The Application Of Diffusion Tensor Imaging In Post Concussion Syndrome

Objective To study the application of the Tract-Based Spatial Statistics for the diffusion tensor imaging (DTI) in the post concussion symptoms (PCS) after mild traumatic brain injury (mTBI) , to explore the connection between fractional anisotropy (FA) , mean diffusivity(MD) and PCS.Materials and Methods 17 clinical diagnosised mTBI patients at early stage (24-48 hours after injury)were selected, whose conventional imaging scans (CT and conventional MRI) were negative as well as 17 normal controls. DTI scan was performed for all patients and controls. The Rivermead Postconcussion Symptoms Questionnaire (RPSQ) was selected for evaluating the severity of the PCS in mTBI patients. First, the DTI data was transformed from DICOM to NIfTI by the dcm2nii, also extracted the diffusion directions and the b-values as a text file. Then, used tools in the FDT (the FMRIB's Diffusion Toolbox) FSL (the FMRIB's Software Library, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Oxford University, UK) toolbox to create a single FA image from each subject, in brief: 1. Correct your original data for the effects of head movement and eddy currents using eddy_correct 2. Create a brain mask by running bet on one of the b=0 (no diffusion weighting) images 3. Fit the diffusion tensor model using dtifit. After this, voxelwise statistical analysis of the FA data was carried out using TBSS (Tract-Based Spatial Statistics), part of FSL. All subjects'FA data were aligned into a 1×1×1mm common space (MNI152 space, Montreal Neurological Institute) using the FMRIB58_FA standard-space image as the target by the nonlinear registration tool FNIRT (FMRIB's Nonlinear Registration Tool). Next, the mean FA image was created and thinned to create a mean FA skeleton, at last each subject's aligned FA data was projected onto this skeleton and the resulting 4D skeletonised FA image fed into voxelwise cross-subject statistics. For MD data, we made use of the processing of FA. First, the nonlinear-registrated MD data obtained using the nonlinear-registrated result of FA data, and then taked advantage of the process of skeletonised FA, the skeletonised MD image resulted. Voxelwise statistic and inference was performed using the last FA image by permutation-based nonparametric inference in the FSL toolbox randomise, resulting the connection of the patients and the controls, the patient and the RPSQ score. The postprocessing images were thickened and cluster strengthened, ultimatedly, produced pseudo-color pictures for visual display.Results Comparing patients with controls, FA was increased in the right superior fronto-occipital fasciculus, the latter part of the left superior fronto-occipital fasciculus, the body of the corpus callosum, the temporal part of the superior longitudinal fasciculus and the inferior longitudinal fasciculus, as well as the mesencephalon, while MD was decreased in the the latter part of the left superior fronto-occipital fasciculus, the body of the corpus callosum, the posterior limb of the right internal capsule, the mesencephalon and the pons plpontes. There was no significantly correlation between FA or MD and the PRSQ scores for the severity of PCS.Conclusions The post concussion symptoms after mTBI was significantly correlated with a reduction of white matter integrity and a manifestation of traumatic axonal injury, even in the absence of macrostructural evidence from conventional imaging techniques. The cytotoxic oedema and localized inflammatory responses prevail in the acute stage of the injury of neuraxon for the mTBI patients. The TBSS method for DTI imaging can provide objective evidence of microstructural brain injury as a pathological substrate of the PCS.