Genotype-specific spinal cord damage in spinocerebellar ataxias: an ENIGMA-Ataxia study.

BACKGROUND: Spinal cord damage is a feature of many spinocerebellar ataxias (SCAs), but well-powered in vivo studies are lacking and links with disease severity and progression remain unclear. Here we characterise cervical spinal cord morphometric abnormalities in SCA1, SCA2, SCA3 and SCA6 using a large multisite MRI dataset. METHODS: Upper spinal cord (vertebrae C1-C4) cross-sectional area (CSA) and eccentricity (flattening) were assessed using MRI data from nine sites within the ENIGMA-Ataxia consortium, including 364 people with ataxic SCA, 56 individuals with preataxic SCA and 394 nonataxic controls. Correlations and subgroup analyses within the SCA cohorts were undertaken based on disease duration and ataxia severity. RESULTS: Individuals in the ataxic stage of SCA1, SCA2 and SCA3, relative to non-ataxic controls, had significantly reduced CSA and increased eccentricity at all examined levels. CSA showed large effect sizes (d>2.0) and correlated with ataxia severity (r<-0.43) and disease duration (r<-0.21). Eccentricity correlated only with ataxia severity in SCA2 (r=0.28). No significant spinal cord differences were evident in SCA6. In preataxic individuals, CSA was significantly reduced in SCA2 (d=1.6) and SCA3 (d=1.7), and the SCA2 group also showed increased eccentricity (d=1.1) relative to nonataxic controls. Subgroup analyses confirmed that CSA and eccentricity are abnormal in early disease stages in SCA1, SCA2 and SCA3. CSA declined with disease progression in all, whereas eccentricity progressed only in SCA2. CONCLUSIONS: Spinal cord abnormalities are an early and progressive feature of SCA1, SCA2 and SCA3, but not SCA6, which can be captured using quantitative MRI.

Axon fiber orientation as the source of T1 relaxation anisotropy in white matter: A study on corpus callosum in vivo and ex vivo.

PURPOSE: Recent studies indicate that T1 in white matter (WM) is influenced by fiber orientation in B0 . The purpose of the study was to investigate the interrelationships between axon fiber orientation in corpus callosum (CC) and T1 relaxation time in humans in vivo as well as in rat brain ex vivo. METHODS: Volunteers were scanned for relaxometric and diffusion MRI at 3 T and 7 T. Angular T1 plots from WM were computed using fractional anisotropy and fiber-to-field-angle maps. T1 and fiber-to-field angle were measured in five sections of CC to estimate the effects of inherently varying fiber orientations on T1 within the same tracts in vivo. Ex vivo rat-brain preparation encompassing posterior CC was rotated in B0 and T1 , and diffusion MRI images acquired at 9.4 T. T1 angular plots were determined at several rotation angles in B0 . RESULTS: Angular T1 plots from global WM provided reference for estimated fiber orientation-linked T1 changes within CC. In anterior midbody of CC in vivo, where small axons are dominantly present, a shift in axon orientation is accompanied by a change in T1 , matching that estimated from WM T1 data. In CC, where large and giant axons are numerous, the measured T1 change is about 2-fold greater than the estimated one. Ex vivo rotation of the same midsagittal CC region of interest produced angular T1 plots at 9.4 T, matching those observed at 7 T in vivo. CONCLUSION: These data causally link axon fiber orientation in B0 to the T1 relaxation anisotropy in WM.

Clinically Meaningful Magnetic Resonance Endpoints Sensitive to Preataxic Spinocerebellar Ataxia Types 1 and 3.

OBJECTIVE: This study was undertaken to identify magnetic resonance (MR) metrics that are most sensitive to early changes in the brain in spinocerebellar ataxia type 1 (SCA1) and type 3 (SCA3) using an advanced multimodal MR imaging (MRI) protocol in the multisite trial setting. METHODS: SCA1 or SCA3 mutation carriers and controls (n = 107) underwent MR scanning in the US-European READISCA study to obtain structural, diffusion MRI, and MR spectroscopy data using an advanced protocol at 3T. Morphometric, microstructural, and neurochemical metrics were analyzed blinded to diagnosis and compared between preataxic SCA (n = 11 SCA1, n = 28 SCA3), ataxic SCA (n = 14 SCA1, n = 37 SCA3), and control (n = 17) groups using nonparametric testing accounting for multiple comparisons. MR metrics that were most sensitive to preataxic abnormalities were identified using receiver operating characteristic (ROC) analyses. RESULTS: Atrophy and microstructural damage in the brainstem and cerebellar peduncles and neurochemical abnormalities in the pons were prominent in both preataxic groups, when patients did not differ from controls clinically. MR metrics were strongly associated with ataxia symptoms, activities of daily living, and estimated ataxia duration. A neurochemical measure was the most sensitive metric to preataxic changes in SCA1 (ROC area under the curve [AUC] = 0.95), and a microstructural metric was the most sensitive metric to preataxic changes in SCA3 (AUC = 0.92). INTERPRETATION: Changes in cerebellar afferent and efferent pathways underlie the earliest symptoms of both SCAs. MR metrics collected with a harmonized advanced protocol in the multisite trial setting allow detection of disease effects in individuals before ataxia onset with potential clinical trial utility for subject stratification. ANN NEUROL 2022.

White matter microstructure and longitudinal relaxation time anisotropy in human brain at 3 and 7 T.

A high degree of structural order by white matter (WM) fibre tracts creates a physicochemical environment where water relaxations are rendered anisotropic. Recently, angularly dependent longitudinal relaxation has been reported in human WM. We have characterised interrelationships between T1 relaxation and diffusion MRI microstructural indices at 3 and 7 T. Eleven volunteers consented to participate in the study. Multishell diffusion MR images were acquired with b-values of 0/1500/3000 and 0/1000/2000 s/mm2 at 1.5 and 1.05 mm3 isotropic resolutions at 3 and 7 T, respectively. DTIFIT was used to compute DTI indices; the fibre-to-field angle (θFB ) maps were obtained using the principal eigenvector images. The orientations and volume fractions of multiple fibre populations were estimated using BedpostX in FSL, and the orientation dispersion index (ODI) was estimated using the NODDI protocol. MP2RAGE was used to acquire images for T1 maps at 1.0 and 0.9 mm3 isotropic resolutions at 3 and 7 T, respectively. At 3 T, T1 as a function of θFB in WM with high fractional anisotropy and one-fibre orientation volume fraction or low ODI shows a broad peak centred at 50o , but a flat baseline at 0o and 90o . The broad peak amounted up to 7% of the mean T1. At 7 T, the broad peak appeared at 40o and T1 in fibres running parallel to B0 was longer by up to 75 ms (8.3% of the mean T1) than in those perpendicular to the field. The peak at 40o was approximately 5% of mean T1 (i.e., proportionally smaller than that at 54o at 3 T). The data demonstrate T1 anisotropy in WM with high microstructural order at both fields. The angular patterns are indicative of the B0-dependency of T1 anisotropy. Thus myelinated WM fibres influence T1 contrast both by acting as a T1 contrast agent and rendering T1 dependent on fibre orientation with B0.

Progressive Spinal Cord Degeneration in Friedreich's Ataxia: Results from ENIGMA-Ataxia.

BACKGROUND: Spinal cord damage is a hallmark of Friedreich's ataxia (FRDA), but its progression and clinical correlates remain unclear. OBJECTIVE: The objective of this study was to perform a characterization of cervical spinal cord structural damage in a large multisite FRDA cohort. METHODS: We performed a cross-sectional analysis of cervical spinal cord (C1-C4) cross-sectional area (CSA) and eccentricity using magnetic resonance imaging data from eight sites within the ENIGMA-Ataxia initiative, including 256 individuals with FRDA and 223 age- and sex-matched control subjects. Correlations and subgroup analyses within the FRDA cohort were undertaken based on disease duration, ataxia severity, and onset age. RESULTS: Individuals with FRDA, relative to control subjects, had significantly reduced CSA at all examined levels, with large effect sizes (d > 2.1) and significant correlations with disease severity (r < -0.4). Similarly, we found significantly increased eccentricity (d > 1.2), but without significant clinical correlations. Subgroup analyses showed that CSA and eccentricity are abnormal at all disease stages. However, although CSA appears to decrease progressively, eccentricity remains stable over time. CONCLUSIONS: Previous research has shown that increased eccentricity reflects dorsal column (DC) damage, while decreased CSA reflects either DC or corticospinal tract (CST) damage, or both. Hence our data support the hypothesis that damage to the DC and damage to CST follow distinct courses in FRDA: developmental abnormalities likely define the DC, while CST alterations may be both developmental and degenerative. These results provide new insights about FRDA pathogenesis and indicate that CSA of the cervical spinal cord should be investigated further as a potential biomarker of disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

MR Imaging in Ataxias: Consensus Recommendations by the Ataxia Global Initiative Working Group on MRI Biomarkers.

With many viable strategies in the therapeutic pipeline, upcoming clinical trials in hereditary and sporadic degenerative ataxias will benefit from non-invasive MRI biomarkers for patient stratification and the evaluation of therapies. The MRI Biomarkers Working Group of the Ataxia Global Initiative therefore devised guidelines to facilitate harmonized MRI data acquisition in clinical research and trials in ataxias. Recommendations are provided for a basic structural MRI protocol that can be used for clinical care and for an advanced multi-modal MRI protocol relevant for research and trial settings. The advanced protocol consists of modalities with demonstrated utility for tracking brain changes in degenerative ataxias and includes structural MRI, magnetic resonance spectroscopy, diffusion MRI, quantitative susceptibility mapping, and resting-state functional MRI. Acceptable ranges of acquisition parameters are provided to accommodate diverse scanner hardware in research and clinical contexts while maintaining a minimum standard of data quality. Important technical considerations in setting up an advanced multi-modal protocol are outlined, including the order of pulse sequences, and example software packages commonly used for data analysis are provided. Outcome measures most relevant for ataxias are highlighted with use cases from recent ataxia literature. Finally, to facilitate access to the recommendations by the ataxia clinical and research community, examples of datasets collected with the recommended parameters are provided and platform-specific protocols are shared via the Open Science Framework.

Ultra-high field (10.5T) diffusion-weighted MRI of the macaque brain.

Diffu0sion-weighted magnetic resonance imaging (dMRI) is a non-invasive imaging technique that provides information about the barriers to the diffusion of water molecules in tissue. In the brain, this information can be used in several important ways, including to examine tissue abnormalities associated with brain disorders and to infer anatomical connectivity and the organization of white matter bundles through the use of tractography algorithms. However, dMRI also presents certain challenges. For example, historically, the biological validation of tractography models has shown only moderate correlations with anatomical connectivity as determined through invasive tract-tracing studies. Some of the factors contributing to such issues are low spatial resolution, low signal-to-noise ratios, and long scan times required for high-quality data, along with modeling challenges like complex fiber crossing patterns. Leveraging the capabilities provided by an ultra-high field scanner combined with denoising, we have acquired whole-brain, 0.58 mm isotropic resolution dMRI with a 2D-single shot echo planar imaging sequence on a 10.5 Tesla scanner in anesthetized macaques. These data produced high-quality tractograms and maps of scalar diffusion metrics in white matter. This work demonstrates the feasibility and motivation for in-vivo dMRI studies seeking to benefit from ultra-high fields.

Brain Structure and Degeneration Staging in Friedreich Ataxia: Magnetic Resonance Imaging Volumetrics from the ENIGMA-Ataxia Working Group.

OBJECTIVE: Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. METHODS: A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole-brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. RESULTS: The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5-2.6). Cerebellar gray matter alterations were most pronounced in lobules I-VI (d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d = 0.6) and corticospinal tracts (d = 1.4). Earlier onset age predicted less volume in the motor cerebellum (rmax  = 0.35) and peduncles (rmax  = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax  = -0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. INTERPRETATION: FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570-583.

NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing.

Diffusion-weighted magnetic resonance imaging (dMRI) has found great utility for a wide range of neuroscientific and clinical applications. However, high-resolution dMRI, which is required for improved delineation of fine brain structures and connectomics, is hampered by its low signal-to-noise ratio (SNR). Since dMRI relies on the acquisition of multiple different diffusion weighted images of the same anatomy, it is well-suited for denoising methods that utilize correlations across the image series to improve the apparent SNR and the subsequent data analysis. In this work, we introduce and quantitatively evaluate a comprehensive framework, NOise Reduction with DIstribution Corrected (NORDIC) PCA method for processing dMRI. NORDIC uses low-rank modeling of g-factor-corrected complex dMRI reconstruction and non-asymptotic random matrix distributions to remove signal components which cannot be distinguished from thermal noise. The utility of the proposed framework for denoising dMRI is demonstrated on both simulations and experimental data obtained at 3 Tesla with different resolutions using human connectome project style acquisitions. The proposed framework leads to substantially enhanced quantitative performance for estimating diffusion tractography related measures and for resolving crossing fibers as compared to a conventional/state-of-the-art dMRI denoising method.

Diffusion Imaging in the Post HCP Era.

Diffusion imaging is a critical component in the pursuit of developing a better understanding of the human brain. Recent technical advances promise enabling the advancement in the quality of data that can be obtained. In this review the context for different approaches relative to the Human Connectome Project are compared. Significant new gains are anticipated from the use of high-performance head gradients. These gains can be particularly large when the high-performance gradients are employed together with ultrahigh magnetic fields. Transmit array designs are critical in realizing high accelerations in diffusion-weighted (d)MRI acquisitions, while maintaining large field of view (FOV) coverage, and several techniques for optimal signal-encoding are now available. Reconstruction and processing pipelines that precisely disentangle the acquired neuroanatomical information are established and provide the foundation for the application of deep learning in the advancement of dMRI for complex tissues. Level of Evidence: 3 Technical Efficacy Stage: Stage 3.

Diffusion magnetic resonance imaging reveals tract-specific microstructural correlates of electrophysiological impairments in non-myelopathic and myelopathic spinal cord compression.

BACKGROUND AND PURPOSE: Non-myelopathic degenerative cervical spinal cord compression (NMDC) frequently occurs throughout aging and may progress to potentially irreversible degenerative cervical myelopathy (DCM). Whereas standard clinical magnetic resonance imaging (MRI) and electrophysiological measures assess compression severity and neurological dysfunction, respectively, underlying microstructural deficits still have to be established in NMDC and DCM patients. The study aims to establish tract-specific diffusion MRI markers of electrophysiological deficits to predict the progression of asymptomatic NMDC to symptomatic DCM. METHODS: High-resolution 3 T diffusion MRI was acquired for 103 NMDC and 21 DCM patients compared to 60 healthy controls to reveal diffusion alterations and relationships between tract-specific diffusion metrics and corresponding electrophysiological measures and compression severity. Relationship between the degree of DCM disability, assessed by the modified Japanese Orthopaedic Association scale, and tract-specific microstructural changes in DCM patients was also explored. RESULTS: The study identified diffusion-derived abnormalities in the gray matter, dorsal and lateral tracts congruent with trans-synaptic degeneration and demyelination in chronic degenerative spinal cord compression with more profound alterations in DCM than NMDC. Diffusion metrics were affected in the C3-6 area as well as above the compression level at C3 with more profound rostral deficits in DCM than NMDC. Alterations in lateral motor and dorsal sensory tracts correlated with motor and sensory evoked potentials, respectively, whereas electromyography outcomes corresponded with gray matter microstructure. DCM disability corresponded with microstructure alteration in lateral columns. CONCLUSIONS: Outcomes imply the necessity of high-resolution tract-specific diffusion MRI for monitoring degenerative spinal pathology in longitudinal studies.

Self-navigation for 3D multishot EPI with data-reference.

PURPOSE: In this study, we sought to develop a self-navigation strategy for improving the reconstruction of diffusion weighted 3D multishot echo planar imaging (EPI). We propose a method for extracting the phase correction information from the acquisition itself, eliminating the need for a 2D navigator, further accelerating the acquisition. METHODS: In-vivo acquisitions at 3T with 0.9 mm and 1.5 mm isotropic resolutions were used to evaluate the performance of the self-navigation strategy. Sensitivity to motion was tested using a large difference in pitch position of the head. Using a multishell diffusion weighted acquisition, tractography results were obtained at (0.9 mm)3 to validate the quality with conventional acquisition. RESULTS: The use of 3D multislab EPI with self-navigation enables 3D diffusion-weighted spin echo EPI acquisitions that have the same efficiency as 2D single-shot acquisition. For matched acquisition time the image signal-to-noise ratio (SNR) between 3D and 2D acquisition is shown to be comparable for whole-brain coverage with (1.5 mm)3 resolution and for (0.9 mm)3 resolution the 3D acquisition has higher SNR than what can be obtained with 2D acquisitions using current state-of-art multiband techniques. The self-navigation technique was shown to be stable under inter-volume motion. In tractography analysis, the higher resolution afforded by our technique enabled clear delineation of the tapetum and posterior corona radiata. CONCLUSION: The proposed self-navigation approach utilized a self-consistent phase in 3D diffusion weighted acquisitions. Its efficiency and stability were demonstrated for a plurality of common acquisitions. The proposed self-navigation approach allows for faster acquisition of 3D multishot EPI desirable for large field of view and/or higher resolution.

Advances in computational and statistical diffusion MRI.

Computational methods are crucial for the analysis of diffusion magnetic resonance imaging (MRI) of the brain. Computational diffusion MRI can provide rich information at many size scales, including local microstructure measures such as diffusion anisotropies or apparent axon diameters, whole-brain connectivity information that describes the brain's wiring diagram and population-based studies in health and disease. Many of the diffusion MRI analyses performed today were not possible five, ten or twenty years ago, due to the requirements for large amounts of computer memory or processor time. In addition, mathematical frameworks had to be developed or adapted from other fields to create new ways to analyze diffusion MRI data. The purpose of this review is to highlight recent computational and statistical advances in diffusion MRI and to put these advances into context by comparison with the more traditional computational methods that are in popular clinical and scientific use. We aim to provide a high-level overview of interest to diffusion MRI researchers, with a more in-depth treatment to illustrate selected computational advances.

Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning.

We present a sparse Bayesian unmixing algorithm BusineX: Bayesian Unmixing for Sparse Inference-based Estimation of Fiber Crossings (X), for estimation of white matter fiber parameters from compressed (under-sampled) diffusion MRI (dMRI) data. BusineX combines compressive sensing with linear unmixing and introduces sparsity to the previously proposed multiresolution data fusion algorithm RubiX, resulting in a method for improved reconstruction, especially from data with lower number of diffusion gradients. We formulate the estimation of fiber parameters as a sparse signal recovery problem and propose a linear unmixing framework with sparse Bayesian learning for the recovery of sparse signals, the fiber orientations and volume fractions. The data is modeled using a parametric spherical deconvolution approach and represented using a dictionary created with the exponential decay components along different possible diffusion directions. Volume fractions of fibers along these directions define the dictionary weights. The proposed sparse inference, which is based on the dictionary representation, considers the sparsity of fiber populations and exploits the spatial redundancy in data representation, thereby facilitating inference from under-sampled q-space. The algorithm improves parameter estimation from dMRI through data-dependent local learning of hyperparameters, at each voxel and for each possible fiber orientation, that moderate the strength of priors governing the parameter variances. Experimental results on synthetic and in-vivo data show improved accuracy with a lower uncertainty in fiber parameter estimates. BusineX resolves a higher number of second and third fiber crossings. For under-sampled data, the algorithm is also shown to produce more reliable estimates.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI.

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.

Individualized tractography-based parcellation of the globus pallidus pars interna using 7T MRI in movement disorder patients prior to DBS surgery.

The success of deep brain stimulation (DBS) surgeries for the treatment of movement disorders relies on the accurate placement of an electrode within the motor portion of subcortical brain targets. However, the high number of electrodes requiring relocation indicates that today's methods do not ensure sufficient accuracy for all patients. Here, with the goal of aiding DBS targeting, we use 7 Tesla (T) MRI data to identify the functional territories and parcellate the globus pallidus pars interna (GPi) into motor, associative and limbic regions in individual subjects. 7 T MRI scans were performed in seventeen patients (prior to DBS surgery) and one healthy control. Tractography-based parcellation of each patient's GPi was performed. The cortex was divided into four masks representing motor, limbic, associative and "other" regions. Given that no direct connections between the GPi and the cortex have been shown to exist, the parcellation was carried out in two steps: 1) The thalamus was parcellated based on the cortical targets, 2) The GPi was parcellated using the thalamus parcels derived from step 1. Reproducibility, via repeated scans of a healthy subject, and validity of the findings, using different anatomical pathways for parcellation, were assessed. Lastly, post-operative imaging data was used to validate and determine the clinical relevance of the parcellation. The organization of the functional territories of the GPi observed in our individual patient population agrees with that previously reported in the literature: the motor territory was located posterolaterally, followed anteriorly by the associative region, and further antero-ventrally by the limbic territory. While this organizational pattern was observed across patients, there was considerable variability among patients. The organization of the functional territories of the GPi was remarkably reproducible in intra-subject scans. Furthermore, the organizational pattern was observed consistently by performing the parcellation of the GPi via the thalamus and via a different pathway, going through the striatum. Finally, the active therapeutic contact of the DBS electrode, identified with a combination of post-operative imaging and post-surgery DBS programming, overlapped with the high-probability "motor" region of the GPi as defined by imaging-based methods. The consistency, validity, and clinical relevance of our findings have the potential for improving DBS targeting, by increasing patient-specific knowledge of subregions of the GPi to be targeted or avoided, at the stage of surgical planning, and later, at the stage when stimulation is adjusted.

High-resolution whole-brain diffusion MRI at 7T using radiofrequency parallel transmission.

PURPOSE: Investigating the utility of RF parallel transmission (pTx) for Human Connectome Project (HCP)-style whole-brain diffusion MRI (dMRI) data at 7 Tesla (7T). METHODS: Healthy subjects were scanned in pTx and single-transmit (1Tx) modes. Multiband (MB), single-spoke pTx pulses were designed to image sagittal slices. HCP-style dMRI data (i.e., 1.05-mm resolutions, MB2, b-values = 1000/2000 s/mm2 , 286 images and 40-min scan) and data with higher accelerations (MB3 and MB4) were acquired with pTx. RESULTS: pTx significantly improved flip-angle detected signal uniformity across the brain, yielding ∼19% increase in temporal SNR (tSNR) averaged over the brain relative to 1Tx. This allowed significantly enhanced estimation of multiple fiber orientations (with ∼21% decrease in dispersion) in HCP-style 7T dMRI datasets. Additionally, pTx pulses achieved substantially lower power deposition, permitting higher accelerations, enabling collection of the same data in 2/3 and 1/2 the scan time or of more data in the same scan time. CONCLUSION: pTx provides a solution to two major limitations for slice-accelerated high-resolution whole-brain dMRI at 7T; it improves flip-angle uniformity, and enables higher slice acceleration relative to current state-of-the-art. As such, pTx provides significant advantages for rapid acquisition of high-quality, high-resolution truly whole-brain dMRI data.

AutoVOI: real-time automatic prescription of volume-of-interest for single voxel spectroscopy.

PURPOSE: To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. METHODS: AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T1 -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. RESULTS: The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra- and inter-subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra- and inter-subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool. CONCLUSION: Robust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.

Fusion in diffusion MRI for improved fibre orientation estimation: An application to the 3T and 7T data of the Human Connectome Project.

Determining the acquisition parameters in diffusion magnetic resonance imaging (dMRI) is governed by a series of trade-offs. Images of lower resolution have less spatial specificity but higher signal to noise ratio (SNR). At the same time higher angular contrast, important for resolving complex fibre patterns, also yields lower SNR. Considering these trade-offs, the Human Connectome Project (HCP) acquires high quality dMRI data for the same subjects at different field strengths (3T and 7T), which are publically released. Due to differences in the signal behavior and in the underlying scanner hardware, the HCP 3T and 7T data have complementary features in k- and q-space. The 3T dMRI has higher angular contrast and resolution, while the 7T dMRI has higher spatial resolution. Given the availability of these datasets, we explore the idea of fusing them together with the aim of combining their benefits. We extend a previously proposed data-fusion framework and apply it to integrate both datasets from the same subject into a single joint analysis. We use a generative model for performing parametric spherical deconvolution and estimate fibre orientations by simultaneously using data acquired under different protocols. We illustrate unique features from each dataset and how they are retained after fusion. We further show that this allows us to complement benefits and improve brain connectivity analysis compared to analyzing each of the datasets individually.