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WINDOWSTOTHEBRAIN   |    
Traumatic Axonal Injury: Atlas of Major Pathways
Katherine H. Taber, Ph.D.; Robin A. Hurley, M.D.
The Journal of Neuropsychiatry and Clinical Neurosciences 2007;19:iv-104.
View Author and Article Information

Drs. Taber and Hurley are affiliated with the Veterans Affairs Mid Atlantic Mental Illness Research, Education, and Clinical Center, and the Mental Health Service Line, Salisbury Veterans Affairs Medical Center, Salisbury, North Carolina. Dr. Taber is also affiliated with the Division of Biomedical Sciences, Virginia VA School of Osteopathic Medicine, Blacksburg, Virginia, and the Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas. Dr. Hurley is also affiliated with the Departments of Psychiatry and Radiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, and the Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas. Address correspondence to Dr. Hurley, Hefner VA Medical Center, 1601 Brenner Avenue, Salisbury, NC 28144; Robin.Hurley@med.va.gov (e-mail).

There is increasing evidence that combat-related traumatic brain injuries are a frequent occurrence. Recent studies detailing the most common injuries have found that approximately one-half involved the head or neck.9,10 The great majority of injuries were due to explosions. Several studies from the Defense and Veterans Brain Injury Center (DVBIC) of soldiers returning from Afghanistan and Iraq document the occurrence of traumatic brain injury (TBI) in many soldiers.1114 Between January 2003 and February 2005, 59% of returning soldiers treated at Walter Reed Army Medical Center who had been near an explosion while deployed had suffered a traumatic brain injury (44% mild, 56% moderate-severe).11 Common postconcussive symptoms included headache (47%), irritability/aggression (45%), and difficulty with memory (46%) and attention/concentration (41%).12 A study of 596 active duty soldiers (all serving full-time at regular duty stations in the United States) found that 96 (16.1%) reported an injury while deployed, for which the symptoms (e.g., alternation in or loss of consciousness) were consistent with TBI.13 This is similar to an earlier study of active duty soldiers, which found that 13.5% of nonparatroopers reported sustaining a TBI while in the Army.15 The vast majority of these were mild TBIs, as indicated by either no or only brief loss of consciousness. In most cases, these less severe injuries would not have required medical evacuation.14 It is well known that civilian mild TBI is underrecognized by both medical personnel and patients, resulting in significant underreporting.16 There is evidence for a similar situation in the military and concern that combat-related mild TBI may often be unrecognized by both medical personnel and soldiers.13,15,17

Identification of TBI, particularly mild TBI, is often quite challenging. The most common type of injury, and the most likely injury to occur in mild TBI, is traumatic axonal injury (also called diffuse axonal injury).18 While magnetic resonance imaging (MRI) is more sensitive than computed tomography (CT) in detecting this type of brain injury, even MRI is often negative.1823 In addition, some areas of injury may become less visible with time.21 In such cases, MRI in the subacute and chronic stages is less likely to be positive than if acquired immediately following injury. There is increasing evidence that functional imaging (e.g., cerebral blood flow, cerebral metabolic rate) may be considerably more sensitive to the effects of TBI than structural imaging.2327

Even small areas of injury within the white matter may have devastating consequences. Knowledge of the locations of major tracts and the brain areas they interconnect is thus critical for understanding clinical symptoms in the context of TBI. White matter tracts of particular importance in neuropsychiatry include those interconnecting areas of cortex (e.g., corpus callosum, association fiber tracts), those connecting areas of cortex to subcortical structures critical for cognitive/emotional functions (e.g., thalamic radiations) and those interconnecting these subcortical areas (e.g., fornix).2,28Tables 1 to 3 summarize the classic functional anatomy of the major white matter pathways important for cognitive and emotional functioning (Figure 1). They are based on recent studies delineating the anatomy of white matter in humans, primarily using diffusion tensor imaging.1,2,68,2933

Intriguing results from sophisticated radioisotope tract-tracing studies in nonhuman primates suggests that there may be significant errors in the classic view of cerebral white matter.34,35 For example, this work has delineated three different components (in both location and areas connected) of the superior longitudinal fasciculus. A fourth pathway, which this research group considered to be the arcuate fasciculus, was also identified. A recent diffusion tensor imaging study36 supports the existence of all four of these pathways in humans. Methods for delineating connections within the intact brain are undergoing rapid development and refinement. It is extremely likely that over the next decade, our understanding of the pathways within the brain that are important for cognitive and emotional functioning will change dramatically.

Care must be taken in applying this summary of functional anatomy to individual patients, as studies comparing pathway topography between subjects have shown considerable normal variability (Figure 2).68 This is parallel to the normal variation in size, shape, and location of Brodmann’s areas (Figure 2).35 This known phenomenon adds a distinct level of uncertainty in predicting individual functional deficits following a brain injury. It should also be kept in mind that in many places multiple pathways travel close together, making it likely that a TBI will affect more than one and produce complex symptom clusters. These symptoms may not become evident for extended periods of time. Atlases and other visual external memory aids can assist clinicians in rapid memory recall of functional circuits and areas for review on patient imaging examinations.

TABLE 1. Commissures Connecting Cortical Areas in Left and Right Hemispheres
TABLE 2. Long Tracts Connecting Cortical Areas Within Each Hemisphere
TABLE 3. Pathways Connecting Cortical With Subcortical Areas Within Each Hemisphere
 
Figure 1. The structures involved in the dorsolateral (pink), anterior cingulate (green), and orbitofrontal (blue) prefrontal-subcortical circuits are color-coded onto the left side of axial magnetic resonance images (A—E). The approximate extent and locations of the classic major long cortical association tracts are color-coded onto the right side of axial magnetic resonance images (A—E) and summarized in cartoon form on a lateral view of the brain (Cover).
 
Figure 2. Variability (or probability) maps created by transforming the functional anatomy of individual brains into a common anatomic space indicate considerable normal variation.
On the right is a variability map for primary visual cortex (Brodmann’s area 17), with the number of individuals (out of 10) which overlapped. On the left is a probability map (30% threshold) of the corpus callosum, color-coded by cortical area of fiber origin. Note the large areas of overlap, indicating differences in functional anatomy across individuals.
.
Mori S, Wakana S, Nagae-Poetscher LM, et al: MRI Atlas of Human White Matter. New York, Elsevier, 2005
 
.
Aralasmak A, Ulmer JL, Kocak M, et al: Association, commissural, and projection pathways and their functional deficit reported in literature. J Comput Assist Tomogr 2006; 30:695—715
 
.
Amunts K, Malikovic A, Mohlberg H, et al: Brodmann’s areas 17 and 18 brought into sterotaxic space: where and how variable? Neuroimage 2000; 11:66—84
 
.
Amunts K, Weiss PH, Mohlberg H, et al: Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—the roles of Brodmann areas 44 and 45. Neuroimage 2004; 22:42—56
 
.
Uylings HB, Rajkowska G, Sanz-Arigita E, et al: Consequences of large interindividual variability for human brain atlases: converging macroscopical imaging and microscopical neuroanatomy. Anat Embryol 2005; 210:431
 
.
Burgel U, Amunts K, Hoemke L, et al: White matter fiber tracts of the human brain: three-dimensional mapping at microscopic resolution, topography and intersubject variability. Neuroimage 2006; 29:1092—1105
 
.
Hofer S, Frahm J: Topography of the human corpus callosum revisited—comprehensive fiber tractography using diffusion tensor MRI. Neuroimage 2006; 32:989—994
 
.
Zarei M, Johansen-Berg H, Smith S, et al: Functional anatomy of interhemispheric cortical connections in the human brain. J Anat 2006; 209:311—320
 
.
Murray CK, Reynolds JC, Schroeder JM, et al: Spectrum of care provided at an Echelon II medical unit during Operation Iraqi Freedom. Mil Med 2005; 170:516—520
 
.
Gondusky JS, Reiter MP: Protecting military convoys in Iraq: an examination of battle injuries sustained by a mechanized battalion during Operation Iraqi Freedom, II. Mil Med 2005; 170:546—549
 
.
Okie S: Traumatic brain injury in the war zone. N Engl J Med 2005; 352:2043—2047
 
.
Warden DL, Ryan LM, Helmick KM, et al: War neurotrauma: the Defense and Veterans Brain Injury Center (DVBIC) experience at Walter Reed Army Medical Center (WRAMC). J Neurotrauma 2005; 22:1178
 
.
Schwab KA, Baker G, Ivins BJ, et al: The Brief Traumatic Brain Injury Screen (BTBIS): investigating the validity of a self-report instrument for detecting traumatic brain injury (TBI) in troops returning from deployment in Afghanistan and Iraq. Neurology 2006; 66:A235
 
.
Warden D: Military TBI during the Iraq and Afghanistan wars. J Head Trauma Rehabil 2006; 21:398—402
 
.
Ivins BJ, Schwab KA, Warden D, et al: Traumatic brain injury in U.S. Army paratroopers: prevalence and character. J Trauma 2003; 55:617—621
 
.
Langlois JA, Rutland-Brown W, Wald MM: The epidemiology and impact of traumatic brain injury: a brief overview. J Head Trauma Rehabil 2006; 21:375—378
 
.
Drake AI, McDonald EC, Magnus NE, et al: Utility of Glasgow Coma Scale—Extended in symptom prediction following mild traumatic brain injury. Brain Inj 2006; 20:469—475
 
.
Hurley RA, McGowan JC, Arfanakis K, et al: Traumatic axonal injury: novel insights into evolution and identification. J Neuropsychiatry Clin Neurosci 2004; 16:1—7
 
.
Gutierrez-Cadavid JE: Imaging of head trauma, in Imaging of the Nervous System. Edited by Latchaw RE, Kucharczyk J, Moseley ME. Philadelphia, Elsevier Mosby, 2005, pp 869—904
 
.
Le TH, Gean AD: Imaging of head trauma. Semin Roentgenol 2006; 41:177—189
 
.
Brandstack N, Kurki T, Tenovuo O, et al: MR imaging of head trauma: visibility of contusions and other intraparenchymal injuries in early and late stage. Brain Inj 2006; 20:409—416
 
.
Kurca E, Sivak S, Kucera P: Impaired cognitive functions in mild traumatic brain injury patients with normal and pathologic MRI. Neuroradiology 2006; Jun 20 [e-pub ahead of print]
 
.
Shin YB, Kim SJ, Kin IJ, et al: Voxel-based statistical analysis of cerebral blood flow using technetium-99m ECD brain SPECT in patients with traumatic brain injury: group and individual analyses. Brain Inj 2006; 20:661—667
 
.
Barkai G, Goshen E, Tzila Zwas S, et al: Acetazolamide-enhanced neuroSPECT scan reveals functional impairment after minimal traumatic brain injury not otherwise discernible. Psychiatry Res 2004; 132:279—283
 
.
Gowda NK, Agrawal D, Bal C, et al: Technetium tc-99m ethyl cysteinate dimer brain single-photon emission CT in mild traumatic brain injury: a prospective study. AJNR Am J Neuroradiol 2006; 27:447—451
 
.
Shiga T, Ikoma K, Katoh C, et al: Loss of neuronal integrity: a cause of hypometabolism in patients with traumatic brain injury without MRI abnormality in the chronic stage. Eur J Nucl Med Mol Imaging 2006; 33:817—822
 
.
Pavel D, Jobe T, Devore-Best S, et al: Viewing the functional consequences of traumatic brain injury by using brain SPECT. Brain Cogn 2006; 60:211—213
 
.
Tekin S, Cummings JL: Frontal-subcortical neuronal circuits and clinical neuropsychiatry: an update. J Psychosom Res 2002; 53:647—654
 
.
Catani M, Howard RJ, Pajevic S, et al: Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Neuroimage 2002; 17:77—94
 
.
Jellison BJ, Field AS, Medow J, et al: Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am J Neuroradiol 2004; 25:356—369
 
.
Kier EL, Staib LH, Davis LM, et al: MR imaging of the temporal stem: anatomic dissection tractography of the uncinate fasciculus, inferior occipitofrontal fasciculus, and Meyer’s loop of the optic radiation. AJNR Am J Neuroradiol 2004; 25:677—691
 
.
O’Donnell LJ, Kubicki M, Shenton ME, et al: A method for clustering white matter fiber tracts. AJNR Am J Neuroradiol 2006; 27:1032—1036
 
.
Heiervang E, Behrens TE, Mackay CE, et al: Between session reproducibility and between-subject variability of diffusion MR and tractography measures. Neuroimage 2006; 33:867—877
 
.
Schmahmann JD, Pandya DN: Fiber Pathways of the Brain. New York, Oxford University Press, 2006
 
.
Schmahmann JD, Pandya DN, Wang R, et al: Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 2007 (e-pub ahead of print)
 
.
Makris N, Kennedy DN, McInerney S, et al: Segmentation of subcomponents within the superior longitudinal fascicle in humans: a quantitative, in vivo, DT-MRI study. Cerebral Cortex 2005; 15:854-869
 
.
Zarei M, Johansen-Berg H, Jenkinson M, et al: Two-dimensional population map of cortical connections in the human internal capsule. J Magn Reson Imaging 2007; 25:48—54
 
.
Nolte J: The Human Brain. St. Louis, Mosby, 2002
 

Figure 1. The structures involved in the dorsolateral (pink), anterior cingulate (green), and orbitofrontal (blue) prefrontal-subcortical circuits are color-coded onto the left side of axial magnetic resonance images (A—E). The approximate extent and locations of the classic major long cortical association tracts are color-coded onto the right side of axial magnetic resonance images (A—E) and summarized in cartoon form on a lateral view of the brain (Cover).

Figure 2. Variability (or probability) maps created by transforming the functional anatomy of individual brains into a common anatomic space indicate considerable normal variation. On the right is a variability map for primary visual cortex (Brodmann’s area 17), with the number of individuals (out of 10) which overlapped. On the left is a probability map (30% threshold) of the corpus callosum, color-coded by cortical area of fiber origin. Note the large areas of overlap, indicating differences in functional anatomy across individuals.
TABLE 1. Commissures Connecting Cortical Areas in Left and Right Hemispheres
TABLE 2. Long Tracts Connecting Cortical Areas Within Each Hemisphere
TABLE 3. Pathways Connecting Cortical With Subcortical Areas Within Each Hemisphere
+

References

.
Mori S, Wakana S, Nagae-Poetscher LM, et al: MRI Atlas of Human White Matter. New York, Elsevier, 2005
 
.
Aralasmak A, Ulmer JL, Kocak M, et al: Association, commissural, and projection pathways and their functional deficit reported in literature. J Comput Assist Tomogr 2006; 30:695—715
 
.
Amunts K, Malikovic A, Mohlberg H, et al: Brodmann’s areas 17 and 18 brought into sterotaxic space: where and how variable? Neuroimage 2000; 11:66—84
 
.
Amunts K, Weiss PH, Mohlberg H, et al: Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—the roles of Brodmann areas 44 and 45. Neuroimage 2004; 22:42—56
 
.
Uylings HB, Rajkowska G, Sanz-Arigita E, et al: Consequences of large interindividual variability for human brain atlases: converging macroscopical imaging and microscopical neuroanatomy. Anat Embryol 2005; 210:431
 
.
Burgel U, Amunts K, Hoemke L, et al: White matter fiber tracts of the human brain: three-dimensional mapping at microscopic resolution, topography and intersubject variability. Neuroimage 2006; 29:1092—1105
 
.
Hofer S, Frahm J: Topography of the human corpus callosum revisited—comprehensive fiber tractography using diffusion tensor MRI. Neuroimage 2006; 32:989—994
 
.
Zarei M, Johansen-Berg H, Smith S, et al: Functional anatomy of interhemispheric cortical connections in the human brain. J Anat 2006; 209:311—320
 
.
Murray CK, Reynolds JC, Schroeder JM, et al: Spectrum of care provided at an Echelon II medical unit during Operation Iraqi Freedom. Mil Med 2005; 170:516—520
 
.
Gondusky JS, Reiter MP: Protecting military convoys in Iraq: an examination of battle injuries sustained by a mechanized battalion during Operation Iraqi Freedom, II. Mil Med 2005; 170:546—549
 
.
Okie S: Traumatic brain injury in the war zone. N Engl J Med 2005; 352:2043—2047
 
.
Warden DL, Ryan LM, Helmick KM, et al: War neurotrauma: the Defense and Veterans Brain Injury Center (DVBIC) experience at Walter Reed Army Medical Center (WRAMC). J Neurotrauma 2005; 22:1178
 
.
Schwab KA, Baker G, Ivins BJ, et al: The Brief Traumatic Brain Injury Screen (BTBIS): investigating the validity of a self-report instrument for detecting traumatic brain injury (TBI) in troops returning from deployment in Afghanistan and Iraq. Neurology 2006; 66:A235
 
.
Warden D: Military TBI during the Iraq and Afghanistan wars. J Head Trauma Rehabil 2006; 21:398—402
 
.
Ivins BJ, Schwab KA, Warden D, et al: Traumatic brain injury in U.S. Army paratroopers: prevalence and character. J Trauma 2003; 55:617—621
 
.
Langlois JA, Rutland-Brown W, Wald MM: The epidemiology and impact of traumatic brain injury: a brief overview. J Head Trauma Rehabil 2006; 21:375—378
 
.
Drake AI, McDonald EC, Magnus NE, et al: Utility of Glasgow Coma Scale—Extended in symptom prediction following mild traumatic brain injury. Brain Inj 2006; 20:469—475
 
.
Hurley RA, McGowan JC, Arfanakis K, et al: Traumatic axonal injury: novel insights into evolution and identification. J Neuropsychiatry Clin Neurosci 2004; 16:1—7
 
.
Gutierrez-Cadavid JE: Imaging of head trauma, in Imaging of the Nervous System. Edited by Latchaw RE, Kucharczyk J, Moseley ME. Philadelphia, Elsevier Mosby, 2005, pp 869—904
 
.
Le TH, Gean AD: Imaging of head trauma. Semin Roentgenol 2006; 41:177—189
 
.
Brandstack N, Kurki T, Tenovuo O, et al: MR imaging of head trauma: visibility of contusions and other intraparenchymal injuries in early and late stage. Brain Inj 2006; 20:409—416
 
.
Kurca E, Sivak S, Kucera P: Impaired cognitive functions in mild traumatic brain injury patients with normal and pathologic MRI. Neuroradiology 2006; Jun 20 [e-pub ahead of print]
 
.
Shin YB, Kim SJ, Kin IJ, et al: Voxel-based statistical analysis of cerebral blood flow using technetium-99m ECD brain SPECT in patients with traumatic brain injury: group and individual analyses. Brain Inj 2006; 20:661—667
 
.
Barkai G, Goshen E, Tzila Zwas S, et al: Acetazolamide-enhanced neuroSPECT scan reveals functional impairment after minimal traumatic brain injury not otherwise discernible. Psychiatry Res 2004; 132:279—283
 
.
Gowda NK, Agrawal D, Bal C, et al: Technetium tc-99m ethyl cysteinate dimer brain single-photon emission CT in mild traumatic brain injury: a prospective study. AJNR Am J Neuroradiol 2006; 27:447—451
 
.
Shiga T, Ikoma K, Katoh C, et al: Loss of neuronal integrity: a cause of hypometabolism in patients with traumatic brain injury without MRI abnormality in the chronic stage. Eur J Nucl Med Mol Imaging 2006; 33:817—822
 
.
Pavel D, Jobe T, Devore-Best S, et al: Viewing the functional consequences of traumatic brain injury by using brain SPECT. Brain Cogn 2006; 60:211—213
 
.
Tekin S, Cummings JL: Frontal-subcortical neuronal circuits and clinical neuropsychiatry: an update. J Psychosom Res 2002; 53:647—654
 
.
Catani M, Howard RJ, Pajevic S, et al: Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Neuroimage 2002; 17:77—94
 
.
Jellison BJ, Field AS, Medow J, et al: Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am J Neuroradiol 2004; 25:356—369
 
.
Kier EL, Staib LH, Davis LM, et al: MR imaging of the temporal stem: anatomic dissection tractography of the uncinate fasciculus, inferior occipitofrontal fasciculus, and Meyer’s loop of the optic radiation. AJNR Am J Neuroradiol 2004; 25:677—691
 
.
O’Donnell LJ, Kubicki M, Shenton ME, et al: A method for clustering white matter fiber tracts. AJNR Am J Neuroradiol 2006; 27:1032—1036
 
.
Heiervang E, Behrens TE, Mackay CE, et al: Between session reproducibility and between-subject variability of diffusion MR and tractography measures. Neuroimage 2006; 33:867—877
 
.
Schmahmann JD, Pandya DN: Fiber Pathways of the Brain. New York, Oxford University Press, 2006
 
.
Schmahmann JD, Pandya DN, Wang R, et al: Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 2007 (e-pub ahead of print)
 
.
Makris N, Kennedy DN, McInerney S, et al: Segmentation of subcomponents within the superior longitudinal fascicle in humans: a quantitative, in vivo, DT-MRI study. Cerebral Cortex 2005; 15:854-869
 
.
Zarei M, Johansen-Berg H, Jenkinson M, et al: Two-dimensional population map of cortical connections in the human internal capsule. J Magn Reson Imaging 2007; 25:48—54
 
.
Nolte J: The Human Brain. St. Louis, Mosby, 2002
 
+
+

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