Validation of a highly accelerated post-contrast wave-controlled aliasing in parallel imaging (CAIPI) 3D-T1 MPRAGE compared to standard 3D-T1 MPRAGE for detection of intracranial enhancing lesions on 3-T MRI.

OBJECTIVES: High-resolution post-contrast T1-weighted imaging is a workhorse sequence in the evaluation of neurological disorders. The T1-MPRAGE sequence has been widely adopted for the visualization of enhancing pathology in the brain. However, this three-dimensional (3D) acquisition is lengthy and prone to motion artifact, which often compromises diagnostic quality. The goal of this study was to compare a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) post-contrast 3D T1-MPRAGE sequence (Wave-T1-MPRAGE) with the standard 3D T1-MPRAGE sequence for visualizing enhancing lesions in brain imaging at 3 T. METHODS: This study included 80 patients undergoing contrast-enhanced brain MRI. The participants were scanned with a standard post-contrast T1-MPRAGE sequence (acceleration factor [R] = 2 using GRAPPA parallel imaging technique, acquisition time [TA] = 5 min 18 s) and a prototype post-contrast Wave-T1-MPRAGE sequence (R = 4, TA = 2 min 32 s). Two neuroradiologists performed a head-to-head evaluation of both sequences and rated the visualization of enhancement, sharpness, noise, motion artifacts, and overall diagnostic quality. A 15% noninferiority margin was used to test whether post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE. Inter-rater and intra-rater agreement were calculated. Quantitative assessment of CNR/SNR was performed. RESULTS: Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE for delineating enhancing lesions with unanimous agreement in all cases between raters. Wave-T1-MPRAGE was noninferior in the perception of noise (p < 0.001), motion artifact (p < 0.001), and overall diagnostic quality (p < 0.001). CONCLUSION: High-accelerated post-contrast Wave-T1-MPRAGE enabled a two-fold reduction in acquisition time compared to the standard sequence with comparable performance for visualization of enhancing pathology and equivalent perception of noise, motion artifacts and overall diagnostic quality without loss of clinically important information. KEY POINTS: • Post-contrast wave-controlled aliasing in parallel imaging (CAIPI) T1-MPRAGE accelerated the acquisition of three-dimensional (3D) high-resolution post-contrast images by more than two-fold. • Post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE with unanimous agreement between reviewers (100% in 80 cases) for the visualization of intracranial enhancing lesions. • Wave-T1-MPRAGE was equivalent to the standard sequence in the perception of noise in 94% (75 of 80) of cases and was preferred in 16% (13 of 80) of cases for decreased motion artifact.

Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution.

Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatial resolution improve the accuracy of cortical surface and thickness estimation compared to the standard 1-millimeter isotropic resolution. Nonetheless, sub-millimeter resolution acquisitions require averaging multiple repetitions to achieve sufficient signal-to-noise ratio and are therefore long and potentially vulnerable to subject motion. We address this challenge by synthesizing sub-millimeter resolution images from standard 1-millimeter isotropic resolution images using a data-driven supervised machine learning-based super-resolution approach achieved via a deep convolutional neural network. We systematically characterize our approach using a large-scale simulated dataset and demonstrate its efficacy in empirical data. The super-resolution data provide improved cortical surfaces similar to those obtained from native sub-millimeter resolution data. The whole-brain mean absolute discrepancy in cortical surface positioning and thickness estimation is below 100 µm at the single-subject level and below 50 µm at the group level for the simulated data, and below 200 µm at the single-subject level and below 100 µm at the group level for the empirical data, making the accuracy of cortical surfaces derived from super-resolution sufficient for most applications.

Association between Gut Microbiota with Mild Cognitive Impairment and Alzheimer's Disease in a Thai Population.

BACKGROUND: Mild cognitive impairment (MCI) and Alzheimer's disease (AD) are common in older adults. Much recent work has implicated the connection between the gut and the brain via bidirectional communication of the gastrointestinal tract and the central nervous system through biochemical signaling. Altered gut microbiota composition has shown controversial results based on geographic location, age, diet, physical activity, psychological status, underlying diseases, medication, and drug use. OBJECTIVES: This study aimed to investigate the relationships of gut microbiota with MCI and AD. METHODS: 16S metagenome profiles from stool collection of participant groups (normal; n = 20, MCI; n = 12, AD; n = 20) were analyzed. The diagnosis of cognitive conditions was made by standard criteria consisting of clinical interviews, physical examinations, cognitive assessments, laboratory examinations, and neuroimaging by both structural neuroimaging and amyloid positron emission tomography scans. Correlations between medical factors with food frequency and the fecal microbiome were elucidated. RESULTS: A significant difference at the operational taxonomic unit level was observed. The significantly higher abundance of bacteria in nondementia patients belonged to the Clostridiales order, including Clostridium sensu stricto 1 (p < 0.0001), Fusicatenibacter (p = 0.0007), Lachnospiraceae (p = 0.001), Agathobacter (p = 0.021), and Fecalibacterium (p < 0.0001). In contrast, Escherichia-Shigella (p = 0.0002), Bacteroides (p = 0.0014), Holdemanella (p < 0.0001), Romboutsia (p = 0.001), and Megamonas (p = 0.047) were the dominant genera in the AD group. Left and right hippocampus and right amygdala volumes were significantly decreased in the AD group (p < 0.001) and significantly correlated with the groups of bacteria that were significantly different between groups. CONCLUSION: There was a relationship between the composition of the gut microbiome and neurodegenerative disorders, including MCI and AD. Reduction of Clostridiaceae and increases in Enterobacteriaceae and Bacteroides were associated with persons with MCI and AD, consistent with previous studies. The altered gut microbiome could be potentially targeted for the early diagnosis of dementia and the reduction of AD risk.

Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising.

Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T1-weighted magnetic resonance (MR) images with sub-millimeter isotropic spatial resolution instead of the standard 1-mm isotropic resolution for improved accuracy of cortical surface positioning and thickness estimation. Nonetheless, sub-millimeter resolution images are noisy by nature and require averaging multiple repetitions to increase the signal-to-noise ratio for precisely delineating the cortical boundary. The prolonged acquisition time and potential motion artifacts pose significant barriers to the wide adoption of cortical surface reconstruction at sub-millimeter resolution for a broad range of neuroscientific and clinical applications. We address this challenge by evaluating the cortical surface reconstruction resulting from denoised single-repetition sub-millimeter T1-weighted images. We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). The denoised single-repetition images were found to be highly similar to 6-repetition averaged images, with a low whole-brain averaged mean absolute difference of ~0.016, high whole-brain averaged peak signal-to-noise ratio of ~33.5 dB and structural similarity index of ~0.92, and minimal gray matter-white matter contrast loss (2% to 9%). The whole-brain mean absolute discrepancies in gray matter-white matter surface placement, gray matter-cerebrospinal fluid surface placement and cortical thickness estimation were lower than 165 µm, 155 µm and 145 µm-sufficiently accurate for most applications. These discrepancies were approximately one third to half of those from 1-mm isotropic resolution data. The denoising performance was equivalent to averaging ~2.5 repetitions of the data in terms of image similarity, and 1.6-2.2 repetitions in terms of the cortical surface placement accuracy. The scan-rescan variability of the cortical surface positioning and thickness estimation was lower than 170 µm. Our unique dataset and systematic characterization support the use of denoising methods for improved cortical surface reconstruction at sub-millimeter resolution.

Scan-rescan repeatability of axonal imaging metrics using high-gradient diffusion MRI and statistical implications for study design.

Axon diameter mapping using diffusion MRI in the living human brain has attracted growing interests with the increasing availability of high gradient strength MRI systems. A systematic assessment of the consistency of axon diameter estimates within and between individuals is needed to gain a comprehensive understanding of how such methods extend to quantifying differences in axon diameter index between groups and facilitate the design of neurobiological studies using such measures. We examined the scan-rescan repeatability of axon diameter index estimation based on the spherical mean technique (SMT) approach using diffusion MRI data acquired with gradient strengths up to 300 mT/m on a 3T Connectom system in 7 healthy volunteers. We performed statistical power analyses using data acquired with the same protocol in a larger cohort consisting of 15 healthy adults to investigate the implications for study design. Results revealed a high degree of repeatability in voxel-wise restricted volume fraction estimates and tract-wise estimates of axon diameter index derived from high-gradient diffusion MRI data. On the region of interest (ROI) level, across white matter tracts in the whole brain, the Pearson's correlation coefficient of the axon diameter index estimated between scan and rescan experiments was r = 0.72 with an absolute deviation of 0.18 µm. For an anticipated 10% effect size in studies of axon diameter index, most white matter regions required a sample size of less than 15 people to observe a measurable difference between groups using an ROI-based approach. To facilitate the use of high-gradient strength diffusion MRI data for neuroscientific studies of axonal microstructure, the comprehensive multi-gradient strength, multi-diffusion time data used in this work will be made publicly available, in support of open science and increasing the accessibility of such data to the greater scientific community.

Distortion-free, high-isotropic-resolution diffusion MRI with gSlider BUDA-EPI and multicoil dynamic B0 shimming.

PURPOSE: We combine SNR-efficient acquisition and model-based reconstruction strategies with newly available hardware instrumentation to achieve distortion-free in vivo diffusion MRI of the brain at submillimeter-isotropic resolution with high fidelity and sensitivity on a clinical 3T scanner. METHODS: We propose blip-up/down acquisition (BUDA) for multishot EPI using interleaved blip-up/blip-down phase encoding and incorporate B0 forward-modeling into structured low-rank reconstruction to enable distortion-free and navigator-free diffusion MRI. We further combine BUDA-EPI with an SNR-efficient simultaneous multislab acquisition (generalized slice-dithered enhanced resolution ["gSlider"]), to achieve high-isotropic-resolution diffusion MRI. To validate gSlider BUDA-EPI, whole-brain diffusion data at 860-µm and 780-µm data sets were acquired. Finally, to improve the conditioning and minimize noise penalty in BUDA reconstruction at very high resolutions where B0 inhomogeneity can have a detrimental effect, the level of B0 inhomogeneity was reduced by incorporating slab-by-slab dynamic shimming with a 32-channel AC/DC coil into the acquisition. Whole-brain 600-µm diffusion data were then acquired with this combined approach of gSlider BUDA-EPI with dynamic shimming. RESULTS: The results of 860-µm and 780-µm datasets show high geometry fidelity with gSlider BUDA-EPI. With dynamic shimming, the BUDA reconstruction's noise penalty was further alleviated. This enables whole-brain 600-µm isotropic resolution diffusion imaging with high image quality. CONCLUSIONS: The gSlider BUDA-EPI method enables high-quality, distortion-free diffusion imaging across the whole brain at submillimeter resolution, where the use of multicoil dynamic B0 shimming further improves reconstruction performance, which can be particularly useful at very high resolutions.

DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning.

Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue microstructure and structural connectivity in the living human brain. Nonetheless, the angular sampling requirement for DTI leads to long scan times and poses a critical barrier to performing high-quality DTI in routine clinical practice and large-scale research studies. In this work we present a new processing framework for DTI entitled DeepDTI that minimizes the data requirement of DTI to six diffusion-weighted images (DWIs) required by conventional voxel-wise fitting methods for deriving the six unique unknowns in a diffusion tensor using data-driven supervised deep learning. DeepDTI maps the input non-diffusion-weighted (b â€‹= â€‹0) image and six DWI volumes sampled along optimized diffusion-encoding directions, along with T1-weighted and T2-weighted image volumes, to the residuals between the input and high-quality output b = 0 image and DWI volumes using a 10-layer three-dimensional convolutional neural network (CNN). The inputs and outputs of DeepDTI are uniquely formulated, which not only enables residual learning to boost CNN performance but also enables tensor fitting of resultant high-quality DWIs to generate orientational DTI metrics for tractography. The very deep CNN used by DeepDTI leverages the redundancy in local and non-local spatial information and across diffusion-encoding directions and image contrasts in the data. The performance of DeepDTI was systematically quantified in terms of the quality of the output images, DTI metrics, DTI-based tractography and tract-specific analysis results. We demonstrate rotationally-invariant and robust estimation of DTI metrics from DeepDTI that are comparable to those obtained with two b â€‹= â€‹0 images and 21 DWIs for the primary eigenvector derived from DTI and two b â€‹= â€‹0 images and 26-30 DWIs for various scalar metrics derived from DTI, achieving 3.3-4.6 נ​acceleration, and twice as good as those of a state-of-the-art denoising algorithm at the group level. The twenty major white-matter tracts can be accurately identified from the tractography of DeepDTI results. The mean distance between the core of the major white-matter tracts identified from DeepDTI results and those from the ground-truth results using 18 â€‹b â€‹= â€‹0 images and 90 DWIs measures around 1-1.5 â€‹mm. DeepDTI leverages domain knowledge of diffusion MRI physics and power of deep learning to render DTI, DTI-based tractography, major white-matter tracts identification and tract-specific analysis more feasible for a wider range of neuroscientific and clinical studies.

Effect of spinal tap test on the performance of sit-to-stand, walking, and turning in patients with idiopathic normal pressure hydrocephalus.

The aim of the study was to investigate the effect of the spinal tap test on sit-to-stand (STS), walking, and turning and to determine the relationship among the outcome measures of STS, walking, and turning in patients with iNPH. Twenty-seven patients with clinical symptoms of iNPH were objectively examined for STS, walking, and turning by the Force Distribution Measurement (FDM) platform connected with a video camera. Assessments were performed at before and 24 hours after spinal tap. Motor abilities were assessed by the STS time, time of walking over 3 meters, and time and number of steps when turning over 180 degrees. Significant improvements were found in the STS time (p = 0.046), walking time (p = 0.048), and turning step (p = 0.001). In addition, turning time was improved but not statistically significant (p = 0.064). Significant relationships were found among all outcome measures (p < 0.001). The relationship among these outcome measures indicated that the individuals had similar ability levels to perform different activities. This may serve as a new choice of outcome measures to evaluate the effect of intervention in different severity levels of patients with iNPH.

Feasibility Study of Language Lateralization using Thai Version of Language Paradigm for Functional MRI in Clinical Service.

Objective: To evaluate the concordance of language lateralization between functional magnetic resonance imaging (fMRI) using Thai version of language paradigm and Wada test or awake surgery with direct cortical brain stimulation (DCS). Material and Method: Retrospective study of thirteen patients (3 males and 10 females with mean age of 33.9 years old) with epilepsy (7 cases) or brain tumor (6 cases) was performed. Every patient underwent both fMRI (word generation, verb generation, naming picture, and sentence completion tasks) and Wada test or awake surgery with DCS (defined as the gold standard). The lateralization index (LI) of fMRI was automatically calculated by using the LI-toolbox on SPM8. The hemispheric lateralization was also evaluated visually. The concordance between fMRI and gold standard were analyzed. Results: The concordance between the lateralization of fMRI by visual assessment and gold standard was 92.3%. Concordance between the calculated LI by fMRI and gold standard was varied along with the task and regional calculation method. The concordance was good in all tasks (except for naming picture task) when using calculated LI from frontal or whole brain excluded cerebellum and occipital lobe (range 76.92 to 88.98% and 76.92 to 92.31%, respectively). Conclusion: There was good concordance between fMRI and gold standard. Regional calculation from frontal lobes and whole brain excluded cerebellum and occipital lobes gave the best results. The results supported feasibility to use the fMRI with Thai language paradigm as an alternative way to determine the language dominant hemisphere in Thai patients. In case of language dominant hemisphere is unclear, further invasive investigation of language mapping such as Wada test or DCS is crucial.

Clinical improvements in temporospatial gait variables after a spinal tap test in individuals with idiopathic normal pressure hydrocephalus.

Idiopathic Normal Pressure Hydrocephalus (iNPH) is a neurological condition that often presents gait disturbance in the early stages of the disease and affects other motor activities. This study investigated changes in temporospatial gait variables after cerebrospinal fluid (CSF) removal using a spinal tap test in individuals with idiopathic normal pressure hydrocephalus (iNPH), and explored if the tap test responders and non-responders could be clinically identified from temporospatial gait variables. Sixty-two individuals with iNPH were recruited from an outpatient clinic, eleven were excluded, leaving a total of 51 who were included in the analysis. Temporospatial gait variables at self-selected speed were recorded at pre- and 24-h post-tap tests which were compared using Paired t-tests, Cohen's d effect size, and percentage change. A previously defined minimal clinical important change (MCIC) for gait speed was used to determine the changes and to classify tap test responders and non-responders. A mixed model ANOVA was used to determine the within-group, between-group, and interaction effects. Comparisons of the data between pre- and post-tap tests showed significant improvements with small to medium effect sizes for left step length, right step time, stride length and time, cadence, and gait speed. Gait speed showed the largest percentage change among temporospatial gait variables. Within-group and interaction effects were found in some variables but no between-group effect was found. Tap test responders showed significant improvements in right step length and time, stride length and time, cadence, and gait speed while non-responders did not. Some individuals with iNPH showed clinically important improvements in temporospatial gait variables after the tap test, particularly in step/stride length and time, cadence, who could be classified by gait speed. However, gait-related balance variables did not change. Therefore, additional treatments should focus on improving such variables.

Axonal and myelin changes and their inter-relationship in the optic radiations in people with multiple sclerosis.

Background: The imaging g-ratio, estimated from axonal volume fraction (AVF) and myelin volume fraction (MVF), is a novel biomarker of microstructural tissue integrity in multiple sclerosis (MS). Objective: To assess axonal and myelin changes and their inter-relationship as measured by g-ratio in the optic radiations (OR) in people with MS (pwMS) with and without previous optic neuritis (ON) compared to healthy controls (HC). Methods: Thirty pwMS and 17 HCs were scanned on a 3Tesla Connectom scanner. AVF and MVF, derived from a multi-shell diffusion protocol and macromolecular tissue volume, respectively, were measured in normal-appearing white matter (NAWM) and lesions within the OR and used to calculate imaging g-ratio. Results: OR AVF and MVF were decreased in pwMS compared to HC, and in OR lesions compared to NAWM, whereas the g-ratio was not different. Compared to pwMS with previous ON, AVF and g-ratio tended to be higher in pwMS without prior ON. AVF and MVF, particularly in NAWM, were positively correlated with retinal thickness, which was more pronounced in pwMS with prior ON. Conclusion: Axonal measures reflect microstructural tissue damage in the OR, particularly in the setting of remote ON, and correlate with established metrics of visual health in MS.

Associations between corpus callosum damage, clinical disability, and surface-based homologous inter-hemispheric connectivity in multiple sclerosis.

Axonal damage in the corpus callosum is prevalent in multiple sclerosis (MS). Although callosal damage is associated with disrupted functional connectivity between hemispheres, it is unclear how this relates to cognitive and physical disability. We investigated this phenomenon using advanced measures of microstructural integrity in the corpus callosum and surface-based homologous inter-hemispheric connectivity (sHIC) in the cortex. We found that sHIC was significantly decreased in primary motor, somatosensory, visual, and temporal cortical areas in a group of 36 participants with MS (29 relapsing-remitting, 4 secondary progressive MS, and 3 primary-progressive MS) compared with 42 healthy controls (cluster level, p < 0.05). In participants with MS, global sHIC correlated with fractional anisotropy and restricted volume fraction in the posterior segment of the corpus callosum (r = 0.426, p = 0.013; r = 0.399, p = 0.020, respectively). Lower sHIC, particularly in somatomotor and posterior cortical areas, was associated with cognitive impairment and higher disability scores on the Expanded Disability Status Scale (EDSS). We demonstrated that higher levels of sHIC attenuated the effects of posterior callosal damage on physical disability and cognitive dysfunction, as measured by the EDSS and Brief Visuospatial Memory Test-Revised (interaction effect, p < 0.05). We also observed a positive association between global sHIC and years of education (r = 0.402, p = 0.018), supporting the phenomenon of "brain reserve" in MS. Our data suggest that preserved sHIC helps prevent cognitive and physical decline in MS.

High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN).

PURPOSE: The goal of this study is to leverage an advanced fast imaging technique, wave-controlled aliasing in parallel imaging (Wave-CAIPI), and a generative adversarial network (GAN) for denoising to achieve accelerated high-quality high-signal-to-noise-ratio (SNR) volumetric magnetic resonance imaging (MRI). METHODS: Three-dimensional (3D) T2 -weighted fluid-attenuated inversion recovery (FLAIR) image data were acquired on 33 multiple sclerosis (MS) patients using a prototype Wave-CAIPI sequence (acceleration factor R = 3 × 2, 2.75 min) and a standard T2 -sampling perfection with application-optimized contrasts by using flip angle evolution (SPACE) FLAIR sequence (R = 2, 7.25 min). A hybrid denoising GAN entitled "HDnGAN" consisting of a 3D generator and a 2D discriminator was proposed to denoise highly accelerated Wave-CAIPI images. HDnGAN benefits from the improved image synthesis performance provided by the 3D generator and increased training samples from a limited number of patients for training the 2D discriminator. HDnGAN was trained and validated on data from 25 MS patients with the standard FLAIR images as the target and evaluated on data from eight MS patients not seen during training. HDnGAN was compared to other denoising methods including adaptive optimized nonlocal means (AONLM), block matching with 4D filtering (BM4D), modified U-Net (MU-Net), and 3D GAN in qualitative and quantitative analysis of output images using the mean squared error (MSE) and Visual Geometry Group (VGG) perceptual loss compared to standard FLAIR images, and a reader assessment by two neuroradiologists regarding sharpness, SNR, lesion conspicuity, and overall quality. Finally, the performance of these denoising methods was compared at higher noise levels using simulated data with added Rician noise. RESULTS: HDnGAN effectively denoised low-SNR Wave-CAIPI images with sharpness and rich textural details, which could be adjusted by controlling the contribution of the adversarial loss to the total loss when training the generator. Quantitatively, HDnGAN (λ = 10-3 ) achieved low MSE and the lowest VGG perceptual loss. The reader study showed that HDnGAN (λ = 10-3 ) significantly improved the SNR of Wave-CAIPI images (p < 0.001), outperformed AONLM (p = 0.015), BM4D (p < 0.001), MU-Net (p < 0.001), and 3D GAN (λ = 10-3 ) (p < 0.001) regarding image sharpness, and outperformed MU-Net (p < 0.001) and 3D GAN (λ = 10-3 ) (p = 0.001) regarding lesion conspicuity. The overall quality score of HDnGAN (λ = 10-3 ) (4.25 ± 0.43) was significantly higher than those from Wave-CAIPI (3.69 ± 0.46, p = 0.003), BM4D (3.50 ± 0.71, p = 0.001), MU-Net (3.25 ± 0.75, p < 0.001), and 3D GAN (λ = 10-3 ) (3.50 ± 0.50, p < 0.001), with no significant difference compared to standard FLAIR images (4.38 ± 0.48, p = 0.333). The advantages of HDnGAN over other methods were more obvious at higher noise levels. CONCLUSION: HDnGAN provides robust and feasible denoising while preserving rich textural detail in empirical volumetric MRI data. Our study using empirical patient data and systematic evaluation supports the use of HDnGAN in combination with modern fast imaging techniques such as Wave-CAIPI to achieve high-fidelity fast volumetric MRI and represents an important step to the clinical translation of GANs.

Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients.

Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3 T Connectome scanner equipped with 300 mT/m maximum gradient strength and a custom-built 64-channel head coil. For each participant, the one-hour long acquisition systematically sampled the accessible diffusion measurement space, including two diffusion times (19 and 49 ms), eight gradient strengths linearly spaced between 30 mT/m and 290 mT/m for each diffusion time, and 32 or 64 uniformly distributed directions. The diffusion MRI data were preprocessed to correct for gradient nonlinearity, eddy currents, and susceptibility induced distortions. In addition, scan/rescan data from a subset of seven individuals were also acquired and provided. The MGH Connectome Diffusion Microstructure Dataset (CDMD) may serve as a test bed for the development of new data analysis methods, such as fiber orientation estimation, tractography and microstructural modelling.

A Cavernous Venous Malformation of the Orbit Mimicking an Idiopathic Orbital Inflammation.

Orbital cavernous venous malformations (CVMs) are usually slow progressing. Multiple CVMs, bilateral orbital CVMs, and acute presentations are rare. We present a rare, bilateral, orbital CVM with acute painful visual loss in the left eye. The initial clinical presentation mimicked an idiopathic orbital inflammation. Orbital magnetic resonance imaging revealed its rare location at the left orbital apex. Finally, pathology confirmed the presence of an intralesional hemorrhage of a CVM.

Axonal damage in the optic radiation assessed by white matter tract integrity metrics is associated with retinal thinning in multiple sclerosis.

INTRODUCTION: White matter damage in the visual pathway is common in multiple sclerosis (MS) and is associated with retinal thinning, although the underlying mechanism of association remains unclear. The goal of this work was to evaluate the presence and extent of white matter tract integrity (WMTI) alterations in the optic radiation (OR) in people with MS and to investigate the association between WMTI metrics and retinal thinning in the eyes of MS patients without a history of optic neuritis (ON) as measured by optical coherence tomography (OCT). We hypothesized that WMTI metrics would reflect axonal damage that occurs in the OR in MS, and that axonal alterations revealed by WMTI would be associated with retinal thinning. METHODS: Twenty-nine MS patients without previous ON in at least one eye and twenty-nine age-matched healthy controls (HC) were scanned on a dedicated high-gradient 3-Tesla MRI scanner with 300 mT/m maximum gradient strength using a multi-shell diffusion MRI protocol (b = 800, 1500, 2400 s/mm2). The patients were divided into two subgroups according to history without ON (N = 18) or with ON in one eye (N = 11). Diffusion tensor imaging (DTI) metrics and WMTI metrics derived from diffusion kurtosis imaging were assessed in normal-appearing white matter (NAWM) of the OR and in focal lesions. Retinal thickness in the eyes of MS patients was measured by OCT. Student's t-test was used to assess group differences between MRI metrics. Linear regression was used to study the relationship between OCT metrics, including retinal nerve fiber layer (RNFL) and combined ganglion cell and inner plexiform layer thickness (GCL/IPL), visual acuity measures and DTI and WMTI metrics. RESULTS: OR NAWM in MS showed significantly decreased axonal water fraction (AWF) compared to HC (0.36 vs 0.39, p < 0.001), with similar trends observed in AWF of lesions compared to NAWM (0.27 vs 0.36, p < 0.001). Fractional anisotropy (FA) was lower in OR NAWM of MS patients compared to HC (0.49 vs 0.52, p < 0.001). In patients without ON, AWF was the only diffusion MRI metric that was significantly associated with average RNFL (r = 0.68, p = 0.005), adjusting for age, sex and disease duration and correcting for multiple comparisons. Of all the DTI and WMTI metrics, AWF was the strongest and most significant predictor of average RNFL thickness in MS patients without ON. There was no significant correlation between visual acuity scores and DTI or WMTI metrics after correction for multiple comparisons. CONCLUSION: Axonal damage may be the substrate of previously observed DTI alterations in the OR, as supported by the significant reduction in AWF within both NAWM and lesions of the OR in MS. Our results support the concept that axonal damage is widespread throughout the visual pathway in MS and may be mediated through trans-synaptic degeneration.

Differences in clinical features between optic neuritis in neuromyelitis optica spectrum disorders and in multiple sclerosis.

BACKGROUND: Optic neuritis (ON) is one of the common manifestations both in neuromyelitis-optica spectrum disorders (NMOSD) and in multiple sclerosis (MS). OBJECTIVES: The objective of this paper is to compare clinical presentations, laboratories and imaging findings in ON associated with MS and NMOSD. METHODS: A retrospective chart review was performed in patients presenting with ON in 59 NMOSD patients with 72 eyes' involvement and 163 ON attacks, and 20 MS patients with 23 eyes' involvement and 36 ON attacks. RESULTS: ON-NMOSD patients had recurrent ON more often and tended to have simultaneous bilateral ON involvement at their first ON attack. Individuals with ON-NMOSD revealed worse visual acuity at first ON attacks and also had poorer long-term visual outcome than those with ON-MS, with nearly half of ON-NMOSD patients still having LogMAR visual acuity ≥1 at their last follow-up (p = 0.035). Significant thinner average retinal nerve fiber layer thickness was found in the ON-NMOSD group. We found no significant differences in segmentation location of the optic nerve lesions and the length of involvement between the two groups. CONCLUSIONS: It was difficult to completely differentiate ON-NMOSD from ON-MS. ON-NMOSD patients, however, tended to have simultaneous bilateral ON involvement and poorer long-term visual outcome than individuals with ON-MS.

The characteristics of spinal imaging in different types of demyelinating diseases.

BACKGROUND: Transverse myelitis is the common presentation in demyelinating conditions. OBJECTIVE: To determine the characteristics of spinal lesions among each type of demyelinating diseases. METHODS: Medical records and spinal imaging of patients who were [1] older than 18years, [2] had at least one attack of TM, [3] had available spinal MRI data and [4] were tested for aquaporin-4 antibody were included. RESULTS: One hundred and fifty-eight patients were eligible (27 clinically isolated syndrome [CIS], 38 MS, 55 seropositive neuromyelitis optica spectrum disorders [NMOSD], 9 seronegative NMOSD, and 29 idiopathic transverse myelitis [IDD-TM]). All groups showed female preponderance and no difference of age at onset. In each patient group, no significant difference in the mean number of spinal lesions was found. The most common levels of involvement were thoracic in IDD-TM, cervical in CIS and MS, as well as cervico-thoracic in both NMOSD groups. Long extensive TM was the most common finding in both the seropositive and seronegative NMOSD groups compared to the other groups. Peripheral location and <30% of spinal cord area involvement were the characteristic findings in CIS and MS. Central location and intermediately involved of the cross-sectional cord area were the determinants for the seropositive and seronegative NMOSD groups, respectively. CONCLUSION: Spinal MRI findings can help to differentiate among demyelinating diseases in who presented with TM.