0
0

Chapter 5. Structural Imaging

Erin D. Bigler, Ph.D.
DOI: 10.1176/appi.books.9781585624201.673559

Sections

Excerpt

Structural imaging refers to various techniques that generate static views of the brain, primarily using the methods of computed tomography (CT) and magnetic resonance (MR) imaging (MRI). The brain can be readily compartmentalized into three areas: white matter (WM), gray matter (GM), and cerebral spinal fluid (CSF)–filled spaces or cavities. Brain tissue has its own vasculature and blood vessels that can be separately imaged using structural imaging techniques, but the totality of the brain's vasculature makes up a small percentage of total brain volume. Because of the water content of blood and the makeup of cerebral vessels, most of the cerebral vasculature gets classified within the spectrum of CSF or of the parenchymal tissue where a vessel is embedded using standard imaging sequences. Thus, the microvasculature within GM and WM (unless a disease state exists or a hemorrhage has occurred) becomes classified as the tissue that it is embedded in. From a structural imaging and gross anatomy perspective, this general rule of WM, GM, or CSF classification applies for any region of interest.

Your session has timed out. Please sign back in to continue.
Sign In Your Session has timed out. Please sign back in to continue.
Sign In to Access Full Content
 
Username
Password
Sign in via Athens (What is this?)
Athens is a service for single sign-on which enables access to all of an institution's subscriptions on- or off-site.
Not a subscriber?

Subscribe Now/Learn More

PsychiatryOnline subscription options offer access to the DSM-5 library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing PsychiatryOnline@psych.org or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Figure 5–1. Relative density of vessels in the visual cortex of monkeys.The left panel demonstrates the relative density of vessels in the visual cortex of monkeys. The dense vascular mesh is displayed by perfusing the tissue with barium sulfate and imaging it with synchrotron-based X-ray microtomography (courtesy B. Weber, Max Planck Institute for Biological Cybernetics). The vessel diameter is color coded. Cortical surface without pial vessels is displayed at the top, white matter (WM) at the bottom. At the left of the panel is a Nissl slice from the same area, showing the neural density for layers II through to the WM. Although the density of the vessels appears to be high in this 3-D representation, it is actually less than 3% (see section at the right; white spots are cross-sections of vessels). The average distance between the small vessels (capillaries) is about 50 'µm. This is approximately the distance that oxygen molecules travel by diffusion within the limited transit time of the blood. The dense population of neurons, synapses, and glia occupy the intervascular space, as depicted in the drawing at the top right—a hypothetical distribution of vascular and neural elements in a small section (red rectangle). The drawing in the background shows some of the typical neuronal types (e.g., red, large pyramidal cell; dark blue, inhibitory basket cells; light blue, chandelier inhibitory neurons; and gray, stellate cells) and their processes. As shown in the left panel, this is approximately the gross resolution of magnetic resonance imaging (i.e., mm3).Source. Reprinted from Logothetis NK: "What We Can Do and What We Cannot Do With fMRI." Nature 453:869–878, 2008. Copyright © 2008. Used with permission of Macmillan Publishers, Ltd.

Figure 5–2. Diffusion tensor imaging (DTI) of the corpus callosum.The left panel is a partially rotated left-frontal oblique view of a DTI sequence referred to as B0. DTI sequences have a fuzzy appearance to them and in their unprocessed state lack the anatomical clarity of other magnetic resonance imaging sequences. Major brain landmarks can still be identified, which in this view include the cingulated gyrus (A), corpus callosum (B), and fornix (C). However, from the various DTI sequences, fiber tract directionality can be determined as shown in the panel on the right, which depicts the left hemisphere tracts emanating from the entirety of the length of the corpus callosum. This image is from a normal adult control subject; note the fullness of the projecting tracts. DTI convention depicts anterior-to-posterior projecting tracts as green, vertically oriented tracts as blue, and laterally or back-and-forth projecting tracts as warm colors (red-orange). In this figure only the aggregate fiber tracts of the corpus callosum and fornix are shown, but all regions of the brain and their white matter connections can be shown with DTI.

Figure 5–3. Heterogeneity of severe traumatic brain injury (TBI) shown by computed tomography (CT) scans of six different patients with severe TBI, defined as a Glasgow Coma Scale score of <8.Highlighting the significant heterogeneity of pathological findings, CT scans represent patients with epidural hematomas (EDH), contusions and parenchymal hematomas (Contusion/Hematoma), diffuse axonal injury (DAI), subdural hematoma (SDH), subarachnoid hemorrhage and intraventricular hemorrhage (SAH/IVH), and diffuse brain swelling (Diffuse Swelling).Source. Reprinted from Saatman KE, Duhaime AC, Bullock R, et al: "Classification of Traumatic Brain Injury for Targeted Therapies." Journal of Neurotrauma 25:719–738, 2008. Used with permission of Mary Ann Liebert, Inc. Publishers.

Figure 5–4. Day-of-injury computed tomography (CT) compared with follow-up magnetic resonance imaging (MRI).The day-of-injury CT images (top row) are registered at the same level of the follow-up MR (T1 sequence) images obtained 2 years postinjury (bottom row). The CT demonstrates multiple hemorrhagic lesions scattered throughout the brain but particularly in the frontotemporal and periventricular regions. Also, note the size of the ventricle on acute imaging. Even though there is effacement of the ventricle because of trauma-induced intracranial edema, the ventricle can be used to estimate original pretrauma size and used to track changes over time. Ventricular dilation is readily apparent on the follow-up MRI, seen below each CT.

Figure 5–5. Computed tomography (CT) imaging from the same case in Figure 5–4, showing the day-of-injury hemorrhagic lesions (top row), compared with the chronic hemosiderin deposits seen on the gradient recalled echo sequence (bottom row) registered in the same orientation as the CT.

Figure 5–6. The day-of-injury (DOI) computed tomography (CT) scans from Figures 5–4 and 5–5 have been analyzed in 3-D space outlining the ventricle (aquamarine color) on the DOI (A, left) compared with the follow-up magnetic resonance imaging (MRI) on the right (B), performed 2 years postinjury.Note the obvious ventricular dilation, a sign of nonspecific parenchyma volume loss. The bottom left CT scan (C) shows the multiple hemorrhagic lesions in red as occurred on the DOI, identified by points of increased density as shown in Figures 5–4 and 5–5. Note their congregation in the frontotemporal and periventricular regions. Superimposed on the 3-D follow-up MRI (D) is the combination of white matter signal changes (shown in red) revealed on the fluid-attenuated inversion recovery sequence and the regions of hemosiderin deposition identified in the gradient recalled echo sequence (shown in yellow).

Figure 5–7. Sequential changes from traumatic brain injury.This is the same patient shown in Figures 5–4, 5–5, and 5–6. (A) Day-of-injury computed tomography (CT), but despite multiple hemorrhagic lesions the temporal horns can still be visualized. In contrast, but 2 years postinjury, prominent temporal horn dilation is evident, with associated hippocampal atrophy as shown in the T1 (B), T2 (C), and fluid-attenuated inversion-recovery (FLAIR) (D) image sequences. The FLAIR sequence (D) also demonstrates signal abnormalities in the left temporal lobe.

Figure 5–8. Detection of microhemorrhage in traumatic brain injury (TBI).This patient sustained a mild TBI, and the computed tomography on the left (A) was interpreted as within normal limits, as was the standard gradient recalled echo (GRE) sequence magnetic resonance image scan (B) also performed on the day of injury. In contrast, the susceptibility- weighted imaging sequence scan shows multiple hemorrhagic lesions (C, arrows; note, again, the frontal location of the small hemorrhagic lesions). This illustrates the greater sensitivity of the GRE in detecting hemorrhagic abnormalities associated with TBI.Source. Bigler 2008. Figure courtesy of Dr. J.V. Hunter, Texas Children'€™s Hospital.

Figure 5–9. Methods of quantitative image analysis.This patient sustained a moderate traumatic brain injury (TBI) in a motor vehicle accident. Axial maps created by statistical parametric mapping (SPM) are shown at top left. As can be readily identified on the gradient recalled echo (GRE) sequence shown at top right, there is hemosiderin in the right frontal region (arrow). The T1 anatomical scan is unimpressive with regard to obvious abnormality, but visually the interhemispheric fissure may be more prominent than what would be expected for a teenager, and likewise some of the frontal sulci are prominent. By applying quantitative analysis (lower right), frontal lobe volume is almost a standard deviation below a control sample of similarly aged individuals, supporting the clinical impression of some frontal atrophy. Voxel-based morphology (VBM) analyses clearly demonstrate that the extent of atrophic change in both white matter (WM) and gray matter (GM) concentration in and around the hemosiderin-defined shear lesion is actually considerably greater than that shown on the GRE sequence where just the hemosiderin deposit can be visualized. The VBM map superimposes the location of the WM and GM abnormalities on a standard 3-D surface magnetic resonance imaging brain reconstruction.

Figure 5–10. Diffusion tensor imaging (DTI) of the corpus callosum.The left images show DTI tractography (upper left) of the corpus callosum superimposed on the T1 image of a traumatic brain injury patient who suffered a severe injury. Note, in comparison with the age-matched individual on the right without a history of brain injury, that the tractography demonstrates a significant reduction in the number of aggregate white matter tracts that can be identified coursing across the corpus callosum and projecting into the left hemisphere. The lower images show the midsagittal plane of the DTI color maps. The arrow in the lower left panel points to the corpus callosum highlighted in red, because DTI is sensitive to the directionality of the fiber tracts; red denotes lateral back-and-forth direction, whereas green reflects anterior-posterior and blue indicates vertical. The arrow in the upper left points to a corpus callosum tract coming out of the forceps minor projection system and is shown here to give the reader orientation for interpreting Figure 5–11.

Figure 5–11. White matter damage in traumatic brain injury (TBI).(A) The top 3-D image shows a cutaway with the left hemisphere diffusion tensor imaging (DTI) tractography findings from a child who sustained a severe TBI. Note the thinning out of tracts, similar to that observed in the case depicted in Figure 5–10. The arrow points to the location of the forceps minor region of white matter projection in the frontal lobe where the mild TBI case presented below shows discontinuity of the tracts in this region. Whereas the disruption of white matter tracts may be substantial in moderate to severe TBI, DTI findings when present in mild TBI are quite subtle and typically much less dramatic. (B) Fluid-attenuated inversion recovery (FLAIR) scan, fractional anisotropy (FA) map, and fiber tracking in a 49-year-old patient with TBI who was imaged 16 months after the initial trauma. The FLAIR image shows no abnormalities (top left). After analysis of the color-coded FA map (top middle), a region with reduced FA was identified in the WM of the left frontal lobe. This region of interest (ROI), illustrated in the top right T2-weighted image, included forceps minor and fronto-temporo-occipital fibers (bottom left), superior oblique view; the ROI is red and located centrally; the fibers are superimposed on an axial T2-weighted scan. At the level of the ROI, the respective fibers are discontinuous (arrow, bottom right; the ROI is left out in this image).Source. Panel (B) images reprinted from Rutgers DR, Toulgoat F, Cazejust J, et al: "White Matter Abnormalities in Mild Traumatic Brain Injury: A Diffusion Tensor Imaging Study." American Journal of Neuroradiology 29:514–519, 2008. Used with permission of the American Society of Neuroradiology.

Figure 5–12. Magnetic resonance spectroscopy of traumatic brain injury.(A) Position of the spectroscopic imaging voxel of interest (VOI), as viewed in the axial and sagittal planes. On the axial image, the outlined sections inside the VOI depict voxels typically selected for the four regions of interest, and the pattern surrounding the VOI is the area covered by the eight multiple regional saturation technique pulses for saturating lipid signals from the scalp. (B) Average spectra obtained from the left frontal lobe of a patient versus that of a control subject demonstrate a decrease in N-acetyl aspartate (NAA) after traumatic brain injury. Cho = choline; Cre = creatine; ppm = parts per million.Source. Reprinted from Hunter JV, Thornton RJ, Wang ZJ, et al: "Late Proton MR Spectroscopy in Children After Traumatic Brain Injury: Correlation With Cognitive Outcomes." American Journal of Neuroradiology 26:482–488, 2005. Used with permission of the American Society of Neuroradiology.

Figure 5–13. Lesion tracings are projected on selected axial slices of a template brain derived from 12 healthy control subjects.The color scale indicates degree of lesion overlap across patients (max = 5). Lower right sagittal image indicates slice location of the three axial images, with the most ventral axial image appearing in the upper left, the middle axial image in the upper right, and the most dorsal axial image in the lower left.Source. Reprinted from Levine B, Kovacevic N, Nica EI, et al: "The Toronto Traumatic Brain Injury Study: Injury Severity and Quantified MRI." Neurology 70:771–778, 2008. Used with permission.

Figure 5–14. Loss of white matter tracts in traumatic brain injury (TBI).(Top left) Severe TBI in a child with extensive frontal encephalomalacia. (Top right) Similarly aged and demographically matched child with normal scan. These anatomical scans do not permit a visualization of the extent of the loss of connectivity that occurs from damage. Note the dramatic differences in the complexity of the connectivity emanating from similar frontal regions when comparing a damaged frontal lobe with that of a typically developing child. Diffusion tensor imaging tractography projections are superimposed on an axial T1 anatomical magnetic resonance image in a 12-year-old female who had sustained a severe TBI (Glasgow Coma Score = 5) as a result of falling backward off the back of a pickup truck, striking the back of her head on the pavement but sustaining significant contracoup frontal contusions. The same color schema applies as discussed previously. These images show that the frontal injury results in marked thinning and loss of frontal projecting tracts emanating from the frontal polar region of the brain. This illustration dramatically shows the loss of brain interconnectiveness as a consequence of focal damage distal to the endpoint of where fiber tracts project (see Oni et al. 2010 for additional information).

Figure 5–15. Regions of significant cortical loss in pediatric traumatic brain injury compared with brains of typically developing children, reflecting adjustments made for age and gender.The P-value color scale indicates group differences ranging from dark blue (P <0.005) to light blue (P <0.00001). Results are displayed on a customized averaged pediatric subject. (A) Lateral view (with surfaces inflated to reveal the extent of significant regions) showing group differences bilaterally for temporal and frontal lobe (P <0.005). (B) Lateral view (now shown as pial surfaces) indicating the same significant regions as displayed in A. (C) Midsagittal pial surfaces showing significant cortical regional differences.

Figure 5–16. Cortical thinning related to impaired prospective memory in traumatic brain injury.Areas of cortical thinning that were associated with event-based prospective memory (EB-PM) performance in pediatric traumatic brain injury are shown in sagittal, inferior, medial, and coronal views. As in Figure 5–15, the P-value color scale indicates group differences ranging from dark blue (P <0.005) to light blue (P <0.00001). Bilateral middle and inferior frontal, middle and inferior temporal, and parahippocampal and cingulate gyri thicknesses were found to be significantly related to EB-PM performance. Regions of significant brain-behavior relation appear to be spatially larger in the left hemisphere. Involvement of the temporal lobes and parahippocampal gyri highlights the inherent role of retrieval processes in supporting PM functioning.
Table Reference Number
Table 5–1. Diagnostic categories of abnormalities visualized on CT scanning

References

Ashwal S, Babikian T, Gardner-Nichols J, et al: Susceptibility-weighted imaging and proton magnetic resonance spectroscopy in assessment of outcome after pediatric traumatic brain injury. Arch Phys Med Rehabil 87 (12 suppl 2):S50–S58, 2006
 
Babikian T, Freier MC, Ashwal S, et al: MR spectroscopy: predicting long-term neuropsychological outcome following pediatric TBI. J Magn Reson Imaging 24:801–811, 2006
[PubMed]
 
Bazarian JJ, Zhong J, Blyth B, et al: Diffusion tensor imaging detects clinically important axonal damage after mild traumatic brain injury: a pilot study. J Neurotrauma 24:1447–1459, 2007
[PubMed]
 
Belanger HG, Vanderploeg RD, Curtiss G, et al: Recent neuroimaging techniques in mild traumatic brain injury. J Neuropsychiatry Clin Neurosci 19:5–20, 2007
[PubMed]
 
Bendlin BB, Ries ML, Lazar M, et al: Longitudinal changes in patients with traumatic brain injury assessed with diffusion-tensor and volumetric imaging. Neuroimage 42:503–514, 2008
[PubMed]
 
Bigler ED: Structural imaging, in Textbook of Traumatic Brain Injury. Edited by Silver JM, McAllister TW, Yudofsky SC. Washington, DC, American Psychiatric Publishing, 2005, pp 79–105
 
Bigler ED: Anterior and middle cranial fossa in traumatic brain injury: relevant neuroanatomy and neuropathology in the study of neuropsychological outcome. Neuropsychology 21:515–531, 2007
[PubMed]
 
Bigler ED: Neuropsychology and clinical neuroscience of persistent post-concussive syndrome. J Int Neuropsychol Soc 14:1–22, 2008
[PubMed]
 
Bigler ED, Blatter DD, Anderson CV, et al: Hippocampal volume in normal aging and traumatic brain injury. Am J Neuroradiol 18:11–23, 1997
[PubMed]
 
Bigler ED, Ryser DK, Gandhi P, et al: Day-of-injury computerized tomography, rehabilitation status, and development of cerebral atrophy in persons with traumatic brain injury. Am J Phys Med Rehabil 85:793–806, 2006
[PubMed]
 
Bosnell R, Giorgio A, Johansen-Berg H: Imaging white matter diffusion changes with development and recovery from brain injury. Dev Neurorehabil 11:174–186, 2008
[PubMed]
 
Brewer JB, Magda S, Airriess C, et al: Fully automated quantification of regional brain volumes for improved detection of focal atrophy in Alzheimer disease. Am J Neuroradiol 30:578–580, 2009
[PubMed]
 
Chu EA, Wilde EA, Hunter JV, et al: Voxel-based analysis of diffusion tensor imaging in mild traumatic brain injury in adolescents. Am J Neuroradiol 31:340–346, 2010
[PubMed]
 
Cohen BA, Inglese M, Rusinek H, et al: Proton MR spectroscopy and MRI-volumetry in mild traumatic brain injury. Am J Neuroradiol 28:907–913, 2007
[PubMed]
 
Coles JP: Imaging after brain injury. Br J Anaesth 99:49–60, 2007
[PubMed]
 
Douglas RJ, Martin KA: Neuronal circuits of the neocortex. Ann Rev Neurosci 27:419–451, 2004
[PubMed]
 
Douglas RJ, Martin KA: Mapping the matrix: the ways of neocortex. Neuron 56:226–238, 2007
[PubMed]
 
Fabbri A, Servadei F, Marchesini G, et al: Early predictors of unfavourable outcome in subjects with moderate head injury in the emergency department. J Neurol Neurosurg Psychiatry 79:567–573, 2008
[PubMed]
 
Gale SD, Baxter L, Roundy N, et al: Traumatic brain injury and grey matter concentration: a preliminary voxel based morphometry study. J Neurol Neurosurg Psychiatry 76:984–988, 2005
[PubMed]
 
Gallagher CN, Hutchinson PJ, Pickard JD: Neuroimaging in trauma. Curr Opin Neurol 20:403–409, 2007
[PubMed]
 
Gasparovic C, Yeo R, Mannell M, et al: Neurometabolite concentrations in gray and white matter in mild traumatic brain injury: a 1H magnetic resonance spectroscopy study. J Neurotrauma 26:1635–1643, 2009
[PubMed]
 
Ghosh A, Wilde EA, Hunter JV, et al: The relation between Glasgow Coma Scale score and later cerebral atrophy in paediatric traumatic brain injury. Brain Inj 23:228–233, 2009
[PubMed]
 
Guleria S, Gupta RK, Saksena S, et al: Retrograde Wallerian degeneration of cranial corticospinal tracts in cervical spinal cord injury patients using diffusion tensor imaging. J Neurosci Res 86:2271–2280, 2008
[PubMed]
 
Guye M, Bartolomei F, Ranjeva JP: Imaging structural and functional connectivity: towards a unified definition of human brain organization? Curr Opin Neurol 21:393–403, 2008
[PubMed]
 
Hagmann P, Kurant M, Gigandet X, et al: Mapping human whole-brain structural networks with diffusion MRI. PLoS ONE 2(7):e597, 2007
 
Hagmann P, Cammoun L, Gigandet X, et al: Mapping the structural core of human cerebral cortex. PLoS Biol 6(7):e159, 2008
 
Hahnel S, Stippich C, Weber I, et al: Prevalence of cerebral microhemorrhages in amateur boxers as detected by 3T MR imaging. Am J Neuroradiol 29:388–391, 2008
[PubMed]
 
Henry-Feugeas MC, Azouvi P, Fontaine A, et al: MRI analysis of brain atrophy after severe closed-head injury: relation to clinical status. Brain Inj 14:597–604, 2000
[PubMed]
 
Hillary FG, Liu WC, Genova HM, et al: Examining lactate in severe TBI using proton magnetic resonance spectroscopy. Brain Inj 21:981–991, 2007
[PubMed]
 
Honey CJ, Sporns O: Dynamical consequences of lesions in cortical networks. Hum Brain Mapp 29:802–809, 2008
[PubMed]
 
Hou DJ, Tong KA, Ashwal S, et al: Diffusion-weighted magnetic resonance imaging improves outcome prediction in adult traumatic brain injury. J Neurotrauma 24:1558–1569, 2007
[PubMed]
 
Hunter JV, Thornton RJ, Wang ZJ, et al: Late proton MR spectroscopy in children after traumatic brain injury: correlation with cognitive outcomes. Am J Neuroradiol 26:482–488, 2005
[PubMed]
 
Hurley RA, McGowan JC, Arfanakis K, et al: Traumatic axonal injury: novel insights into evolution and identification. J Neuropsychiatry Clin Neurosci 16:1–7, 2004
[PubMed]
 
Jones NR, Blumbergs PC, Brown CJ, et al: Correlation of postmortem MRI and CT appearances with neuropathology in brain trauma: a comparison of two methods. J Clin Neurosci 5:73–79, 1998
[PubMed]
 
Katz DI, Alexander MP: Traumatic brain injury: predicting course of recovery and outcome for patients admitted to rehabilitation. Arch Neurol 51:661–670, 1994
[PubMed]
 
Khan AR, Wang L, Beg MF: FreeSurfer-initiated fully automated subcortical brain segmentation in MRI using large deformation diffeomorphic metric mapping. Neuroimage 41:735–746, 2008
[PubMed]
 
Kim J, Avants B, Patel S, et al: Structural consequences of diffuse traumatic brain injury: a large deformation tensor-based morphometry study. Neuroimage 39:1014–1026, 2008
[PubMed]
 
Kraus MF, Susmaras T, Caughlin BP, et al: White matter integrity and cognition in chronic traumatic brain injury: a diffusion tensor imaging study. Brain 130:2508–2519, 2007
[PubMed]
 
Kumar A, Cook IA: White matter injury, neural connectivity and the pathophysiology of psychiatric disorders. Dev Neurosci 24:255–261, 2002
[PubMed]
 
Kumar R, Gupta RK, Husain M, et al: Comparative evaluation of corpus callosum DTI metrics in acute mild and moderate traumatic brain injury: its correlation with neuropsychometric tests. Brain Inj 23:675–685, 2009
[PubMed]
 
Le TH, Gean AD: Neuroimaging of traumatic brain injury. Mt Sinai J Med 76:145–162, 2009
[PubMed]
 
Lee H, Wintermark M, Gean AD, et al: Focal lesions in acute mild traumatic brain injury and neurocognitive outcome: CT versus 3T MRI. J Neurotrauma 25:1049–1056, 2008
[PubMed]
 
Levin HS, Wilde EA, Chu Z, et al: Diffusion tensor imaging in relation to cognitive and functional outcome of traumatic brain injury in children. J Head Trauma Rehabil 23:197–208, 2008
[PubMed]
 
Levine B, Fujiwara E, O'Connor C, et al: In vivo characterization of traumatic brain injury neuropathology with structural and functional neuroimaging. J Neurotrauma 23:1396–1411, 2006
[PubMed]
 
Levine B, Kovacevic N, Nica EI, et al: The Toronto traumatic brain injury study: injury severity and quantified MRI. Neurology 70:771–778, 2008
[PubMed]
 
Lipton ML, Gulko E, Zimmerman ME, et al: Diffusion-tensor imaging implicates prefrontal axonal injury in executive function impairment following very mild traumatic brain injury. Radiology 252:816–824, 2009
[PubMed]
 
Logothetis NK: What we can do and what we cannot do with fMRI. Nature 453:869–878, 2008
[PubMed]
 
Maas AI, Hukkelhoven CW, Marshall LF, et al: Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery 57:1173–1182, 2005
[PubMed]
 
Maas AI, Stocchetti N, Bullock R: Moderate and severe traumatic brain injury in adults. Lancet Neurol 7:728–741, 2008
[PubMed]
 
MacKenzie JD, Siddiqi F, Babb JS, et al: Brain atrophy in mild or moderate traumatic brain injury: a longitudinal quantitative analysis. Am J Neuroradiol 23:1509–1515, 2002
[PubMed]
 
Mamere AE, Saraiva LA, Matos AL, et al: Evaluation of delayed neuronal and axonal damage secondary to moderate and severe traumatic brain injury using quantitative MR imaging techniques. Am J Neuroradiol 30:947–952, 2009
[PubMed]
 
Marino S, Zei E, Battaglini M, et al: Acute metabolic brain changes following traumatic brain injury and their relevance to clinical severity and outcome. J Neurol Neurosurg Psychiatry 78:501–507, 2007
[PubMed]
 
Marquez de la Plata C, Ardelean A, Koovakkattu D, et al: Magnetic resonance imaging of diffuse axonal injury: quantitative assessment of white matter lesion volume. J Neurotrauma 24:591–598, 2007
 
Marshall LF, Marshall SB, Klauber MR, et al: The diagnosis of head injury requires a classification based on computed axial tomography. J Neurotrauma 9 (suppl 1):S287–S292, 1992
 
Maruichi K, Kuroda S, Chiba Y, et al: Graded model of diffuse axonal injury for studying head injury-induced cognitive dysfunction in rats. Neuropathology 29:132–139, 2009
[PubMed]
 
Mayer AR, Mannell MV, Ling J, et al: Auditory orienting and inhibition of return in mild traumatic brain injury: a FMRI study. Hum Brain Mapp 30:4152–4166, 2009
[PubMed]
 
McCauley SR, Wilde EA, Merkley TL, et al: Patterns of cortical thinning in relation to event-based prospective memory performance three months after moderate to severe traumatic brain injury in children. Dev Neuropsychol 35:333–351, 2010
[PubMed]
 
Merkley TL, Bigler ED, Wilde EA, et al: Diffuse changes in cortical thickness in pediatric moderate-to-severe traumatic brain injury. J Neurotrauma 25:1343–1345, 2008
[PubMed]
 
Miles A: On the mechanism of brain injuries. Brain 15:153–189, 1892
 
Miles L, Grossman RI, Johnson G, et al: Short-term DTI predictors of cognitive dysfunction in mild traumatic brain injury. Brain Inj 22:115–122, 2008
[PubMed]
 
Mukherjee P, Berman JI, Chung SW, et al: Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. Am J Neuroradiol 29:632–641, 2008a
 
Mukherjee P, Chung SW, Berman JI, et al: Diffusion tensor MR imaging and fiber tractography: technical considerations. Am J Neuroradiol 29:843–852, 2008b
 
Murray GD, Butcher I, McHugh GS, et al: Multivariable prognostic analysis in traumatic brain injury: results from the IMPACT study. J Neurotrauma 24:329–337, 2007
[PubMed]
 
Niogi SN, Mukherjee P, Ghajar J, et al: Extent of microstructural white matter injury in postconcussive syndrome correlates with impaired cognitive reaction time: a 3T diffusion tensor imaging study of mild traumatic brain injury. Am J Neuroradiol 29:967–973, 2008a
 
Niogi SN, Mukherjee P, Ghajar J, et al: Structural dissociation of attentional control and memory in adults with and without mild traumatic brain injury. Brain 131:3209–3221, 2008b
 
Oni MB, Wilde EA, Bigler ED, et al: Diffusion tensor imaging analysis of frontal lobes in pediatric traumatic brain injury. J Child Neurol 2010 [Epub ahead of print]
 
Orrison WW, Hanson EH, Alamo T, et al: Traumatic brain injury: a review and high-field MRI findings in 100 unarmed combatants using a literature-based checklist approach. J Neurotrauma 26:689–701, 2009
[PubMed]
 
Pascual JM, Solivera J, Prieto R, et al: Time course of early metabolic changes following diffuse traumatic brain injury in rats as detected by (1)H NMR spectroscopy. J Neurotrauma 24:944–959, 2007
[PubMed]
 
Povlishock JT, Katz DI: Update of neuropathology and neurological recovery after traumatic brain injury. J Head Trauma Rehabil 20:76–94, 2005
[PubMed]
 
Reddick WE, Laningham FH, Glass JO, et al: Quantitative morphologic evaluation of magnetic resonance imaging during and after treatment of childhood leukemia. Neuroradiology 49:889–904, 2007
[PubMed]
 
Rigotti DJ, Inglese M, Gonen O: Whole-brain N-acetylaspartate as a surrogate marker of neuronal damage in diffuse neurologic disorders. Am J Neuroradiol 28:1843–1849, 2007
[PubMed]
 
Rutgers DR, Fillard P, Paradot G, et al: Diffusion tensor imaging characteristics of the corpus callosum in mild, moderate, and severe traumatic brain injury. Am J Neuroradiol 29:1730–1735, 2008a
 
Rutgers DR, Toulgoat F, Cazejust J, et al: White matter abnormalities in mild traumatic brain injury: a diffusion tensor imaging study. Am J Neuroradiol 29:514–519, 2008b
 
Saatman KE, Duhaime AC, Bullock R, et al: Classification of traumatic brain injury for targeted therapies. J Neurotrauma 25:719–738, 2008
[PubMed]
 
Scheid R, Walther K, Guthke T, et al: Cognitive sequelae of diffuse axonal injury. Arch Neurol 63:418–424, 2006
[PubMed]
 
Scheid R, Ott DV, Roth H, et al: Comparative magnetic resonance imaging at 1.5 and 3 Tesla for the evaluation of traumatic microbleeds. J Neurotrauma 24:1811–1816, 2007
[PubMed]
 
Schooler C, Caplan LJ, Revell AJ, et al: Brain lesion and memory functioning: short-term memory deficit is independent of lesion location. Psychon Bull Rev 15:521–527, 2008
[PubMed]
 
Sherer M, Struchen MA, Yablon SA, et al: Comparison of indices of traumatic brain injury severity: Glasgow Coma Scale, length of coma and post-traumatic amnesia. J Neurol Neurosurg Psychiatry 79:678–685, 2008
[PubMed]
 
Signoretti S, Marmarou A, Aygok GA, et al: Assessment of mitochondrial impairment in traumatic brain injury using high-resolution proton magnetic resonance spectroscopy. J Neurosurg 108:42–52, 2008
[PubMed]
 
Silver JM, McAllister TW, Yudofsky SC (eds): Textbook of Traumatic Brain Injury, 2nd Edition. Washington, DC, American Psychiatric Publishing, 2005
 
Singh M, Jeong J, Hwang D, et al: Novel diffusion tensor imaging methodology to detect and quantify injured regions and affected brain pathways in traumatic brain injury. Magn Reson Imaging 28:22–40, 2010
[PubMed]
 
Steyerberg EW, Mushkudiani N, Perel P, et al: Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 5(8):e165, 2008
 
Sullivan EV, Pfefferbaum A: Neuroradiological characterization of normal adult ageing. Br J Radiol 80:S99–S108, 2007
 
Sundgren PC, Dong Q, Gomez-Hassan D, et al: Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 46:339–350, 2004
[PubMed]
 
Tollard E, Galanaud D, Perlbarg V, et al: Experience of diffusion tensor imaging and 1H spectroscopy for outcome prediction in severe traumatic brain injury: preliminary results. Crit Care Med 37:1448–1455, 2009
[PubMed]
 
Tong KA, Ashwal S, Obenaus A, et al: Susceptibility-weighted MR imaging: a review of clinical applications in children. Am J Neuroradiol 29:9–17, 2008
[PubMed]
 
Toyama Y, Kobayashi T, Nishiyama Y, et al: CT for acute stage of closed head injury. Radiat Med 23:309–316, 2005
[PubMed]
 
Turkheimer E, Cullum CM, Hubler DW, et al: Quantifying cortical atrophy. J Neurol Neurosurg Psychiatry 47:1314–1318, 1984
[PubMed]
 
van Baalen B, Odding E, Maas AI, et al: Traumatic brain injury: classification of initial severity and determination of functional outcome. Disabil Rehabil 25:9–18, 2003
 
Wang JY, Bakhadirov K, Devous MD Sr, et al: Diffusion tensor tractography of traumatic diffuse axonal injury. Arch Neurol 65:619–626, 2008
[PubMed]
 
Wilde EA, Bigler ED, Haider JM, et al: Vulnerability of the anterior commissure in moderate to severe pediatric traumatic brain injury. J Child Neurol 21:769–776, 2006a
 
Wilde EA, Chu Z, Bigler ED, et al: Diffusion tensor imaging in the corpus callosum in children after moderate to severe traumatic brain injury. J Neurotrauma 23:1412–1426, 2006b
 
Wilde EA, Bigler ED, Hunter JV, et al: Hippocampus, amygdala, and basal ganglia morphometrics in children after moderate-to-severe traumatic brain injury. Dev Med Child Neurol 49:294–299, 2007
[PubMed]
 
Wilde EA, McCauley SR, Hunter JV, et al: Diffusion tensor imaging of acute mild traumatic brain injury in adolescents. Neurology 70:948–955, 2008
[PubMed]
 
Yeo RA, Phillips JP, Jung RE, et al: Magnetic resonance spectroscopy detects brain injury and predicts cognitive functioning in children with brain injuries. J Neurotrauma 23:1427–1435, 2006
[PubMed]
 
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Related Content
Articles
Books
The American Psychiatric Publishing Textbook of Psychiatry, 5th Edition > Chapter 2.  >
Dulcan's Textbook of Child and Adolescent Psychiatry > Chapter 10.  >
The American Psychiatric Publishing Textbook of Psychopharmacology, 4th Edition > Chapter 10.  >
Textbook of Traumatic Brain Injury, 2nd Edition > Chapter 2.  >
Textbook of Traumatic Brain Injury, 2nd Edition > Chapter 4.  >
Topic Collections
Psychiatric News
PubMed Articles
 
  • Print
  • PDF
  • E-mail
  • Chapter Alerts
  • Get Citation