Zouridakis, George2018-03-022018-03-02December 22016-12December 2http://hdl.handle.net/10657/2771In this study we investigated whether Diffusion Tensor Imaging (DTI) could be used to assess recovery in patients with mild traumatic brain injury (mTBI). Thirteen acute mTBI patients 18-50 years of age and seven age- and sex-matched controls with no head injury were recruited from the emergency department of Huntington Memorial Hospital in Pasadena, CA. Images were acquired on three different visits, two weeks and four weeks, respectively, after the first recording, using a 3.0 T. Image distortions, resulting from susceptibility-induced and by eddy current-induced off-resonance fields, were corrected using routines from the software package FSL. An affine linear registration routine part of FSL was also used to align the 32 images to the reference image. For each DTI dataset, diffusion Fractional Anisotropy (FA), Mean Diffusivity (MD) or Apparent Diffusion Coefficient (ADC), and probabilistic tractography were estimated using FSL and the software package MedInria, with an FA threshold of 200, a minimum length for the detected fibers of 20 mm, and volume sampling every 5 voxels. To perform a quantitative analysis across the two groups, we first used the Johns Hopkins University tractography atlas to define 20 regions of interest (ROI), and the scans from the control subjects to create a reference database that included the mean and standard deviation values in each ROI. Then we computed z-scores for each subject’s data and compared the groups using MANOVA with p value set at 0.05, corrected for multiple comparisons, considering group and visit as the independent variables.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).TractographyDiffusionAssessing Recovery of Mild Traumatic Brain Injury Patients Using Diffusion Tensor Imaging2018-03-02Thesisborn digital