Microstructural Tissue Changes in a Rat Model of Mild Traumatic Brain Injury

Abstract

Our study investigates the potential of diffusion MRI (dMRI), including diffusion tensor imaging (DTI), fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI), to detect microstructural tissue abnormalities in rats after mild traumatic brain injury (mTBI). The brains of sham-operated and mTBI rats 35 days after lateral fluid percussion injury were imaged ex vivo in a 11.7-T scanner. Voxel-based analyses of DTI-, fixel- and NODDI-based metrics detected extensive tissue changes in directly affected brain areas close to the primary injury, and more importantly, also in distal areas connected to primary injury and indirectly affected by the secondary injury mechanisms. Histology revealed ongoing axonal abnormalities and inflammation, 35 days after the injury, in the brain areas highlighted in the group analyses. Fractional anisotropy (FA), fiber density (FD) and fiber density and fiber bundle cross-section (FDC) showed similar pattern of significant areas throughout the brain; however, FA showed more significant voxels in gray matter areas, while FD and FDC in white matter areas, and orientation dispersion index (ODI) in areas most damage based on histology. Region-of-interest (ROI)-based analyses on dMRI maps and histology in selected brain regions revealed that the changes in MRI parameters could be attributed to both alterations in myelinated fiber bundles and increased cellularity. This study demonstrates that the combination of dMRI methods can provide a more complete insight into the microstructural alterations in white and gray matter after mTBI, which may aid diagnosis and prognosis following a mild brain injury.

Advanced diffusion imaging to track progression in Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy

“…A previous study that conducted NODDI and Fixel based analysis in a rat model of traumatic brain injury also showed a lack of agreement between the modalities. ( Chary et al, 2021 ). It is possible that alternate multi-shell scan parameters would have better outcomes for the NODDI analysis.…”

A multiscale tissue assessment in a rat model of mild traumatic brain injury

“…When utilizing in vivo DTI at 3 days after the injury, we found significant differences in DTI parameters in the external capsule, somatosensory cortex, corpus callosum, and cingulum, but not in the internal capsule ( 32 ). On day 28, in vivo and on day 35 ex vivo, the differences between sham-operated and mTBI animals were still evident in the external capsule, corpus callosum and cingulum, but no differences could be detected in the somatosensory cortex or the internal capsule ( 32 , 33 ). Similarly, other investigators have reported significant differences in the corpus callosum, cingulum, external capsule, and the somatosensory cortex in the acute phase of mTBI in vivo ( 25 , 51–54 ) as well as differences in the corpus callosum and cingulum in the subacute phase both in vivo ( 29–31 ) and ex vivo ( 27 ).…”

“…DTI parameters from the corpus callosum and cingulum in mTBI animals exhibited moderate deviations from the DTI values in sham-operated animals, while parameters from the internal capsule did not show any apparent changes in DTI values between these animal groups. The animals selected for these analyses were representative of larger groups included in our previous studies ( 32 , 33 ). When utilizing in vivo DTI at 3 days after the injury, we found significant differences in DTI parameters in the external capsule, somatosensory cortex, corpus callosum, and cingulum, but not in the internal capsule ( 32 ).…”

“…DTI changes have been associated with axonal damage in white matter ( 27 , 32 , 33 ) and with astro- and microgliosis in white and grey matter after mTBI ( 30 , 31 , 51 , 55 ). The correlation between DTI and the tissue parameters extracted from advanced histological analyses, such as ST, automated cell counting, or morphological skeleton-based approaches, can improve the characterization of DTI in terms of tissue microstructure ( 31–33 , 49 ).…”

“…Then, a bias field correction was applied to remove spatial intensity inhomogeneities ( 38 ); motion and eddy current correction was performed using Advanced Normalization Tools software ( 39 ). All DTI maps were then created as previously described ( 33 ).…”