Severity of traumatic brain injury (TBI) positively correlates with the risk of post-traumatic epilepsy (PTE). Studies on post-traumatic epileptogenesis would greatly benefit from markers that at acute phase would reliably predict the extent and severity of histologic brain damage caused by TBI in individual subjects. Currently in experimental models, severity of TBI is determined by the pressure of applied load that does not directly reflect the extent of inflicted brain injury, mortality within experimental population, or impairment in behavioral tests that are laborious to perform. We aimed to compare MRI markers measured at acute post-injury phase to previously used indicators of injury severity in the ability to predict the extent of histologically determined post-traumatic tissue damage. We used lateral fluid-percussion injury model in rat that is a clinically relevant model of closed head injury in humans, and results in PTE in severe cases. Rats (48 injured, 12 controls) were divided into moderate (mTBI) and severe (sTBI) groups according to impact strength. MRI data (T2, T2*, lesion volume) were acquired 3 days post-injury. Motor deficits were analysed using neuroscore (NS) and beam balance (BB) tests 2 and 3 days post-injury, respectively. Histological evaluation of lesion volume (Fluoro-Jade B) was used as the reference outcome measure, and was performed 2 weeks after TBI. From MRI parameters studied, quantitative T2 values of cortical lesion not only correlated with histologic lesion volume (P<0.001, r=0.6, N=34), as well as NS (P<0.01, r=-0.5, N=34) and BB (P<0.01, r=-0.5, N=34) results, but also successfully differentiated animals with mTBI from those with sTBI 70.6 +/- 6.2 6.2 ms vs. 75.9 +/- 2.6 ms, P<0.001). Quantitative T2 of the lesion early after TBI can serve as an indicator of the severity of post-traumatic cortical damage and neuro-motor impairment, and has a potential as a clinical marker for identification of individuals with elevated risk of PTE.
"Currently, quantitative semi-automatic MRI analysis of moderate to severe experimental TBI has been used to investigate tissue pathology (Immonen et al., 2009; Irimia et al., 2011; Kharatishvili et al., 2009). In these experimental models, manually defined regions of interest revealed positive correlations between T2 relaxation values and poor histological and behavioral outcomes (Immonen et al., 2009; Kharatishvili et al., 2009). However, little work has been done using models of mTBI. "
[Show abstract][Hide abstract] ABSTRACT: Mild traumatic brain injury (mTBI) has become an increasing public health concern as subsequent injuries can exacerbate existing neuropathology and result in neurological deficits. This study investigated the temporal development of cortical lesions using magnetic resonance imaging (MRI) to assess two mTBIs delivered to opposite cortical hemispheres. The controlled cortical impact model was used to produce an initial mTBI on the right cortex followed by a second injury induced on the left cortex at 3 (rmTBI 3d) or 7 (rmTBI 7d) days later. Histogram analysis was combined with a novel semi-automated computational approach to perform a voxel-wise examination of extravascular blood and edema volumes within the lesion. Examination of lesion volume 1d post last injury revealed increased tissue abnormalities within rmTBI 7d animals compared to other groups, particularly at the site of the second impact. Histogram analysis of lesion T2 values suggested increased edematous tissue within the rmTBI 3d group and elevated blood deposition in the rm TBI 7d animals. Further quantification of lesion composition for blood and edema containing voxels supported our histogram findings, with increased edema at the site of second impact in rmTBI 3d animals and elevated blood deposition in the rmTBI 7d group at the site of the first injury. Histological measurements revealed spatial overlap of regions containing blood deposition and microglial activation within the cortices of all animals. In conclusion, our findings suggest that there is a window of tissue vulnerability where a second distant mTBI, induced 7d after an initial injury, exacerbates tissue abnormalities consistent with hemorrhagic progression.
"The drastic increase in blast-induced traumatic brain injuries among both military (nearly 50% of the Iraq war injured returnees) and civilian casualties – mainly due to terrorists explosive devices – have generated important research efforts in the last few years  . Impact-and/or acceleration-induced brain traumatic injuries have already been the focus of many cellular and macroscopical studies through in vivo        , ex vivo  , in vitro     , medical postanalysis     and modeling approaches              . However, the specific effects of a blast – a pressure wave of finite amplitude generated by a rapid release of energy  – on the brain is still widely unknown. "
[Show abstract][Hide abstract] ABSTRACT: Traumatic brain injuries have recently been put under the spotlight as one of the most important causes of accidental brain dysfunctions. Significant experimental and modeling efforts are thus underway to study the associated biological, mechanical and physical mechanisms. In the field of cell mechanics, progress is also being made at the experimental and modeling levels to better characterize many of the cell functions, including differentiation, growth, migration and death. The work presented here aims to bridge both efforts by proposing a continuum model of a neuronal cell submitted to blast loading. In this approach, the cytoplasm, nucleus and membrane (plus cortex) are differentiated in a representative cell geometry, and different suitable material constitutive models are chosen for each one. The material parameters are calibrated against published experimental work on cell nanoindentation at multiple rates. The final cell model is ultimately subjected to blast loading within a complete computational framework of fluid-structure interaction. The results are compared to the nanoindentation simulation, and the specific effects of the blast wave on the pressure and shear levels at the interfaces are identified. As a conclusion, the presented model successfully captures some of the intrinsic intracellular phenomena occurring during the cellular deformation under blast loading that potentially lead to cell damage. It suggests, more particularly, that the localization of damage at the nucleus membrane is similar to what has already been observed at the overall cell membrane. This degree of damage is additionally predicted to be worsened by a longer blast positive phase duration. In conclusion, the proposed model ultimately provides a new three-dimensional computational tool to evaluate intracellular damage during blast loading.
"In experimental models of TBI, T2 maps are used to identify and quantify regions of both edema (high T2 values) and extravascular blood (low T2 values). MRI T2 maps have been used for manual quantitative analysis of TBI . However, edema, particularly in mTBI, can be subtle and transient further making identification of putative injury difficult. "
[Show abstract][Hide abstract] ABSTRACT: Mild traumatic brain injury (mTBI) is difficult to detect as the current tools are qualitative, which can lead to poor diagnosis and treatment. The low contrast appearance of mTBI abnormalities on magnetic resonance (MR) images makes quantification problematic for image processing and analysis techniques. To overcome these difficulties, an algorithm is proposed that takes advantage of subject information and texture information from MR images. A contextual model is developed to simulate the progression of the disease using multiple inputs, such as the time post-injury and the location of injury. Textural features are used along with feature selection for a single MR modality. Results from a probabilistic support vector machine using textural features are fused with the contextual model to obtain a robust estimation of abnormal tissue. A novel rat temporal dataset demonstrates the ability of our approach to outperform other state of the art approaches.
Image Processing (ICIP), 2012 19th IEEE International Conference on; 01/2012
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