A review of magnetic resonance imaging and …...Abstract Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often

A review of magnetic resonance imaging and diffusion tensorimaging findings in mild traumatic brain injury

M. E. Shenton & H. M. Hamoda & J. S. Schneiderman & S. Bouix &

O. Pasternak & Y. Rathi & M.-A. Vu & M. P. Purohit & K. Helmer &

I. Koerte & A. P. Lin & C.-F. Westin & R. Kikinis & M. Kubicki &R. A. Stern & R. Zafonte

Published online: 22 March 2012

Abstract Mild traumatic brain injury (mTBI), also referredto as concussion, remains a controversial diagnosis becausethe brain often appears quite normal on conventional com-puted tomography (CT) and magnetic resonance imaging(MRI) scans. Such conventional tools, however, do notadequately depict brain injury in mTBI because they arenot sensitive to detecting diffuse axonal injuries (DAI), alsodescribed as traumatic axonal injuries (TAI), the major braininjuries in mTBI. Furthermore, for the 15 to 30 % of thosediagnosed with mTBI on the basis of cognitive and clinical

symptoms, i.e., the “miserable minority,” the cognitive andphysical symptoms do not resolve following the first3 months post-injury. Instead, they persist, and in somecases lead to long-term disability. The explanation givenfor these chronic symptoms, i.e., postconcussive syndrome,particularly in cases where there is no discernible radiologicalevidence for brain injury, has led some to posit a psychogenicorigin. Such attributions are made all the easier since bothposttraumatic stress disorder (PTSD) and depression are fre-quently co-morbid with mTBI. The challenge is thus to use

M. E. ShentonClinical Neuroscience Laboratory, Laboratory of Neuroscience,Department of Psychiatry, VA Boston Healthcare System,and Harvard Medical School,Brockton, MA, USA

M. E. Shenton (*) :H. M. Hamoda : J. S. Schneiderman :S. Bouix :O. Pasternak :Y. Rathi :M.-A. Vu :M. P. Purohit :I. Koerte :M. KubickiPsychiatry Neuroimaging Laboratory, Departments of Psychiatryand Radiology, Brigham and Women’s Hospital,and Harvard Medical School,1249 Boylston Street,Boston, MA 02215, USAe-mail: [email protected]: http://pnl.bwh.harvard.edu

H. M. HamodaDepartment of Psychiatry, Children’s Hospital, and HarvardMedical School,Boston, MA, USA

O. Pasternak :C.-F. WestinLaboratory of Mathematics in Imaging, Department of Radiology,Brigham and Women’s Hospital, and Harvard Medical School,Boston, MA, USA

M. P. Purohit : R. ZafonteSpaulding Rehabilitation Hospital,Massachusetts General Hospital and Harvard Medical School,Boston, MA, USA

M. P. PurohitDivision of Medicine, Beth Israel-Deaconness Medical Center,and Harvard Medical School,Boston, MA, USA

K. HelmerDepartment of Radiology, Athinoula A.Martinos Center,Massachusetts General Hospital, and Harvard Medical School,Charlestown, MA, USA

A. P. LinCenter for Clinical Spectroscopy, Department of Radiology,Brigham and Women’s Hospital, and Harvard Medical School,Boston, MA, USA

R. KikinisSurgical Planning Laboratory, MRI Division,Department of Radiology, Brigham and Women’s Hospital,and Harvard Medical School,Boston, MA, USA

R. A. SternCenter for The Study of Traumatic Encephalopathy,Departments of Neurology and Neurosurgery,Boston University Medical School,Boston, MA, USA

Brain Imaging and Behavior (2012) 6:137–192DOI 10.1007/s11682-012-9156-5

# Springer Science+Business Media, LLC (outside the USA) 2012

http://pnl.bwh.harvard.edu

neuroimaging tools that are sensitive to DAI/TAI, such asdiffusion tensor imaging (DTI), in order to detect brain inju-ries in mTBI. Of note here, recent advances in neuroimagingtechniques, such as DTI, make it possible to characterize betterextant brain abnormalities in mTBI. These advances may leadto the development of biomarkers of injury, as well as tostaging of reorganization and reversal of white matter changesfollowing injury, and to the ability to track and to characterizechanges in brain injury over time. Such tools will likely beused in future research to evaluate treatment efficacy, giventheir enhanced sensitivity to alterations in the brain. In thisarticle we review the incidence of mTBI and the importance ofcharacterizing this patient population using objective radio-logical measures. Evidence is presented for detecting brainabnormalities in mTBI based on studies that use advancedneuroimaging techniques. Taken together, these findings sug-gest that more sensitive neuroimaging tools improve the de-tection of brain abnormalities (i.e., diagnosis) in mTBI. Thesetools will likely also provide important information relevant tooutcome (prognosis), as well as play an important role inlongitudinal studies that are needed to understand the dynamicnature of brain injury in mTBI. Additionally, summary tablesof MRI and DTI findings are included. We believe that theenhanced sensitivity of newer and more advanced neuroimag-ing techniques for identifying areas of brain damage in mTBIwill be important for documenting the biological basis ofpostconcussive symptoms, which are likely associated withsubtle brain alterations, alterations that have heretofore goneundetected due to the lack of sensitivity of earlier neuroimag-ing techniques. Nonetheless, it is noteworthy to point out thatdetecting brain abnormalities in mTBI does not mean thatother disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They argu-ably are. The controversy of psychogenic versus physiogenic,however, is not productive because the psychogenic view doesnot carefully consider the limitations of conventional neuro-imaging techniques in detecting subtle brain injuries in mTBI,and the physiogenic view does not carefully consider the factthat PTSD and depression, and other co-morbid conditions,may be present in those suffering from mTBI. Finally, we endwith a discussion of future directions in research that will leadto the improved care of patients diagnosed with mTBI.

Keywords Mild traumatic braininjury . mTBI . TBI . Diffusion tensorimaging . DTI .Magnetic resonanceimaging .MRI . Diffusion-weightedimaging . DWI . Susceptibility-weightedimaging . SWI . Signature injuryof war . Concussion . Postconcussivesyndrome . Postconcussive symptoms . ComplicatedmTBI . UncomplicatedmTBI . Physiogenesis . Psychogenesis . Miserable minority

Introduction

The scope of the problem More than 1.7 million people eachyear in the United States experience a traumatic brain injury(TBI), with 75 to 85 % of these injuries categorized as mild(mTBI; CDC 2010; Faul et al. 2010; Bazarian et al. 2006).This number is likely an underestimate because it does notinclude those who are seen in private clinics or by primarycare physicians, nor does it include those who do not seekmedical treatment (Langlois et al. 2006). It is estimated, infact, that 14 % of mTBI patients are seen in private clinics orby their own doctors, with an additional 25 % receiving nomedical attention (Sosin et al 1996). Based on the largenumber of known and likely unknown cases, traumatic braininjury has been referred to as the “silent epidemic” (e.g.,Goldstein 1990). Recently, the public has become moreaware of TBI based on news reports of sports injuriesleading to long-term effects of repetitive trauma to the brain,as well as news reports about soldiers returning from Iraqand Afghanistan with TBI. With respect to the latter, themost frequent combat-related injury incurred by soldiersreturning from Iraq and Afghanistan is TBI, and most par-ticularly mTBI (Okie 2005). The frequency of these injurieshas led to TBI being called the “signature injury of war”(Okie 2005). Further, approximately 22 % of the woundedsoldiers arriving at Lundstuhl Regional Medical Center inGermany have head, neck, or face injuries, with cases ofTBI resulting primarily from improvised explosive devices(IEDs), landmines, high pressure waves from blasts, bluntforce injury to the head from objects in motion, and motorvehicle accidents (Okie 2005; Warden 2006). Of particularnote, mTBI characterizes most of the blast-induced traumaticbrain injuries seen in service members returning from Iraqand Afghanistan, with reports of 300,000 service memberssustaining at least one mTBI as of 2008 (Tanielian andJaycox 2008). Mild TBI is thus a major health problem thataffects both civilians and military populations. The estimatedeconomic cost is also enormous, with mTBI accounting for44 % of the 56 billion dollars spent annually in the UnitedStates in treating TBI (Thurman 2001).

Lack of radiological evidence Mild TBI is, however, diffi-cult to diagnose because often the brain appears quite nor-mal on conventional computed tomography (CT) andmagnetic resonance imaging (MRI) (e.g., Bazarian et al.2007; Inglese et al. 2005; Hughes et al. 2004; Iverson etal. 2000; Miller 1996; Mittl et al. 1994; Povlishock andCoburn 1989; Scheid et al. 2003). This lack of radiologicalevidence of brain injury in mTBI has led clinicians typicallyto diagnose mTBI on the basis of clinical and cognitivesymptoms, which are generally based on self-report, andare non-specific as they overlap with other diagnoses (e.g.,Hoge et al. 2008; Stein and McAllister 2009). To complicate

138 Brain Imaging and Behavior (2012) 6:137–192

matters further, while most of the symptoms in mTBI aretransient and resolve within days to weeks, approximately15 to 30 % of patients evince cognitive, physiological, andclinical symptoms that do not resolve 3 months post-injury(e.g., Alexander 1995; Bazarian et al. 1999; Bigler 2008;Rimel et al. 1981; Vanderploeg et al. 2007). Instead, thesesymptoms persist and in some cases lead to permanentdisability (Carroll et al. 2004a and b; Nolin and Heroux2006), and to what has been referred to as persistent post-concussive symptoms (PPCS), or postconcussive syndrome(PCS), although the latter term, “PCS,” is controversial(e.g., Arciniegas et al. 2005).

This “miserable minority” (Ruff et al. 1996) oftenexperience persistent postconcussive symptoms (PPCS) thatinclude dizziness, headache, irritability, fatigue, sleep distur-bances, nausea, blurred vision, hypersensitivity to light andnoise, depression, anxiety, as well as deficits in attention,concentration, memory, executive function, and speed of pro-cessing (e.g., Bigler 2008). Kurtzke and Kurland (1993) esti-mates the incidence of persistent symptoms as being equal tothe annual incidence of Parkinson’s disease, Multiple Sclero-sis, Guillain-Barré Syndrome, Motor Neuron Disease, andMyasthenia Gravis, combined. Moreover, the modal age forinjury is young, in the 20’s and 30’s. Thus mTBI affects alarge number of individuals in the prime of life, where there is,to date, no consistent or reliable correlations between cogni-tive/clinical symptoms and radiological evidence of braininjury based on conventional neuroimaging.

The explanation given for PPCS, particularly when there isno discernible radiological evidence, has led some to posit apsychogenic origin (e.g., Belanger et al. 2009; Hoge et al.2008; Lishman 1988; Machulda et al. 1988). More specifical-ly, Hoge and colleagues (2008; 2009) suggest that postcon-cussive symptoms reported by soldiers with mTBI are largelyor entirely mediated by posttraumatic stress disorder (PTSD)and depression. In their study, after controlling for both PTSDand depression, the only remaining symptom was headaches.Headaches, nonetheless, are an important symptom of TBI,particularly mTBI.

The term “miserable minority,” described above, has beenused to identify those who likely have a more psychogenicetiology to their symptoms (e.g., Ruff et al. 1996). Suchattributions are easy to make given that the symptoms ofmTBI, as noted above, overlap with other disorders (e.g.,Hoge et al. 2008). Belanger et al. (2009) also suggest thatmost of the symptoms reported by those with mTBI are likelythe result of emotional distress. Others have also argued thatemotional distress and/or psychiatric problems account forthose who continue to experience postconcussive symptoms(e.g., Belanger et al. 2009; Greiffenstein 2008; Hoge et al.2008; Lishman 1988; Machulda et al. 1988).

Persistent symptoms, however, may be the result of moresubtle neurological alterations that are beneath the threshold

of what can be detected using conventional neuroimagingtechniques that all too often do not reveal brain pathology inmTBI (e.g., Hayes and Dixon 1994; Huisman et al. 2004;Fitzgerald and Crosson 2011; Green et al. 2010; Miller 1996;Niogi and Mukherjee 2010). This is not at all surprising, sinceconventional techniques are not sensitive to detecting diffuse/traumatic axonal injuries (DAI/TAI), the major brain injuriesobserved in mTBI (e.g., Benson et al. 2007).

There is also evidence from the literature to suggest thatin several cases of mTBI where there was no radiologicalevidence of brain injury, autopsy following death frominjuries other than mTBI revealed microscopic diffuse axo-nal injuries that conventional neuroimaging tools did notdetect, presumably because they were not sufficiently sen-sitive (e.g., Adams et al. 1989; Bigler 2004; Blumbergs et al.1994; Oppenheimer 1968).

We would argue that the controversy between mTBIbeing psychogenic versus physiogenic in origin is not pro-ductive because the psychogenic view does not carefullyconsider the limitations of conventional neuroimaging tech-niques in detecting subtle brain injuries in mTBI, and thephysiogenic view does not carefully consider the fact thatPTSD and depression, and other co-morbid conditions, maybe present in those suffering from mTBI. Further, patientswith mTBI may complain more when their symptoms arenot validated. That is, when there is no radiological evi-dence that explains their symptoms, and yet they still expe-rience symptoms, these patients may complain morebecause of the lack of validation, versus those patientswho have radiological evidence that validates their symp-toms, leading them to complain less, simply because theyhave a medical explanation for their symptoms.

The challenge The challenge then is to use neuroimagingtools that are sensitive to DAI/TAI, such as Diffusion TensorImaging (DTI), to detect brain injuries in mTBI. Specifical-ly, with recent advances in imaging such as DTI it will nowbe possible to characterize better extant brain injuries inmTBI. Of note, DTI is a relatively new neuroimaging tech-nique that is sensitive to subtle changes in white matter fibertracts and is capable of revealing microstructural axonalinjuries (Basser et al. 1994; Pierpaoli and Basser 1996;Pierpaoli and Basser 1996), which are also potentially re-sponsible for persistent postconcussive symptoms.

Other promising techniques include susceptibility weight-ed imaging (SWI), which is sensitive to micro-hemorrhagesthat may occur in mTBI (e.g., Babikian et al. 2005; Haacke etal. 2004; Park et al. 2009; Scheid et al. 2007), and MagneticResonance Spectroscopy (MRS), which measures brainchemistry sensitive to neuronal injury and DAI (e.g., Babikianet al. 2006; Brooks et al. 2001; Garnett et al. 2000; Holshouseret al. 2005; Lin et al. 2005; Lin et al. 2010; Provencher 2001;Ross et al. 1998; Ross et al. 2005; Seeger et al. 2003; Shutter

Brain Imaging and Behavior (2012) 6:137–192 139

et al. 2004; Vagnozzi et al. 2010). In this review we focusprimarily on MRI and, most particularly, on DTI findings inmTBI. In a separate article in this special issue, Dr. AlexanderLin and colleagues review MRS, single photon emissiontomography (SPECT), and positron emission tomography(PET) findings relevant to brain chemistry alterations inmTBI, and Dr. Brenna McDonald and colleagues reviewfunctional MRI (fMRI) findings in mTBI. The reader is alsoreferred to Dr. Robert Stern and colleagues’ article, also in thisissue, which reviews the evidence for repetitive concussiveand subconcussive injuries in the etiology of chronic traumaticencephalopathy in sports-related injuries such as professionalfootball (see also Stern et al. 2011).

Focus of this review Here we present evidence for brainabnormalities in mTBI based on studies using advancedMRI/DTI neuroimaging techniques. Importantly, theseadvances make it possible to use more sensitive tools toinvestigate the more subtle brain alterations in mTBI. Theseadvances will likely lead to the development of biomarkersof injury, as well as to staging of reorganization and reversalof white matter and gray matter changes following injury,and to the ability to chart the progression of brain injuryover time. Such tools will also likely be used in futureresearch to evaluate treatment efficacy, given their enhancedsensitivity to alterations in the brain.

Taken together, the findings presented below suggestthat more sensitive neuroimaging tools improve the de-tection of brain injuries in mTBI (i.e., diagnosis). Thesetools will, in the near future, likely provide importantinformation relevant to outcome (prognosis), as well asplay a key role in longitudinal studies that are needed tounderstand the dynamic nature of brain injury in mTBI.We also believe that the enhanced sensitivity of newerand more advanced neuroimaging techniques for identi-fying brain pathology in mTBI will be important fordocumenting the biological basis of persistent postcon-cussive symptoms, which are likely associated withsubtle brain alterations, alterations that heretofore havegone undetected due to the lack of sensitivity of earlier,conventional neuroimaging techniques.

Below we provide a brief primer of neuroimaging tech-niques, although the reader is referred to Kou et al. (2010),Johnston et al. (2001), Le and Gean (2009), and Niogi andMukherjee 2010 for more detailed information. For a de-scription of the molecular pathophysiology of brain injury,the reader is referred to Barkhoudarian et al. (2011). Thereader is also referred to Dr. Erin Bigler’s article in thisspecial issue for information regarding post-mortem andhistological findings in mTBI as well as for a discussionof the physiological mechanisms underlying TBI. Dr. Bigleremphasizes that neuroimaging abnormalities are “gross indi-cators” of the underlying cellular damage resulting from

trauma-induced pathology. We concur and believe that wenow have neuroimaging tools that are sufficiently sensitiveto discern both more gross indicators of pathology, as wellas microstructural changes in white matter, and micro-hemorrhages using newer imaging technologies. The readeris also referred to Smith et al. (1995) and to several recent andexcellent reviews of neuroimaging findings in mTBI (e.g.,Belanger et al. 2007; Bruns and Jagoda 2009; Gentry 1994;Green et al. 2010; Hunter et al. 2011; Kou et al. 2010; Le andGean (2009); Maller et al. 2010; Niogi and Mukherjee 2010).Jang (2011) has also published a recent review of the use ofDTI in evaluating corticospinal tract injuries after TBI.

Following the brief primer, we present MRI and DTI find-ings relevant to mTBI. We used PUBMED to locate thesearticles. The following keywords were used: (MRI or DTI orDiffusion Tensor) AND (Concussion or Mild TBI or MildTraumatic Brain Injury or mTBI). The dates for the articlesselected were inclusive to September 16, 2011. We did notinclude articles that were case studies, nor did we includearticles that focused on pediatric and adolescent populations(see article in this special issue by Wilde and colleagues,which covers this topic). We also did not include articles thatdid not specify the severity of injury, but instead describedonly the mechanism of injury, i.e., falls, motor vehicle acci-dent, hit by tram (e.g., Liu et al. 1999). For the morphometricMRI empirical studies, we note that most included mild,moderate, and severe TBI, rather than mTBI alone. Conse-quently we included all three. This was less the case for theDTI empirical studies, where many focused only on mTBI.We were thus able to separate empirical studies that focusedsolely on mTBI from those that included several levels ofseverity, although we report on both. We include detailedsummary tables of MRI and DTI findings in order to providethe interested reader with a more in depth and detailed reviewof each empirical study included in this review. Following thereview of MRI and DTI findings, we present future directionsfor research in mTBI, which include the use of multiplemodalities for imaging the same patients, and the importanceof following patients longitudinally. We also present newimaging methods that go beyond advanced imagingapproaches reviewed here that, to date, are still as yet not usedroutinely in a clinical setting. The potential for developingbiomarkers to identify and to characterize mTBI is also pre-sented. The need here is critical as mTBI is not only difficult todetect but the injuries to the brain are heterogeneous, andbiomarkers are needed for individualized diagnosis as wellas for early and effective treatment interventions.

Neuroimaging primer and role of neuroimaging in mTBI

Overview TBI is a heterogeneous disorder and there is noone single imaging modality that is capable of characterizing


the multifaceted nature of TBI. Advances in neuroimagingare, nonetheless, unprecedented and we are now able tovisualize and to quantify information about brain alterationsin the living brain in a manner that has previously not beenpossible. These advances began with computed axial tomog-raphy (CT) in the 1970’s, and then with magnetic resonanceimaging (MRI) in the mid-1980’s, with more refined andadvanced MR imaging over the last 25 years, including per-fusion weighted imaging (useful for measuring abnormalblood supply and perfusion), susceptibility-weighted imaging(SWI; useful for measuring micro-hemorrhages – e.g., Haackeet al. 2004; Park et al. 2009), magnetization transfer MRI(useful for measuring traumatic lesions – e.g., see review inLe and Gean 2009), diffusion weighted imaging (DWI; usefulfor measuring edema and developed initially for studies ofstroke – see review in Le and Gean (2009)), diffusion tensorimaging (DTI; useful for measuring white matter integrity –e.g., Basser et al. 1994), and functional MRI (fMRI; usefulfor measuring altered cortical responses to controlled stimuli –e.g., see article by McDonald et al. in this issue). Other neuro-imaging tools, although not a complete list, include positronemission tomography (PET; useful for measuring regionalbrain metabolism using 2-fluro-2-deoxy-d-glucose, bothhyper and hypo metabolism observed in TBI – see Le andGean (2009) for review), single photon emission tomography(SPECT; useful for measuring cerebral blood flow but lesssensitive to smaller lesions that are observed on MRI – seearticle by Lin et al. in this issue), and magnetic resonancespectroscopy (MRS; useful for measuring brain metabolites/altered brain chemistry – see article by Lin et al. in this issue).The clinical use of such tools lags behind their development,although the gap between development and clinical applica-tion is narrowing.

Below, we provide a brief primer for some of the neuro-imaging tools available today. We include skull films, CT,and MRI including DWI/DTI, and susceptibility weightedimaging. This primer is not detailed nor is it comprehensive.Instead, our intention is to provide the reader who is lessfamiliar with neuroimaging techniques with a context forsome of the tools available for investigating mTBI. Otherneuroimaging modalities, which will not be described here,include MRS, PET, SPECT, and fMRI. MRS, PET, andSPECT, will be reviewed by Dr. Alexander Lin and col-leagues, and Dr. Brenna McDonald and colleagues willreview fMRI, in separate articles in this issue. Table 1provides a brief summary of these neuroimaging tools.

Skull-X-ray and CT Skull films, or skull X-rays, whileexcellent for detecting skull fracture, are not used routinelyto investigate brain trauma because they provide very limit-ed information (e.g., Bell and Loop 1971; Hackney 1991).Figure 1 depicts a normal skull film. Computed Tomogra-phy or Computed Axial Tomography (CT) supplanted the

use of skull films for evaluating neurotrauma when thistechnology became available in the 1970s. CT providesthree-dimensional images of the inside of an object, in thiscase the brain, using two-dimensional X-Ray imagesobtained around a single axis of rotation. Since CT wasintroduced in the 1970s, it has become the imaging modalityof choice for evaluating closed head injury in the emergencyroom (ER) (e.g., Johnston et al. 2001).

CT is, in fact, the main imaging modality used in the first24 h for the management of neurotrauma in the ER (e.g.,Coles 2007). The reasons for this are because it is widelyavailable in most hospitals, it is fast, and it is accurate fordetecting emergent conditions such as skull fractures, brainswelling, intracranial hemorrhage, herniation, and radio-opaque foreign bodies in the brain (see review in Johnstonet al. 2001; Le and Gean (2009)). The use of thin-volumeCT scanners are also often located in close physical prox-imity to the ER, thus making it easy to transport neuro-trauma patients. Additionally, the presence of metallicobjects will not result in possibly dangerous accidents inthe CT suite as would be the case using an MR scan,depending upon the nature of the trauma, and dependingupon whether or not unknown small pieces of metal arehidden inside the patient following a car accident or othertype of brain trauma. Of further note, MRI scanners aregenerally not in close physical proximity to the ER, andthe scanning time is longer, which is an important consid-eration for patients who are not medically stable. Moreover,the CT environment is able to accommodate the set up of lifesupport and monitoring equipment that is, at this time, oftenmore compatible for the CT than for the MRI environment,although this is changing. CT thus remains the most impor-tant neuroimaging tool used in the first 24 h of acute neuro-trauma in the ER, where the most important question to beanswered quickly is: does this person need immediate neu-rosurgical intervention?

Figure 2 depicts a normal CT scan. Note that the skulland the brain are visible, although there is no differentiationbetween gray and white matter, which is discernible usingMRI. There are also bone artifacts with CT that are notpresent with MRI, which means that areas of injury aroundbone are easier to detect using MRI. MRI also uses noionizing energy, as CT does, which becomes importantwhen considering pediatric populations. This is also a con-sideration when several repeat scans are needed over time tofollow the progression of injury.

MRI and SWI Magnetic resonance imaging was introducedin the mid-1980s with the first images acquired on low-fieldmagnets, i.e., 0.5 Tesla (T). Originally this type of imagingwas called nuclear magnetic resonance (NMR) imaging butthe name was changed to magnetic resonance (MR) imag-ing, or MRI. The basic principle behind MRI is that


radiofrequency (RF) pulses are used to excite hydrogennuclei (single proton) in water molecules in the human body,in this case the brain. By modulating the basic magneticfield, and the timing of a sequence of RF pulses, the scanner

produces a signal that is spatially encoded and results inimages. While NMR can be observed with a number ofnuclei, hydrogen imaging is the only one that is widely usedin the medical use of MRI.

MR images can be produced with different contrasts andcan be optimized to show excellent contrast between grayand white matter, which CT does not. Early MRI scans hadpoor spatial resolution and the time to acquire images wasslow, taking many minutes to acquire even one image. Sincethe mid-1980s, however, the field strengths of the magnethave increased from 0.5 to 1.0, to 1.5 T, and to 3.0 T andbeyond. In combination with advances in the capabilities ofthe gradient magnetic fields and the RF equipment available(parallel imaging), it is now possible to acquire sub-millimeter morphologic images and rich contrast combina-tions in clinical settings, in a shorter period of time. More-over, reconstruction algorithms can recreate images evenwhen the volume of the pixel elements (voxels) is notcompletely isotropic (i.e., the same size in all directions).Figure 3 depicts MRI scans acquired on a 3 T magnet using

Table 1 Summary of modalities

Imaging Technique/Modality: Function: Advantages Offered:

X-ray Imaging of bony structures Primarily used for detecting fractures.

Computed Tomography (CT) 3D X-ray imaging of an object (e.g., brainand skull).

Quick, able to have medical equipment inscanning area, good for skull fractures orgross injuries/abnormalities requiringemergent surgical intervention such assubdural hematomas.

Clinical Magnetic Resonance Imaging(MRI)

Uses radiofrequency pulses to detectchanges in spin signal of hydrogen atoms.

Better resolution than CT, particularly forsoft tissue, can provide gross delineationbetween gray and white matter structures,better visualization of brain stem areascompared to CT, can also detect subacutehemorrhages and macroscopic areas ofwhite matter damage.

Diffusion Weighted Imaging (DWI)/Diffusion Tensor Imaging (DTI)

Special type of MRI sequence that uses thediffusion properties of water to detectmicrostructural tissue architecture.

Best imaging technique available fordetecting white matter integrity/damage,able to detect microscopic white matterdamage and trace specific tracts of thebrain (e.g., corpus callosum, superiorlongitudinal fasciculus, uncinate).

Susceptibility Weighted Imaging (SWI) Special type of MRI technique that takesadvantage of susceptibility differencesamong structures (e.g., oxygenated vs.deoxygenated blood and iron).

Provides increased sensitivity to detect areasof micro-hemorrhage, particularly at gray-white matter junctions, that are not de-tectable on standard MRI.

Magnetic Resonance Spectroscopy (MRS) Measures brain chemistry by producing aspectrum where individual chemicals, ormetabolites can be identified andconcentrations can be measured.

Provides neurophysiological data that isrelated to structural damage/changes,neuronal health, neurotransmission,hypoxia, and other brain functions.

Positron Emission Tomography (PET) Uses radiotracers labeled with differentisotopes that emit signals indicating areasof uptake or binding in the brain, mostcommonly used is 18-Fluorodeoxyglucose, an analog of glucose.

Provides information on the concentrationof a chemical or protein in the brain suchas the amount of glucose, which reflectsactivity, or the density of a type of proteinsuch as beta amyloid, a hallmark ofneurodegenerative disease.

Fig. 1 Lateral (left) and frontal (right) view of normal skull X-ray.(Courtesy of Amir Arsalan Zamani, M.D.)


1.5 mm slices. Note the high contrast between gray andwhite matter that is not visible on CT (see Figure 2). Cere-bral spinal fluid (CSF) is also prominent, and one can usethe differences in signal intensity of gray matter, whitematter, and CSF to parcellate automatically the brain intothese three tissue classes (e.g., Fischl et al. 2004; Pohl et al.2007). Of note here, the different tissue classes, from theparcellation, include quantitative information such as whole

brain volume for gray matter, white matter, and CSF. Thiswork is based on research developed over more than adecade in the field of computer vision.

Due to its superior contrast resolution for soft tissues,MRI technology is far more sensitive than CT in detectingsmall contusions, white matter shearing, small foci of axonalinjury, and small subacute hemorrhages (see review in Niogiand Mukherjee 2010). That MRI is able to discern these

Fig. 2 CT scan of a normalbrain. Left side is at the level ofthe temporal lobe where bonecan be seen as white areas(see red arrows). Right side is atthe level of the frontal lobe.(Courtesy of Amir ArsalanZamani, M.D.)

Fig. 3 Structural MRI scansacquired on a 3 T magnet using1.5 mm slices: a T1-weightedimage, b T2-weighted image,c T1-weighted image showinggray matter, white matter,and CSF parcellation, andd T1-weighted image showingthe corpus callosum regionof interest


more subtle abnormalities, compared with CT, makes itparticularly well suited for evaluating mTBI. Additionally,there is higher contrast between brain and CSF, and betweengray and white matter, as well as better detection of edemawith MRI than CT, all important factors in evaluating TBI(see review in Johnston et al. 2001).

Of further note, and of particular interest to mTBI, Mittland coworkers (1994) found that in mTBI, where CT find-ings were negative, 30 % of these cases showed lesions onMRI that were compatible with hemorrhagic and non-hemorrhagic diffuse axonal injuries. The increased sensitiv-ity of MRI over CT in discerning radiological evidence ofbrain injury in mTBI has also been shown, and commentedupon, by a number of other investigators including Jenkinsand coworkers (1986), Levin and coworkers (1984; 1987),Eisenberg and Levin (1989), and Bazarian and coworkers(2007). Gentry and coworkers (1988) also observed that in aprospective study of 40 closed injury patients, MRI wassuperior to CT in detecting non-hemorrhagic lesions. Thesefindings, taken together, suggest that while CT may becritically important in the first 24 h to assess the immediateneed for neurosurgical intervention, for mTBI, MRI is likelyto be more sensitive for detecting small and subtle abnor-malities that are not detected using CT (e.g., Gentry et al.1988; Levin et al. 1987).

There are also several types of MRI sequences that add towhat can be gleaned from conventional MRI, including theuse of T1, T2-weighted FLAIR (FLuid Attenuated InversionRecovery) to examine macroscopic white matter lesions andcontusions on the cortical surface, as well as susceptibility-weighted imaging (SWI), which is a type of gradient-recalled echo (GRE) MRI that can be performed on conven-tional scanners. SWI was originally developed for venogra-phy and called Blood-Oxygen-Level-Dependent (BOLD)venographic imaging (Ashwal et al. 2006; Haacke et al.2009; Reichenbach et al. 2000; see also review in Kou etal. 2010 and Niogi and Mukherjee 2010). SWI takes advan-tage of susceptibility differences between tissues, resultingin an enhanced contrast that is sensitive to paramagneticproperties of intravascular deoxyhemoglobin, i.e., sensitiveto venous blood, to hemorrhage, and to iron in the brain. Inessence, susceptibility differences are detected as phasedifferences in the MRI signal. In the image processing stage,SWI superimposes these phase differences on the usual(magnitude) MR image, thereby allowing the susceptibilitydifferences to be accentuated in the final image. Of furthernote, SWI shows six times greater ability to detect hemor-rhagic diffuse axonal injuries than other MRI techniques(Tong et al. 2003; 2004). This technique is thus particularlyappropriate for discerning micro-hemorrhages in TBI, as itis sensitive to bleeding in gray/white matter boundaries,where small and subtle lesions are not discernible usingother MRI techniques, making it particularly useful in the

more acute and subacute stages following brain trauma.SWI, in conjunction with diffusion measures (e.g., DTI),will thus likely be important for discerning the subtle natureof mTBI abnormalities in the future. SWI is offered as alicensed acquisition and processing package by several ven-dors, but it can be acquired and processed on any scannersthat are 1.0 T, 1.5 T, 3.0 T, or above. Figure 4 depictssusceptibility-weighted images, where small black areasindicate blood vessels.

DWI and DTI Diffusion weighted imaging (DWI), devel-oped in 1991 for use in humans (e.g., Le Bihan 1991), isbased on the random motion of water molecules (i.e.,Brownian motion). This motion in the brain is affected bythe intrinsic speed of water displacement depending uponthe tissue properties and type, i.e., gray matter, white matter,and CSF. DWI was first used to evaluate acute cerebralischemia where it was thought that decreased diffusionwas the result of neuronal and glial swelling and likelyrelated to cytotoxic edema, whereas increased diffusionwas thought to reflect vasogenic edema. The method hasbeen applied to TBI with mixed results (see Niogi andMukherjee 2010).

Apparent Diffusion Coefficient (ADC) is a measure ofdiffusion, on average, and the word “apparent” is used toemphasize that what is quantified is at the level of the voxel,and not at the microscopic level. This measure has beenused as an indicator of edema, which, in conjunction withDTI (see below), can be used to quantify, indirectly, bothedema and damage to the integrity of white matter fiberbundles in TBI (see review in Assaf and Pasternak 2008;Niogi and Mukherjee 2010). A measure of free water, how-ever, derived from DTI (Pasternak et al. 2009; Pasternak etal. 2010; 2011a; b) may provide a better measure of edema,and this will be discussed further in the section on futuredirections of research.

DTI is a DWI technique that has opened up new possi-bilities for investigating white matter in vivo as it providesinformation about white matter anatomy that is not availableusing any other method — either in vivo or in vitro (Basseret al. 1994; Pierpaoli and Basser 1996; Pierpaoli and Basser1996; see also review in Assaf and Pasternak 2008). Attoday’s image resolution, it does not detect water behaviorwithin individual axons. Instead it describes local diffusionproperties. In other words, the individual behavior of axonscannot be described using DTI, but diffusion properties canbe described that are relevant to fiber bundles.

DTI differs from conventional MRI in that it is sensitiveto microstructural changes, particularly in white matter,whereas CT and conventional MRI (including also FLAIR)reveal only macroscopic changes in the brain. Thus subtlechanges using DTI can reveal microstructural axonal inju-ries (Basser et al. 1994; Pierpaoli and Basser 1996; Pierpaoli


and Basser 1996), which are potentially responsible also forpersistent postconcussive symptoms.

The concept underlying DTI is that the local profile of thediffusion in different directions provides important indirectinformation about the microstructure of the underlying tis-sue. It has been invaluable in investigations of white matterpathology in multiple sclerosis, stroke, normal aging, Alz-heimer’s disease, schizophrenia and other psychiatric disor-ders, as well as in characterizing diffuse axonal injuries inmTBI (see reviews in Assaf and Pasternak 2008; Kou et al.2010; Shenton et al. 2010; Whitford et al. 2011).

The latter focus on TBI is relatively recent (see review ofthe literature, below). Those investigating mTBI, in partic-ular, have been disappointed by the lack of informationgleaned from conventional MRI and CT, although, as notedpreviously, this is not surprising given that the most com-mon injuries observed in mTBI are diffuse axonal injury/traumatic axonal injury (DAI/TAI), which are not easilydetected using conventional MR or CT scans. With theadvent of DTI, however, DAI/TAI have the potential to bequantified and this information can be used for diagnosis,prognosis, and for the evaluation of treatment efficacy.

Quantification of pathology using DTI is based on meas-ures that calculate the amount of restriction of water move-ment in the brain, which is determined to a large extent bythe tissue being measured. For example, the movement ofwater is unrestricted in a medium such as CSF, where itdiffuses equally in all directions (i.e., isotropic). However,in white matter, the movement of water is more restricted byaxonal membranes, myelin sheaths, microtubules, neurofila-ments, etc. In white matter, this restriction is dependent onthe directionality of the axons (i.e., diffusion is not equal inall directions) and is referred to as anisotropic diffusion.

Using tensors, adapted from the field of engineering, theaverage shape of the diffusion is characterized as more orless spherical when there is no impediment to water diffu-sion, as for example in CSF (i.e., unrestricted water is free todiffuse in all directions: isotropic). However, the average

shape of the diffusion becomes more elongated, or cigarshaped, when there is a preferred orientation in which wateris restricted, as for example in white matter. Here, waterdiffuses freely in directions parallel to axons but it is re-stricted in directions that are perpendicular to the axons,which results in the magnitude of the diffusion along theaxons being larger than the two perpendicular directions,leading to an elongated ellipsoidal shape of the diffusiontensor, described as anisotropic. The measurement of thedistance that water diffuses, over a given period of time, forat least six non-collinear directions, makes it possible toreconstruct a diffusion tensor (and the associated ellipsoid)that best describes water diffusion within a given voxel.Consequently, the volume (size) and shape of the ellipsoidcan be calculated, and this provides important informationabout the diffusion properties, and hence about microstruc-tural aspects of brain tissue.

There are various ways that the shape and size of adiffusion ellipsoid can be quantified, but the two mostcommon indices used are Fractional Anisotropy (FA) forshape, and Mean Diffusivity (MD) for size. FA is a scalarmeasure that ranges from 0 to 1, with 0 being completelyisotropic, meaning that water diffuses equally in all direc-tions, and 1 depicting the most extreme anisotropic scenarioin which molecules are diffusing along a single axis. Ac-cordingly, in CSF and gray matter, as noted above, thedirection of water is equal in all directions (i.e., isotropic),and the value is close to 0. In contrast, in white matter, forexample in the corpus callosum, the water is relatively freealong the axons, but restricted perpendicular to the axons,and therefore more anisotropic, with FA being closer to 1.Thus in white matter, reduced FA is generally thought toreflect loss of white matter integrity that may reflect damageto myelin or axon membrane damage, or perhaps reducedaxonal packing density, and/or reduced axonal coherence(see review in Kubicki et al. 2007).

Mean diffusivity (MD), the second most common mea-sure (and proportional to the trace of the diffusion tensor), is

Fig. 4 Sagittal (left) andaxial (right) view ofsusceptibility-weighted images(SWI) of a normal brain.Small black areas indicateblood vessels in the brainthat are enhanced using SWI


different from FA in that it is a measure of the size of theellipsoid, rather than the shape, as is the case for FA. MD issimilar to ADC, described above for DWI, but instead it isthe average ADC along the three principal diffusion direc-tions, where one axis is in the direction of the largestmagnitude of the diffusion in the voxel, and the other twoare perpendicular to the main diffusion direction. The maindiffusion direction in white matter is referred to as thelongitudinal or axial direction, while the other two direc-tions are referred to as the radial or tangent axes. FA andMD are frequently observed as being inversely related. (Forfurther descriptions of DTI and associated methods of anal-yses, the reader is referred to Pierpaoli and Basser 1996;Pierpaoli and Basser 1996; Smith et al. 2006; and thereviews in Ashwal et al. 2006; Fitzgerald and Crosson2011; Hunter et al. 2011; Le and Gean 2009; Kou et al.2010; and Niogi and Mukherjee 2010).

Figure 5, 6, and 7 depict the kind information that can beextracted from diffusion tensor images. For example,Figure 5 shows diffusion images that highlight white matter,along with colored maps that reflect the directions of thewhite matter fiber tracts in the brain. Figure 6 shows whitematter tracts superimposed on structural images. Figure 7shows an area identified as tumor in the frontal lobe, wherewhite matter fiber tracts can be visualized in relation to thetumor and in relation to the frontal horn of the lateralventricles. These figures reflect important, recent advancesin methodology that are sufficiently robust and sensitive thatthey can be used for visualizing and quantifying whitematter pathology in vivo, for the assessment of mTBI clin-ically. These tools are available now for this purpose andwill be discussed further in the future directions section ofthis article.

DTI, however, is somewhat non-specific and it is notknown whether disruptions in FA and MD are the result ofdisturbances in axonal membranes, myelin sheath, micro-tubules, neurofilaments, or other factors. More specificmeasures, which are being developed (see below), are need-ed to delineate further the biological meaning of alterationsin white matter integrity (see review in Assaf and Pasternak2008; Niogi and Mukherjee 2010).

While FA and MD are the two main dependent measuresderived from DTI, there are other measures that have beendeveloped, including Mode (Ennis and Kindlmann 2006),which defines more precisely the shape of the diffusiontensor (useful in distinguishing the anatomy of fiber tracts,including distinguishing fiber crossings from pathology).Other measures include Inter-Voxel Coherence (Pfefferbaumet al. 2000), which measures how similar anisotropic tensorsare in neighboring voxels, useful in measuring anomalies inmacroscopic axonal organization within the tract of interest,and Axial and Radial Diffusivity, which are purported tomeasure axonal and myelin pathology, respectively (Song etal. 2001; Song et al. 2003; Budde et al. 2007; Budde et al.2011). These additional measures may provide more specificinformation regarding the microstructural abnormalitiesdiscerned using the sensitive, albeit less specific, measuresof FA and MD.

Finally, another relatively new post-processing method isfiber tractography, which was developed to visualize and toquantify white matter fiber bundles in the brain (e.g.,Conturo et al. 1999; Mori et al. 1999; Basser et al. 2000).This method makes it possible to follow fiber tracts along adiffusion direction in very small steps so as to create longfiber tracts that connect distant brain regions. The accuracyof fiber tractography is dependent upon a number of factorsincluding image resolution, noise, image distortions andpartial volume effects that result from multiple tracts cross-ing in a single voxel. The main advantage of DTI tractog-raphy, from a clinical research perspective, is that the wholefiber bundle, instead of just a portion of the fiber bundle, canbe evaluated. DTI tractography is thus a promising tool thatcan be used not only to understand how specific brainregions are connected and where damage occurs along fiberbundles, but it can also be used to understand how thisconnectivity may be relevant to functional abnormalities.Further, tractography methods can be used to both visualizeand to quantify white matter fiber bundle damage in a singlecase and thus these methods are potentially important fordiagnosing mTBI based on radiological evidence.

Importantly, many of the measures described above arejust beginning to be applied to investigate brain injuries in

Fig. 5 Diffusion tensor imagesacquired on a 3 T magnet. Left:fractional anisotropy (FA) map.White areas are areas of highanisotropy. Right: color byorientation map. Diffusion inthe left-right direction isshown in red, diffusion in thesuperior-inferior direction isshown in blue, and diffusion inthe anterior-posterior directionis shown in green


Fig. 6 Fiber tractography ofcommonly damaged tracts inmild traumatic brain injury,including: a the anterior coronaradiata and the genu of corpuscallosum, b the uncinatefasciculus, c the cingulumbundle in green and the body ofcorpus callosum in red, andd the inferior longitudinalfasciculus (Niogi andMukherjee 2010; reprintedwith permission WoltersKluwer Health / LippincottWilliams & Wilkins)

Fig. 7 Diffusion MRI data forneurosurgical planning. Thetractography region of interest(ROI) is a box placed aroundthe tumor (in green) in thefrontal lobe. The ROI is alsovisualized with rectangles in theslice views below. Tracts arethen created based on theprincipal diffusion directions,which are color-coded (bottom).Diffusion ellipsoids are shownalong the tract to visualize theshape of the local diffusion


mTBI and thus this area is a relatively new frontier forexploration. The application of DTI, and the measures de-rived from DTI, will likely contribute enormously to ourunderstanding of the nature and dynamics of brain injuriesin mTBI.

Review of MRI findings in mTBI

Much of the work with MRI has been to investigate thehigher sensitivity of MRI, compared with CT, for detectingbrain abnormalities in mTBI (see previous discussion). Lessattention has been given to investigating morphometricabnormalities in mTBI using area, cortical thickness, and/or volume measures. Table 2 lists studies, by first author andyear, which have examined aspects of morphometric abnor-malities in patients with mTBI. Most of these studies, how-ever, include a range of TBI, from mild to severe (e.g.,Anderson et al. 1995; Anderson et al. 1996; Bergeson etal. 2004; Bigler et al. 1997; Ding et al. 2008; Fujiwara et al.2008; Gale et al. 2005; Levine et al. 2008; Mackenzie et al.2002; Schonberger et al. 2009; Strangman et al. 2010; Tateand Bigler 2000; Trivedi et al. 2007; Warner et al. 2010a; b;Wilde et al. 2004; Wilde et al. 2006; Yount et al. 2002), withonly a small number of studies that investigate morphometricabnormalities specifically in mTBI (e.g., Cohen et al. 2007;Holli et al. 2010). Additionally, while most of the studieslisted in Table 2 categorize severity of TBI (i.e., mild, moder-ate, or severe) based on scores derived from the GlasgowComa Scale (GCS; Teasdale and Jennett 1974), one studydefines severity by posttraumatic amnesia (PTA) duration(Himanen et al. 2005).

The time of scan post-injury has also varied considerablyfrom study to study with the least amount of time being amedian of one day (Warner et al., 2010), up to a mean of30 years (Himanen et al. 2005), with one study that did notreport time of scan post-injury (Yurgelun-Todd et al. 2011).Additionally, most of these studies were performed using a1.5 T magnet, with only a small number performed using a3 T magnet (e.g., Ding et al. 2008; Trivedi et al. 2007;Warner et al. 2010a; b; Yurgelun-Todd et al. 2011). Thereare also different methods used to evaluate brain injuries,ranging from manual and automated measures of lesion vol-ume (e.g., Cohen et al. 2007; Ding et al. 2008; Schonberger etal. 2009), to volume analysis (e.g., Anderson et al. 1995;Anderson et al. 1996; Bergerson Bergeson et al. 2004; Bigleret al. 1997; Ding et al. 2008; Gale et al. 1995; Himanen et al.2005; Mackenzie et al. 2002; Schonberger et al. 2009;Strangman et al. 2010; Tate and Bigler 2000; Trivedi et al.2007; Warner et al. 2010a; b; Wilde et al. 2004; Wilde et al.2006; Yount et al. 2002), to voxel-based-morphometry(VBM; Gale et al. 2005), to texture analysis (Holli et al.2010a and b), to semi-automated brain region extraction

based template (SABRE) analysis (Fujiwara et al. 2008;Levine et al. 2008), to the use of FreeSurfer for volumetricanalysis of multiple brain regions (e.g., Strangman et al. 2010;Warner et al. 2010a; b; Yurgelun-Todd et al. 2011).

With all the differences among the studies, the mostimportant take home message is that MRI can be used todetect brain abnormalities in patients with TBI. It is also notsurprising that the injuries that are most apparent are ob-served in more moderate and severe cases of TBI. Further,the volume of lesions can be detected, although whether ornot these lesions are in frontal or non-frontal regions doesnot seem to differentiate between groups on measures ofcognitive function (Anderson et al. 1995). Mild TBIpatients, nonetheless, evince MR lesions in 30% of a sampleof 20 patients (Cohen et al. 2007), and in one study, func-tional outcome was correlated with lesion volume andcerebral atrophy, although this study did not analyze,separately, mild, moderate, and severe cases of TBI(Ding et al. 2008).

Overall brain volume reduction (atrophy) also seems tobe a common finding in what are likely to be more severepatients (e.g., Cohen et al. 2007; Ding et al. 2008; Gale et al.1995; Gale et al. 2005; Levine et al. 2008; Mackenzie et al.2002; Trivedi et al. 2007; Warner et al. 2010a; Yount et al.2002), and there are also volume reductions noted in overallgray matter (e.g., Cohen et al. 2007; Ding et al. 2008;Fujiwara et al. 2008; Schonberger et al. 2009; Trivedi etal. 2007), with a finding also of gray matter volume reduc-tion in the frontal lobe (e.g., Fujiwara et al. 2008; Strangmanet al. 2010; Yurgelun-Todd et al. 2011), and in frontal andtemporal lobes in some cases (e.g., Bergeson et al. 2004;Gale et al. 2005; Levine et al. 2008). Additionally, Bergesonet al. (2004) reported a correlation between frontal andtemporal lobe atrophy and deficits in memory and executivefunction in patients with a range of severity from mild, tosevere (GCS; 3-14).

Overall reduction in white matter has also been reported(e.g., Ding et al. 2008; Levine et al. 2008; Schonberger et al.2009), as well as white matter reduction at the level of themesencephalon, corona radiata, centrum semiovale (Holli etal. 2010a and b), and corpus callosum (Holli et al. 2010aand b; Warner et al. 2010a; Yount et al. 2002). Ding andcoworkers noted that the changes in white and gray matterover time were correlated with acute diffuse axonal injuriesand the latter predicted post-injury cerebral atrophy.

More specific reductions in volume in brain regions havealso been observed, including in the hippocampus (Bigler etal. 1997; Himanen et al. 2005; Strangman et al. 2010; Tateand Bigler 2000; Warner et al. 2010a), amygdala (e.g.,Warner et al. 2010a; b), fornix (Gale et al. 1995; Tate andBigler 2000), thalamus (e.g., Strangman et al. 2010; Warneret al. 2010a; Yount et al. 2002), regions involving thecingulate gyrus (e.g., Gale et al. 2005; Levine et al. 2008;


Tab

le2

MRmorph

ometry

stud

ies

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

And

erson

1995

Sub

acute.

≥6weeks.

Not

Specified

Patients:68

TBIpatients(49M,

19F),[G

CS3-15

];38

with

fron

tal

lesion

sand29

with

nofron

tal

lesion

s.

Volum

etricAnalysis.

-Nosign

ificantdifferenceswere

observed

betweenthetwogrou

pson

lesion

size

andventricleto

brain

ratio

(VBR).

Con

trols:Non

e.-Nosign

ificantdifferenceswere

observed

betweengrou

pson

testsof

neurop

sycholog

ical

functio

ning

.

Gale

1995

Chron

ic.

1.5T

Patients:88

TBIpatients(51M,

37F;meanage28

.5),[G

CS3-

15],36

mTBI[G

CS11-15],22

mod

erateTBI[G

CS7-10

],29

severe

TBI[G

CS3-6].

Volum

etricAnalysis.

-Patientshaddecreasedfornix-to-

brainratio

,totalbrainvo

lume,CC

volume;

andincreasedtempo

ral

horn

volume,ventricularvo

lume,

ventricle-to-brain

ratio

,and

interpedun

cularcisternvo

lume.

Average

21mon

ths.

Con

trols:73

controls(36M,37

F;

meanage31

).-Fornix-to-brain

ratio

correlated

with

multip

leneurop

sycholog

ical

measures.

-Cerebralpedu

ncle

andCCvo

lume

correlated

with

neurop

sycholog

ical

testsof

motor

functio

n.

-GCSwas

correlated

with

fornix-to-

brainratio

,internal

capsulevo

lume,

brainvo

lume,andcerebralpedu

ncle

volume.

And

erson

1996

Sub

acuteandChron

ic.

Not

Specified

Patients:63

TBIpatients(45M,

18F);35

with

lesion

s(26M,9

F;

meanage29

.43),28

with

out

lesion

s(19M,9F;meanage

31.33).

Volum

etricAnalysis

-Sub

jectswith

lesion

shad

sign

ificantly

smallerthalam

i,high

erVBR,andlower

GCS.

≥6weeks.

-Moresevere

injuries

(GCS<9)

had

sign

ificantly

smallerthalam

icvo

lumes

andgreaterVBRthan

less

severely

injuredsubjects.

Con

trols:33

controls(26M,9F;

meanage29

.24).

-VBRwas

negativ

elycorrelated

with

GCSandthalam

icvo

lume,and

positiv

elycorrelated

with

lesion

volume.

-GCSwas

negativ

elycorrelated

with

lesion

volume,andpo

sitiv

ely

correlated

with

thalam

icvo

lume.

Bigler

1997

Sub

acuteandChron

ic.

1.5

Patients:94

TBIpatients(59M

and

35F;meanage27

)[G

CS3-15

].Volum

etricAnalysis.

-Patientsrelativ

eto

controlsshow

edredu

cedhipp

ocam

palvo

lumeand

44scans≤

100days

post-injury,

55scans>

100days

post-injury.


Tab

le2

(con

tinued)

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

temporalhorn

enlargem

ent.These

measurescorrelated

with

cogn

itive

outcom

e.

Con

trols:96

controls(37M,59

F;

meanage31

).-In

patients>70days

post-injury,

temporalhornvolumecorrelated

with

IQ,and

hippocam

palvolum

ecorrelated

with

verbalmem

oryfunction.

Tate

2000

Sub

acuteandChron

ic.

≥2mon

ths.

1.5

Patients:86

TBIpatients(58M,

28F;

meanage30.9),[G

CS3-15].

Volum

etricAnalysis.

-Decreased

fornix

andhipp

ocam

pal

volumein

patientsversus

controls

Con

trols:46

controls(31M,15

F;

meanage37

.21).

-Fornixandhipp

ocam

palvo

lumes

correlated

with

degree

ofinjury

severity

inpatients.

-Hippo

campalv

olum

ecorrelated

with

mem

oryfunctio

ning

.

MacKenzie

2002

Sub

acuteandChron

ic.

1.5T

Patients:14

patients(m

eanage

36.1)[G

CS9-15

];11

with

mTBI

[GCS13

-15],and3with

mod

erateTBI[G

CS9-12

].

Volum

etricAnalysis.

-Brain

volumes,C

SFvo

lumes,and

%Volum

eof

Brain

Parenchym

a(V

BP)

wereno

tsign

ificantly

different

betweenpatientsandcontrolsat

the

sing

letim

epo

int.

14patientsat

>3mon

thsafter

injury,7patientsat

2tim

epo

ints>3mon

thsapart.

Con

trols:10

controls(m

eanage

34.9)un

derw

enton

eMRsession,

and4/10

underw

ent2sessions>

3mon

thsapart.

-Rateof

declinein

%VBPandchange

in%VBPbetweenthefirstand

second

timepo

intswere

sign

ificantly

greaterin

patients.

-Chang

ein

%VBPwas

greaterin

patientswith

loss

ofconsciou

sness

than

inthosewith

out.

You

nt20

02Chron

ic.

1.5T

Patients:27

patients(18M,9F;

meanage26

)with

TBI,

[GCS4-14

].Nofocallesion

sor

infarctio

nson

MRI.

Volum

etricAnalysis.

-Patientshadsign

ificantatroph

y,prim

arily

inthepo

steriorcing

ulate

gyrus,anddegree

ofatroph

ywas

correlated

with

severity

ofinjury.

Average

22.8

mon

ths.

Con

trols:12

ageandgend

er-

matched

controls.

-Patientsalso

hadredu

cedCCand

thalam

iccross-sectionalsurface

areas,with

associated

increasedlat-

eral

ventricularvo

lume,as

wellas

redu

cedbrainvo

lumeandincreased

ventricle-to-brain

ratio

.

-Neuropsycho

logicalperformance

was

notrelatedto

changesin


Tab

le2

(con

tinued)

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

cing

ulategy

ruscross-sectional

surfacearea

intheTBIpatients.

Bergeson

2004

Sub

acuteandChron

ic.

1.5T

Patients:75

TBIpatients(50M,

25F;m

eanage32

.9)[G

CS3-14

].Volum

etricAnalysis.

-Patientshadsign

ificantly

increased

atroph

yinfron

taland

tempo

rallob

escomparedto

controls.

≥90

days.

Con

trols:75

controls(50M,25

F;

meanage31

.4).

-Atrop

hyin

fron

talandtempo

ral

lobescorrelated

with

deficitsin

mem

oryandexecutivefunctio

n.

Wild

e20

04Sub

acuteandChron

ic.

1.5T

Patients:77

patients[G

CS3-15

];25

TBIandpo

sitiv

ebloo

dalcoho

llevel(BAL)and52

TBIwith

negativ

eBAL.

Volum

etricAnalysis.

-Increasedgeneralbrainatroph

ywas

observed

inpatientswith

apo

sitiv

eBALand/or

ahistoryof

mod

erateto

heavyalcoho

luse.

≥90

days.

Con

trols:Non

e.

Gale

2005

Chron

ic.

1.5T

Patients:9patientswith

ahistoryof

TBI(8

M,1F;meanage29

.1),

[GCS5-15

].

Vox

elBased

Morph

ometry.

-Patientsshow

edredu

cedgray

matter

concentrationin

fron

taland

tempo

ralcortices,cing

ulategy

rus,

subcortical

gray

matter,andin

the

cerebellu

m.

App

roximately1year

(mean10

.6mon

ths).

Con

trols:9controls:(8

M,1F;

meanage28

.8).

-Decreased

gray

matterconcentration

was

also

correlated

with

lower

scores

ontestsof

attentionandlower

GCS.

Him

anen

2005

Chron

ic.

1.5T

Patients:61

patients(41M,20

F;

meanageat

injury

29.4);17

mTBI[post-traumatic

amnesia

(PTA

)<1hr],12

mod

erateTBI

[PTA

1–24

hrs],11

severe

[PTA

1-7days],21

very

severe

[PTA

>7days][G

CSno

trepo

rted].

Volum

etricAnalysis.

-Reduced

hipp

ocam

palandincreased

lateralventricularvo

lumes

were

significantly

associated

with

impaired

mem

oryfunctio

ns,m

emory

complaints,andexecutive

functio

ns.

Average

30years.

Con

trols:Non

e.-Volum

eof

thelateralventricles

was

thebestpredictorof

cogn

itive

outcom

e.

-There

was

also

amod

estrelationship

betweenseverity

ofinjury

and

cogn

itive

performance.

Wild

e20

06Suacute

andChron

ic.

1.5T

Patients:60

patientswith

severe-

to-m

ild[G

CS3–15

]TBI(38M,

22F;meanage28

.6).

Volum

etricAnalysis.

-LongerPost-Traum

aticAmnesia

(PTA

)duratio

npredictedincreased

brainatrophy(ventricletobrainratio

).≥90

days.

Con

trols:Non

e.-6%

increase

intheod

dsof

developing

lateratroph

ywith

each

additio

naldayof

PTA

.


Tab

le2

(con

tinued)

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

Coh

en20

07Acute

toChron

ic.

1.5T

Patients:20

mTBIpatients(11M,

9F;m

edianage35),[G

CS13-15].

LesionDetectio

nand

Volum

etricAnalysis.

-MRim

aging-visiblelesion

swere

seen

in30

%of

patients.

7patientswith

in9days,

13patientsfrom

1.2mon

thsto

31.5

(average

4.6years).

Con

trols:19

controls(11M,8F;

medianage39

).-The

mostcommon

lesion

swere

punctatefociandgliosisdistantfrom

thetraumasite,kn

ownto

beassociated

with

axon

alinjury

and

gliosisin

region

ssusceptib

leto

sheering

injury.

-Patientsexhibitedincreasedglob

alandgray

matteratroph

y.

-Brain

atroph

ydidno

tdifferentiate

patientswith

andwith

outlesion

s.

Trivedi

2007

Sub

acute.

3T

Patients:37

TBIpatients(27M,

9F,

1N/A;meanage29

.3);11

mTBI[G

CS≥1

3],10

mod

erate

TBI[G

CS9-12

],16

severe

TBI

[GCS≤8

].

Volum

etricAnalysis.

-Patientshadagreaterdeclinein

%brainvo

lumechange

(%BVC)

comparedto

controls.

App

roximately79

days;

rescannedat

approx

imately

409days.

-Greater

%BVCcorrelated

with

long

erdu

ratio

nof

comapo

st-injury.

Con

trols:30

controls(13M,7F;

meanage24

.5).

Ding

2008

Acute

andChron

ic.

3T

Patients:20

patientswith

TBI

(13M,7F;meanage26

);4

complicated-m

ildTBI[G

CS

≥13],4mod

erateTBI[G

CS9-

12];and12

severe

TBI[G

CS≤8

].

FLAIR

LesionVolum

eand

Volum

etricAnalysis.

-Chang

ein

who

lebrain,

whitematter,

andgray

mattervo

lumes,correlated

with

acuteFLAIR

Lesions

volume.

(≤1mon

th)and(≥

6mon

ths).

-Volum

eof

acuteFL

AIR

lesions

correlated

with

volumeof

decreased

FLAIR

signalin

thefollo

w-upscans.

Con

trols:20

controls(13M,7F;

meanage28

)-Fun

ctionalou

tcom

ecorrelated

with

acuteFLAIR

lesion

volumeand

chroniccerebral

atroph

y.

-FLAIR

lesion

sim

agingwere

strong

lypredictiv

eof

post-traum

atic

cerebral

atroph

y.

Fujiwara

2008

Chron

ic.

1.5T

Patients:58

TBIpatientsun

derw

ent

MRI;12

mild

[GCS13

-15],27

mod

erate[G

CS9-12

],and19

se-

vere

[GCS3-8].18

patientswith

focalcortical

contusions

and40

with

diffuseinjury

only.

Sem

i-Autom

ated

Segmentatio

n(SABRE).

-There

werepatternsof

region

alvo

lumeloss

associated

with

test

performance

across

allthree

behavioralmeasures.The

taskswere

sensitive

toeffectsof

TBI.

App

roximately1year.

Con

trols:25

controls;behavioral

testingon

ly.

-Perform

ance

intheSmell

IdentificationTest(SIT),Object

Alternation(O

A),andtheIowa

Gam

blingTask

(IGT)was

correlated

with

gray

matterloss

includ

ing


Tab

le2

(con

tinued)

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

ventralfron

talcortex.SIT

was

the

mostsensitive

toventralfron

tal

cortex

damage,even

inpatients

with

outfocallesion

s.

-The

SIT

was

furtherrelatedto

tempo

rallobe

andpo

sterior

cing

ulate/retrosplenialvo

lumes.

-OAandtheIG

Twereassociated

with

superior

medialfron

talvo

lumes.

Levine

2008

Chron

ic.

1.5T

Patients:69

TBIpatients;13

mild

[meanGCS14

.6],30

mod

erate

[meanGCS11.1],26

severe

[meanGCS6.7].

Sem

i-Autom

ated

Segmentatio

n(SABRE).

-Stepw

isedo

se–respon

serelatio

nship

betweenparenchy

mal

volumeloss

andTBIseverity.

≥1year.

Con

trols:12

age-

andsex-matched

controls.

-Patientswith

mod

erateandsevere

TBIweredifferentiatedbasedon

brainvo

lumepattern

from

those

with

mild

TBI,who

werein

turn

differentiatedfrom

non-injured

controlsubjects.

-Volum

eloss

correlated

with

TBI

severity,particularly

widespreadin

white

matterandsulcal/sub

dural

CSF.

-The

mostreliableeffectswere

observed

inthefron

tal,tempo

ral,

andcing

ulateregion

s,althou

gheffectswereob

served

tovarying

degreesin

mostbrainregion

s.

-Focal

lesion

swereassociated

with

greatervo

lumeloss

infron

taland

tempo

ralregion

scomparedto

subjectswith

outfocallesion

s.

-Significantly

redu

cedfron

taland

tempo

ralvo

lumeloss

seen

inpatientswith

diffuseinjury

comparedto

controls.

Schon

berger

2009

Chron

ic.

1.5T

Patients:99

patientswith

mild

tosevereTBI(74M,24F;m

eanage

34.5),[G

CS3-15

].

LesionVolum

e,Autom

ated

Segmentatio

nand

Volum

etricAnalysis

(SPM5).

-Older

ageandlonger

posttraumatic

amnesia(PTA

)correlated

with

larger

lesion

volumes

inbothgray

andwhite

matterin

almostallbrainregions.

Average

2.3years.

Con

trols:Non

e.-Older

agewas

correlated

with

smallergray

mattervo

lumes

inmost


Tab

le2

(con

tinued)

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

neo-cortical

brainregion

s,while

long

erPTA

was

associated

with

smallerwhite

mattervo

lumes

inmostbrainregion

s.

-Con

clud

edthat

olderageworsens

theim

pact

ofbraininjury;PTA

isa

good

measure

ofseverity

butisno

trelatedto

theparticular

kind

ofinjury.

Holli

2010

(a)

Acute.

1.5T

Patients:42

mTBIpatients(17M,

25F;m

eanage38

),[G

CS13

-15].

Allpatientshadno

rmal

clinical

CTandMRI.

Texture

analysis(M

aZda).

-Significant

differenceswerefoundin

texturebetweentheleftandrightside

ofmesencephalon,inthewhitematter

ofthecorona

radiate,andin

portions

ofcorpus

callo

sum

inpatients.

≤3weeks.

Con

trols:10

controls(4

M,6F;

meanage39

.8).

-Con

trolswereless

asym

metricalin

texturethan

patients.

Strangm

an20

10Chron

ic.

1.5T

Patients50

TBIpatients(36M,

14F;meanage47

.2)with

TBI

with

repo

rted

mem

ory

difficulties;12

mild

[LOC

≤30min,or

GCS13

-15],12

mod

erate[LOC30

min

-24hr

orGCS9-12

],24

severe

[LOC

>24

hror

GCS<9],2n/a.

Autom

ated

Segmentatio

nand

Volum

etricAnalysis

(FreeSurfer).

-Volum

eredu

ctionin

the

hipp

ocam

pus,lateralprefrontal

cortex,thalam

us,andseveral

subregions

ofthecing

ulatecortex

predictedrehabilitationou

tcom

e.

Average

11.5

years.

Con

trols:Non

e.

Warner

2010

aAcute.

3T

Patients:25

patientswith

diffuse

traumatic

axon

alinjury

(18M,

7F;meanage26

.8),[G

CS3-15

].

Autom

ated

Segmentatio

nand

Volum

etricAnalysis

(FreeSurfer).

-Patientsshow

edmajor

glob

albrainatroph

ywith

ameanwho

le-

brainparenchy

mal

volumeloss

of4.5%.

Initial

median1daypo

st-

injury.Follow-upat

median

7.9mon

thspo

st-injury.

Con

trols:22

Con

trols(14M,8F,

meanage32

.4).

-In

patientssign

ificantly

decreased

volumewas

observed

inthe

amyg

dala,hipp

ocam

pus,thalam

us,

CC,putam

en,precuneus,p

ostcentral

gyrus,paracentrallobu

le,and

parietal

andfron

talcortices.

-Caudateandinferior

tempo

ralcortex

didno

tshow

atroph

yin

patients.

-Lossof

who

le-brain

parenchy

mal

volume,atroph

yof

theinferior

parietal

cortex,pars

orbitalis,

pericalcarinecortex,and


Tab

le2

(con

tinued)

FirstAutho

rYear

Tim

ePost-Injury

Magnet

Sub

jects

AnalysisMetho

dMainFinding

s

supram

arginalgyruspredicted

long

-term

disability.

Warner

2010

bAcute.

3T

Patients:24

patientswith

diffuse

traumatic

axon

alinjury

(16M,

8F;meanage27

.2)[m

eanGCS

6.4;

rang

eno

trepo

rted].

Autom

ated

Segmentatio

nand

Volum

etricAnalysis

(FreeSurfer).

-Bilateralthalam

usvo

lumes

correlated

with

processing

speed.

Initial≤1weekpo

st-injury.

Follow-upat

4-16

mon

ths

post-injury.

Con

trols:Non

e.

-Amyg

dala,hippo

campal,andarang

eof

cortical

region

volumes

were

correlated

with

learning

andmem

ory

performance.

-Thalamus,superior

fron

tal,superior

parietal,andprecun

euscortices

correlated

with

executivefunctio

n.

-Sub

cortical

andcortical

brain

volumes

wereassociated

with

learning

andmem

oryandprocessing

speed,

butno

texecutivefunctio

n.

Yurgelun-Tod

d20

11Not

Reported.

3T

Patients:15

patientswith

oneor

moreTBI(allM;m

eanage34

.9);

14with

atleaston

emild

TBI;1

with

mod

erate/

severe

TBI.[G

CS

notrepo

rted;(m

ild,mod

erateand

severe

accordingto

The

Ohio

State

University

—TBI

IdentificationMetho

d(O

SU-TBI)].14

subjectswere

norm

alon

aclinical

MRI.

Autom

ated

Segmentatio

nand

Volum

etricAnalysis

(FreeSurfer).

-Patientsexhibitedlower

righ

t,left

andtotalfron

tallobe

volumethan

patients.

Con

trols17

controls(allM;mean

age34

.0).

-Right

andtotalcing

ulum

FAcorrelated

with

suicidal

ideatio

nand

impu

lsivity.

Key:M

male,Ffemale,GCSGlasgow

Com

aScale,C

CCorpusCallosum.A

cutedefinedas

under1month,subacuteisdefinedas

>1month

but<6months,andchronicisdefinedas

>6months


Strangman et al. 2010; Yount et al. 2002), as well as in-creased lateral ventricles, temporal horns of the lateral ven-tricles, and/or ventricular brain ratio (e.g., Anderson et al.1995; Bigler et al. 1997; Gale et al. 1995; Himanen et al.2005; Wilde et al. 2006; Yount et al. 2002). Reduced vol-ume in subcortical gray matter regions has also beenreported (Gale et al. 2005), as has reduced volume in theputamen, precuneus, post-central gyrus, paracentral lobule,parietal cortex, pericalcarine cortex, and supramarginalgyrus (Warner et al. 2010a).

Taken together, these findings suggest that morphometricbrain abnormalities are observed in patients with TBI, al-though many studies did not separate mTBI from moderateand severe TBI. Moreover, in addition to combining mildTBI with moderate and severe cases, the differences amongthe studies reviewed make the interpretations of findingsdifficult, and have led to a sponsored work group meetingin 2009, entitled “the Common Data Elements Neuroimag-ing Working Group.” This work group was established tomake recommendations for “common data elements” thatwill likely be useful for characterizing “radiological featuresand definitions,” which are critically needed to characterizeTBI (Duhaime et al. 2010). This work group was sponsoredby multiple national healthcare agencies, including the De-fense Centers of Excellence (DCOE), The National Instituteof Neurological Diseases and Stroke (NINDS), The Nation-al Institute on Disability and Rehabilitation Research(NIDRR), and the Veterans Administration (VA). This workgroup was also charged with making recommendations forradiological image acquisition parameters that should bestandardized in the quest for delineating brain injuries inTBI, particularly given that different imaging acquisitionparameters have been used for different applications, as wellas for different research studies. Further, if radiologicalimaging is to be used as surrogate endpoints for evaluatingtreatment in clinical trials, then some type of standardizationof the image acquisition parameters is an important consid-eration (Duhaime et al. 2010; Haacke et al. 2010).

Haacke et al. (2010) also notes that brain imaging, partic-ularly using more advanced imaging techniques, affords animportant and unique opportunity to visualize and to quantifybrain injuries in TBI, which is particularly useful in what hedescribes as the 90 % of cases that are categorized as mild. Heand his coworkers note that a systematic characterization ofbrain injuries in TBI will likely lead to increased predictivepower in the area of clinical trials and clinical interventions.The new methods that Haacke and coworkers describe (2010)include, DTI, SWI, MRS, SPECT, PET, Magnetoencephalog-raphy, and Transcranial Doppler. Haacke et al. (2010) alsodiscuss the importance of combining techniques in the samesubjects, such as PET and fMRI.

Selecting optimal protocols has been the focus of inves-tigation in other disorders such as Alzheimer’s disease (e.g.,

Leung et al. 2010) and schizophrenia (e.g., Zou et al. 2005).One has to keep in mind, however, that for multi-centerstudies, not all centers have the most up to date, state-of-the-art imaging, and for this reason some compromisesneed to be made to acquire the best imaging data possibleacross centers, with a focus on more state-of-the-art andexperimental protocols being more possible at researchcenters. Nonetheless, the points raised by this workinggroup (Duhaime et al. 2010; Haacke et al. 2010) are im-portant and there is much room for improvement in thekind of imaging data and analyses performed in the inves-tigation of TBI. For mTBI this becomes even more crucialas subtle, small changes are unlikely to be detected usingmore gross radiological measures of brain pathology. Be-low, we review findings from diffusion imaging studies ofmTBI, an important technology for characterizing diffuseaxonal and focal axonal injuries, and which is among themost promising imaging tools for revealing subtle, smallareas of brain injury in mTBI.

Review of DTI findings in mTBI

DTI is a sensitive measure of axonal injury that is particu-larly important for evaluating small and subtle brain alter-ations that are characteristic of most mTBI. DTI will alsolikely become an important diagnostic tool for individualcases of mTBI, particularly where MR and CT are negative.With respect to the latter, DTI can depict multifocal anddiffuse axonal injuries in individual cases of mTBI. Norma-tive atlases of DTI derived measures that depict anatomicalvariation in healthy controls can also be created so thatindividual cases may then be compared with an atlas inorder to discern the pattern of pathology in an individualcase (e.g., Bouix et al. 2011; Pasternak et al. 2010). We willreturn to the use of atlases in the section on future directionsof research, which follows.

Below we review DTI findings in mTBI. Table 3 liststhose studies that focus on mTBI only, or that include othercategories such as moderate and severe TBI, but nonethelessconduct statistical analyses separately for the mTBI group.Table 4, on the other hand, includes those studies that do notseparate findings in mild TBI from moderate and severeTBI, making findings from these studies more similar tomany of the findings reported for morphometry measures inTable 2, where mild, moderate, and severe TBI were oftennot analyzed separately.

Arfanakis and coworkers (2002) were the first to use DTIto investigate diffuse axonal injuries in mTBI. They inves-tigated FA and MD in anterior and posterior corpus cal-losum, external capsule, and anterior and posterior internalcapsule in 5 patients with acute mTBI (within 24 h of injury)and 10 controls. These brain regions were selected as likely


showing damage based on post-mortem findings. Resultsshowed no mean diffusivity (MD) differences betweenmTBI patients and controls. Group differences were, how-ever, observed for the corpus callosum and the internalcapsule, where fractional anisotropy (FA) was reduced inthe mTBI group compared with controls. Importantly, thelatter findings are consistent with histopathology findings inmTBI patients who died from other causes (e.g., Adams et al.1989; Bigler 2004; Blumbergs et al. 1994; Oppenheimer1968). These investigators concluded that DTI is an importantearly indicator of brain injury in mTBI and has the potentialfor being an important prognostic indicator of later injury.These investigators were also prescient in noting that longitu-dinal studies are needed to understand the dynamic nature ofmTBI and how it may reflect changes in brain alterations overtime. They did not, however, include a follow up scan ofsubjects in their study.

Inglese and coworkers (2005) used DTI measures to inves-tigate both acute (n020mTBI mean of 4 days post-injury) andchronic mTBI patients (n026 mTBI, mean of 5.7 years post-injury) compared with controls (n029). These investigatorsused FA andMDmeasures of diffusion to detect abnormalitiesin the centrum semiovale, the corpus callosum, and the inter-nal capsule. They reported FA reduction in all three structuresin mTBI compared with controls, as well as increased MD inthe splenium of the corpus callosum, which was higher in theacute sample, but lower in the posterior limb of the internalcapsule compared to the chronic sample. These findings aresimilar to the Arfanakis et al. (2002) study, although theseinvestigators also included patients with chronic TBl. Thesefindings also highlight the importance of detecting brain alter-ations that change over the course of brain injury.

Miles et al. (2008) also investigated mTBI patients onaverage 4 days post-injury and again at 6 months follow upon neuropsychological measures (only). They reported in-creased MD and reduced FA in the centrum semiovale, genuand splenium of the corpus callosum, and in the posteriorlimb of the internal capsule in mTBI compared with con-trols. Moreover, 41% of mTBI cases evinced cognitiveimpairments at baseline, and 33% at follow up 6 monthslater. More specifically, while there was no correlation be-tween baseline measures of MD/FA and cognitive measures,baseline MD and FA correlated significantly with cognitivemeasures at follow up, with FA predicting executive func-tion, and a trend for MD to be associated with reaction time.These findings suggest that there may be predictors ofcognitive function from baseline measures of impairmentas measured on DTI, even when there are no correlationsbetween these measures and cognitive measures at baseline.These investigators also did not include follow up DTI scansat 6 months, only cognitive follow up.

Other investigators examining acute and subacute timeperiods report similar findings. For example, one study of

mild and moderate TBI was conducted within 5 to 14 dayspost-injury in patients who had positive findings on clinicalCT. TBI patients showed reduced FA in the genu of thecorpus callosum (mTBI only) and increased radial diffusiv-ity (RD) in the genu of the corpus callosum in both mild andmoderate TBI (Kumar et al. 2009). Matsushita and cow-orkers (2011) investigated both mild and moderate TBIpatients with a median of 3.5 days post-injury. Theyreported decreased FA in the splenium of the corpus cal-losum in mTBI compared with controls. Other parts of thecorpus showed reduced FA in the moderate group includinggenu, stem, and splenium. These findings suggest moreabnormalities in the moderate TBI group.

Bazarian and coworkers (2007) acquired DTI data frommTBI patients within 72 h of brain trauma and they includeda measure of postconcussive symptoms and quality of lifeassessments. They repeated these assessments 1 month later.Decreased trace was reported particularly in the left anteriorinternal capsule, and increased median FA was reported inthe posterior corpus callosum in mTBI compared with con-trols. Of note, trace measures correlated with postconcussivescores at 72 h and at 1 month post-injury and FA valuescorrelated with 72 h postconcussive score as well as with atest of visual motor speed and impulse control. All subjectsevinced normal findings at time of injury on conventionalCT, suggesting that normal findings on conventional CT andMRI are inadequate for characterizing the kind of injuryobserved in mTBI.

The findings of lower trace and increased FA, however,are more perplexing as the expectation is that if there isdamage to the integrity of white matter then FA will bereduced, and MD likely increased, and this is often reported(see Table 3 and 4). An increase in FA and a decrease in MDmay indicate axonal swelling that occurs early in the courseof injury and may correlate with poor clinical outcome.Bazarian and coworkers (2007) have also suggested thispossibility.

Bazarian and coworkers (2011), in another study thatinvolved one athlete with a concussion and an additional8 athletes with multiple (26-399) subconcussive blows tothe head, reported FA and MD changes that were greatest inthe one concussed athlete, intermediate in the subconcussivegroup, and lowest for controls. Of note, they observed thatboth FA and MD changed in both directions, i.e., increasesand decreases were observed. Kou and coworkers (2010)suggest that increased MD and decreased FA may indicatevasogenic edema, which will likely resolve over time,whereas increased FA and reduced MD may indicate cyto-toxic edema, reflected by axonal swelling and more restrict-ed diffusion of water, thereby explaining the increase in FAand decrease in MD. Thus increased FA and associateddecreased MD, early in the course of brain injury, mayindicate a poor prognosis and hence identifying this group


Tab

le3

DTIstud

iesin

mild

TBI

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Arfanakis

2002

Acute.

1.5T

Patients:5patients(3

M,

2F;m

eanage35

.6)[G

CS

13-15].Con

ventionalCT

norm

al.

AnalysisandMetho

ds:ROI

Analysis.

5ROIstructures

with

selected

volumes

(i.e.,

representativ

eon

ly),in

the

leftandrigh

themisph

eres:

Anteriorandpo

steriorCC,

external

capsule,anterior

andpo

steriorinternal

capsule.

-Patientsbu

tno

tcontrols

show

edFA

differencesfor

ROIs

betweenho

molog

ous

hemisph

eres.

(24hrs).In2patients,baselin

ecomparedwith

DTIat1mon

thfollo

w-up.

Con

trols:10

controls(5

M,

5F;meanage28

.9years).

Dependent

Measures:Trace,FA

andLI.(LatticeIndex).

-Reduced

FAin

patientsin

theinternalcapsuleandCC

comparedto

controls.

-Notracedifferences

repo

rted.

-Atfollo

w-uptwopatients

show

edim

prov

ementin

somebu

tno

tallareas.

Inglese

2005

Acute

andChron

ic.

1.5T

Patients:46

patients(29M,

17F;meanage36

)[G

CS

13-15].Con

ventional

MRIshow

edcontusions

in5patientsand

hematom

asin

3.

AnalysisandMetho

ds:Who

le-

Brain

Histogram

Analysisand

ROIAnalysis.

3ROIstructures

with

selected

voxels(i.e.,

representativ

e,on

ly):the

centrum

semiovale,CC,

andinternal

capsule.

-Nodifferencesbetween

grou

psusinghistog

ram-

derivedmeasures.

In20

ofthepatients,im

aging

was

performed

atameanof

4.05

days

post-injury.

Con

trols:29

age-

andsex-

matched

controls(15M,

14F;meanage35

).Negativefind

ings

onconv

entio

nalMRI.

Dependent

Measures:FA

and

MD.

-Patientsshow

edredu

cedFA

intheCC,internal

capsule,

andcentrum

semiovale,and

increasedMD

intheCC

andinternal

capsule,

comparedto

controls.

Intheremaining

26,im

aging

was

performed

ameanof

5.7yearspo

st-injury.

-MD

insplenium

ofCCwas

high

erin

patientsscanned

earlierbu

tlower

inthe

posteriorlim

bof

the

internal

capsule,compared

topatientsscannedlater.

Bazarian

2007

Acute.

3T

Patients:6subjects[G

CS

13-15].Con

ventionalCT

norm

al.

AnalysisandMetho

ds:2types

ofwho

lebrainanalyses

performed:VBM

andano

vel,

quantileanalysis.

1)Who

lebrainanalysis.

-Who

lebrainanalysis

show

edlower

1stp

ercentile

tracevalues

inpatients

comparedwith

controls.

72hours:post-concussive(PCS)

andneurobehavioraltestin

g.

Con

trols:6age-

andsex-

matched

orthop

edic

controls;Con

ventional

CTno

rmal.Sub

jects

(patientsandcontrols)

includ

ed8M

and4F;

aged

18-31.

ROIan

alysis:Regions

ofinterestwerealso

analyzed

usingaqu

antileapproach.

2)5ROIs

wereselected

and

manually

outlinedin

nativ

espace:

anterior

internal

capsule,po

steriorinternal

capsule,anterior

CC,

posteriorCC,andexternal

capsule.

-Trace

from

who

lebrain

analysiscorrelated

with

PCSscores

at72

hrsandat

1mon

thpo

st-injury.

At1mon

th:qu

ality

oflifeand

PCSassessments(n=11).

DependentMeasures:FA

,Trace.

PCS,neurob

ehavioralbattery,

andqu

ality

oflifeassessments.

-Trace

from

who

lebrain

analysiswas

lower

inthe

leftanterior

internal

capsule,andshow

edhigh

ermedianFA

values

inthe

posteriorCCin

patients

comparedwith

controls.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

-FA

values

correlated

with

72-h

PCSscore,visual

motor

speed,

andim

pulse

control.

-Finding

ssugg

estlower

traceandincreasedFA

may

indicate

axon

alsw

ellin

gearlyin

thecourse

ofaxon

alinjury,which

correlates

poorly

with

clinical

outcom

e.

Kraus

2007

Chron

ic.

3T

Patients:37

TBIpatients;

20mTBI(8

M,12

F;

meanage35

.85)

[LOC

<30

min],17

mod

erateto

severe

TBI(8

M,9F;

meanage34

.88)

[LOC

>30

min

and/or

GCS

<13

].5in

each

TBIgrou

pwith

otherassociated

trauma.

AnalysisandMetho

ds:ROI

analysis.ROIs

draw

non

standardized

space,FA

maps.

13ROIstructures:anterior

andpo

steriorcorona

radiata,cortico-spinal

tracts,cing

ulum

fiber

bund

les,external

capsule,

forcepsminor

andmajor,

genu

,bod

yandsplenium

oftheCC,inferior

fron

to-

occipitalfasciculus,

superior

long

itudinal

fasciculus

andsagittal

stratum.

-FA

decreaseswereseen

inall13

ROIs

formod

erate/

severe

TBI,bu

ton

lyin

the

cortico-spinal

tract,sagittal

stratum,andsuperior

long

itudinalfasciculus

inmTBI.

≥6mon

thsou

tfrom

injury;

average10

7mon

thsforall

TBIsubjects.

Con

trols:18

controls(7

M,

11F;meanage32

.83).

Dependent

Measures:FA

,RD,

AD,w

hite

matterload

defined

astotalnum

berof

region

swith

redu

cedFA

.Neurocogn

itive

measuresrelevant

toattention,

mem

ory,andexecutive

functio

n.

-Patientswith

mod

erate/

severe

TBIcomparedto

controlsshow

edincreased

AD

andRD.

-Patientswith

mTBI

comparedto

controls

show

edincreasesin

AD,

butno

tRD,sugg

estin

gmyelin

damageno

tpresent.

-Whitematterchangesalon

gaspectrum

from

mTBIto

mod

erate/severe

TBIand

axon

albu

tno

tmyelin

damagemay

characterize

mTBI.

Lipton

2008

Chron

ic.

8mon

thsto

3years

Retrospectiv

estud

yof

consecutiveadmission

sof

mTBI.

1.5T

Patients:17

mTBIpatients

(8M,9F;age26

–70

)[G

CS13

-15,

LOC

<20

min].NegativeCT/

MRIfind

ings

attim

eof

initial

injury.Later,at

timeof

scanning

,1mTBI

subjecth

adasm

allareaof

AnalysisandMetho

ds:Who

le-

brainhistog

ram

analysisand

Vox

el-w

iseanalysisof

retrospectivecases.

Who

le-brain

analysis.

-mTBIpatientsshow

eddecreasedFA

andincreased

MD

inCC,subcortical

white

matter,andinternal

capsules,bilaterally.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

sign

alintensity

likelydu

eto

gliosis.

Con

trols:10

controlsof

similarageandgend

erdistribu

tion.

Negative

MRIfind

ings

attim

eof

scan.

Dependent

Measures:FA

,MD.

Histogram

parameters,i.e.,

kurtosis,skew

.

-Who

lebraindecrease

inFA

inmTBIby

histog

ram

analysis.

-Reduced

FAandincreased

MD

sugg

eststhat

mTBI

may

beat

oneendof

the

diffuseaxon

alspectrum

andthepatients

complaining

ofsymptom

smanymon

ths,andin

some

casesseveralyears,po

st-

injury

arecharacterizedby

lack

ofwhite

matter

integrity

inbrainregion

skn

ownto

beaffected

inTBI.

Miles

2008

Acute.

1.5T

Patients:17

patients(11M,

6F;meanage33

.44,

rang

e18

-58)

[GCS13

-15,

LOC<20

min].

AnalysisandMetho

ds:ROI

analysis.

StructuralROIusingcircles:

centra

semiovale,thegenu

andthesplenium

oftheCC,

andthepo

steriorlim

bof

theinternal

capsule.

-mTBIpatientshad

increasedMD

andredu

ced

FAcomparedwith

controls.

Average

4days

(range:1–

10).

Con

trols:29

sex-

andage-

matched

controls(15M,

14F;meanage35

,rang

e18

-61).Not

matched

oneducation.

Dependent

Measures:FA

,MD.

Neuropsycho

logicalmeasures

atbaselin

e(≤24

hour

ofim

aging)

and6mon

thfollo

w-

upfor12

/17mTBI.

-OfthemTBIpatients41

%hadcogn

itive

impairments

atbaselin

eand33

%at

follo

w-up.

Follow-upat

6mon

thsfor

neurop

sycholog

ical

measures.

-Atbaselin

eno

depend

ent

measuresweresign

ificantly

correlated.

-IncreasedMD

and

decreasedFA

atbaselin

ecorrelated

with

cogn

itive

measuresat

follo

w-up.

-Finding

ssugg

estshort-term

predictors

ofcogn

itive

functio

nat

6mon

ths.

(Note:

therewas

noDTIat

6mon

thfollo

w-up).


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Niogi

2008

aSub

acuteandChron

ic.

≥1month

(range

1–65

months).

≥1persistent

symptom

for

postconcussive

syndrome.

3T

Patients:34

patients(18M,

16F;meanage37

.4,

rang

e16

-61).[G

CS13

-15

].11

mTBI-negativ

eMRIfind

ings;11

mTBI

micro-hemorrhage;

12mTBI-no

n-specific

white

matterhy

perintensitiesor

chronichemorrhagic

contusions.

AnalysisandMetho

ds:ROI

Analysis.ManualROI,

ellip

soid

shapes

foreach

ROI.

ROIstructures:un

cinate

fasciculus,anterior

corona

radiata,anterior

aspect

oftheinferior

long

itudinal

fasciculus,genu

oftheCC,

thecing

ulum

bund

le,and

thesuperior

long

itudinal

fasciculus.

-Reduced

FAin

mTBI

patientsin

anterior

corona

radiata(41%

ofpatients),

uncinate

fasciculus

(29%),

genu

oftheCC(21%),

inferior

long

itudinal

fasciculus

(21%),and

cing

ulum

bund

le(18%).

Con

trols:26

controls

(19M,77F;meanage

28.3,rang

e17

-58).

Dependent

Measures:FA

.Reactiontim

eto

Attention

NetworkTask(Fan

etal.

2005).

-Reactiontim

eon

asimple

cogn

itive

task

correlated

tonu

mberof

damaged

white

matterstructures.

-(N

ote:

10/11mTBIwith

negativ

eMRIfind

ings

show

edFA

redu

ctions

relativ

eto

controls.)

Niogi

(Extension

of20

08apaper)

2008

bSub

acuteandChron

ic.

3T

Patients:43

patients(28M,

15F;meanage32

.4)

[GCS13

-15].Negative

find

ings

forconv

entio

nal

MRIim

ages

of12

/43

patients.

AnalysisandMetho

ds:

ROIstructures:un

cinate

fasciculus,anterior

corona

radiata,anterior

aspect

oftheinferior

long

itudinal

fasciculus,genu

oftheCC,

thecing

ulum

bund

le,and

thesuperior

long

itudinal

fasciculus.

-mTBIandcontrolsshow

edasign

ificantcorrelation

betweenattentionalcontrol,

measuredby

the

AttentionalNetworkTask,

andFA

inleftanterior

corona

radiata,as

wellas

asign

ificantcorrelation

betweenmem

ory

performance,measuredby

theCVLT

,andFA

inthe

uncinate

fasciculus,

bilaterally.

≥1mon

thpo

st-injury(m

ean

16.9

mon

ths,rang

e1–

53mon

ths).

Con

trols:23

controls

(17M,6F;meanage

29.9)Negativefind

ings

forconv

entio

nalMRI.

ROIanalysis.ManualROI,

ellip

soid

shapes

foreach

ROI.

-In

mTBI,FA

was

redu

cedin

both

thesebrainregion

scomparedwith

controls.

≥1persistent

symptom

for

postconcussive

synd

rome.

Dependent

Measures:FA

.AttentionNetworkTask(Fan

etal.20

05),CaliforniaVerbal

LearningTest(CVLT

)to

test

mem

oryperformance.

-Finding

ssugg

estFA

canbe

used

asabiom

arkerfor

neurocog

nitiv

efunctio

nanddy

sfun

ction.

Rutgers

2008

aSub

acuteandChron

ic.

Median5.5mon

ths(range

0.1-

109.3mon

ths).

1.5T

Patients:21

mTBIpatients

(12M,9

F;m

eanage32

±9)

[GCS13

-15].17

/21

patientsnegativ

efind

ings

AnalysisandMetho

ds:ROI,

tractography.

ROIstructures:cerebrallob

arwhite

matter,cing

ulum

,CC,anterior

andpo

sterior

limbof

theinternal

-Onaverage,patients

show

edredu

cedFA

in9

region

s,predom

inantly

incerebral

lobarwhite

matter,


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

onMRI;others

contusions

and1extra-

axialhematom

a.

capsules,mesenceph

alon

,brainstem

,and

cerebellu

m.

Cerebrallobarwhite

matter

was

subd

ivided

into

centrum

semiovale,fron

tal

lobe,parietallob

e,tempo

ral

lobe,andoccipitallobe.

cing

ulum

,andCC

comparedto

controls(191

region

s).

Con

trols:11

controls(8

M,

3F;meanage37

±9).No

know

nhistoryof

positiv

eMRIfind

ings.

Dependent

Measures:FA

,vo

lume,ADC,nu

mberand

leng

thof

throug

h-passing

fibers

ineach

ROI,

tractography

measure

ofdiscon

tinuity.

-Discontinuity

onfiber

tracking

was

seen

inon

ly19

.3%

offibers.

-Other

region

sprim

arily

invo

lved

supratentorial

projectio

nfiberbu

ndles,

callo

salfibers,andfron

to-

tempo

ro-occipital

associationfiberbu

ndles.

-The

internal

capsules

and

infratentorial

white

matter

wererelativ

elyun

affected.

-There

was

noassociation

betweentim

einterval

ofscanning

andpo

st-injury

measures.

Rutgers

2008

bChron

ic.

1.5T

Patients:39

TBIpatients

(27M,1

2F;m

eanage34

±12

);24

mild

[GCS13

-15

];9,

mod

erate[G

CS9-

12];and6,

severe

TBI

[GCS≤8

].

AnalysisandMetho

ds:ROI

analysisdo

neby

draw

ingROI

manually

onthepartsof

the

CCon

FAmapsof

each

subject.

ROIstructures:CCgenu

,bo

dy,andsplenium

.-Patientswith

mTBI<

3mon

thspo

st-traum

a(n=

12)show

edredu

cedFA

and

increasedADCin

thegenu

oftheCC.

Average

2.8mon

ths.

Con

trols:10

controls(7

M,

3F;meanage37

±9).No

know

nhistoryof

positiv

eMRIfind

ings.

Dependent

Measures:FA

,ADC,

numberof

fibers.

-Patientswith

mTBI

investigated

>3mon

ths

post-traum

a(n=12

)show

edno

differences.

-Moresevere

traumawas

associated

with

genu

and

splenium

FAredu

ction,

increasedADC,andfewer

numbers

offibers.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Huang

2009

“Post-acute”.

1.5T

Patients:10

patientsmild

TBI(m

eanage25

.0±

11.5;meaneducation

12.7±4.7years)[G

CS13

-15

].7of

10negativ

efind

ings

onconv

entio

nal

CT/M

RI.

AnalysisandMetho

ds:

Probabilistic

tractography,

Tract

Based

SpatialStatistics,

MEG

Fronto-occipitalfasciculus,

superior

long

itudinal

fasciculus,inferior

long

itudinalfasciculus,

uncinate

fasciculus,CC,

andcing

ulum

bund

les.

-Resultspresentedas

acase

series.

Con

trols:14

age-matched

healthysubjects(m

ean

age27

.4±15

.2,mean

education12

.9±

3.2years).

Dependent

Measures:MEG

delta

slow

waves,FA

Autom

ated

Who

leBrain

Analysis.

-MEG

slow

waves

originated

from

cortical

gray

areaswith

redu

ced

DTI.

-In

somecases,abno

rmal

MEG

delta

waves

were

observed

insubjects

with

outob

viou

sDTI

abno

rmality,indicatin

gthat

MEG

may

bemore

sensitive

than

DTIin

diagno

sing

mTBI.

Lipton

2009

Acute.

≤2weeks.

3T

Patients:20

mTBIpatients

(9M,11

F;meanage

33.4)[CGS13

-15,

LOC

<20

min,PTA

<24

hr].

AnalysisandMetho

ds:Vox

el-

wiseanalysis.

Autom

ated

analysisof

who

lebrain.

-Patientshadmultip

leclusters

ofredu

cedFA

infron

talwhite

matter,

includ

ingdo

rsolateral

prefrontal

cortex,with

severalclusters

also

show

inghigh

erMD

ascomparedto

controls.

Con

trols:20

matched

controls(9

M,1

1F;mean

age34

.2).

Dependent

Measures:FA

,MD.

-Reduced

dorsolateral

prefrontal

cortex

FAwas

sign

ificantly

correlated

with

worse

executive

functio

ning

inpatients.

Lo

2009

Chron

ic.

≥2years.

1.5T

Patients:10

patients(5

M,

5F;agerang

e20

-51)

[CGS13

-15].For

those

who

hadconv

entio

nal

MR/CT,

thefind

ings

were

negativ

e.Following

research

scan,1subject

hadasm

allfocalarea

show

inglobargliosis.

AnalysisandMetho

ds:ROI.

ROIs

placed

inthegenu

and

splenium

oftheCC,

posteriorlim

bof

the

internal

capsule,andin

the

pontinetegm

entum.

-Com

paredto

controls,

patientshadlower

FAand

high

erADCin

theleftgenu

oftheCC.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Con

trols:10

controls(5

M,

5F;meanage44

).Con

trolswerepatients

referred

forMRIdu

eto

headache

andhadno

historyof

head

trauma.

Dependent

Measures:FA

,ADC.

-Patientsshow

edincreased

FAin

thepo

steriorlim

bof

theinternal

capsule

bilaterally

comparedto

controls.

Geary

2010

Chron

ic.

≥6mon

ths.

3T

Patients:40

mTBIpatients

(17M,23

F;meanage

34.53)

[American

Con

gressof

Rehabilitatio

nMedicine,

1993

criteria].14

subjects

hadprevious

head

trauma.

NegativeMRI/CT

find

ings.

AnalysisandMetho

ds:ROI.

ROIs

structures:anterior

and

posteriorcorona

radiata,

corticospinaltracts

(including

partsof

the

corticop

ontin

etractand

superior

thalam

icradiation),external

capsule,

cing

ulum

,forcepsminor,

forcepsmajor,inferior

fron

to-occipitalfasciculus,

superior

long

itudinal

fasciculus,un

cinate

fasciculus,sagittalstratum,

andbo

dy,genu

,and

splenium

ofCC.

-TBIpatientshaddecreased

FAin

thesuperior

long

itudinalfasciculus,

sagittalstratum,and

uncinate

fasciculus

comparedto

controls.

Con

trols:35

controls

(16M,19

F;meanage

32.54)

matched

topatients

onage,education,

years

ofem

ploy

ment,and

estim

ated

prem

orbid

intelligence.

Dependent

Measures:FA

.-Poo

rperformance

ona

verbal

mem

orytask

was

correlated

with

redu

cedFA

intheun

cinate

fasciculus

andin

thesuperior

long

itudinalfasciculus

inpatients.

Holli(b)

2010

Acute.

≤3weeks.

1.5T

Patients:42

patients(17M,

25F;meanage,38

.8)

[GCS13

-15].DTI

analyses

wereperformed

on34

patients.Negative

CT/M

RIfind

ings.

AnalysisandMetho

ds:Texture

analysis(M

aZda).

Regions

correspo

ndingto

the

mesenceph

alon

,centrum

semiovale,andCC.

-Significant

asym

metries

intextureparameterswere

seen

inallthreeregion

sstud

iedin

thepatients,

theseasym

metries

were

less

prevalentin

the

controls.

Dependent

Measures:FA

,ADC.

-Several

textureparameters

correlated

with

FAand

ADCvalues.

-FA

values

intheleft

mesenceph

alon

were


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

10age-

andsex-matched

controls(4

M,6F;mean

age,39

.8).

positiv

elycorrelated

with

verbal

mem

ory.

-ADCin

thebo

dyof

theCC

was

negativ

elycorrelated

with

visual

mem

ory.

Maruta

2010

Sub

acuteto

Chron

ic.

6weeks

and5years(m

ean

2.7years).

3T

Patients:17

patients(10M,

7F;agerang

e20

-52),

[GCS15

with

chronic

postconcussive

synd

rome,

recruitedfrom

clinics].

8no

rmal,9show

edabno

rmalities.

AnalysisandMetho

ds:ROIs

selected

apriori.

Anteriorcorona

radiata,genu

oftheCC,un

cinate

fasciculus,cing

ulum

bund

le,forcepsmajor,and

superior

cerebellar

pedu

ncle.

-Gazeerrorvariability

correlated

with

themean

FAvalues

oftherigh

tanterior

corona

radiata

(ACR)andtheleftsuperior

cerebellarpedu

ncle,and

the

genu

oftheCC.

Con

trols:9controls(6

M,

3F;agerang

e19

-31).No

priorhistoryof

TBI.

Dependent

Measures:FA

.-Reactiontim

ecorrelated

toFA

inthegenu

oftheCC,

andFA

intheleftun

cinate

fasciculus

correlated

with

poorer

verbal

mem

ory.

Mayer

2010

Acute.

≤21

days

(mean12

days).

3T

Patients:22

patients(m

ean

age27

.45)

[GCS13

-15,

LOC<30

min,PTA

<24

hr].

AnalysisandMetho

ds:ROI.

Genu,

splenium

,andbo

dyof

theCC,as

wellas

the

superior

long

itudinal

fasciculus,thecorona

radiata,thesuperior

corona

radiata,theun

cinate

fasciculus,andtheinternal

capsuleforbo

thhemisph

eres.

-TBIpatientshadincreased

FAandredu

cedRD

inthe

CCandseveralleft

hemisph

eretractscompared

tocontrols,i.e.,un

cinate

fasciculus,internal

capsule,

andcorona

radiata.

Con

trols:21

sex-,age-,and

education-matched

controls(m

eanage

26.81).

Dependent

Measures:FA

,AD,

RD.

-Follow-updata

show

edpartialno

rmalizationof

DTIvalues

inseveralwhite

mattertracts.

-The

authorsconcludedthat

initialinjury

toaxon

smight

disrup

tionichemeostasis

andthebalanceof

intra/

extracellu

larwater,which

effectsdiffusionthat

isperpendicularto

theaxon

s.

Zhang

2010

Sub

acute.

30(±2)

days.

3T

Patients:15

stud

ent-athletes

with

mTBI(m

eanage

20.8

years)

[Grade

1MTBIaccordingto

Cantu

AnalysisandMetho

ds:Vox

el-

wisewho

lebrainanalysisand

ROI.

The

CCwas

chosen

asa

prim

aryROIand

subd

ivided

into

thegenu

,bo

dy,andsplenium

.In

-Neither

who

le-brain

analysis

norROIanalysisshow

edsign

ificantalteratio

nin

FA.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

2006

.GCSno

trepo

rted].

NegativeMRIfind

ings.

additio

n,therigh

thipp

ocam

pus,leftandrigh

tdo

rsolateral

prefrontal

cortexes

wereevaluated.

Con

trols:15

norm

alstud

ent-athletes

with

nohistoryof

mTBI(m

ean

age21

.3).NegativeMRI

find

ings.The

entire

samplewas

70%M

and

30%F.

Dependent

Measures:FA

,ADC.

-mTBIpatientsshow

edlarger

variability

ofFA

inthegenu

,andbo

dyof

the

CCthan

controls.

-mTBIpatientsshow

eddecreasedADCin

leftand

righ

tdo

rsolateral

prefrontal

cortex

comparedto

controls.

Warner

2010

bAcute.

≤1week

Follow-upat

4-16

mon

ths.

3T

Patients:24

patientswith

diffusetraumatic

axon

alinjury

(16M,8F;mean

age27

.2)[m

eanGCS6.4;

rang

eno

trepo

rted].

AnalysisandMetho

ds:

Autom

ated

Segmentatio

nand

Volum

etricAnalysis

(FreeSurfer).

CC,fornix

body,bilateral

fornix

crus,bilateral

perforantpathway,

cing

ulum

,un

cinate

fasciculus,andinferior

fron

to-occipitalfasciculus.

-The

volumeof

the

hipp

ocam

puscorrelated

with

theFA

inthefornix

body,fornix

crus,perforant

pathway,andcing

ulum

bund

le.

Con

trols:Non

e.Dependent

Measures:Regional

Volum

es,FA

,MD.

-Volum

eof

therigh

tprecun

euscorrelated

with

MD

inthefornix

body

and

righ

tun

cinate

fasciculus.

Note:

Morph

ometricfind

ings

notrelatedto

DTIare

presentedin

Table

2.

Bazarian

2011

Acute.

(72ho

urspo

st-injury).

Prospectiv

ecoho

rtstud

y.

Sub

jectsun

derw

entDTIpre-

andpo

stseason

with

ina3-

mon

thinterval.

(Con

cussed

subjectsun

derw

ent

repeat

testing≤72

hoursof

injury.Sub

jectswho

didno

tsuffer

aconcussion

during

the

season

underw

entrepeat

3T

Patients:One

athlete

concussion

[witn

essed

LOC>20

min,transient

amnesiaor

confusion;

GCSno

trepo

rted]and

8athletes

with

26-399

subcon

cussivehead

blow

s.Con

trols:6controlsub

jects.

2controlsubjectshad

isolated

minor

orthop

edic

injuries.

AnalysisandMetho

ds:Who

lebrainanalysis.FA

andMD

changesweremeasuredin

five

ROIs.

Dependent

Measures:FA

,MD.

Externalcapsule,po

sterior

andanterior

CC,po

sterior

andanterior

limbof

the

internal

capsule.

-FA

changeswerehigh

estfor

theconcussion

subject,

interm

ediary

forsubjects

with

subcon

cussivehead

blow

s,andlowestfor

controls.

-MD

changeswerehigh

est

fortheconcussion

subject,

interm

ediary

forsubjects

with

subcon

cussivehead

blow

sandlowestfor

controls.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

testing≤1weekof

theendof

thesportsseason

3mon

ths

afterinitial

testing).

-The

changesin

FAandMD

intheconcussion

subject

werein

therigh

tcorona

radiataandrigh

tinferior

long

itudinalfasciculus.

-FA

andMD

changesfrom

pre-season

topo

st-season

werein

both

directions,i.e.,

increasedanddecreasedFA

andMD,althou

ghmore

werein

theexpected

direction,

i.e.,decreasedFA

andincreasedMD.

Cub

on20

11Sub

acuteandChron

ic.

≥1mon

th(m

ean115days,SD

104days)forthesports-

relatedconcussion

subjects.

≥1year

forsubjectswith

mod

erateandsevere

TBI.

3T

Patients:10

college

stud

ents

with

concussion

(5M,

5F;meanage19

.7years)

[Diagn

osisbasedon

InternationalCon

sensus

Agreements20

00,GCS

notrepo

rted].2mod

erate

TBIsubjects(m

eanage

20)[G

CS9-12

].3severe

TBI(m

eanage47

.3)

[GCS≤8

].

AnalysisandMetho

ds:TBSS.

Who

lebrainWM

skeleton

(TBSS).

-Con

cussed

subjectsshow

edincreasedMD

inseveral

clusters

intheleft

hemisph

erein

comparison

tocontrols.

Con

trols:10

sex-

andage-

matched

athletes

(5M,

5F;m

eanage20

.4years).

Sex-andage-

matched

controls,forthe2

mod

erate(m

eanage22

)and3severe

TBIsubjects

(meanage46

).

Dependent

Measures:FA

,MD.

-The

largestclusterinclud

edsagittalstratum

(including

theinferior

long

itudinal

fasciculus

andinferior

fron

to-occipitalfasciculus),

retrolenticular

partof

the

internal

capsule,the

posteriorthalam

icradiation

(including

theop

ticradiation),theacou

stic

radiation,

andthesuperior

long

itudinalfasciculus.

-The

second

largestcluster

was

locatedalon

gthe

superior

long

itudinal

fasciculus,anterior

and

superior

tothepartof

the

superior

long

itudinal

fasciculus.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Davenpo

rt20

11Chron

ic.

2–5yearsafterblastinjury.

3T

25veterans

with

mTBI

(24M,1F;meanage36

)[LOC<30

min,PTA

<24

hours,and

neurolog

ical

symptom

s;GCSno

trepo

rted).

AnalysisandMetho

ds:20

standard

prob

abilistic

tractography

-based

ROIs.

Forceps

major,forceps

minor,anterior

thalam

icradiations,hipp

ocam

pal

portionof

cing

ulum

,cing

ulum

,corticospinal

tract,inferior

fron

to-

occipitalfasciculus,inferior

long

itudinalfasciculus,

superior

long

itudinal

fasciculus,tem

poralp

ortio

nof

superior

long

itudinal

fasciculus,un

cinate.

-A

glob

alpattern

oflower

white

matterintegrity

was

seen

inblastmTBIpatients

butno

tin

controls.

Con

trols:33

veterans

(28M,5F;meanage

32.5).

Dependent

Measures:FA

.-Patientswith

multip

leblast

injuries

tend

edto

have

agreaterFA

voxelsdecreased

then

individu

alswith

asing

leblastinjury.

Grossman

2011

Chron

ic.

MRIandaneurop

sycholog

ical

battery

either

≤1year

after

injury,or>1year

afterinjury.

3T

Patients:22

patients(14M,

8F;m

eanage38

.2)[G

CS

13-15].

AnalysisandMetho

ds:ROI.

Thalamus

andtheanterior

limb,

genu

,andpo

sterior

limbof

theinternal,the

splenium

oftheCC,and

the

centrum

semiovale.

-Low

ered

DTIandDKI

derivedmeasuresin

the

thalam

usandtheinternal

capsulewereseen

inpatientsexam

ined

oneyear

afterinjury

incomparison

tocontrols.

Con

trols:14

healthy

controls(9

M,5F;mean

age36

.5)matched

topatientsaccordingto

gend

er,age,andform

aleducation

Dependent

Measures:MK,FA

,MD.

-In

additio

nto

theseregion

s,patientsexam

ined

more

than

oneyear

afterinjury

also

show

edsimilar

differencesin

thesplenium

ofthecorpus

callo

sum

and

thecentrum

semiovale.

-Com

bineduseof

DTIand

DKIprov

ides

amore

sensitive

tool

for

identifying

braininjury.

-MK

inthethalam

usmight

beuseful

forearly

predictio

nof

perm

anent

braindamageandcogn

itive

outcom

e.

Henry

2011

Acute.

1–6days

post-con

cussion.

3T

Patients:18

athletes

with

mTBI(allM;meanage

AnalysisandMetho

ds:Vox

el-

basedapproach

(VBA).

Avo

xel-wise2x2repeated-

measuresanalysisof

-mTBIpatientsshow

edincreasedFA

indo

rsal


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

For

patients,follo

w-up6mon

ths

later;forcontrols,2n

dscan

18mon

thsafterinitial

scan.

22.08)

[Diagn

osisbased

onAmerican

Academyof

Neurology

Quality

Stand

ards

Sub

committee

andNeurology,19

97;

GCSno

trepo

rted].

variance

(ANOVA)using

SPM8to

thederivedscalar

images

(FA,AD,andMD)

was

used.

corticospinaltractsandin

theCCat

both

timepo

ints

comparedto

control.

Con

trols:10

athletes

(allM;

meanage22

.81).

Dependent

Measures:FA

,MD,

AD

-mTBIpatientsshow

edincreasedAD

intherigh

tcorticospinaltractsat

both

timepo

intscomparedto

controls.

.-mTBIpatientsshow

eddecreasedMD

inthe

corticospinaltractsandCC

atbo

thtim

epo

ints

comparedto

controls.

Lange

2011

Sub

acute.

6-8weeks.

3T

Patients:60

mTBIpatients

(43M,17

F;meanage

30.8)[Closedhead

injury

and;LOC>1minute,PTA

>15

minutes,G

CS<15

,or

abno

rmality

onCT].n=

41negativ

eCTfind

ings,

N=15

positiv

eCT

find

ings,andn=4no

tordered.

N=21

with

postconcussive

disorder

basedon

ICD-10;

N=39

with

outpo

stconcussive

disorder.

AnalysisandMetho

ds:ROIs.

Genu,

body,andsplenium

oftheCC.

-Nodifferenceson

FAor

MDbetweenmTBIpatients

andcontrols.

Con

trols:34

controls

(25M,9F;meanage

37.1)with

orthop

edic/

soft-tissueinjuries.N=0

positiv

efind

ings,n=3

negativ

efind

ings,andn=

31no

tordered.

52.9%%

ofcontrolsmet

ICD-10

criteriaforpo

stconcussive

disorder.

Dependent

Measures:FA

,MD.

-mTBIpatientsrepo

rted

morepo

st-concussion

symptom

sthan

controls.

-mTBIpatientsshow

eda

nonsignificant

trend

increase

inMD

inthe


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

splenium

oftheCC

comparedto

controls.

MacDon

ald

2011

Sub

acute.

≤90

days.

1.5T

Patients:63

patients(allM,

medianage24

)[D

iagn

osisbasedon

U.S.

military

clinical

criteria

fortraumatic

braininjury;

GCSno

trepo

rted].

AnalysisandMetho

ds:ROI.

Genuandsplenium

ofthe

CC,therigh

tandleft

middlecerebellar

pedu

ncles,therigh

tand

left

cerebral

pedu

ncles,the

righ

tandleftun

cinate

fasciculi,andtherigh

tand

leftcing

ulum

bund

les.

-TBIsubjectsshow

eddecreasedRAin

themiddle

cerebellarpedu

ncles,

cing

ulum

bund

les,andin

therigh

torbitofron

talwhite

matter.

21controls(allM,median

age31

)expo

sedto

blasts,

butno

newith

sustained

TBI.

Dependent

Measures:Relative

anisotropy

(RA),MD,AD,

RD.

-Follow-upDTIscansin

47TBIsubjects6-12

mon

ths

latershow

edpersistent

abno

rmalities.

Matthew

s20

11Self-repo

rted

historyof

concussion

.3T

Patients:22

patientswith

ahistoryof

blast-related

TBI.[LOC<30

min,PTA

<25

hr,CGS13

-15].11

TBIpatientswith

Major

DepressiveDisorder

(MDD)(allM,meanage

26.8).11

TBIpatients

with

outMDD

(allM,

meanage30

.3).

AnalysisandMetho

ds:VBA

-Patientswith

MDD

show

edlower

FAin

corona

radiata,

CCandsuperior

long

itudinalfasciculus

comparedto

non-MDD

patients.

Con

trols:Non

e.-FA

inthesuperior

long

itudinalfasciculus

correlated

negativ

elywith

depressive

symptom

s.

Matsushita

2011

Acute.

Median3.5days.

1.5T

Patients:20

patients(18M,

2F;meanage39

.3):9

mild

TBI[G

CS13

-15,

LOC<30

min,PTA

<24

hr].11

mod

erateTBI

[LOC≥3

0min

and/or

GCS9-12

].

AnalysisandMetho

ds:ROI.

Genu,

stem

,andsplenium

oftheCCandthecorona

radiata,anterior

limbof

the

internal

capsule,po

sterior

limbof

theinternalcapsule,

fron

talwhite

matter,and

occipitalw

hitematterof

the

periventricularwhite

matter.

-Decreased

FAin

the

splenium

oftheCCin

mTBIcomparedto

controls.

Con

trols:27

matched

controls(13M,14

F;

meanage42

.9).

Dependent

Measures:FA

.-Decreased

FAin

thegenu

,stem

andsplenium

ofthe

CCin

mod

erateTBI

comparedto

controls.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Messe

2011

Acute.

7-28

days

(sub

acuteph

ase),

Sub

acute.

3-4mon

ths(lateph

ase).

1.5T

Patients:23

patients[LOC

<30

min,CGS13

-15,

PTA

<24

hr,or

neurolog

ical

symptom

s];

11with

good

outcom

e(8

M,3

F;m

eanage27

.8),

12with

poor

outcom

e(7

M,5

F;m

eanage31

.3).

7of

11with

good

outcom

ehadnegativ

eMRIfind

ings

and6ou

tof

12po

orou

tcom

ehad

negativ

eMRIfind

ings.

AnalysisandMetho

ds:

VBM,TBSS.

Who

leBrain.

-MD

was

high

erin

poor

outcom

epatientscompared

with

bothcontrolsandgo

odou

tcom

epatients,in

the

forcepsmajor

andminor

oftheCC,inferior

fron

to-

occipitalfasciculus,and

inferior

long

itudinal

fasciculus.

Con

trols:23

controls

(12M,11

F;meanage

30).

Dependent

Measures:FA

,MD,

AD,RD.

-MD

was

high

erin

poor

outcom

epatientscompared

tocontrolsin

superior

long

itudinalfasciculus

and

corticospinaltract,andleft

anterior

thalam

icradiation.

-Nodifference

indiffusion

variableswas

foun

dbetweenpatientswith

good

outcom

eandcontrols.

Smits

2011

Sub

acute.

Average

30.6

days.

3T

Patients:19

patients

includ

ed(10M,9

F;m

ean

age26

)[G

CS13

-15].

AnalysisandMetho

ds:TBSS.

Who

leBrain.

-There

wereno

differences

inMD

betweenpatients

andcontrols.

Con

trols:12

controls(8

M,

4F;meanage28

).Dependent

Measures:FA

,MD.

-Decreased

FAwas

inthe

righ

ttempo

ralsubcortical

white

matterin

patients

comparedto

controls.

These

region

sinclud

edinferior

fron

to-occipital

fasciculus.

-IncreasedMD

was

correlated

with

severity

ofpo

st-con

cussivesymptom

sin

theinferior

fron

to-

occipitalfasciculus,inferior

long

itudinalfasciculus

and

thesuperior

long

itudinal

fasciculus.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

-Decreased

FAcorrelated

with

severity

ofpo

st-

concussive

symptom

sin

theun

cinate

fasciculus,

inferior

fron

to-occipital

fasciculus,internal

capsule,

CC,parietal

subcortical

white

matterandfron

tal

subcortical

white

matter.

-Microstructural

changesin

white

matterarelik

elya

neurop

atho

logicalsubstrate

ofpo

stconcussive

synd

rome.

Spo

nheim

2011

Chron

ic.

Several

Mon

ths.

1.5T

Patients:9patients(allM;

meanage33

.7)

[Diagn

osisbasedon

American

Con

gressof

Rehabilitatio

nMedicine

Special

InterestGroup

onMild

Traum

atic

Brain

Injury

andtheconcussion

gradingsystem

bythe

American

Academyof

Neurology

;GCSno

trepo

rted].

AnalysisandMetho

ds:ROI.

Forceps

major,forcepsmajor

andanterior

thalam

icradiations.

-EEG

phasesynchron

ywas

less

inlateralfron

tal

region

sin

patients.

Con

trols:8controls(allM;

meanage30

.3).

Dependent

Measures:

Electroenceph

alog

ram

(EEG)

phasesynchron

izationandFA

.

-EEG

phasesynchron

ywas

correlated

with

FAin

the

leftanterior

thalam

icradiations

andtheforceps

minor

inpatientsbu

tno

tcontrols.

McA

llister

2012

Acute.

Preseason

and≤10

days

ofa

diagno

sedconcussion

.

3T

Sub

jects:10

athletes

(allM;

agerang

e15

-23)

with

mTBI[D

iagn

osisby

certifiedathletic

traineror

team

physician;

GCSno

trepo

rted].

AnalysisandMetho

ds:Strain

andstrain

rate

calculations

basedon

Dartm

outh

Sub

ject-

SpecificFEHeadmod

el(helmetswornto

record

head

impactsdu

ring

play

onthe

field).DTImapsforCC.

CC.

-Chang

ein

FAcorrelated

with

meanandmaxim

umstrain

rate.


Tab

le3

(con

tinued)

FirstAutho

rYear

Typ

eof

Study

(tim

epo

st-injury)

Magnet

Sub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Non

e.Dependent

Measures:FA

,MD,

Strain,

StrainRate.

-Chang

ein

MD

correlated

with

meanandmaxim

umstrain.

-Chang

ein

MD

correlated

with

leng

thof

injury-to-

imaginginterval,bu

tchange

inFA

didno

t.

Key:M

Male,

FFem

ale,

PTA

Posttraumatic

Amnesia,

LOC

Lossof

Con

sciousness,GCSGlascow

Com

aScale,CC

Corpu

sCallosum,ADC

ApparentDiffusion

Coefficient,FA

Fractional

Anisotrop

y,MDMeanDiffusivity,R

DRadialD

iffusivity,A

DAxialDiffusivity,D

KIDiffusionalKurtosisIm

aging,DTIDiffusion

TensorIm

aging,MKMeanKurtosis,ROIRegionof

Interest,T

BSS

Tract-Based

SpatialStatistics

Thistablepresentsfind

ings

derivedfrom

diffusiontensor

imaging(D

TI)includ

ing:

Trace,M

eanDiffusivity

(MD),FractionalA

nisotrop

y(FA),AxialDiffusivity

(AD),RadialD

iffusivity

(RD),and

MeanKurtosis(M

K).In

stud

ieswhere

non-DTIdiffusionweigh

tedim

aging(D

WI)was

also

presentedweinclud

ethemainmeasure,A

pparentDiffusion

Coefficient

(ADC).In

thedescriptionof

subjects,w

eprov

ide,whenavailable,theGlasgow

Com

aScale(G

CS)score,Lossof

Con

sciousness

(LOC)du

ratio

n,andPosttraumaticAmnesia(PTA

)du

ratio

n.Acuteisdefinedas

under1mon

th,

subacute

isdefinedas

>1mon

thbu

tless

than

6mon

ths,andchronicisdefinedas

>6mon

ths


Tab

le4

DTIstud

ieswith

differentDTIseveritiesinclud

ingmild

FirstAuthor

Year

Typ

eof

Study

[tim

epo

st-injury]

MagnetSub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

Huism

an20

04Acute

<7days.

1.5T

Patients:20

patients(15M,5

F;

meanage31

).[G

CS4-15

].AnalysisandMetho

ds:ROI

Analysis.

Posterior

limbof

theinternal

capsule(bilaterally

)andthe

splenium

oftheCC.

-FA

values

weresign

ificantly

redu

cedin

theinternal

capsule.

Con

trols:15

healthysubjects

with

amatchingage

distribu

tion(m

eanage35

).

Dependent

Measures:FA

,ADC.Measurementsin

thethalam

usandpu

tamen

served

asinternal

references.

-FA

values

weresign

ificantly

correlated

with

GCSandRankin

scores

fortheinternal

capsule

andsplenium

.

-ADCvalues

weresign

ificantly

redu

cedwith

inthesplenium

.

-Correlatio

nbetweenFA

and

clinical

markers

was

betterthan

that

fortheADCvalues.

-ADCof

theinternal

capsulewas

notcorrelated

with

theGCSand

Rankinscores.

Salmon

d20

06Chron

ic>6mon

ths.

3T

Patients:16

patients(13M,3

F;

meanage32

)[M

edianGCS7,

rang

e3-13

].

AnalysisandMetho

ds:Vox

elbasedanalysis.

Mapsof

FAandMD

were

calculated

from

the

diffusion-weigh

tedim

ages.

-Major

white

mattertractsand

associationfibersinthetempo

ral,

fron

tal,parietal

andoccipital

lobesshow

edbilateraldecreases

inFA

.

Con

trols:16

controls[12M,

3F;meanage34

].Dependent

Measures:FA

,MD.

-Increasesin

MD

werefoun

din

widespreadareasof

thecortex.

-A

positiv

ecorrelationwas

foun

dbetweenMD

andim

pairmentof

learning

andmem

oryin

theleft

posteriorcing

ulate,left

hipp

ocam

palform

ationandleft

tempo

ral,fron

talandoccipital

cortex.

Benson

2007

Acute

toChron

ic.

Variablefrom

days

toyears

(mean35.3months,range

3days

to15

years).

1.5T

Patients:

AnalysisandMetho

ds:

Who

le-brain

analysisusing

histog

ram

shapeparameters.

-White

matterwho

le-brain

FAhistog

ramsshow

edadecrease

inFA

inTBIpatientswith

noov

erlapbetweenpatient

and

controls.

20patients(13M,7

F;m

eanage

35.5)[G

CS3-15

].6mTBIand

14mod

erate/severe

TBIAll

CT+except

N=3mTBI.

White

matterwho

le-brain

FAhistog

ram

parameters.

-Histogram

shapeparameters

correlated

with

each

otherand

with

admission

GCSandPTA

.

Con

trols:14

age-matched

controls(m

eanage27

.5).

Dependent

Measures:FA

,Kurtosis,Skewness.

-MeanFA

was

thebestpredictorof

PTA

duratio

n(r=-.64

)andGCS

(-.47).


Tab

le4

(con

tinued)

FirstAuthor

Year

Typ

eof

Study

[tim

epo

st-injury]

MagnetSub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

-40

%%

ofPTA

variance

inADC

was

accoun

tedforby

FA.

-Mostof

theFA

decrease

was

likelyaccoun

tedforby

increased

diffusionin

theshortaxis

dimension

,reflectin

gdy

smyelin

ationandaxon

alsw

ellin

g.

-The

correlationof

injury

severity

with

changesin

FAsugg

estsa

role

forDTIin

earlydiagno

sis

andprog

nosisof

TBI.

Kum

ar20

09Acute.

5–14

days.

1.5T

Patients:83

patients[62M,

21F;meanage34

.25].26

mTBI[G

CS13

–15

,mean

14.5].57

mod

erateTBI[G

CS

9–12

].Allwerepo

sitiv

efor

clinical

find

ings

onCTat

injury.

AnalysisandMetho

ds:ROI.

CC(divided

into

7segm

ents).

-Decreased

FAin

genu

inmTBI

comparedto

mod

erateTBI,and

inbo

thTBIgrou

pscompared

with

controls.

Con

trols:33

age-

andsex-

matched

controls(22M,1

1F;

meanage32

.1).

Dependent

Measures:FA

,RD,

MD,AD.

-Decreased

FAin

splenium

inmod

erateTBIcomparedto

controls.

-Decreased

MD

inmod

erateTBI

comparedto

controls.

-IncreasedRD

ingenu

and

splenium

inmTBIandmod

erate

TBIcomparedto

controls.

-IncreasedRD

inmidbo

dyCCin

mod

erateTBIcomparedto

controls.

-Decreased

AD

ingenu

inmod

erateTBIcomparedto

controls.

-Poo

rneurop

sycholog

ical

outcom

eat

6-mon

thswas

associated

with

DTabno

rmalities

intheCC.

Levin

2010

Chron

ic.

Post-injury

interval

871.5days.

3T

Patients:37

veterans

(meanage

31.5)with

mild

ormod

erate

TBI[G

CSno

tprov

ided].5

AnalysisandMetho

ds:

Tractog

raph

y,standard

sing

le-

sliceROImeasurement,and

Non

-tractog

raph

yROI

protocolsinclud

edthetotal

CC(including

genu

,bo

dy,

-Nogrou

pdifferencesin

FAand

ADCwerefoun

d.How

ever,FA

oftheleftandrigh

tpo

sterior


Tab

le4

(con

tinued)

FirstAuthor

Year

Typ

eof

Study

[tim

epo

st-injury]

MagnetSub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

hadpo

sitiv

efind

ings

onclinical

MRI.

voxel-basedanalysis.

Manually

-tracedROIs

ona

slice-by

-slicebasis,and

quantitativefibertractography

toassess

whitematterintegrity

splenium

,and

total),and

the

righ

tandleftanterior

and

posteriorlim

bsof

the

internal

capsule.

internal

capsuleandleft

corticospinaltractpo

sitiv

ely

correlated

with

totalwords

consistently

recalled.

Con

trols:15

veterans

with

outa

historyof

TBIor

expo

sure

toblast(m

eanage31

.4),

includ

ing7subjectswith

extracranialinjury

(meanpo

st-

injury

interval

919.5days),

and8who

wereun

injured.

Dependent

Measures:FA

,ADC

-ADCfortheleftandrigh

tun

cinate

fasciculiandleft

posteriorinternal

capsulewas

negativ

elycorrelated

with

this

measure

ofverbal

mem

ory.

-Correlatio

nsof

DTIvariables

with

symptom

measureswere

non-

sign

ificantandinconsistent.

Hartik

ainen

2010

Acute.

3weeks.

1.5T

Patients:18

patients(6

M,1

2F;

11asym

ptom

atic

and7

symptom

atic;meanage43

)with

mild

andmod

erateTBI.

Allmod

eratesubjectshad

positiv

efind

ings

onclinical

CTor

MRI.

AnalysisandMetho

ds:ROI

Thalamus,internal

capsule,

centrum

semiovale,and

mesenceph

alon

.

-Sym

ptom

atic

patientshadhigh

erFA

andlower

ADCin

the

mesenceph

alon

then

asym

ptom

atic

patients.

Con

trols:Non

e.Dependent

Measures:FA

,ADC

-Non

eof

theotherFA

orADC

measurementsweresign

ificantly

differentbetweensymptom

atic

andasym

ptom

atic

patients.

Little

2010

Chron

ic.

≥12mon

ths.

3T

Patients:12

patientswith

mTBI

(meanage31

.2).12

mod

erate

tosevere

TBI(m

eanage33

.3)

Severity

was

basedon

duratio

nof

Lossof

Con

sciousness

andPost-

Traum

atic

Amnesia.4mTBI

and9mod

erateto

severe

patientshadpo

sitiv

efind

ings

onMRIor

CT.

AnalysisandMetho

ds:ROI.

12ROIs

incortical

andCC

structures

and7subcortical

ROIs

(anterior,ventral

anterior,ventrallateral,

dorsom

edial,ventral

posteriorlateral,ventral

posteriormedial,and

pulvinar

thalam

icnu

clei).

-TBIpatientsshow

edredu

ctions

inFA

intheanterior

andpo

sterior

corona

radiata,forcepsmajor,the

body

ofCC,and

fibersidentified

from

seed

voxelsin

theanterior

andventralanterior

thalam

icnu

clei.

Con

trols:12

age-andeducation-

matched

controls(m

eanage

30.8).

Dependent

Measures:FA

.-FA

from

cortico-corticoandCC

ROIs

didno

taccoun

tfor

sign

ificantvariance

inneurop

sycholog

ical

functio

n.How

ever,FA

from

thethalam

icseed

voxelsdidaccoun

tfor


Tab

le4

(con

tinued)

FirstAuthor

Year

Typ

eof

Study

[tim

epo

st-injury]

MagnetSub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

variance

inexecutivefunctio

n,attention,

andmem

ory.

Singh

2010

Acute

toChron

ic.

Mean~1

mon

th.

1.5T

Patients:12

patients(m

eanage

28)with

mild

tomod

erate

braininjuries

(lossof

consciou

snessfor<1h)

prim

arily

dueto

falls,assault

ortrafficaccidents.

AnalysisandMetho

ds:ROI

analysis.

Differences

intheFA

maps

betweeneach

TBIsubject

andthecontrolgrou

pwere

compu

tedin

acommon

spaceusingat-test,

transformed

back

tothe

individu

alTBIsubject's

head

space,andthen

thresholdedto

create

ROIs

that

wereused

tosorttracts

from

thecontrolgrou

pand

theindividu

alTBIsubject.

Tractcoun

tsforagivenROI

ineach

TBIsubjectwere

comparedto

grou

pmeanfor

thesameROIin

orderto

quantifytheim

pactof

injury

alon

gaffected

pathways.

The

sameprocedurewas

used

tocompare

theTBI

grou

pto

thecontrolg

roup

inacommon

space.

-With

inTBIsubjectsaffected

pathwaysinclud

edhipp

ocam

pal/

fornix,inferior

fron

to-occipital,

inferior

long

itudinalfasciculus,

CC(genuandsplenium

),cortico-

spinal

tractsandtheun

cinate

fasciculus.

Con

trols:10

age-matched

volunteers

(meanage27

).No

evidence

ofneurolog

ical

diseaseon

MRim

aging.

Dependent

Measures:FA

,MD,

AD,RD.

-Mostof

theseregion

swerealso

detected

inthegrou

pstud

y.

Brand

stack

2011

Acute.

Mean7days

1.5T

Patients:22

patients(G

CS6-15

)admitted

totheem

ergency

departmentforTBI.On

clinical

MRI7werenegativ

eforfind

ings,15

show

edcortical

contusions

ortraumatic

axon

alinjury.

AnalysisandMetho

ds:ROI

analysis.

Measurementswere

performed

at46

different

locatio

nsinclud

ingbilateral

cortical,subcortical

and

deep

brainstructures.

-TBIpatientswith

andwith

out

visiblelesion

sdidno

tshow

any

differencesin

ADCvalues

but

both

grou

psdiffered

from

the

controlsin

severalcortical

and

deep

brainregion

s.

Con

trols:14

healthysubjects.

Dependent

Measures:ADC.

-IncreasedADCvalues

were

common

inTBIgrou

psbu

tdecreasedADCvalues

were

relativ

elyun

common

.

-RegionalADCvalues

andthe

numberof

abno

rmal

region

sdid

notcorrelatewith

either

GCSor


Tab

le4

(con

tinued)

FirstAuthor

Year

Typ

eof

Study

[tim

epo

st-injury]

MagnetSub

jects(N

,gend

er,age)

DTIAnalysisMetho

dand

Dependent

Measures

Brain

Region(s)

MainFinding

(s)

GOS(G

lasgow

outcom

escale)-E

scores.

Ljung

qvist

2011

Acute.

With

in11

days

andat

6mon

thspo

st-injury.

1.5T

Patients:8patientswith

TBI

(4M,4F;meanage36

.4)

[GCS3-14

].Allpatientswere

CTnegativ

e.

AnalysisandMetho

ds:ROI

analysis.

Polyg

onal

ROIs

were

manually

placed

intheCC.

-Patientsshow

edaredu

ctioninFA

inthecorpus

callo

sum

inthe

acuteph

asecomparedto

controls.

Con

trols:6controls(3

M,3F;

meanage33

.1).

DependentMeasures:FA

,Trace,

AD,RD.

-There

was

nosign

ificantchange

inAD,RD,or

Trace.

-At6mon

ths,asign

ificant

redu

ctionin

FAandasign

ificant

increase

inTrace

andAD

inpatientscomparedto

controls.

Yurgelun-

Tod

d20

11Not

repo

rted.

3T

Patients:15

Mveterans

with

TBI(m

ild,mod

erateand

severe

accordingto

The

Ohio

State

University

-TBI

IdentificationMetho

d).

AnalysisandMetho

ds:ROI

analysis.

ROIs

formajor

white

matter

tractswerecreatedforthe

genu

andthecing

ulum

using

theJohn

sHop

kins

University

White

Matter

LabelsAtlas.

-TBIpatientsshow

edadecrease

inFA

values

intheleftcing

ulum

,andleftandtotalgenu

compared

tocontrols.

Con

trols:17

Mcontrols:10

civilians,6veterans.

Dependent

Measures:FA

,MD.

-The

TBIgrou

pshow

edgreater

impu

lsivity

-Total

andrigh

tcing

ulum

FApo

sitiv

elycorrelated

with

current

suicidalideatio

nandmeasuresof

impu

lsivity.

Key:M

Male;FFem

ale;GCSGlasgow

Com

aScale,C

CCorpu

sCallosum,A

DCApp

arentD

iffusion

Coefficient,FAFractionalA

nisotrop

y,MDMeanDiffusivity,R

DRadialD

iffusivity,A

DAxial

Diffusivity,ROIRegionof

Interest

Thistablepresentsfind

ings

derivedfrom

Diffusion

TensorIm

aging(D

TI),including

:Trace,M

eanDiffusivity

(MD),FractionalAnisotrop

y(FA),AxialDiffusivity

(AD),RadialDiffusivity

(RD),

andMeanKurtosis(M

K).In

stud

ieswhere

non-DTIdiffusionweigh

tedim

aging(D

WI)was

also

presented,

weinclud

ethemainmeasure,A

pparentD

iffusion

Coefficient

(ADC).In

thedescription

ofthesubjects,weprov

ide,whenavailable,theGlascow

Com

aScale(G

CS)score,Lossof

Con

sciousness

(LOC)du

ratio

n,andPosttraumatic

Amnesia(PTA

)du

ratio

n.Acuteisdefinedas

under

1mon

th,subacute

isdefinedas

>1mon

thbu

tgreaterthan

6mon

ths,andchronicisdefinedas

>6mon

ths.


early post-injury may make early interventions possible.Here, measures such as free water, which characterize wateras belonging to tissue versus extracellular water (e.g.,Pasternak et al. 2009), may be helpful in determining intra-cellular versus extracellular edema, i.e., cytotoxic versusvasogenic edema. Such measures are just beginning to beused in mTBI by our group (e.g., Pasternak, Kubicki and etal. 2011a; b).

A further issue is whether or not an observed increase inFA early in the course of injury is predictive of pooreroutcome, or if an increase in FA at any time over the courseof the injury is a poor indicator of outcome. This question isrelevant, particularly given that some investigators do notreport increased FA at 24 h post-injury (e.g., Arfanakis et al.2002), while others report increased FA at 72 h (Bazarian etal. 2007). Of interest here, Henry et al. (2011) scanned 18athletes with mTBI at 1 to 6 days post-injury, later in post-injury than either the Arfanakis or Bazarian studies, andthey also reported increased FA and decreased MD in dorsalcorticospinal tracts and in the corpus callosum at both base-line and at 6 month follow up. Further, Mayer et al. (2010)scanned mTBI patients 21 days post-injury, on average12 days post-injury. They, too, reported increased FA andreduced radial diffusivity (RD) in the corpus callosum inmTBI patients compared with controls. Finally, a study byHartikainen et al. (2010) compared 11 asymptomatic TBIpatients with 7 symptomatic TBI patients, which includedboth mild and moderate cases, with moderate TBI patientsall having abnormal findings on clinical CT or MRI. Incomparing these two groups, the symptomatic patientsshowed increased FA and lower ADC in the mesencephaloncompared with the asymptomatic patients. Thalamus, inter-nal capsule, and centrum semiovale did not differentiatebetween these two groups. There was no control group.Nonetheless, the notion that more symptomatic patientsshowed increased FA is important and could serve as abiomarker for predicting those patients who have, or willhave, a poorer outcome.

The implications of increased FA and reduced MD, andwhether these measures are indicators of poor outcomeclearly needs further investigation. A longitudinal studywould help to follow the natural progression of brain injuryin mTBI over time in order to determine the significance ofincreased versus decreased FA that is observed in mTBI.Work by Lipton and coworkers (see empirical study in thisspecial issue) have investigated, in a longitudinal design,areas of increased and decreased FA, sometimes observed inthe same patient, and they suggest that increased FA may beassociated with a compensatory mechanism or neuroplastic-ity in response to brain injury, but it is not necessarily adirect reflection of brain injury per se. Further work isneeded to determine the biological meaning and implica-tions of increased and decreased FA, as the story may be

more complex than interpretations given thus far to explainthese phenomenon.

Other noteworthy findings of brain injury in mTBI in-clude reduced FA in frontal white matter, including dorso-lateral prefrontal cortex, where Lipton et al. (2009) reportedseveral clusters of increased MD, which were correlatedwith worse executive functioning in a group of acute mTBIpatients compared with controls. Other findings includeabnormalities in mesencephalon, centrum semiovale, andcorpus callosum (Holli et al. 2010b), with findings for themesencephalon being correlated with verbal memory inmTBI patients. Additionally, reduced FA has been reportedin the anterior corona radiata, in the genu of the corpuscallosum, and in the left superior cerebellar peduncle(Maruta et al. 2010). In the latter study, gaze positionalerrors in an eye movement task were correlated with meanFA values of the right anterior corona radiata, the left supe-rior cerebellar peduncle, and the genu of the corpus cal-losum, all tracts that support spatial processing and areinvolved in attention, leading these investigators to suggestthat gaze errors might be a useful screening tool for mTBI.

Kraus and coworkers (2007) focused on chronic patientswho had mild (n020), moderate and severe (n017) injury,and 18 controls. They investigated FA as well as radialdiffusivity (RD), axial diffusivity (AD), and white matterload; the latter defined as the total number of regions withreduced FA. She and her coworkers reported FA decreasesin all thirteen brain regions examined in the moderate tosevere group. In the mTBI group, FA was reduced in onlythe corticospinal tract, sagittal striatum, and superior longi-tudinal fasciculus. Both AD and RD were increased inseveral white matter regions in the moderate to severegroup, whereas in the mTBI group only increases in ADwere observed, suggesting that myelin damage is not presentin mTBI but is present in moderate to severe TBI. Theseinvestigators concluded that white matter changes that indi-cate diffuse axonal injury in TBI show alterations along aspectrum from mild to severe TBI.

Lipton et al. (2008) also investigated more chronicpatients. They compared 17 mTBI patients who had nega-tive CT/MRI findings at the time of injury, with 10 controlswho also showed negative findings on MRI. One of themTBI subjects subsequently was observed to develop asmall area of increased signal intensity, likely the result ofgliosis. Decreased FA and increased MD were observed inthe corpus callosum, subcortical white matter, and in theinternal capsules, bilaterally. These brain regions are similarto those observed as abnormal in the acute studies notedabove (i.e., Arfanakis et al. 2002; Inglese et al. 2005;Bazarian et al. 2007; Miles et al. 2008).

Niogi and colleagues (2008a) investigated a group ofpatients 1 to 65 months following injury; all characterizedas having more than one symptom of postconcussive


syndrome. Subjects included 34 mTBI patients that wereseparated into those with negative MRI findings (n011),those with micro-hemorrhage (n011), and those with whitematter hyperintensities or chronic hemorrhagic contusions,compared with controls (n026). They investigated sixregions of interest and reported reduced FA in the anteriorcorona radiata (41 %), the uncinate fasciculus (29 %), thegenu of the corpus callosum (21 %), the inferior longitudinalfasciculus (21 %), and the cingulum bundle (18 %). Reac-tion time was correlated with a number of damaged whitematter structures and it was noted that 10 of the 11 of themTBI patients with negative MRI findings showed reduc-tions in FA relative to controls. In a slightly larger sample ofmTBI patients, this group also reported significant correla-tions between attentional control and FA reduction in the leftanterior corona radiata, as well as significant correlationsbetween memory performance and reduced FA in the unci-nate fasciculus, bilaterally (Niogi et al. 2008b). These cog-nitive correlates with white matter fiber tract abnormalitiesfindings are consistent with what would be expected giventhe function of these tracts, further suggesting that FA maybe useful as a biomarker for neurocognitive function anddysfunction in mTBI.

Given the different magnet strengths, with some con-ducted on a 1.5 T magnet, and others conducted on a 3 Tmagnet (see Tables 3 and 4), as well as differences in theanalysis methods employed, and the dependent measuresused, as well as differences in the selection of brain regionsto investigate, in addition to differences in the post-injurytime of the study, and differences in whether subjects hadpositive or negative findings on conventional CT or MRI, itis surprising that there is as much convergence and consis-tency with respect to the detection of brain abnormalities inmTBI using DTI. Given the DTI findings reviewed above,and listed in Tables 3 and 4, as well as the frequently ofnegative CT and structural MRI scans, it is also quite clearthat DTI is by far the most sensitive in vivo method to detectsubtle brain abnormalities in mTBI.

While each of the 43 DTI studies investigating mTBI,and included in Tables 3 (n032) and 4 (n011), report someDTI abnormalities, their anatomical location does not al-ways converge. This lack of convergence is not, however,surprising, given the heterogeneity of brain injuries, as wellas the variability in these studies between time of injury andDTI scan. Some regions, however, are reported more oftenthan the others, which might further suggest their increasedvulnerability to axonal injury.

For example, in reviewing specific brain regions, some,as noted above, including the corpus callosum and parts ofthe corpus, are abnormal in mTBI (e.g., Arfanakis et al.2002; Bazarian et al. 2007; Grossman et al. 2011; Henry etal. 2011; Holli et al. 2010b; Huisman et al. 2004; Inglese etal. 2005; Kumar et al. 2009; Lipton et al. 2008; Little et al.

2010; Ljungqvist et al. 2011; Lo et al. 2009; Messe et al.2011; Maruta et al. 2010; Matthews et al. 2011; Mayer et al.2010; McAllister et al. 2012; Miles et al. 2008; Niogi et al.2008a; b; Rutgers et al. 2008a; b; Singh et al. 2010; Smits etal. 2011; Warner et al. 2010(b); Yurgelun-Todd et al. 2011).

Rutgers and coworkers (2008a) have also reported re-duced FA predominantly in 9 major regions in mTBIpatients, and one of these regions included the corpus cal-losum. In a separate study by this group of investigators(Rutgers et al. 2008b), mTBI and moderate TBI subjectswere included. Patients with mTBI or less than 3 monthspost-injury showed reduced FA and increased ADC in thegenu of the corpus callosum, whereas patients with greaterthan 3 months post-injury showed no such differences. Thisgroup of investigators also showed that more severe traumawas associated with FA reduction in the genu and spleniumof the corpus callosum, along with increased ADC andfewer numbers of fibers. These findings suggest that theremay be a reversal of damage to the corpus callosum inpatients with mTBI who recover after 3 months, and thatmore severe damage to the corpus callosum may be associ-ated with a worse outcome. Again, a longitudinal study thatinvestigates the course of injury over time would provideimportant information regarding the staging, progression,and possible recovery and reversal of brain injuries overtime.

Huisman et al. (2004) included TBI patients with Glas-gow Coma Scale scores between 4 and 15, and hencemoderate and severe were not separated from mild in eval-uating the corpus callosum. Matthews et al. (2011) exam-ined mTBI patients with major depressive disorder andthose without a major depressive disorder. These investiga-tors found that those with a major depressive disordershowed reduced FA in the corpus callosum (also coronaradiata and superior longitudinal fasciculus) compared withthose without a major depression. Zhang et al. (2010), onthe other hand, reported no differences in the corpus cal-losum using either whole brain analysis or region of interestanalyses between mTBI athletes and controls, but mTBIpatients did show greater variability of FA in the genu andin the body of the corpus callosum than did controls. Langeet al. (2011) also reported no differences in FA or MDbetween mTBI and controls, although they did report anon-significant trend for an increase in MD in the spleniumof the corpus callosum in mTBI compared with controls.MacDonald et al. (2011) also reported no differences ingenu or splenium of corpus callosum between mTBI andcontrols. The controls in this study, however, were 21 con-trols with blast exposure but without head trauma. It may be,however, that exposure to blasts results in subconcussiveinjury to the brain as is reported in sports-related injuries(e.g., Cubon and Putukian 2011; McAllister et al. 2012).Accordingly, fewer findings between groups might be


accounted for by the fact that the control group is moresimilar to the mTBI group. Levin et al. (2010) also didnot find differences for the corpus callosum between TBIpatient and controls on FA or ADC measures, but heremTBI cases were not separated from moderate TBI andthe controls were 15 veterans, 7 with extracranial injury.

Again, the issue of using a military population as acontrol group needs more careful consideration as many ofthese individuals may have sustained blast injuries wherethey did not experience loss of consciousness but whichmay, nevertheless, have resulted in subtle alterations to thebrain (and thus use of such controls might result in a de-crease in the sensitivity of the imaging methods).

Davenport and coworkers (2011) selected veterans withand without blast exposure in their study where they investi-gated 25 veterans returning from Operation Enduring Free-dom and Operation Iraqi Freedom who had been exposed toblasts and subsequently developed symptoms indicative ofmTBI, and they included a comparison group comprised of33 veterans who had not experienced either blast exposure orhead injury during their tour of duty. These investigatorsreported diffuse and global patterns of reduced FA in whitematter in the blast exposure group compared to the group notexposed to blast. Furthermore, those who experienced morethan one blast related mTBI showed a larger number ofreduced FAvoxels in the brain. Interestingly, and surprisingly,58 % of the no blast group had experienced a previous mTBIas civilians, prior to entering the service. This group did showdifferences, however, compared with the blast exposure groupwith symptoms. Here the issue may not be exposure per se,but the differentiation between those with and without symp-toms being more important in differentiating between groups.Yurgelun-Todd et al. (2011) also investigated a sample of 15veterans with mild, moderate, and severe TBI and comparedthem with 10 civilians and 6 veterans. They reported de-creased FA in left cingulum and genu of the corpus callosum.The TBI group showed greater impulsivity. In addition, bothtotal and right cingulum FA reduction was correlated withincreased suicidal ideation and increased impulsivity.

Other brain regions reported as abnormal in mTBI in-clude the internal capsule (Arfanakis et al. 2002; Bazarian etal. 2007; Bazarian et al. 2011; Cubon and Putukian 2011;Grossman et al. 2011; Huisman et al. 2004; Inglese et al.2005; Lipton et al. 2008; Lo et al. 2009; Mayer et al. 2010;Miles et al. 2008), the external capsule (Arfanakis et al.2002; Bazarian et al. 2007; Bazarian et al. 2011), the cen-trum semiovale (Grossman et al. 2011; Holli et al. 2010b;Inglese et al. 2005; Miles et al 2008), inferior fronto-occipital fasciculus (Cubon and Putukian 2011; Messe etal. 2011; Singh et al. 2010; Smits et al. 2011), inferiorlongitudinal fasciculus (Cubon and Putukian 2011; Messeet al. 2011; Niogi et al. 2008a; b; Singh et al. 2010), superiorlongitudinal fasciculus (Cubon and Putukian 2011; Geary et

al. 2010; Mayer et al. 2010; Matthews et al. 2011; Niogi etal. 2008a; b), uncinate fasciculus (Geary et al. 2010; Mayeret al. 2010; Niogi et al. 2008a; b; Singh et al. 2010), coronaradiata (Little et al. 2010; Maruta et al. 2010; Matthews et al.2011; Mayer et al. 2010; Niogi et al. 2008a; b), corticospinaltract (Henry et al. 2011; Messe et al. 2011; Singh et al.2010), the cingulum bundle (MacDonald et al. 2011; Niogiet al. 2008a; b; Rutgers et al. 2008a), forceps minor andmajor (parts of corpus callosum; Messe et al. 2011), forcepsmajor (Little et al. 2010; Messe et al. 2011), cerebral lobarwhite matter (Lipton et al. 2009; Rutgers et al. 2008a),mesencephalon (Hartikainen et al. 2010; Holli et al. 2010b),the sagittal stratum (Cubon and Putukian 2011; Geary et al.2010; ), frontal lobe, parietal lobe, temporal lobe, occipitallobe (Salmond et al. 2006), dorsolateral prefrontal cortex(Lipton et al. 2009; Zhang et al. 2010), cerebellar peduncles(MacDonald et al. 2011; Maruta et al. 2010), hippocampus(Singh et al. 2010 ), fornix (Singh et al. 2010 ), thalamus(Grossman et al. 2011), thalamic radiation (Cubon andPutukian 2011; Messe et al. 2011), orbitofrontal white matter(MacDonald et al. 2011), subcortical white matter (Liptonet al. 2008), fronto-temporo-occipital association fiber bun-dles (Rutgers et al. 2008a), acoustic radiation (Cubon andPutukian 2011), and deep cortical brain regions (Brandstacket al. 2011).

In summary, there is a great deal of variability in DTIstudies of mTBI with respect to the time period of scanningat post-injury, as well as other factors including magnetstrength, brain regions examined, and methods of analyses,as noted above. Further, differences in both anatomicallocation of observed brain alterations, as well as in thenature of these alterations (i.e., increased versus decreasedFA), all contribute to the difficulty in interpreting this bodyof data. The findings are nonetheless striking in that they allsuggest that radiological evidence supports small and subtlebrain injuries in mTBI (see Table 3 and 4 for details). Thisevidence would not be possible if conventional MRI and CTscans alone were used to establish brain injury; it takes moreadvanced and sophisticated methods such as DTI that aresensitive to diffuse axonal injury to delineate these abnor-malities. Most of the studies reviewed, however, were cross-sectional studies, with scans acquired at different times post-injury. The cross-sectional nature of most of these studiesfurther highlights the need for longitudinal studies thatfollow a group of mTBI patients from early in the courseof injury, i.e., the first 24 to 72 h, with repeat scans at severalweeks, 1 month, 3 months, 6 months, and 1 year. Such datawould provide important information regarding the reversalof damage as well as provide important information aboutwhat radiological features early in the course of injurypredict good outcome versus poorer outcome with concom-itant post-concussive symptoms. There is also a clear needfor individualized imaging biomarkers (personalized


medicine approach), where a single subject could be com-pared to a normative group for accurate diagnosis, with MRbiomarkers also providing information about prognosis inorder to implement treatment plans. These and other issuesare the topic of future directions of research, which follows.

Future directions of research

Summary Until quite recently no sufficiently robust radio-logical technologies existed, on either the acquisition orpost-processing side, to detect small and subtle brain alter-ations that are extant in mTBI (see also Irimia et al. 2011).Today, there are advanced image acquisition sequencesavailable to identify and to quantify small regions of extra-and intra-cortical bleeding (i.e., SWI), as well as diffuseaxonal injuries (i.e., DTI). These advanced imaging toolsare particularly important for investigating brain pathologyin mTBI, where conventional MRI and CT imaging havefailed to provide radiological evidence of brain injuries.Hence we are now able to detect and to localize brainalterations in mTBI, which is a critical first step, as it meansthat the diagnosis of mTBI can be based on radiologicalevidence, rather than symptoms alone. We are now also ableto evaluate the extent of brain injuries. Moreover, we havethe capability to observe changes post-injury, and longitu-dinally, to determine prognosis based on early and interme-diate stages of brain injury. The latter may lead to the earlyidentification of those individuals who are likely to recoveryversus those who are more likely to experience prolongedpostconcussive symptoms.

Thus a focus on longitudinal studies is needed to under-stand the dynamic nature of brain injury changes over time,as there is very little information about the different patternsof recovery versus non-recovery, and how these changes arereflected by a given imaging modality. For example, lesionsmay be visible using one imaging modality but not another,depending upon the pattern and stage of recovery. Conse-quently, the combined use of multimodal imaging, usingsemi-automated measures for analyses, and including a lon-gitudinal focus would greatly further our understanding ofmTBI. These and other future directions for research areelaborated upon below.

Multi-modal imaging and standardized protocols What isneeded is the establishment of acquisition protocols thatinclude multimodal imaging to characterize brain alterationsin mTBI, as one imaging modality may not accuratelycapture brain alterations in mTBI. Both Duhaime and cow-orkers (2010) and Haacke and coworkers (2010) also dis-cuss the need for more standardized image acquisitionprotocols for both research and for clinical purposes. It isimportant also to select optimal imaging acquisition

protocols that characterize the kind of injury that is presentin mTBI. This approach has been used successfully inresearch in Alzheimer’s disease, multiple sclerosis, and inpsychiatric disorders such as schizophrenia (e.g., Leung etal. 2010; Zou et al. 2005). Following these principles is theClinical Consortium on PTSD and TBI (INTRuST; seedetails: http://intrust.spl.harvardu.edu/pages/imaging andsee http://intrust.sdsc.edu/), a new initiative sponsored bythe Department of Defense, which includes the acquisitionof multimodal imaging, from six multi-national centers,using a high resolution, multi-shell DTI protocol as well aSWI and resting-state fMRI acquisition sequences, in addi-tion to anatomical MRI sequences.

More specific measures of microstructural abnormalities Withregard to diffusion imaging, future advances will likelyinclude more specific parameters than FA and MD. Forexample, free-water is a measure that can be derived fromconventional DTI to increase the specificity of observedmicrostructural abnormalities. The free-water model (Pasternaket al. 2009) assumes that there are two distinct compart-ments, one that is comprised of water molecules that arefreely diffusing in extracellular space, and another that iscomprised of the remaining molecules, which are restrictedby the cellular tissue. As a result, it is possible to estimateexplicitly the volume of extracellular water, a measure thatis sensitive to vasogenic edema, and therefore consequentlylikely specific to neuroinflammation as well. In addition,DTI indices such as FA and MD that are corrected for free-water can be used to estimate the properties of the remainingcompartment, i.e., cellular tissue. These corrected values aretissue specific (Pasternak et al. 2009, 2011c) and the corre-lation between corrected FA and corrected MD is reduced(Metzler-Baddeley et al. 2012), which makes it possible touse these two parameters, separately, to evaluate tissuedegeneration versus extracellular swelling (vasogenic ede-ma and inflammation) and cell swelling (cytotoxic edema).In the very near future, this free-water method may beutilized to investigate and to track brain injury over timeand to establish possible biomarkers that predict outcomebased on knowing the type (vasogenic versus cytotoxic),location, and extent of the edema.

Multi-shell diffusion weighted imaging (DWI) and kurtosisMulti-shell diffusion imaging is another new approach thatmay be useful in future imaging studies of mTBI. Here,DWI is acquired at multiple b-values in the same sessionand it provides additional microstructural information aboutthe organization of white and gray matter. In these scansequences, b-values, which are higher than the standardDTI acquisition (e.g., 3000 mm/s2), are used to obtaindiffusion properties that vary with different gradientstrengths. Diffusion Kurtosis Imaging (DKI), a technique


http://intrust.spl.harvardu.edu/pages/imaging

http://intrust.sdsc.edu/

that uses multi-shell diffusion imaging, measures the non-Gaussian behavior of water diffusion, and has been shownto be sensitive to characterizing subtle changes in neuronaltissue (Jensen et al. 2005).

The kurtosis measure is likely more sensitive to biologicalprocesses such as “reactive astrogliosis” compared with themore general measures of FA and MD (Zhou et al. 2012).Specifically, kurtosis is a measure of the deviation from thediffusion tensor model (Gaussian diffusion), and thus comple-ments the other measures that are derived from the tensormodel. For example, the directionally specific kurtosis mea-sure has been shown to be more sensitive to developmentalchanges in white and gray matter than FA or MD in rat brains(Cheung et al. 2009). Thus, in this way, kurtosis is moresensitive than traditional diffusion measures to changes inrestricted diffusion and thereby has the potential to detectchanges related to cells (i.e., astrocytes, neurons, andoligodendrocytes), as opposed to less specific measures ofchanges in the integrity of tissue (e.g., FA and MD).

Lack of homogeneity in brain trauma and the need for apersonalized medicine approach While we have onlytouched the surface with respect to what more sensitiveimaging technology can inform us about mTBI, another areaof interest for future research is to go beyond group analy-ses, i.e., comparing a group of patients with mTBI with agroup of normal controls. Group analyses, in fact, are some-what misleading because they are predicated on findinglarger differences between groups than within groups. Un-fortunately, brain trauma is a very heterogeneous disorder,and group analyses, particularly those that use whole brainanalyses (i.e., comparing average mTBI brain to averageMRI brain), are not well suited for accurate analysis becausethey obscure the individual differences that characterizebrain injuries. The heterogeneity of brain trauma is a topicthat is also reviewed in this issue by Ms. Sara Rosenbaumand Dr. Michael Lipton.

To circumvent this heterogeneity, a personalized ap-proach needs to be developed that can be incorporated intocomparisons between mTBI and normal controls. Such anapproach must go beyond a visual inspection of DTI mapssuch as FA and ADC, to a quantitative, objective approach.The latter may then be used as both radiological evidence ofbrain injury and to provide an individual profile of braininjury, as well as to form the basis for comparing normalcontrols and patients with mTBI.

One possible approach to this problem is to build norma-tive atlases based on normal controls, along with robuststatistics (e.g., z-score and receiver operator-ROC- curves)to detect “out-of-the-normal” imaging features (e.g., FA,MD, free-water, and kurtosis) at various locations in thebrain. This information may then be used to detect brainregions that are abnormal in any of these measures, leading

to a diagnosis of diffuse axonal injury (FA, MD), or edema(free water), or myelin damage (kurtosis), which would bespecific for each individual case. In this way, one could notonly establish a profile of injury for each individual patient,but one could also perform group analyses based on theseverity and load of injuries (i.e., extent and number of brainregions involved), without relying on the assumption of acommon pattern of injury location among all patients withTBI. The latter assumption is the current approach to groupanalyses including brain-wise, voxel-based analyses thatcreate averages of brain regions, i.e., comparing a group ofhealthy and injured brains simultaneously, and demonstrat-ing where in the brain for the entire group of mTBI (not eachindividual), differs from a group of healthy controls.

Figure 8 shows an example of one mTBI case comparedto a normative atlas of FA and of MD, where z-score mapshighlight brain regions that are more than three standarddeviations from the normative brain atlas for FA (top offigure) and MD (bottom of figure). This is the kind ofinformation that can be evaluated for individual cases,where normative atlases can be built to examine any numberof measures (i.e., FA, MD, free-water, kurtosis, etc.).

A further example is shown in Figure 9, which depictsmore than three standard deviations from the normativebrain atlas for free-water, where subject specific maps werecreated to show abnormal free-water (edema) in two indi-viduals. The individual on the top shows more localizedabnormalities, while the individual on the bottom showsmore small, scattered lesions that have an edematous orneuroinflammatory component (Pasternak et al. 2011b).These findings may vary across subjects, from localizedpathologies to having a more diffuse and scattered patternof pathology, as seen here, and, importantly, provide infor-mation about individual pathology that is not detected usingconventional MR or CT. These variations pose extremechallenges to group comparisons, though group compari-sons may still be made. They also highlight the heterogene-ity that is characteristic of TBI, including mTBI.

Tractography Another promising method for probing alter-ations in white matter in mTBI is tractography. The wordtractography refers to any method for estimating the trajec-tories of the fiber tracts (bundles) in the white matter. Manymethods have been proposed for tractography, and theresults will vary depending on the chosen method. Forexample, deterministic tractography involves directly fol-lowing the main diffusion direction, whereas probabilisticmethods estimate the likelihood of two regions beingconnected (Bjornemo et al. 2002; Behrens et al. 2003).The most common deterministic approach is streamlinetractography (see Figure 10) (Basser et al. 2000; Conturoet al. 1999; Mori et al. 1999; Westin et al. 1999), which isclosely related to an earlier method for visualization of


tensor fields known as hyperstreamlines (Delmarcelle andHesselink 1992). For a clinical and technical overview oftractography in neurological disorders, the reader is referredto Ciccarelli et al. (2008). For reviews of tractographytechniques including explanations of common tractographyartifacts and a comparison of methods, the reader is referredto Jones (2008) and Lazar (2010).

DTI based streamline tractography has been used by severalinvestigative groups to examine schizophrenia and other neu-rological and psychiatric disorders (see review in Kubicki et al.2007; Shenton et al. 2010; Whitford et al. 2011). The mainlimitation of this method is that it does not allow one to tracefibers through complex fiber orientations such as branchingand crossing fibers. This is because DTI based streamline

tractography assumes that there exists only one fiber bundleoriented coherently in a single direction at each voxel. Thusvoxels where different fiber bundles cross cannot be charac-terized using this model. Consequently, several advancedmod-els have been proposed in the literature, such as a high-ordertensor model (Ozarian 2003; Barmpoutis et al. 2009), a spher-ical harmonics based nonparametric model (Anderson 2005)and a multi-tensor model (Tuch et al. 2002; Pasternak et al.2008; Malcolm et al. 2010), among others.

Figure 10 shows a method of tracing the corpus callosumfiber bundle using single tensorDTI based tractography (on thetop) and another method using two-tensor DTI based tractog-raphy (on the bottom) that illustrates the improved fiber track-ing using the two-tensor method. This method makes it

Fig. 8 Z-score maps for apatient with chronic mTBIsubject. Z-score maps werecreated from a comparison toa normative atlas. The regionsin red and yellow showstatistically significantabnormal regions for eitherFA (top) or MD (bottom)

Fig. 9 Z-score maps for twopatients with chronic mTBI.Z-score maps were created froma comparison to a normativeatlas. The images at the topshow a patient with morelocalized regions of increasedfree-water while the images atthe bottom show a patientwith more diffuse regions ofincreased free-water (blue colorindicates statistically significantareas of free-water comparedwith the normative atlas)


possible now to trace multiple fiber tracts that traverse the brainand connect several different brain regions (e.g., Malcolm et al.2010; Pasternak et al. 2008; Tournier et al. 2008).

Figure 11 shows all of the fibers in the brain that travelthrough the corpus callosum, in a single case, using two-tensor tractography (Malcolm et al. 2010). Of note here, themethodology for analysis can remain the same as before, i.e.,trace a certain fiber bundle in healthy controls and compute the“typical” diffusion properties such as FA, MD, etc., then tracethe same bundle in TBI subjects, and finally compare them todetect differences. What is different in terms of moving from asingle tensor model to two and multi-tensor models is that itimproves the ability to accurately identify crossing fiber tracts.

Mean-squared-displacement and return-to-origin probabilitiesOther more sensitive markers of diffusion, such as mean-

squared-displacement and return-to-origin probabilities, canbe obtained from more advanced diffusion scans such asmulti-shell (multiple b-values) diffusion imaging (e.g.,Mitra 1992; Yu-Chien et al. 2007). Although the scan timefor these acquisitions is longer, they provide more subtleinformation beyond what can be obtained from DTI as it iscurrently used. For example, the return-to-origin probabilitymeasures the probability that a water molecule will return toits starting point in a given amount of time. This measurewill be higher for white matter due to restriction on themotion of water as a result of the coherent layout of thewhite matter fibers. This probability will be lower in graymatter and lowest in CSF, where water is essentially free tomove. Thus this measure captures subtle changes in theorganization of white matter and has been shown to be moresensitive to de-myelination of white matter tracts comparedto DTI measures such as FA (Assaf et al. 2005).

Another diffusion measure that is more sensitive to therestriction of water molecules due to cellular boundaries ismean-square-displacement (MSD)(e.g., Assaf et al. 2002).This measure is the mean distance travelled by a watermolecule in a given diffusion time. Thus, MSD is highly

1-Tensor

2-Tensor Kalman Filter

Fig. 10 Part of the corpus callosum fibers, where seeding was done inthe mid-sagittal plane of the corpus callosum. Top figure shows thetracing using the standard single-tensor model and bottom figureshows tracts generated with the two-tensor model

Fig. 11 Panel A shows a coronal view of white matter fiber tractsusing a two-tensor model that go through the corpus callosum Panel Bis a sagittal view of the corpus callosum shown in Panel A


dependent on the cellular structure at any given location andhence could be related to the concentration of certain bio-chemicals. This could be validated by correlating this mea-sure with the concentration of certain biochemicals such asphospholipids as obtained using an MRS scan. Hence, suchmeasures can be very useful for detecting mTBI since theunderlying tissue changes are often very subtle and may bemissed by current DTI and DKI imaging protocols. In thenear future, this approach could also be combined withother brain biomarkers that are based, for example, onblood-serum, the latter a powerful complementary toolthat provides information about genes and proteins af-fected by brain injury (see section below; see alsoMondello et al. 2011).

Identification and delineation of brain injury, and thedevelopment of biomarkers for possible treatment andtreatment efficacy trials Advanced multi-modal neuroimag-ing techniques provide radiological evidence of mTBI thatgo beyond self-report and other more conventional meas-ures, and may elucidate further the mechanisms and neuro-physiology underlying mTBI. This is an important first step.More studies, however, are needed using multi-modal im-aging techniques. Further, based on their enhanced sensitiv-ity, many of these more advanced techniques should be usedto monitor treatment efficacy, and serve as endpoints fornew trials of medication aimed at neuroplasticity or neuro-inflammation in TBI.

One example of multi-modal neuroimaging is to com-bine MRS and DTI in the same subjects. MRS and DTIare highly complimentary given the biochemical andstructural focus of each modality. However, few studieshave utilized the two together. In severe head injury, thecombination of these two modalities has provided greaterdiagnostic accuracy for predicting outcome one year fol-lowing injury (Tollard et al. 2009), than either MRS orDTI alone. It is likely that this same combination wouldalso provide greater sensitivity to the more subtle changes inmTBI.

The co-localization of DTI and MRS may also providegreater insight into the underlying physiological changesthat occur in mTBI. An early MRS study by Cecil andcoworkers (Cecil et al. 1998) did not have DTI available atthe time, but their findings of decreased N-acetyl aspartate(NAA; a putative neuronal and axonal marker; see review inthis issue by Lin et al.) in the corpus callosum corroboratesDTI findings of reduced FA, as previously described in thecurrent review. As NAA is transported down axons and theloss of FA is attributed to axonal injury, a strong correlationbetween these two measures further strengthens the argu-ment for axonal injury. NAA MRS measures can also helpto validate DTI studies in regions of fiber crossings andconfirm that decreased FA can be attributed to loss of fiber

integrity as opposed to technical issues. Studies of schizo-phrenia (e.g., Tang et al. 2007) and motor neuron disease(Nelles et al. 2008) have also utilized MRS and DTI in thiscomplimentary fashion.

Additionally, by combining different biomarkers fromblood with MR biomarkers, we may be able to delineatefurther specific types of brain injury involved in mTBI, aswell as how they change over time, and what the evolutionis of secondary damage or progression of types of injuryover time. More specifically, serum biomarker profiles, asan outcome measure of brain damage, are being used todetect brain damage in ischemic stroke and TBI in animalstudies (Liu et al 2010). This approach may also be useful inhumans where TBI-specific biomarkers could be developed,based on proteomics, to provide distinctive profiles of spe-cific genes and proteins that are altered in mTBI (e.g.,Mondello et al. 2011). The free-water model, describedabove, could also be combined with measures of proteinsinvolved in neuroinflammation in the brain to develop com-bined TBI-specific biomarkers that may detect brain injuriesand predict course, outcome, and treatment response betterthan using either a proteomic or MR biomarker alone.

Thus combining multimodal imaging modalities, andcombining genomic and proteomic biomarkers with MRbiomarkers, may lead to the discovery of more specificbiomarkers of biochemical and physiological processes,which, in turn, may provide important new informationabout primary and secondary consequences of injury, andassist in determining what combination of biomarkers areindicative of axonal injury, inflammation, demyelination,apoptosis, neuroregeneration, etc., and what combinationbest predict outcome and treatment. It is also likely thatthe development of multiple biomarkers will lead to a newstratification of patients based on several biomarkers that,when combined, are more specific to important measures ofbrain injury than is any one biomarker alone. This newapproach to developing multi-modal MR biomarkers andcombining these with serum based proteomic biomarkersto investigate brain injuries in mTBI may go a long way toproviding more accurate diagnosis of mTBI, as well as toproviding important indicators of treatment response andoutcome.

Acknowledgements This work was supported in part by theINTRuST Posttraumatic Stress Disorder and Traumatic Brain InjuryClinical Consortium funded by the Department of Defense PsychologicalHealth/Traumatic Brain Injury Research Program (X81XWH-07-CC-CS-DoD; MES, JSS, SB, OP, MK, YR, M-AV, C-FW, RZ), by an NIHNINDS funded R01 (R01 NS 078337; RS, MES, JSS), by a Center forIntegration of Medicine (CIMIT) Soldier in Medicine Award (SB, MES),by an NIH NIMH funding R01 (R01 MH082918; SB), by funding fromthe National Research Service Award (T32AT000051; MPP) from theNational Center for Complementary and Alternative Medicine(NCCAM) at the National Institute of Health, by the Harvard MedicalSchool Fellowship as part of the Eleanor and Miles Shore Fellowship


Program (HH), by the Deutsche Akademischer Austauschdienst(DAAD; IK), and by funding from NCRR, including the NationalAlliance for Medical Image Computing (NAMIC-U54 EBOO5149;RK, MK, MES), and the Neuroimaging Analysis Center (NAC;P41RR13218; RK and CF).

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