UA cloudflare authentication

Browsing by Author "Cheng, Hu"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Association Between Proteomic Blood Biomarkers and DTI/NODDI Metrics in Adolescent Football Players: A Pilot Study
    (Frontiers, 2020) Kawata, Keisuke; Steinfeldt, Jesse A.; Huibregtse, Megan E.; Nowak, Madeleine K.; Macy, Jonathan T.; Kercher, Kyle; Rettke, Devin J.; Shin, Andrea; Chen, Zhongxue; Ejima, Keisuke; Newman, Sharlene D.; Cheng, Hu; Indiana University Bloomington; University of Alabama Tuscaloosa
    While neuroimaging and blood biomarker have been two of the most active areas of research in the neurotrauma community, these fields rarely intersect to delineate subconcussive brain injury. The aim of the study was to examine the association between diffusion MRI techniques [diffusion tensor imaging (DTI) and neurite orientation/dispersion density imaging (NODDI)] and brain-injury blood biomarker levels [tau, neurofilament-light (NfL), glial-fibrillary-acidic-protein (GFAP)] in high-school football players at their baseline, aiming to detect cumulative neuronal damage from prior seasons. Twenty-five football players were enrolled in the study. MRI measures and blood samples were obtained during preseason data collection. The whole-brain, tract-based spatial statistics was conducted for six diffusion metrics: fractional anisotropy (FA), mean diffusivity (MD), axial/radial diffusivity (AD, RD), neurite density index (NDI), and orientation dispersion index (ODI). Five players were ineligible for MRIs, and three serum samples were excluded due to hemolysis, resulting in 17 completed set of diffusion metrics and blood biomarker levels for association analysis. Our permutation-based regression model revealed that serum tau levels were significantly associated with MD and NDI in various axonal tracts; specifically, elevated serum tau levels correlated to elevated MD (p = 0.0044) and reduced NDI (p = 0.016) in the corpus callosum and surrounding white matter tracts (e.g., longitudinal fasciculus). Additionally, there was a negative association between NfL and ODI in the focal area of the longitudinal fasciculus. Our data suggest that high school football players may develop axonal microstructural abnormality in the corpus callosum and surrounding white matter tracts, such as longitudinal fasciculus. A future study is warranted to determine the longitudinal multimodal relationship in response to repetitive exposure to sports-related head impacts.
  • Thumbnail Image
    Item
    Collegiate athlete brain data for white matter mapping and network neuroscience
    (Nature Portfolio, 2021) Caron, Bradley; Stuck, Ricardo; McPherson, Brent; Bullock, Daniel; Kitchell, Lindsey; Faskowitz, Joshua; Kellar, Derek; Cheng, Hu; Newman, Sharlene; Port, Nicholas; Pestilli, Franco; Indiana University Bloomington; University of Alabama Tuscaloosa; University of Texas Austin; Johns Hopkins University; Johns Hopkins University Applied Physics Laboratory
    We describe a dataset of processed data with associated reproducible preprocessing pipeline collected from two collegiate athlete groups and one non-athlete group. The dataset shares minimally processed diffusion-weighted magnetic resonance imaging (dMRI) data, three models of the diffusion signal in the voxel, full-brain tractograms, segmentation of the major white matter tracts as well as structural connectivity matrices. There is currently a paucity of similar datasets openly shared. Furthermore, major challenges are associated with collecting this type of data. The data and derivatives shared here can be used as a reference to study the effects of long-term exposure to collegiate athletics, such as the effects of repetitive head impacts. We use advanced anatomical and dMRI data processing methods publicly available as reproducible web services at brainlife.io.
  • Thumbnail Image
    Item
    Denoising diffusion weighted imaging data using convolutional neural networks
    (PLOS, 2022) Cheng, Hu; Vinci-Booher, Sophia; Wang, Jian; Caron, Bradley; Wen, Qiuting; Newman, Sharlene; Pestilli, Franco; Indiana University Bloomington; Vanderbilt University; Shandong Normal University; University of Alabama Tuscaloosa; University of Texas Austin
    Diffusion weighted imaging (DWI) with multiple, high b-values is critical for extracting tissue microstructure measurements; however, high b-value DWI images contain high noise levels that can overwhelm the signal of interest and bias microstructural measurements. Here, we propose a simple denoising method that can be applied to any dataset, provided a low-noise, single-subject dataset is acquired using the same DWI sequence. The denoising method uses a one-dimensional convolutional neural network (1D-CNN) and deep learning to learn from a low-noise dataset, voxel-by-voxel. The trained model can then be applied to high-noise datasets from other subjects. We validated the 1D-CNN denoising method by first demonstrating that 1D-CNN denoising resulted in DWI images that were more similar to the noise-free ground truth than comparable denoising methods, e.g., MP-PCA, using simulated DWI data. Using the same DWI acquisition but reconstructed with two common reconstruction methods, i.e. SENSE1 and sum-of-square, to generate a pair of low-noise and high-noise datasets, we then demonstrated that 1D-CNN denoising of high-noise DWI data collected from human subjects showed promising results in three domains: DWI images, diffusion metrics, and tractography. In particular, the denoised images were very similar to a low-noise reference image of that subject, more than the similarity between repeated low-noise images (i.e. computational reproducibility). Finally, we demonstrated the use of the 1D-CNN method in two practical examples to reduce noise from parallel imaging and simultaneous multi-slice acquisition. We conclude that the 1D-CNN denoising method is a simple, effective denoising method for DWI images that overcomes some of the limitations of current state-of-the-art denoising methods, such as the need for a large number of training subjects and the need to account for the rectified noise floor.
  • Thumbnail Image
    Item
    Hippocampal Neurotransmitter Inhibition Suppressed During Gaming Explained by Skill Rather Than Gamer Status
    (Frontiers, 2020) Prena, Kelsey; Cheng, Hu; Newman, Sharlene D.; Boston University; Indiana University Bloomington; University of Alabama Tuscaloosa
    Goal-directed spatial decision making video games combine spatial mapping, memory, and reward; all of which can involve hippocampal excitation through suppression of an inhibitory neurotransmitter, gamma-aminobutyric acid (GABA). In this study, GABA was measured before and after 30 min of video game play within a voxel around the hippocampus. It was predicted that all participants would experience a decrease in GABA during gaming as a result of in-game rewards; and, those who were most competitive with the goal-directed spatial decision making game would display lower hippocampal GABA concentrations after gaming. Those who were not competitive, because they were too skilled or not skilled enough, would demonstrate higher hippocampal GABA concentrations after gaming. While there were no significant differences in hippocampal GABA before and after gaming for gamers and non-gamers alike, there was a significant quadratic regression between performance on a spatial working memory task and post-gaming hippocampal GABA concentrations.
  • Thumbnail Image
    Item
    The relationship between cannabis use and taurine: A MRS and metabolomics study
    (PLOS, 2022) Newman, Sharlene D.; Martin, Ashley M. Schnakenberg; Raymond, David; Cheng, Hu; Wilson, Landon; Barnes, Stephen; O'Donnell, Brian F.; University of Alabama Tuscaloosa; Yale University; US Department of Veterans Affairs; Veterans Health Administration (VHA); VA Connecticut Healthcare System; Indiana University of Pennsylvania; University of Alabama Birmingham; Indiana University Bloomington
    Taurine is an essential amino acid. It has been shown to be neuroprotective including protecting against the neurotoxic effects of glutamate. The goal of the current study was to examine the relationship between CB use and taurine measured in brain using magnetic resonance spectroscopy (MRS), and peripherally from a urine sample. Two experiments are presented. The first is a reanalysis of published data that examined taurine and glutamate in the dorsal anterior cingulate of a CB user group and non-user group using MRS. The second experiment, in a separate CB user group, used metabolomics analysis to measure taurine levels in urine. Because body composition has been associated with the pharmacokinetics of cannabis and taurine levels, a moderation model was examined with body composition included as the covariate. The MRS study found taurine levels were correlated with glutamate in both groups and taurine was correlated with frequency of CB use in the CB user group. The moderation model demonstrated significant effects of CB use and BMI; the interaction was marginally significant with lower BMI individuals showing a positive relationship between CB use and taurine. A similar finding was observed for the urine analysis. Both CB use and weight, as well as the interaction were significant. In this case, individuals with higher weight showed an association between CB use and taurine levels. This study shows the feasibility and potential importance of examining the relationship between taurine and CB use as it may shed light on a mechanism that underlies the neuroprotective effects of CB.