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A Nb-silicide based alloy with nominal composition Nb–18Ti–22Si–6Mo-1.5Cr–2Sn-1Hf (at. %), designed for high temperature aerospace applications, was produced via a powder metallurgy (PM) route. The raw elements were arc melted, crushed, and milled to powder, then consolidated using Field Assisted Sintering Technology (FAST). The compressive creep of the alloy was evaluated using electro-thermal mechanical testing (ETMT). The study demonstrated the production of larger 60 mm diameter samples, with potential for further scale up. The microstructure of the FAST alloy, which is comprised of bcc Nbss and tetragonal αNb5Si3 was more homogenous compared with the cast alloy, with some interstitial contamination that occurred during powder production. The FAST alloy had lower density than state of the art Ni-based superalloys and refractory metal complex concentrated alloys (RCCAs) and high entropy alloys (RHEAs), and its yield strength and specific yield strength was higher than those of the latter metallic Ultra high temperature materials (UHTMs) and comparable to those of Nb-silicide based alloys with B addition. The stress exponent n in compressive creep was in the range 1.7–2.6, similar to that of binary Nb–10Si and Nb–16Si alloys and its creep rate at 1200 °C and 100 MPa was similar to that of the MASC alloy (Nb–25Ti–16Si-8Hf-2Al–2Cr (at.%)). Like the latter, the creep of the FAST alloy did not meet the creep goal.

Objective: The corticospinal tract (CST) reveals progressive microstructural alterations in ALS measurable by DTI. The aim of this study was to evaluate fractional anisotropy (FA) along the CST as a longitudinal marker of disease progression in ALS. Methods: The study cohort consisted of 114 patients with ALS and 110 healthy controls from the second prospective, longitudinal, multicentre study of the Canadian ALS Neuroimaging Consortium (CALSNIC-2). DTI and clinical data from a harmonized protocol across 7 centres were collected. Thirty-nine ALS patients and 61 controls completed baseline and two follow-up visits and were included for longitudinal analyses. Whole brain-based spatial statistics and hypothesis-guided tract-of-interest analyses were performed for cross-sectional and longitudinal analyses. Results: FA was reduced at baseline and longitudinally in the CST, mid-corpus callosum (CC), frontal lobe, and other ALS-related tracts, with alterations most evident in the CST and mid-CC. CST and pontine FA correlated with functional impairment (ALSFRS-R), upper motor neuron function, and clinical disease progression rate. Reduction in FA was largely located in the upper CST; however, the longitudinal decline was greatest in the lower CST. Effect sizes were dependent on region, resulting in study group sizes between 17 and 31 per group over a 9-month interval. Cross-sectional effect sizes were maximal in the upper CST; whereas, longitudinal effect sizes were maximal in mid-callosal tracts. Conclusions: Progressive microstructural alterations in ALS are most prominent in the CST and CC. DTI can provide a biomarker of cerebral degeneration in ALS, with longitudinal changes in white matter demonstrable over a reasonable observation period, with a feasible number of participants, and within a multicentre framework.

Magnetic resonance fingerprinting (MRF) is a quantitative MRI (qMRI) framework that provides simultaneous estimates of multiple relaxation parameters as well as metrics of field inhomogeneity in a single acquisition. However, current challenges exist in the forms of (1) scan time; (2) need for custom image reconstruction; (3) large dictionary sizes; (4) long dictionary-matching time. This study aims to introduce a novel streamlined magnetic-resonance fingerprinting (sMRF) framework based on a single-shot echo-planar imaging (EPI) sequence to simultaneously estimate tissue T1, T2, and T2* with integrated B1+ correction. Encouraged by recent work on EPI-based MRF, we developed a method that combines spin-echo EPI with gradient-echo EPI to achieve T2 in addition to T1 and T2* quantification. To this design, we add simultaneous multi-slice (SMS) acceleration to enable full-brain coverage in a few minutes. Moreover, in the parameter-estimation step, we use deep learning to train a deep neural network (DNN) to accelerate the estimation process by orders of magnitude. Notably, due to the high image quality of the EPI scans, the training process can rely simply on Bloch-simulated data. The DNN also removes the need for storing large dictionaries. Phantom scans along with in-vivo multi-slice scans from seven healthy volunteers were acquired with resolutions of 1.1×1.1×3 mm3 and 1.7×1.7×3 mm3, and the results were validated against ground truth measurements. Excellent correspondence was found between our T1, T2, and T2* estimates and results obtained from standard approaches. In the phantom scan, a strong linear relationship (R = 1–1.04, R2>0.96) was found for all parameter estimates, with a particularly high agreement for T2 estimation (R2>0.99). Similar findings are reported for the in-vivo human data for all of our parameter estimates. Incorporation of DNN results in a reduction of parameter estimation time on the order of 1000 x and a reduction in storage requirements on the order of 2500 x while achieving highly similar results as conventional dictionary matching (%differences of 7.4 ± 0.4%, 3.6 ± 0.3% and 6.0 ± 0.4% error in T1, T2, and T2* estimation). Thus, sMRF has the potential to be the method of choice for future MRF studies by providing ease of implementation, fast whole-brain coverage, and ultra-fast T1/T2/T2* estimation.

Electroencephalography (EEG) concurrently collected with functional magnetic resonance imaging (fMRI) is heavily distorted by the repetitive gradient coil switching during the fMRI acquisition. The performance of the typical template-based gradient artifact suppression method can be suboptimal because the artifact changes over time. Gradient artifact residuals also impede the subsequent suppression of ballistocardiography artifacts.Here we propose recording continuous EEG with temporally sparse fast fMRI (fast fMRI-EEG) to minimize the EEG artifacts caused by MRI gradient coil switching without significantly compromising the field-of-view and spatiotemporal resolution of fMRI. Using simultaneous multi-slice inverse imaging to achieve whole-brain fMRI with isotropic 5-mm resolution in 0.1 ​s, and performing these acquisitions once every 2 ​s, we have 95% of the duty cycle available to record EEG with substantially less gradient artifact. We found that the standard deviation of EEG signals over the entire acquisition period in fast fMRI-EEG was reduced to 54% of that in conventional concurrent echo-planar imaging (EPI) and EEG recordings (EPI-EEG) across participants. When measuring 15-Hz steady-state visual evoked potentials (SSVEPs), the baseline-normalized oscillatory neural response in fast fMRI-EEG was 2.5-fold of that in EPI-EEG. The functional MRI responses associated with the SSVEP delineated by EPI and fast fMRI were similar in the spatial distribution, the elicited waveform, and detection power. Sparsely interleaved fast fMRI-EEG provides high-quality EEG without substantially compromising the quality of fMRI in evoked response measurements, and has the potential utility for applications where the onset of the target stimulus cannot be precisely determined, such as epilepsy.

Amyotrophic lateral sclerosis (ALS) is characterized primarily by motor neuron but also frontotemporal lobar degeneration. Although the cerebellum is involved in both motor and cognitive functions, little is known of its role in ALS. We targeted the dentate nucleus (DN) in the cerebellum and the associated white matter fibers tracts connecting the DN to the rest of the brain using multimodal imaging techniques to examine the cerebellar structural and functional connectivity patterns in ALS patients and hypothesized that the DN is implicated in the pathophysiology of ALS. A cohort of 127 participants (56 healthy subjects (HS); 71 ALS patients) were recruited across Canada through the Canadian ALS Neuroimaging Consortium (CALSNIC). Resting state functional MRI, diffusion tensor imaging (DTI), and 3D weighted T1 structural images were acquired on a 3-tesla scanner. The DN in the cerebellum was used as a seed to evaluate the whole brain cerebral resting-state functional connectivity (rsFC). The superior cerebellar peduncle (SCP), middle cerebellar peduncle (MCP) and inferior cerebellar peduncle (ICP) were used as a region of interest in DTI to evaluate the structural integrity of the DN with the cortex and brain stem. Cerebellar volumetric analysis was done to examine the lobular and DN grey matter (GM) changes in ALS patients. Lastly, an association between DN rsFC and structural alterations were explored. DN rsFC was reduced with cerebrum (supplementary motor area, precentral gyrus, frontal, posterior parietal, temporal), lobule IV, and brain stem, and increased with parieto-occipital region. DN rsFC and white matter (WM) diffusivity alterations at SCP, MCP, and ICP were accompanied by correlations with ALSFRS-R. There were no DN volumetric changes. Notably, DN rsFC correlated with WM abnormalities at superior cerebellar peduncle. The DN plays a pathophysiological role in ALS. Impaired rsFC is likely due to the observed cerebellar peduncular WM damage given the lack of GM atrophy of the DN. This study demonstrates altered cerebellar rsFC connectivity with motor and extra-motor regions in ALS, and impaired rsFC is likely due to the observed cerebellar peduncular WM damage given the lack of GM atrophy of the DN. The correlation between the altered DN connectivity, and the behavioral data support the hypothesis that the DN plays a pathophysiological role in ALS.

Sport-related concussion is associated with acute disturbances in neurometabolic function, with effects that may last weeks to months after injury. However, is presently unknown whether these disturbances resolve at medical clearance to return to play (RTP) or continue to evolve over longer time intervals. Moreover, little is known about how these neurometabolic changes correlate with other measures of brain physiology. In this study, these gaps were addressed by evaluating ninety-nine (99) university-level athletes, including 33 with sport-related concussion and 66 without recent injury, using multi-parameter magnetic resonance imaging (MRI), which included single-voxel spectroscopy (SVS), diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). The concussed athletes were scanned at the acute phase of injury (27/33 imaged), medical clearance to RTP (25/33 imaged), one month post-RTP (25/33 imaged) and one year post-RTP (13/33 imaged). We measured longitudinal changes in N-acetyl aspartate (NAA) and myo-inositol (Ins), over the course of concussion recovery. Concussed athletes showed no significant abnormalities or longitudinal change in NAA values, whereas Ins was significantly elevated at RTP and one month later. Interestingly, Ins response was attenuated by a prior history of concussion. Subsequent analyses identified significant associations between Ins values, DTI measures of white matter microstructure and fMRI measures of functional connectivity. These associations varied over the course of concussion recovery, suggesting that elevated Ins values at RTP and beyond reflect distinct changes in brain physiology, compared to acute injury. These findings provide novel information about neurometabolic recovery after a sport-related concussion, with evidence of disturbances that persist beyond medical clearance to RTP.

Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks. Keywords: fMRI, Functional connectivity, Concussion, Brain injury, Symptoms

Concussion is associated with significant symptoms within hours to days post-injury, including disturbances in physical function, cognition, sleep and emotion. However, little is known about how subjective impairments correlate with objective measures of cerebrovascular function following brain injury. This study examined the relationship between symptoms and cerebral blood flow (CBF) in individuals following sport-related concussion. Seventy university level athletes had CBF measured using Arterial Spin Labelling (ASL), including 35 with acute concussion and 35 matched controls and their symptoms were assessed using the Sport Concussion Assessment Tool 3 (SCAT3). For concussed athletes, greater total symptom severity was associated with elevated posterior cortical CBF, although mean CBF was not significantly different from matched controls (p=0.46). Examining symptom clusters, athletes reporting greater cognitive symptoms also had lower frontal and subcortical CBF, relative to athletes with greater somatic symptoms. The “cognitive” and “somatic” subgroups also exhibited significant differences in CBF relative to controls (p≤0.026). This study demonstrates objective CBF correlates of symptoms in recently concussed athletes and shows that specific symptom clusters may have distinct patterns of altered CBF, significantly extending our understanding of the neurobiology of concussion and traumatic brain injury. Keywords: Sport concussion, Cerebral blood flow, ASL, Symptoms

Concussion is a major health concern, associated with short-term deficits in physical function, emotion and cognition, along with negative long-term health outcomes. However, we remain in the early stages of characterizing MRI markers of concussion, particularly during the first week post-injury when symptoms are most severe. In this study, 52 varsity athletes were scanned using Magnetic Resonance Imaging (MRI), including 26 athletes with acute concussion (scanned 1–7 days post-injury) and 26 matched control athletes. A comprehensive set of functional and structural MRI measures were analyzed, including cerebral blood flow (CBF) and global functional connectivity (Gconn) of grey matter, along with fractional anisotropy (FA) and mean diffusivity (MD) of white matter. An analysis comparing acutely concussed athletes and controls showed limited evidence for reliable mean effects of acute concussion, with only MD showing spatially extensive differences between groups. We subsequently demonstrated that the number of days post-injury explained a significant proportion of inter-subject variability in MRI markers of acutely concussed athletes. Athletes scanned at early acute injury (1–3 days) had elevated CBF and Gconn and reduced FA, but those scanned at late acute injury (5–7 days) had the opposite response. In contrast, MD showed a more complex, spatially-dependent relationship with days post-injury. These novel findings highlight the variability of MRI markers during the acute phase of concussion and the critical importance of considering the acute injury time interval, which has significant implications for studies relating acute MRI data to concussion outcomes.

Background: Brain tumor surgery requires careful balance between maximizing tumor excision and preserving eloquent cortex. In some cases, the surgeon may opt to perform an awake craniotomy including intraoperative mapping of brain function by direct cortical stimulation (DCS) to assist in surgical decision-making. Preoperatively, functional magnetic resonance imaging (fMRI) facilitates planning by identification of eloquent brain areas, helping to guide DCS and other aspects of the surgical plan. However, brain deformation (shift) limits the usefulness of preoperative fMRI during surgery. To address this, an integrated visualization method for fMRI and DCS results is developed that is intuitive for the surgeon. Methods: An image registration pipeline was constructed to display preoperative fMRI data corrected for brain shift overlaid on images of the exposed cortical surface at the beginning and completion of DCS mapping. Preoperative fMRI and DCS data were registered for a range of misalignments, and the residual registration errors were calculated. The pipeline was validated on imaging data from five brain tumor patients who underwent awake craniotomy. Results: Registration errors were well under 5 mm (the approximate spatial resolution of DCS) for misalignments of up to 25 mm and approximately 10–15°. For rotational misalignments up to 20°, the success rate was 95% for an error tolerance of 5 mm. Failures were negligible for rotational misalignments up to 10°. Good quality registrations were observed for all five patients. Conclusions: A proof-of-concept image registration pipeline is presented with acceptable accuracy for intraoperative use, providing multimodality visualization with potential benefits for intraoperative brain mapping. Key words: Awake craniotomy, Brain mapping, Brain tumor resection, Electric stimulation, Functional mapping, Multimodal imaging, Surgical planning