SCAT5 baseline values, test-retest reliability, and reliable change metrics in high school athletes.

OBJECTIVE: In the United States, more than 1 million sport-related concussions afflict children annually, with many cases undetected or unreported. The Sport Concussion Assessment Tool (SCAT) is widely used to detect concussions in high school, collegiate, and professional sports. The objective of this study was to establish baseline values for the SCAT version 5 (SCAT5) in high school athletes. METHODS: Baseline SCAT5 evaluations were conducted in students (ages 14-19 years) from 19 high schools in central Illinois who were participating in various school-sponsored sports. The SCAT5 evaluations were retrospectively extracted from the electronic medical record system for analysis. Statistical analyses included the Wilcoxon rank-sum test for continuous variables and the chi-square test for categorical variables, considering significance at p < 0.05. Test-retest reliability at < 6 months, 10-14 months, and 16-20 months was computed using intraclass correlation and Spearman's rho (ρ). Reliable change indices are provided using the Iverson formula. RESULTS: A total of 2833 unique athletes were included, and the average age was 15.5 ± 1.14 (SD) years. There were 721 female (25.5%) and 2112 male (74.5%) athletes. Students ≥ 15 years old had more prior concussions (p < 0.001), and male athletes were more frequently hospitalized for head injury (p = 0.013). Female athletes exhibited a significantly higher prevalence of mood disorders (14.7% vs 4.6%, p < 0.001), whereas attention-deficit/hyperactivity disorder was more common in male athletes (5.2% vs 13.2%, p < 0.001). Symptom number and severity were significantly greater in female athletes (3.17 ± 4.39 vs 2.08 ± 3.49, p < 0.001; 5.47 ± 9.21 vs 3.52 ± 7.26, p < 0.001, respectively), with mood-related symptoms representing the largest differences. Female athletes and students ≥ 15 years old performed better on most cognitive assessments. Female athletes and students < 15 years old performed better on the modified Balance Error Scoring System (p < 0.001). Test-retest reliability was poor to moderate for most assessment components. Reliable change index cutoff values differed slightly by sex, with female athletes often having a greater cutoff value. CONCLUSIONS: This study underscores the variability of SCAT5 baseline values influenced by age, sex, and medical history among adolescent athletes. It provides a robust dataset, delineating baseline values stratified by sex and age within this demographic. Additionally, the results provide enhanced guidance to clinicians for interpretation of change and reliability of baselines.

Measuring CSF shunt flow with MRI using flow enhancement of signal intensity (FENSI).

PURPOSE: To develop and validate a noninvasive imaging technique for accurately assessing very slow CSF flow within shunt tubes in pediatric patients with hydrocephalus, aiming to identify obstructions that might impede CSF drainage. THEORY AND METHODS: A simulation of shunt flow enhancement of signal intensity (shunt-FENSI) signal is used to establish the relationship between signal change and flow rate. The quantification of flow enhancement of signal intensity data involves normalization, curve fitting, and calibration to match simulated data. Additionally, a phase sweep method is introduced to accommodate the impact of magnetic field inhomogeneity on the flow measurement. The method is tested in flow phantoms, healthy adults, intensive care unit patients with external ventricular drains (EVD), and shunt patients. EVDs enable shunt-flow measurements to be acquired with a ground truth measure of CSF drainage. RESULTS: The flow-rate-to-signal simulation establishes signal-flow relationships and takes into account the T1 of draining fluid. The phase sweep method accurately accounts for phase accumulation due to frequency offsets at the shunt. Results in phantom and healthy human participants reveal reliable quantification of flow rates using controlled flows and agreement with the flow simulation. EVD patients display reliable measures of flow rates. Shunt patient results demonstrate feasibility of the method and consistent flow rates for functional shunts. CONCLUSION: The results demonstrate the technique's applicability, accuracy, and potential for diagnosing and noninvasively monitoring hydrocephalus. Limitations of the current approach include a high sensitivity to motion and strict requirement of imaging slice prescription.

MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline.

Large-scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instructions that requires many software packages with complex dependencies and high computational costs. We developed MaPPeRTrac, an edge-centric tractography pipeline that simplifies and accelerates this process in a wide range of high-performance computing (HPC) environments. It fully automates either probabilistic or deterministic tractography, starting from a subject's magnetic resonance imaging (MRI) data, including structural and diffusion MRI images, to the edge density image (EDI) of their structural connectomes. Dependencies are containerized with Singularity (now called Apptainer) and decoupled from code to enable rapid prototyping and modification. Data derivatives are organized with the Brain Imaging Data Structure (BIDS) to ensure that they are findable, accessible, interoperable, and reusable following FAIR principles. The pipeline takes full advantage of HPC resources using the Parsl parallel programming framework, resulting in the creation of connectome datasets of unprecedented size. MaPPeRTrac is publicly available and tested on commercial and scientific hardware, so it can accelerate brain connectome research for a broader user community. MaPPeRTrac is available at: https://github.com/LLNL/mappertrac .

Ultra-High-Field MRI in the Diagnosis and Management of Gliomas: A Systematic Review.

Importance: Gliomas, tumors of the central nervous system, are classically diagnosed through invasive surgical biopsy and subsequent histopathological study. Innovations in ultra-high field (UHF) imaging, namely 7-Tesla magnetic resonance imaging (7T MRI) are advancing preoperative tumor grading, visualization of intratumoral structures, and appreciation of small brain structures and lesions. Objective: Summarize current innovative uses of UHF imaging techniques in glioma diagnostics and treatment. Methods: A systematic review in accordance with PRISMA guidelines was performed utilizing PubMed. Case reports and series, observational clinical trials, and randomized clinical trials written in English were included. After removing unrelated studies and those with non-human subjects, only those related to 7T MRI were independently reviewed and summarized for data extraction. Some preclinical animal models are briefly described to demonstrate future usages of ultra-high-field imaging. Results: We reviewed 46 studies (43 human and 3 animal models) which reported clinical usages of UHF MRI in the diagnosis and management of gliomas. Current literature generally supports greater resolution imaging from 7T compared to 1.5T or 3T MRI, improving visualization of cerebral microbleeds and white and gray matter, and providing more precise localization for radiotherapy targeting. Additionally, studies found that diffusion or susceptibility-weighted imaging techniques applied to 7T MRI, may be used to predict tumor grade, reveal intratumoral structures such as neovasculature and microstructures like axons, and indicate isocitrate dehydrogenase 1 mutation status in preoperative imaging. Similarly, newer imaging techniques such as magnetic resonance spectroscopy and chemical exchange saturation transfer imaging can be performed on 7T MRI to predict tumor grading and treatment efficacy. Geometrical distortion, a known challenge of 7T MRI, was at a tolerable level in all included studies. Conclusion: UHF imaging has the potential to preoperatively and non-invasively grade gliomas, provide precise therapy target areas, and visualize lesions not seen on conventional MRI.

Hippocampal stiffness in mesial temporal lobe epilepsy measured with MR elastography: Preliminary comparison with healthy participants.

Mesial temporal lobe epilepsy (MTLE) is the most common form of refractory epilepsy. Common imaging biomarkers are often not sensitive enough to identify MTLE sufficiently early to facilitate the greatest benefit from surgical or pharmacological intervention. The objective of this work is to establish hippocampal stiffness measured with magnetic resonance elastography (MRE) as a biomarker for MTLE; we hypothesized that the epileptogenic hippocampus in MTLE is stiffer than the non-epileptogenic hippocampus. MRE was used to measure hippocampal stiffness in a group of patients with unilateral MTLE (n = 12) and a group of healthy comparison participants (n = 13). We calculated the ratio of hippocampal stiffness ipsilateral to epileptogenesis to the contralateral side for both groups. We found a higher hippocampal stiffness ratio in patients with MTLE compared with healthy participants (1.14 v. 0.99; p = 0.004), and that stiffness ratio differentiated MTLE from control groups effectively (AUC = 0.85). Hippocampal stiffness ratio, when added to volume ratio, an established MTLE biomarker, significantly improved the ability to differentiate the two groups (p = 0.038). Stiffness measured with MRE is sensitive to hippocampal pathology in MTLE and the addition of MRE to neuroimaging assessments may improve detection and characterization of the disease.

Viscoelasticity of subcortical gray matter structures.

Viscoelastic mechanical properties of the brain assessed with magnetic resonance elastography (MRE) are sensitive measures of microstructural tissue health in neurodegenerative conditions. Recent efforts have targeted measurements localized to specific neuroanatomical regions differentially affected in disease. In this work, we present a method for measuring the viscoelasticity in subcortical gray matter (SGM) structures, including the amygdala, hippocampus, caudate, putamen, pallidum, and thalamus. The method is based on incorporating high spatial resolution MRE imaging (1.6 mm isotropic voxels) with a mechanical inversion scheme designed to improve local measures in pre-defined regions (soft prior regularization [SPR]). We find that in 21 healthy, young volunteers SGM structures differ from each other in viscoelasticity, quantified as the shear stiffness and damping ratio, but also differ from the global viscoelasticity of the cerebrum. Through repeated examinations on a single volunteer, we estimate the uncertainty to be between 3 and 7% for each SGM measure. Furthermore, we demonstrate that the use of specific methodological considerations-higher spatial resolution and SPR-both decrease uncertainty and increase sensitivity of the SGM measures. The proposed method allows for reliable MRE measures of SGM viscoelasticity for future studies of neurodegenerative conditions. Hum Brain Mapp 37:4221-4233, 2016. © 2016 Wiley Periodicals, Inc.

Observation of direction-dependent mechanical properties in the human brain with multi-excitation MR elastography.

Magnetic resonance elastography (MRE) has shown promise in noninvasively capturing changes in mechanical properties of the human brain caused by neurodegenerative conditions. MRE involves vibrating the brain to generate shear waves, imaging those waves with MRI, and solving an inverse problem to determine mechanical properties. Despite the known anisotropic nature of brain tissue, the inverse problem in brain MRE is based on an isotropic mechanical model. In this study, distinct wave patterns are generated in the brain through the use of multiple excitation directions in order to characterize the potential impact of anisotropic tissue mechanics on isotropic inversion methods. Isotropic inversions of two unique displacement fields result in mechanical property maps that vary locally in areas of highly aligned white matter. Investigation of the corpus callosum, corona radiata, and superior longitudinal fasciculus, three highly ordered white matter tracts, revealed differences in estimated properties between excitations of up to 33%. Using diffusion tensor imaging to identify dominant fiber orientation of bundles, relationships between estimated isotropic properties and shear asymmetry are revealed. This study has implications for future isotropic and anisotropic MRE studies of white matter tracts in the human brain.