Monitoring the acute and subacute recovery of cognitive ocular motor changes after a sports-related concussion.

Identifying when recovery from a sports-related concussion (SRC) has occurred remains a challenge in clinical practice. This study investigated the utility of ocular motor (OM) assessment to monitor recovery post-SRC between sexes and compared to common clinical measures. From 139 preseason baseline assessments (i.e. before they sustained an SRC), 18 (12 males, 6 females) consequent SRCs were sustained and the longitudinal follow-ups were collected at 2, 6, and 13 days post-SRC. Participants completed visually guided, antisaccade (AS), and memory-guided saccade tasks requiring a saccade toward, away from, and to a remembered target, respectively. Changes in latency (processing speed), visual-spatial accuracy, and errors were measured. Clinical measures included The Sports Concussion Assessment Tool, King-Devick test, Stroop task, and Digit span. AS latency was significantly longer at 2 days and returned to baseline by 13-days post-SRC in females only (P < 0.001). Symptom numbers recovered from 2 to 6 days and 13 days (P < 0.05). Persistently poorer AS visual-spatial accuracy was identified at 2, 6 and 13 days post-SRC (P < 0.05) in both males and females but with differing trajectories. Clinical measures demonstrated consistent improvement reminiscent of practice effects. OM saccade assessment may have improved utility in tracking recovery compared to conventional measures and between sexes.

Brain network dynamics in people with visual snow syndrome.

Visual snow syndrome (VSS) is a neurological disorder characterized by a range of continuous visual disturbances. Little is known about the functional pathological mechanisms underlying VSS and their effect on brain network topology, studied using high-resolution resting-state (RS) 7 T MRI. Forty VSS patients and 60 healthy controls underwent RS MRI. Functional connectivity matrices were calculated, and global efficiency (network integration), modularity (network segregation), local efficiency (LE, connectedness neighbors) and eigenvector centrality (significance node in network) were derived using a dynamic approach (temporal fluctuations during acquisition). Network measures were compared between groups, with regions of significant difference correlated with known aberrant ocular motor VSS metrics (shortened latencies and higher number of inhibitory errors) in VSS patients. Lastly, nodal co-modularity, a binary measure of node pairs belonging to the same module, was studied. VSS patients had lower modularity, supramarginal centrality and LE dynamics of multiple (sub)cortical regions, centered around occipital and parietal lobules. In VSS patients, lateral occipital cortex LE dynamics correlated positively with shortened prosaccade latencies (p = .041, r = .353). In VSS patients, occipital, parietal, and motor nodes belonged more often to the same module and demonstrated lower nodal co-modularity with temporal and frontal regions. This study revealed reduced dynamic variation in modularity and local efficiency strength in the VSS brain, suggesting that brain network dynamics are less variable in terms of segregation and local clustering. Further investigation of these changes could inform our understanding of the pathogenesis of the disorder and potentially lead to treatment strategies.

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis.

Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

Choroid plexus volume is enlarged in clinically isolated syndrome patients with optic neuritis.

OBJECTIVES: We investigated choroid plexus (CP) volume in patients presenting with optic neuritis (ON) as a clinically isolated syndrome (CIS), compared to a cohort with established relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HCs). METHODS: Three-dimensional (3D) T1, T2-FLAIR and diffusion-weighted sequences were acquired from 44 ON CIS patients at baseline, 1, 3, 6 and 12 months after the onset of ON. Fifty RRMS patients and 50 HCs were also included for comparison. RESULTS: CP volumes was larger in both ON CIS and RRMS groups compared to HCs, but not significantly different between ON CIS and RRMS patients (analysis of covariance (ANCOVA) adjusted for multiple comparisons). Twenty-three ON CIS patients who converted to clinically definite MS (MS) demonstrated CP volume similar to RRMS patients, but significantly larger compared to HCs. In this sub-group, CP volume was not associated with the severity of optic nerve inflammation or long-term axonal loss, not with brain lesion load. A transient increase of CP volume was observed following an occurrence of new MS lesions on brain magnetic resonance imaging (MRI). INTERPRETATION: Enlarged CP can be observed very early in a disease. It transiently reacts to acute inflammation, but not associated with the degree of tissue destruction.

Sensorimotor network dynamics predict decline in upper and lower limb function in people with multiple sclerosis.

BACKGROUND: Upper and lower limb disabilities are hypothesized to have partially independent underlying (network) disturbances in multiple sclerosis (MS). OBJECTIVE: This study investigated functional network predictors and longitudinal network changes related to upper and lower limb progression in MS. METHODS: Two-hundred fourteen MS patients and 58 controls underwent functional magnetic resonance imaging (fMRI), dexterity (9-Hole Peg Test) and mobility (Timed 25-Foot Walk) measurements (baseline and 5 years). Patients were stratified into progressors (>20% decline) or non-progressors. Functional network efficiency was calculated using static (over entire scan) and dynamic (fluctuations during scan) approaches. Baseline measurements were used to predict progression; significant predictors were explored over time. RESULTS: In both limbs, progression was related to supplementary motor area and caudate efficiency (dynamic and static, respectively). Upper limb progression showed additional specific predictors; cortical grey matter volume, putamen static efficiency and posterior associative sensory (PAS) cortex, putamen, primary somatosensory cortex and thalamus dynamic efficiency. Additional lower limb predictors included motor network grey matter volume, caudate (dynamic) and PAS (static). Only the caudate showed a decline in efficiency over time in one group (non-progressors). CONCLUSION: Disability progression can be predicted using sensorimotor network measures. Upper and lower limb progression showed unique predictors, possibly indicating different network disturbances underlying these types of progression in MS.

Plug-and-play microphones for recording speech and voice with smart devices.

INTRODUCTION Smart devices are widely available and capable of quickly recording and uploading speech segments for health-related analysis. The switch from laboratory recordings with professional-grade microphone set ups to remote, smart device-based recordings offers immense potential for the scalability of voice assessment. Yet, a growing body of literature points to a wide heterogeneity among acoustic metrics for their robustness to variation in recording devices. The addition of consumer-grade plug-and-play microphones has been proposed as a possible solution. Our aim was to assess if the addition of consumer-grade plug-and-play microphones increase the acoustic measurement agreement between ultra-portable devices and a reference microphone. METHODS Speech was simultaneously recorded by a reference high-quality microphone commonly used in research, and by two configurations with plug-and-play microphones. Twelve speech-acoustic features were calculated using recordings from each microphone to determine the agreement intervals in measurements between microphones. Agreement intervals were then compared to expected deviations in speech in various neurological conditions. Each microphone's response to speech and to silence were characterized through acoustic analysis to explore possible reasons for differences in acoustic measurements between microphones. The statistical differentiation of two groups, neurotypical and people with Multiple Sclerosis, using metrics from each tested microphone was compared to that of the reference microphone. RESULTS The two consumer-grade plug-and-play microphones favoured high frequencies (mean centre of gravity difference ≥ +175.3Hz) and recorded more noise (mean difference in signal-to-noise ≤ -4.2dB) when compared to the reference microphone. Between consumer-grade microphones, differences in relative noise were closely related to distance between the microphone and the speaker's mouth. Agreement intervals between the reference and consumer-grade microphones remained under disease-expected deviations only for fundamental frequency (f0, agreement interval ≤0.06Hz), f0 instability (f0 CoV, agreement interval ≤0.05%) and for tracking of second formant movement (agreement interval ≤1.4Hz/millisecond). Agreement between microphones was poor for other metrics, particularly for fine timing metrics (mean pause length and pause length variability for various tasks). The statistical difference between the two groups of speakers was smaller with the plug-and-play than with the reference microphone. CONCLUSION Measurement of f0 and F2 slope were robust to variation in recording equipment while other acoustic metrics were not. Thus, the tested plug-and-play microphones should not be used interchangeably with professional-grade microphones for speech analysis. Plug-and-play microphones may assist in equipment standardization within speech studies, including remote or self-recording, possibly with small loss in accuracy and statistical power as observed in this study.

Gait stability reflects motor tracts damage at early stages of multiple sclerosis.

BACKGROUND: Gait in people with multiple sclerosis (PwMS) is affected even when no changes can be observed on clinical examination. A sensitive measure of gait deterioration is stability; however, its correlation with motor tract damage has not yet been established. OBJECTIVE: To compare stability between PwMS and healthy controls (HCs) and determine associations between stability and diffusion magnetic resonance image (MRI) measures of axonal damage in selected sensorimotor tracts. METHODS: Twenty-five PwMS (Expanded Disability Status Scale (EDSS) < 2.5) and 15 HCs walked on a treadmill. Stability from sacrum (LDESAC), shoulder (LDESHO) and cervical (LDECER) was calculated using the local divergence exponent (LDE). Participants underwent a 7T-MRI brain scan to obtain fibre-specific measures of axonal loss within the corticospinal tract (CST), interhemispheric sensorimotor tract (IHST) and cerebellothalamic tract (CTT). Correlation analyses between LDE and fibre density (FD) within tracts, fibre cross-section (FC) and FD modulated by FC (FDC) were conducted. Between-groups LDE differences were analysed using analysis of variance (ANOVA). RESULTS: Correlations between all stability measures with CSTFD, between CSTFDC with LDESAC and LDECER, and LDECER with IHSTFD and IHSTFDC were significant yet moderate (R < -0.4). Stability was significantly different between groups. CONCLUSIONS: Poorer gait stability is associated with corticospinal tract (CST) axonal loss in PwMS with no-to-low disability and is a sensitive indicator of neurodegeneration.

White and Gray Matter Abnormalities in Australian Footballers With a History of Sports-Related Concussion: An MRI Study.

Sports-related concussion (SRC) is a form of mild traumatic brain injury that has been linked to long-term neurological abnormalities. Australian rules football is a collision sport with wide national participation and is growing in popularity worldwide. However, the chronic neurological consequences of SRC in Australian footballers remain poorly understood. This study investigated the presence of brain abnormalities in Australian footballers with a history of sports-related concussion (HoC) using multimodal MRI. Male Australian footballers with HoC (n = 26), as well as noncollision sport athletes with no HoC (n = 27), were recruited to the study. None of the footballers had sustained a concussion in the preceding 6 months, and all players were asymptomatic. Data were acquired using a 3T MRI scanner. White matter integrity was assessed using diffusion tensor imaging. Cortical thickness, subcortical volumes, and cavum septum pellucidum (CSP) were analyzed using structural MRI. Australian footballers had evidence of widespread microstructural white matter damage and cortical thinning. No significant differences were found regarding subcortical volumes or CSP. These novel findings provide evidence of persisting white and gray matter abnormalities in Australian footballers with HoC, and raise concerns related to the long-term neurological health of these athletes.

QSMART: Quantitative susceptibility mapping artifact reduction technique.

PURPOSE: Quantitative susceptibility mapping (QSM) is a novel MR technique that allows mapping of tissue susceptibility values from MR phase images. QSM is an ill-conditioned inverse problem, and although several methods have been proposed in the field, in the presence of a wide range of susceptibility sources, streaking artifacts appear around high susceptibility regions and contaminate the whole QSM map. QSMART is a post-processing pipeline that uses two-stage parallel inversion to reduce the streaking artifacts and remove banding artifact at the cortical surface and around the vasculature. METHOD: Tissue and vein susceptibility values were separately estimated by generating a mask of vasculature driven from the magnitude data using a Frangi filter. Spatially dependent filtering was used for the background field removal step and the two susceptibility estimates were combined in the final QSM map. QSMART was compared to RESHARP/iLSQR and V-SHARP/iLSQR inversion in a numerical phantom, 7T in vivo single and multiple-orientation scans, 9.4T ex vivo mouse data, and 4.7T in vivo rat brain with induced focal ischemia. RESULTS: Spatially dependent filtering showed better suppression of phase artifacts near cortex compared to RESHARP and V-SHARP, while preserving voxels located within regions of interest without brain edge erosion. QSMART showed successful reduction of streaking artifacts as well as improved contrast between different brain tissues compared to the QSM maps obtained by RESHARP/iLSQR and V-SHARP/iLSQR. CONCLUSION: QSMART can reduce QSM artifacts to enable more robust estimation of susceptibility values in vivo and ex vivo.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities.

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.

Functional correlates of motor control impairments in multiple sclerosis: A 7 Tesla task functional MRI study.

Upper and lower limb impairments are common in people with multiple sclerosis (pwMS), yet difficult to clinically identify in early stages of disease progression. Tasks involving complex motor control can potentially reveal more subtle deficits in early stages, and can be performed during functional MRI (fMRI) acquisition, to investigate underlying neural mechanisms, providing markers for early motor progression. We investigated brain activation during visually guided force matching of hand or foot in 28 minimally disabled pwMS (Expanded Disability Status Scale (EDSS) < 4 and pyramidal and cerebellar Kurtzke Functional Systems Scores ≤ 2) and 17 healthy controls (HC) using ultra-high field 7-Tesla fMRI, allowing us to visualise sensorimotor network activity in high detail. Task activations and performance (tracking lag and error) were compared between groups, and correlations were performed. PwMS showed delayed (+124 s, p = .002) and more erroneous (+0.15 N, p = .001) lower limb tracking, together with lower cerebellar, occipital and superior parietal cortical activation compared to HC. Lower activity within these regions correlated with worse EDSS (p = .034), lower force error (p = .006) and higher lesion load (p < .05). Despite no differences in upper limb task performance, pwMS displayed lower inferior occipital cortical activation. These results demonstrate that ultra-high field fMRI during complex hand and foot tracking can identify subtle impairments in lower limb movements and upper and lower limb brain activity, and differentiates upper and lower limb impairments in minimally disabled pwMS.

Increased functional sensorimotor network efficiency relates to disability in multiple sclerosis.

BACKGROUND: Network abnormalities could help explain physical disability in multiple sclerosis (MS), which remains poorly understood. OBJECTIVE: This study investigates functional network efficiency changes in the sensorimotor system. METHODS: We included 222 MS patients, divided into low disability (LD, Expanded Disability Status Scale (EDSS) ⩽3.5, n = 185) and high disability (HD, EDSS ⩾6, n = 37), and 82 healthy controls (HC). Functional connectivity was assessed between 23 sensorimotor regions. Measures of efficiency were computed and compared between groups using general linear models corrected for age and sex. Binary logistic regression models related disability status to local functional network efficiency (LE), brain volumes and demographics. Functional connectivity patterns of regions important for disability were explored. RESULTS: HD patients demonstrated significantly higher LE of the left primary somatosensory cortex (S1) and right pallidum compared to LD and HC, and left premotor cortex compared to HC only. The logistic regression model for disability (R2 = 0.38) included age, deep grey matter volume and left S1 LE. S1 functional connectivity was increased with prefrontal and secondary sensory areas in HD patients, compared to LD and HC. CONCLUSION: Clinical disability in MS associates with functional sensorimotor increases in efficiency and connectivity, centred around S1, independent of structural damage.

Microstructural correlates of 23Na relaxation in human brain at 7 Tesla.

23Na provides the second strongest MR-observable signal in biological tissue and exhibits bi-exponential T2∗ relaxation in micro-environments such as the brain. There is significant interest in developing 23Na biomarkers for neurological diseases that are associated with sodium channel dysfunction such as multiple sclerosis and epilepsy. We have previously reported methods for acquisition of multi-echo sodium MRI and continuous distribution modelling of sodium relaxation properties as surrogate markers of brain microstructure. This study aimed to compare 23Na T2∗ relaxation times to more established measures of tissue microstructure derived from advanced diffusion MRI at 7 â€‹T. Six healthy volunteers were scanned using a 3D multi-echo radial ultra-short TE sequence using a dual-tuned 1H/23Na birdcage coil, and a high-resolution multi-shell, high angular resolution diffusion imaging sequence using a 32-channel 1H receive coil. 23Na T2∗ relaxation parameters [mean T2∗ (T2∗mean) and fast relaxation fraction (T2∗ff)] were calculated from a voxel-wise continuous gamma distribution signal model. White matter (restricted anisotropic diffusion) and grey matter (restricted isotropic diffusion) density were calculated from multi-shell multi-tissue constrained spherical deconvolution. Sodium parameters were compared with white and grey matter diffusion properties. Sodium T2∗mean and T2∗ff showed little variation across a range of white matter axonal fibre and grey matter densities. We conclude that sodium T2∗ relaxation parameters are not greatly influenced by relative differences in intra- and extracellular partial volumes. We suggest that care be taken when interpreting sodium relaxation changes in terms of tissue microstructure in healthy tissue.

Compressed sensing effects on quantitative analysis of undersampled human brain sodium MRI.

PURPOSE: The clinical application of sodium MRI is hampered due to relatively low image quality and associated long acquisition times. Compressed sensing (CS) aims at a reduction of measurement time, but has been found to encompass quantitative estimation bias when used in low SNR x-Nuclei imaging. This work analyses CS in quantitative human brain sodium MRI from undersampled acquisitions and provides recommendations for tissue sodium concentration (TSC) estimation. METHODS: CS reconstructions from 3D radial acquisitions of 5 healthy volunteers were investigated over varying undersampling factors (USFs) and CS penalty weights on different sparsity domains, Wavelet, Discrete Cosine Transform (DCT), and Identity. Resulting images were compared with highly sampled and undersampled NUFFT-based images and evaluated for image quality (i.e. structural similarity), image intensity bias, and its effect on TSC estimates in gray and white matter. RESULTS: Wavelet-based CS reconstructions show highest image quality with stable TSC estimates for most USFs. Up to an USF of 4, images showed good structural detail. DCT and Identity-based CS enable good image quality, however show a bias in TSC with a reduction in estimates across USFs. CONCLUSIONS: The image intensity bias is lowest in Wavelet-based reconstructions and enables an up to fourfold acquisition speed up while maintaining good structural detail. The associated acquisition time reduction can facilitate a translation of sodium MRI into clinical routine.

Extracting more for less: multi-echo MP2RAGE for simultaneous T1 -weighted imaging, T1 mapping, R2∗ mapping, SWI, and QSM from a single acquisition.

PURPOSE: To demonstrate simultaneous T1 -weighted imaging, T1 mapping, R2∗ mapping, SWI, and QSM from a single multi-echo (ME) MP2RAGE acquisition. METHODS: A single-echo (SE) MP2RAGE sequence at 7 tesla was extended to ME with 4 bipolar gradient echo readouts. T1 -weighted images and T1 maps calculated from individual echoes were combined using sum of squares and averaged, respectively. ME-combined SWI and associated minimum intensity projection images were generated with TE-adjusted homodyne filters. A QSM reconstruction pipeline was used, including a phase-offsets correction and coil combination method to properly combine the phase images from the 32 receiver channels. Measurements of susceptibility, R2∗ , and T1 of brain tissue from ME-MP2RAGE were compared with those from standard ME-gradient echo and SE-MP2RAGE. RESULTS: The ME combined T1 -weighted, T1 map, SWI, and minimum intensity projection images showed increased SNRs compared to the SE results. The proposed coil combination method led to QSM results free of phase-singularity artifacts, which were present in the standard adaptive combination method. T1 -weighted, T1 , and susceptibility maps from ME-MP2RAGE were comparable to those obtained from SE-MP2RAGE and ME-gradient echo, whereas R2∗ maps showed increased blurring and reduced SNR. T1 , R2∗ , and susceptibility values of brain tissue from ME-MP2RAGE were consistent with those from SE-MP2RAGE and ME-gradient echo. CONCLUSION: High-resolution structural T1 weighted imaging, T1 mapping, R2∗ mapping, SWI, and QSM can be extracted from a single 8.5-min ME-MP2RAGE acquisition using a customized reconstruction pipeline. This method can be applied to replace separate SE-MP2RAGE and ME-gradient echo acquisitions to significantly shorten total scan time.

Acoustic Speech Analytics Are Predictive of Cerebellar Dysfunction in Multiple Sclerosis.

Speech production relies on motor control and cognitive processing and is linked to cerebellar function. In diseases where the cerebellum is impaired, such as multiple sclerosis (MS), speech abnormalities are common and can be detected by instrumental assessments. However, the potential of speech assessments to be used to monitor cerebellar impairment in MS remains unexplored. The aim of this study is to build an objectively measured speech score that reflects cerebellar function, pathology and quality of life in MS. Eighty-five people with MS and 21 controls participated in the study. Speech was independently assessed through objective acoustic analysis and blind expert listener ratings. Cerebellar function and overall disease disability were measured through validated clinical scores; cerebellar pathology was assessed via magnetic resonance imaging, and validated questionnaires informed quality of life. Selected speech variables were entered in a regression model to predict cerebellar function. The resulting model was condensed into one composite speech score and tested for prediction of abnormal 9-hole peg test (9HPT), and for correlations with the remaining cerebellar scores, imaging measurements and self-assessed quality of life. Slow rate of syllable repetition and increased free speech pause percentage were the strongest predictors of cerebellar impairment, complemented by phonatory instability. Those variables formed the acoustic composite score that accounted for 54% of variation in cerebellar function, correlated with cerebellar white matter volume (r = 0.3, p = 0.017), quality of life (r = 0.5, p < 0.001) and predicted an abnormal 9HPT with 85% accuracy. An objective multi-feature speech metric was highly representative of motor cerebellar impairment in MS.

Functional neuroplasticity in response to cerebello-thalamic injury underpins the clinical presentation of tremor in multiple sclerosis.

BACKGROUND: Tremor is present in almost half of multiple sclerosis (MS) patients. The lack of understanding of its pathophysiology is hampering progress in development of treatments. OBJECTIVES: To clarify the structural and functional brain changes associated with the clinical phenotype of upper limb tremor in people with MS. METHODS: Fifteen healthy controls (46.1 ± 15.4 years), 27 MS participants without tremor (46.7 ± 11.6 years) and 42 with tremor (46.6 ± 11.5 years) were included. Tremor was quantified using the Bain score (0-10) for overall severity, handwriting and Archimedes spiral drawing. Functional magnetic resonance imaging activations were compared between participants groups during performance of a joystick task designed to isolate tremulous movement. Inflammation and atrophy of cerebello-thalamo-cortical brain structures were quantified. RESULTS: Tremor participants were found to have atrophy of the cerebellum and thalamus, and higher ipsilateral cerebellar lesion load compared to participants without tremor (p < 0.020). We found higher ipsilateral activation in the inferior parietal lobule, the premotor cortex and supplementary motor area in MS tremor participants compared to MS participants without tremor during the joystick task. Finally, stronger activation in those areas was associated with lower tremor severity. CONCLUSION: Subcortical neurodegeneration and inflammation along the cerebello-thalamo-cortical and cortical functional neuroplasticity contribute to the severity of tremor in MS.

A continuum of T2* components: Flexible fast fraction mapping in sodium MRI.

PURPOSE: Parameter mapping in sodium MRI data is challenging due to inherently low SNR and spatial resolution, prompting the need to employ robust models and estimation techniques. This work aims to develop a continuum model of sodium T2* -decay to overcome the limitations of the commonly employed bi-exponential models. Estimates of mean T2* -decay and fast component fraction in tissue are emergent from the inferred continuum model. METHODS: A closed-form continuum model was derived assuming a gamma distribution of T2* components. Sodium MRI was performed on four healthy human subjects and a phantom consisting of closely packed vials filled with an aqueous solution of varying sodium and agarose concentrations. The continuum model was applied to the phantom and in vivo human multi-echo 7T data. Parameter maps by voxelwise model-fitting were obtained. RESULTS: The continuum model demonstrated comparable estimation performance to the bi-exponential model. The parameter maps provided improved contrast between tissue structures. The fast component fraction, an indicator of the heterogeneity of localised sodium motion regimes in tissue, was zero in CSF and high in WM structures. CONCLUSIONS: The continuum distribution model provides high quality, high contrast parameter maps, and informative voxelwise estimates of the relative weighting between fast and slow decay components.

Zero-gradient-excitation ramped hybrid encoding (zGRF -RHE) sodium MRI.

PURPOSE: Fast bi-exponential transverse signal decay compounds sodium image quality. This work aims at enhancing image characteristics using a special case of ramped hybrid encoding (RHE). Zero-gradient-excitation (zGRF )-RHE provides (1) gradient-free excitation for high flip angle, artifact-free excitation profiles and (2) gradient ramping during dead-time for the optimization of encoding time (tenc ) to reduce T2* signal decay influence during acquisition. METHODS: Radial zGRF -RHE and standard radial UTE were investigated over a range of receiver bandwidths in simulations, phantom and in vivo brain experiments. Central k-space in zGRF -RHE was acquired through single point measurements at the minimum achievable TE. T2* blurring artifacts and image SNR and CNR were assessed. RESULTS: zGRF -RHE enabled 90° flip angle artifact-free excitation, whereas gradient pre-ramping provided greater tenc efficiency for any readout bandwidths. Experiments confirmed simulation results, revealing sharper edge characteristics particularly at short readout durations (TRO ). Significant SNR improvements of up to 4.8% were observed for longer TRO . CONCLUSION: zGRF -RHE allows for artifact-free high flip angle excitation with time-efficient encoding improving on image characteristics. This hybrid encoding concept with gradient pre-ramping is trajectory independent and can be introduced in any center-out UTE trajectory design.

Optimized partial-coverage functional analysis pipeline (OPFAP): a semi-automated pipeline for skull stripping and co-registration of partial-coverage, ultra-high-field functional images.

OBJECTIVE: Ultra-high-field functional MRI (UHF-fMRI) allows for higher spatiotemporal resolution imaging. However, higher-resolution imaging entails coverage limitations. Processing partial-coverage images using standard pipelines leads to sub-optimal results. We aimed to develop a simple, semi-automated pipeline for processing partial-coverage UHF-fMRI data using widely used image processing algorithms. MATERIALS AND METHODS: We developed automated pipelines for optimized skull stripping and co-registration of partial-coverage UHF functional images, using built-in functions of the Centre for Functional Magnetic Resonance Imaging of the Brain's (FMRIB's) Software library (FSL) and advanced normalization tools. We incorporated the pipelines into the FSL's functional analysis pipeline and provide a semi-automated optimized partial-coverage functional analysis pipeline (OPFAP). RESULTS: Compared to the standard pipeline, the OPFAP yielded images with 15 and 30% greater volume of non-zero voxels after skull stripping the functional and anatomical images, respectively (all p = 0.0004), which reflected the conservation of cortical voxels lost when the standard pipeline was used. The OPFAP yielded the greatest Dice and Jaccard coefficients (87 and 80%, respectively; all p < 0.0001) between the co-registered participant gyri maps and the template gyri maps, demonstrating the goodness of the co-registration results. Furthermore, the greatest volume of group-level activation in the most number of functionally relevant regions was observed when the OPFAP was used. Importantly, group-level activations were not observed when using the standard pipeline. CONCLUSION: These results suggest that the OPFAP should be used for processing partial-coverage UHF-fMRI data for detecting high-resolution macroscopic blood oxygenation level-dependent activations.