contrast and resolution, head digitations could be examined revealing that the majority of subjects had 3-4 (48%) or 2 (32%) bilaterally with no effect of age. One millimeter isotropic DTI yielded high quality diffusion-weighted maps of the human hippocampus that showed regionally specific age effects and cognitive correlations along the anterior-posterior axis from 5 to 74 years.

R2* and quantitative susceptibility mapping in deep gray matter of 498 healthy controls from 5 to 90 years.

Putative MRI markers of iron in deep gray matter have demonstrated age related changes during discrete periods of healthy childhood or adulthood, but few studies have included subjects across the lifespan. This study reports both transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) of four primary deep gray matter regions (thalamus, putamen, caudate, and globus pallidus) in 498 healthy individuals aged 5-90 years. In the caudate, putamen, and globus pallidus, increases of QSM and R2* were steepest during childhood continuing gradually throughout adulthood, except caudate susceptibility which reached a plateau in the late 30s. The thalamus had a unique profile with steeper changes of R2* (reflecting additive effects of myelin and iron) than QSM during childhood, both reaching a plateau in the mid-30s to early 40s and decreasing thereafter. There were no hemispheric or sex differences for any region. Notably, both R2* and QSM values showed more inter-subject variability with increasing age from 5 to 90 years, potentially reflecting a common starting point in iron/myelination during childhood that diverges as a result of lifestyle and genetic factors that accumulate with age.

Three-dimensional Yarnball k-space acquisition for accelerated MRI.

PURPOSE: To introduce an efficient sampling technique named Yarnball, which may serve as a direct alternative to 3D Cones. METHODS: Yarnball evolves through 3D k-space with increasing loop size, and the differential equations defining this flexible trajectory are presented in detail. The sampling efficiencies of Yarnball and 3D Cones were compared through point spread function analysis and simulated imaging (which highlights undersampling in the absence of other scanning effects). The feasibility of Yarnball implementation was demonstrated for fully sampled T1 -weighted images of the human head at 3 T. RESULTS: The mostly large 3D loops of the Yarnball trajectory facilitate rapid sampling under peripheral nerve stimulation constraint, an advantage that increases with readout duration (TRO ). Point spread function analysis yielded 89% (TRO = 2 ms) and 77% (TRO = 10 ms) of Yarnball voxels with magnitude less than 0.01% of the point spread function peak. For 3D Cones, these values were only 52% and 29%. The 3D-Cones technique required 1.4 times (TRO = 2 ms) and 1.8 times (TRO = 10 ms) more trajectories than Yarnball to produce simulated images of a sphere free from undersampling artifact. For a prolate spheroidal (head-like) object, 1.75 times and 2.6 times more trajectories were required for 3D Cones. Yarnball produced 0.72 mm (1/2kmax ) isotropic T1 -weighted human brain images free from undersampling artifact in only 98 seconds at 3 T. CONCLUSION: Yarnball demonstrated greater k-space sampling efficiency than directly comparable 3D Cones, and may have value wherever 3D Cones has been considered. Yarnball may also have value in the context of rapid T1 -weighted brain imaging.