60 research outputs found

    Multimodal surface-based morphometry reveals diffuse cortical atrophy in traumatic brain injury.

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Patients with traumatic brain injury (TBI) often present with significant cognitive deficits without corresponding evidence of cortical damage on neuroradiological examinations. One explanation for this puzzling observation is that the diffuse cortical abnormalities that characterize TBI are difficult to detect with standard imaging procedures. Here we investigated a patient with severe TBI-related cognitive impairments whose scan was interpreted as normal by a board-certified radiologist in order to determine if quantitative neuroimaging could detect cortical abnormalities not evident with standard neuroimaging procedures.</p> <p>Methods</p> <p>Cortical abnormalities were quantified using multimodal surfaced-based morphometry (MSBM) that statistically combined information from high-resolution structural MRI and diffusion tensor imaging (DTI). Normal values of cortical anatomy and cortical and pericortical DTI properties were quantified in a population of 43 healthy control subjects. Corresponding measures from the patient were obtained in two independent imaging sessions. These data were quantified using both the average values for each lobe and the measurements from each point on the cortical surface. The results were statistically analyzed as z-scores from the mean with a p < 0.05 criterion, corrected for multiple comparisons. False positive rates were verified by comparing the data from each control subject with the data from the remaining control population using identical statistical procedures.</p> <p>Results</p> <p>The TBI patient showed significant regional abnormalities in cortical thickness, gray matter diffusivity and pericortical white matter integrity that replicated across imaging sessions. Consistent with the patient's impaired performance on neuropsychological tests of executive function, cortical abnormalities were most pronounced in the frontal lobes.</p> <p>Conclusions</p> <p>MSBM is a promising tool for detecting subtle cortical abnormalities with high sensitivity and selectivity. MSBM may be particularly useful in evaluating cortical structure in TBI and other neurological conditions that produce diffuse abnormalities in both cortical structure and tissue properties.</p

    Structural Modifications of the Brain in Acclimatization to High-Altitude

    Get PDF
    Adaptive changes in respiratory and cardiovascular responses at high altitude (HA) have been well clarified. However, the central mechanisms underlying HA acclimatization remain unclear. Using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) with fractional anisotropy (FA) calculation, we investigated 28 Han immigrant residents (17–22 yr) born and raised at HA of 2616–4200 m in Qinghai-Tibetan Plateau for at least 17 years and who currently attended college at sea-level (SL). Their family migrated from SL to HA 2–3 generations ago and has resided at HA ever since. Control subjects were matched SL residents. HA residents (vs. SL) showed decreased grey matter volume in the bilateral anterior insula, right anterior cingulate cortex, bilateral prefrontal cortex, left precentral cortex, and right lingual cortex. HA residents (vs. SL) had significantly higher FA mainly in the bilateral anterior limb of internal capsule, bilateral superior and inferior longitudinal fasciculus, corpus callosum, bilateral superior corona radiata, bilateral anterior external capsule, right posterior cingulum, and right corticospinal tract. Higher FA values in those regions were associated with decreased or unchanged radial diffusivity coinciding with no change of longitudinal diffusivity in HA vs. SL group. Conversely, HA residents had lower FA in the left optic radiation and left superior longitudinal fasciculus. Our data demonstrates that HA acclimatization is associated with brain structural modifications, including the loss of regional cortical grey matter accompanied by changes in the white matter, which may underlie the physiological adaptation of residents at HA

    Delayed mGluR5 activation limits neuroinflammation and neurodegeneration after traumatic brain injury

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Traumatic brain injury initiates biochemical processes that lead to secondary neurodegeneration. Imaging studies suggest that tissue loss may continue for months or years after traumatic brain injury in association with chronic microglial activation. Recently we found that metabotropic glutamate receptor 5 (mGluR5) activation by (<it>RS</it>)-2-chloro-5-hydroxyphenylglycine (CHPG) decreases microglial activation and release of associated pro-inflammatory factors <it>in vitro</it>, which is mediated in part through inhibition of reduced nicotinamide adenine dinucleotide phosphate (NADPH) oxidase. Here we examined whether delayed CHPG administration reduces chronic neuroinflammation and associated neurodegeneration after experimental traumatic brain injury in mice.</p> <p>Methods</p> <p>One month after controlled cortical impact traumatic brain injury, C57Bl/6 mice were randomly assigned to treatment with single dose intracerebroventricular CHPG, vehicle or CHPG plus a selective mGluR5 antagonist, 3-((2-Methyl-4-thiazolyl)ethynyl)pyridine. Lesion volume, white matter tract integrity and neurological recovery were assessed over the following three months.</p> <p>Results</p> <p>Traumatic brain injury resulted in mGluR5 expression in reactive microglia of the cortex and hippocampus at one month post-injury. Delayed CHPG treatment reduced expression of reactive microglia expressing NADPH oxidase subunits; decreased hippocampal neuronal loss; limited lesion progression, as measured by repeated T2-weighted magnetic resonance imaging (at one, two and three months) and white matter loss, as measured by high field <it>ex vivo </it>diffusion tensor imaging at four months; and significantly improved motor and cognitive recovery in comparison to the other treatment groups.</p> <p>Conclusion</p> <p>Markedly delayed, single dose treatment with CHPG significantly improves functional recovery and limits lesion progression after experimental traumatic brain injury, likely in part through actions at mGluR5 receptors that modulate neuroinflammation.</p

    Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state.

    Get PDF
    RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.Published versio

    Mapping Connectivity Damage in the Case of Phineas Gage

    Get PDF
    White matter (WM) mapping of the human brain using neuroimaging techniques has gained considerable interest in the neuroscience community. Using diffusion weighted (DWI) and magnetic resonance imaging (MRI), WM fiber pathways between brain regions may be systematically assessed to make inferences concerning their role in normal brain function, influence on behavior, as well as concerning the consequences of network-level brain damage. In this paper, we investigate the detailed connectomics in a noted example of severe traumatic brain injury (TBI) which has proved important to and controversial in the history of neuroscience. We model the WM damage in the notable case of Phineas P. Gage, in whom a “tamping iron” was accidentally shot through his skull and brain, resulting in profound behavioral changes. The specific effects of this injury on Mr. Gage's WM connectivity have not previously been considered in detail. Using computed tomography (CT) image data of the Gage skull in conjunction with modern anatomical MRI and diffusion imaging data obtained in contemporary right handed male subjects (aged 25–36), we computationally simulate the passage of the iron through the skull on the basis of reported and observed skull fiducial landmarks and assess the extent of cortical gray matter (GM) and WM damage. Specifically, we find that while considerable damage was, indeed, localized to the left frontal cortex, the impact on measures of network connectedness between directly affected and other brain areas was profound, widespread, and a probable contributor to both the reported acute as well as long-term behavioral changes. Yet, while significantly affecting several likely network hubs, damage to Mr. Gage's WM network may not have been more severe than expected from that of a similarly sized “average” brain lesion. These results provide new insight into the remarkable brain injury experienced by this noteworthy patient

    Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition

    Full text link
    Objective: To study the relationship between thalamic glucose metabolism and neurological outcome after severe traumatic brain injury (TBI). Methods: Forty-nine patients with severe and closed TBI and 10 healthy control subjects with 18F-FDG PET were studied. Patients were divided into three groups: MCS&VS group (n ¼ 17), patients in a vegetative or a minimally conscious state; In-PTA group (n ¼ 12), patients in a state of post-traumatic amnesia (PTA); and Out-PTA group (n ¼ 20), patients who had emerged from PTA. SPM5 software implemented in MATLAB 7 was used to determine the quantitative differences between patients and controls. FDG-PET images were spatially normalized and an automated thalamic ROI mask was generated. Group differences were analysed with two sample voxel-wise t-tests. Results: Thalamic hypometabolism was the most prominent in patients with low consciousness (MCS&VS group) and the thalamic hypometabolism in the In-PTA group was more prominent than that in the Out-PTA group. Healthy control subjects showed the greatest thalamic metabolism. These differences in metabolism were more pronounced in the internal regions of the thalamus. Conclusions: The results confirm the vulnerability of the thalamus to suffer the effect of the dynamic forces generated during a TBI. Patients with thalamic hypometabolism could represent a sub-set of subjects that are highly vulnerable to neurological disability after TBI.Lull Noguera, N.; Noé, E.; Lull Noguera, JJ.; Garcia Panach, J.; Chirivella, J.; Ferri, J.; López-Aznar, D.... (2010). Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition. Brain Injury. 24(9):1098-1107. doi:10.3109/02699052.2010.494592S10981107249Gallagher, C. N., Hutchinson, P. J., & Pickard, J. D. (2007). Neuroimaging in trauma. Current Opinion in Neurology, 20(4), 403-409. doi:10.1097/wco.0b013e32821b987bWoischneck, D., Klein, S., Rei�berg, S., D�hring, W., Peters, B., & Firsching, R. (2001). Classification of Severe Head Injury Based on Magnetic Resonance Imaging. Acta Neurochirurgica, 143(3), 263-271. doi:10.1007/s007010170106Grados, M. A. (2001). Depth of lesion model in children and adolescents with moderate to severe traumatic brain injury: use of SPGR MRI to predict severity and outcome. Journal of Neurology, Neurosurgery & Psychiatry, 70(3), 350-358. doi:10.1136/jnnp.70.3.350Meythaler, J. M., Peduzzi, J. D., Eleftheriou, E., & Novack, T. A. (2001). Current concepts: Diffuse axonal injury–associated traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 82(10), 1461-1471. doi:10.1053/apmr.2001.25137Scheid, R., Walther, K., Guthke, T., Preul, C., & von Cramon, D. Y. (2006). Cognitive Sequelae of Diffuse Axonal Injury. Archives of Neurology, 63(3), 418. doi:10.1001/archneur.63.3.418Brandstack, N., Kurki, T., Tenovuo, O., & Isoniemi, H. (2006). MR imaging of head trauma: Visibility of contusions and other intraparenchymal injuries in early and late stage. Brain Injury, 20(4), 409-416. doi:10.1080/02699050500487951Xu, J., Rasmussen, I.-A., Lagopoulos, J., & Håberg, A. (2007). Diffuse Axonal Injury in Severe Traumatic Brain Injury Visualized Using High-Resolution Diffusion Tensor Imaging. Journal of Neurotrauma, 24(5), 753-765. doi:10.1089/neu.2006.0208Levine, B., Fujiwara, E., O’connor, C., Richard, N., Kovacevic, N., Mandic, M., … Black, S. E. (2006). In Vivo Characterization of Traumatic Brain Injury Neuropathology with Structural and Functional Neuroimaging. Journal of Neurotrauma, 23(10), 1396-1411. doi:10.1089/neu.2006.23.1396Metting, Z., Rödiger, L. A., De Keyser, J., & van der Naalt, J. (2007). Structural and functional neuroimaging in mild-to-moderate head injury. The Lancet Neurology, 6(8), 699-710. doi:10.1016/s1474-4422(07)70191-6Nakayama, N. (2006). Relationship between regional cerebral metabolism and consciousness disturbance in traumatic diffuse brain injury without large focal lesions: an FDG-PET study with statistical parametric mapping analysis. Journal of Neurology, Neurosurgery & Psychiatry, 77(7), 856-862. doi:10.1136/jnnp.2005.080523Nakayama, N. (2006). Evidence for white matter disruption in traumatic brain injury without macroscopic lesions. Journal of Neurology, Neurosurgery & Psychiatry, 77(7), 850-855. doi:10.1136/jnnp.2005.077875O’Leary, D. D. M., Schlaggar, B. L., & Tuttle, R. (1994). Specification of Neocortical Areas and Thalamocortical Connections. Annual Review of Neuroscience, 17(1), 419-439. doi:10.1146/annurev.ne.17.030194.002223Mitelman, S. A., Byne, W., Kemether, E. M., Newmark, R. E., Hazlett, E. A., Haznedar, M. M., & Buchsbaum, M. S. (2006). Metabolic thalamocortical correlations during a verbal learning task and their comparison with correlations among regional volumes. Brain Research, 1114(1), 125-137. doi:10.1016/j.brainres.2006.07.043Laureys, S., Faymonville, M., Luxen, A., Lamy, M., Franck, G., & Maquet, P. (2000). Restoration of thalamocortical connectivity after recovery from persistent vegetative state. The Lancet, 355(9217), 1790-1791. doi:10.1016/s0140-6736(00)02271-6Laureys, S., Goldman, S., Phillips, C., Van Bogaert, P., Aerts, J., Luxen, A., … Maquet, P. (1999). Impaired Effective Cortical Connectivity in Vegetative State: Preliminary Investigation Using PET. NeuroImage, 9(4), 377-382. doi:10.1006/nimg.1998.0414Laureys, S., Owen, A. M., & Schiff, N. D. (2004). Brain function in coma, vegetative state, and related disorders. The Lancet Neurology, 3(9), 537-546. doi:10.1016/s1474-4422(04)00852-xGuye, M., Bartolomei, F., & Ranjeva, J.-P. (2008). Imaging structural and functional connectivity: towards a unified definition of human brain organization? Current Opinion in Neurology, 24(4), 393-403. doi:10.1097/wco.0b013e3283065cfbPrice, C. J., & Friston, K. J. (2002). Functional Imaging Studies of Neuropsychological Patients: Applications and Limitations. Neurocase, 8(5), 345-354. doi:10.1076/neur.8.4.345.16186Kim, J., Avants, B., Patel, S., Whyte, J., Coslett, B. H., Pluta, J., … Gee, J. C. (2008). Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study. NeuroImage, 39(3), 1014-1026. doi:10.1016/j.neuroimage.2007.10.005Maxwell, W. L., MacKinnon, M. A., Smith, D. H., McIntosh, T. K., & Graham, D. I. (2006). Thalamic Nuclei After Human Blunt Head Injury. Journal of Neuropathology & Experimental Neurology, 65(5), 478-488. doi:10.1097/01.jnen.0000229241.28619.75SIDAROS, A., SKIMMINGE, A., LIPTROT, M., SIDAROS, K., ENGBERG, A., HERNING, M., … ROSTRUP, E. (2009). Long-term global and regional brain volume changes following severe traumatic brain injury: A longitudinal study with clinical correlates. NeuroImage, 44(1), 1-8. doi:10.1016/j.neuroimage.2008.08.030Ashburner, J., & Friston, K. J. (2000). Voxel-Based Morphometry—The Methods. NeuroImage, 11(6), 805-821. doi:10.1006/nimg.2000.0582Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001). A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains. NeuroImage, 14(1), 21-36. doi:10.1006/nimg.2001.0786Giacino, J. T., Ashwal, S., Childs, N., Cranford, R., Jennett, B., Katz, D. I., … Zasler, N. D. (2002). The minimally conscious state: Definition and diagnostic criteria. Neurology, 58(3), 349-353. doi:10.1212/wnl.58.3.349Gispert, J. ., Pascau, J., Reig, S., Martínez-Lázaro, R., Molina, V., García-Barreno, P., & Desco, M. (2003). Influence of the normalization template on the outcome of statistical parametric mapping of PET scans. NeuroImage, 19(3), 601-612. doi:10.1016/s1053-8119(03)00072-7Ashburner, J., & Friston, K. J. (1999). Nonlinear spatial normalization using basis functions. Human Brain Mapping, 7(4), 254-266. doi:10.1002/(sici)1097-0193(1999)7:43.0.co;2-gTzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., … Joliot, M. (2002). Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. NeuroImage, 15(1), 273-289. doi:10.1006/nimg.2001.0978Genovese, C. R., Lazar, N. A., & Nichols, T. (2002). Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate. NeuroImage, 15(4), 870-878. doi:10.1006/nimg.2001.1037LAUREYS, S., LEMAIRE, C., MAQUET, P., PHILLIPS, C., & FRANCK, G. (1999). Cerebral metabolism during vegetative state and after recovery to consciousness. Journal of Neurology, Neurosurgery & Psychiatry, 67(1), 121-122. doi:10.1136/jnnp.67.1.121Tommasino, C., Grana, C., Lucignani, G., Torri, G., & Fazio, F. (1995). Regional Cerebral Metabolism of Glucose in Comatose and Vegetative State Patients. Journal of Neurosurgical Anesthesiology, 7(2), 109-116. doi:10.1097/00008506-199504000-00006ANDERSON, C. V., WOOD, D.-M. G., BIGLER, E. D., & BLATTER, D. D. (1996). Lesion Volume, Injury Severity, and Thalamic Integrity following Head Injury. Journal of Neurotrauma, 13(2), 59-65. doi:10.1089/neu.1996.13.59Ge, Y., Patel, M. B., Chen, Q., Grossman, E. J., Zhang, K., Miles, L., … Grossman, R. I. (2009). Assessment of thalamic perfusion in patients with mild traumatic brain injury by true FISP arterial spin labelling MR imaging at 3T. Brain Injury, 23(7-8), 666-674. doi:10.1080/02699050903014899Uzan, M. (2003). Thalamic proton magnetic resonance spectroscopy in vegetative state induced by traumatic brain injury. Journal of Neurology, Neurosurgery & Psychiatry, 74(1), 33-38. doi:10.1136/jnnp.74.1.33OMMAYA, A. K., & GENNARELLI, T. A. (1974). CEREBRAL CONCUSSION AND TRAUMATIC UNCONSCIOUSNESS. Brain, 97(1), 633-654. doi:10.1093/brain/97.1.633Giacino, J., & Whyte, J. (2005). The Vegetative and Minimally Conscious States. Journal of Head Trauma Rehabilitation, 20(1), 30-50. doi:10.1097/00001199-200501000-00005Zeman, A. (2001). Consciousness. Brain, 124(7), 1263-1289. doi:10.1093/brain/124.7.1263Kinney, H. C., Korein, J., Panigrahy, A., Dikkes, P., & Goode, R. (1994). Neuropathological Findings in the Brain of Karen Ann Quinlan -- The Role of the Thalamus in the Persistent Vegetative State. New England Journal of Medicine, 330(21), 1469-1475. doi:10.1056/nejm199405263302101Saeeduddin Ahmed, Rex Bierley, Java. (2000). Post-traumatic amnesia after closed head injury: a review of the literature and some suggestions for further research. Brain Injury, 14(9), 765-780. doi:10.1080/026990500421886Wilson, J. T., Hadley, D. M., Wiedmann, K. D., & Teasdale, G. M. (1995). Neuropsychological consequences of two patterns of brain damage shown by MRI in survivors of severe head injury. Journal of Neurology, Neurosurgery & Psychiatry, 59(3), 328-331. doi:10.1136/jnnp.59.3.328Wilson, J. T., Teasdale, G. M., Hadley, D. M., Wiedmann, K. D., & Lang, D. (1994). Post-traumatic amnesia: still a valuable yardstick. Journal of Neurology, Neurosurgery & Psychiatry, 57(2), 198-201. doi:10.1136/jnnp.57.2.198Fearing, M. A., Bigler, E. D., Wilde, E. A., Johnson, J. L., Hunter, J. V., Xiaoqi Li, … Levin, H. S. (2008). Morphometric MRI Findings in the Thalamus and Brainstem in Children After Moderate to Severe Traumatic Brain Injury. Journal of Child Neurology, 23(7), 729-737. doi:10.1177/0883073808314159Little, D. M., Kraus, M. F., Joseph, J., Geary, E. K., Susmaras, T., Zhou, X. J., … Gorelick, P. B. (2010). Thalamic integrity underlies executive dysfunction in traumatic brain injury. Neurology, 74(7), 558-564. doi:10.1212/wnl.0b013e3181cff5d
    corecore