Diffusion Tensor Imaging of Mild to Moderate Blast-RelatedTraumatic Brain Injury and Its Sequelae

Harvey S. Levin,1,2 Elisabeth Wilde,1,2,3 Maya Troyanskaya,1 Nancy J. Petersen,2,4 Randall Scheibel,1,2

Mary Newsome,1,2 Majdi Radaideh,2,3 Trevor Wu,5 Ragini Yallampalli,1 Zili Chu,3 and Xiaoqi Li1

Abstract

To evaluate the effects of mild to moderate blast-related traumatic brain injury (TBI) on the microstructure ofbrain white matter (WM) and neurobehavioral outcomes, we studied 37 veterans and service members (meanage 31.5 years, SD¼ 7.2; post-injury interval 871.5 days; SD¼ 343.1), whose report of acute neurological statuswas consistent with sustaining mild to moderate TBI due to blast while serving in Iraq or Afghanistan. Fifteenveterans without a history of TBI or exposure to blast (mean age 31.4 years, SD¼ 5.4) served as a comparisongroup, including seven subjects with extracranial injury (post-injury interval 919.5 days, SD¼ 455.1), and eightwho were uninjured. Magnetic resonance imaging disclosed focal lesions in five TBI participants. Post-concussion symptoms (Neurobehavioral Symptom Inventory), post-traumatic stress disorder (PTSD) symptoms(PTSD Checklist-Civilian), and global distress and depression (Brief Symptom Inventory) were worse in the TBIparticipants than the comparison group, but no group differences were found in perceived physical or mentalfunctioning (SF-12). Verbal memory (Selective Reminding) was less efficient in the TBI group, but there were nogroup differences in nonverbal memory (Selective Reminding) or decision making (Iowa Gambling Task). Verbalmemory in the TBI group was unrelated to PTSD severity. Diffusion tensor imaging (DTI) using tractography,standard single-slice region-of-interest measurement, and voxel-based analysis disclosed no group differences infractional anisotropy (FA) and apparent diffusion coefficient (ADC). However, FA of the left and right posteriorinternal capsule and left corticospinal tract was positively correlated with total words consistently recalled,whereas ADC for the left and right uncinate fasciculi and left posterior internal capsule was negatively corre-lated with this measure of verbal memory. Correlations of DTI variables with symptom measures were non-significant and inconsistent. Our data do not show WM injury in mild to moderate blast-related TBI in veteransdespite their residual symptoms and difficulty in verbal memory. Limitations of the study and implications forfuture research are also discussed.

Key words: blast-related traumatic brain injury; diffusion tensor imaging; outcome

Introduction

Traumatic brain injury (TBI) is a leading cause ofmorbidity and disability in service members deployed in

Iraq and Afghanistan (Warden, 2006), accounting for one-fourth of medical evacuations (French and Parkinson, 2008;Galarneau et al., 2008). An explosive mechanism was linkedto 78% of the clinician-confirmed injuries sustained by U.S.service members over a 3-year period, and the head and neckwere involved in 30% of these injuries (Owens et al., 2008). Inpost-deployment questionnaires, 12% (Schneiderman et al.,2008) to 23% (Hoge et al., 2008; Terrio et al., 2009) of returnees

reported that they had sustained a TBI; blast accounted for 79–88% of these injuries (Hoge et al., 2008; Terrio et al., 2009), and98% had acute injury features consistent with mild TBI (Hogeet al., 2008). Of 1292 soldiers in an Army unit who reported ona post-deployment questionnaire that they had sustained aninjury approximately 6 months earlier, a clinical interviewconfirmed that TBI associated with brief loss or alteration ofconsciousness had occurred in 907 (22.8%) of these servicemembers (Terrio et al., 2009). Despite the apparent mild na-ture of clinician-confirmed TBI studied by Terrio and associ-ates (2009), post-concussion symptoms reported at 6 monthspost-injury included memory deficit (16.3%), headache

Departments of 1Physical Medicine and Rehabilitation, 3Radiology, and 4Medicine, Baylor College of Medicine, Houston, Texas.2Michael E. DeBakey VA Medical Center, Houston, Texas.5Department of Psychology, Brigham Young University, Provo, Utah.

JOURNAL OF NEUROTRAUMA 27:683–694 (April 2010)ª Mary Ann Liebert, Inc.DOI: 10.1089=neu.2009.1073

683

(20.20%), and irritability (21.30%). Other studies have con-firmed the presence of cognitive, behavioral, and emotionalpost-concussion symptoms on post-deployment question-naires completed by service members who reported havingsustained injuries consistent with mild TBI (Belanger et al.,2009; Hoge et al., 2008; Schneiderman et al., 2008). Comorbidpost-traumatic stress disorder (PTSD) and depression com-plicate outcomes in nearly half of returnees reporting mildblast-related TBI (Hoge et al., 2008; Schneiderman et al., 2008),posing a challenge for treatment. However, the neuralmechanisms mediating these symptoms that are presentmonths after mild blast-related TBI are unknown, and imag-ing studies of those affected are sparse.

The blast wave of increased pressure produced by anexplosion may be construed as the primary mechanism ofblast-related TBI (Cernak and Noble-Haeusslein, 2009), butsecondary and tertiary injuries that occur when the body isstruck by projectiles such as debris or propelled by the explo-sion reportedly account for the majority of injuries resultingfrom improvised explosive devices (Champion et al., 2009).Although there is a lack of consensus concerning the contri-bution of specific neural mechanisms to brain injury resultingfrom blast (Cernak and Noble-Haeusslein, 2009), a recent re-port showed that the cognitive functioning in service mem-bers who had sustained TBI was similar across blast, motorvehicle crashes, and non-blast blunt injury (Belanger et al.,2009). This similarity in the pattern of cognitive findings hasgiven rise to the possibility that blast-related TBI may involveaxonal injury similar to the neuropathology that has beenreported in civilian TBI (Blumbergs et al., 1994; Oppenheimer,1968). Disruption of white matter (WM) integrity with func-tional disconnections due to axonal injury has been implicatedin slowing of cognitive processing and other cognitive im-pairments related to civilian TBI severity (Meythaler et al.,2001; Povlishock and Katz, 2005). The lack of brain imagingstudies of service members and veterans with blast-relatedTBI has limited progress in characterizing the pathology ofthese injuries, giving impetus to performing this study.

To evaluate neuropathology in a sample of Operation En-during Freedom and Operation Iraqi Freedom (OEF=OIF)veterans who reported blast-induced TBI, we utilized mag-netic resonance imaging (MRI) with diffusion tensor imaging(DTI), a relatively new MRI technique that evaluates WMmicrostructure by measuring diffusion of water. WM tractsnormally constrain the isotropic diffusion of water, a charac-teristic indexed by fractional anisotropy (FA), wherein an FAvalue approaching 1.0 reflects maximal anisotropic diffusion,with values approaching zero indicating compromise of WMintegrity. Conversely, the apparent diffusion coefficient(ADC) generally increases with TBI severity, especially whenDTI is performed in the chronic post-injury period. DTI issensitive to a continuum of civilian TBI severity (Benson et al.,2007; Kraus et al., 2007) and chronicity (Bazarian et al., 2007;Inglese et al., 2005; Kraus et al., 2007; Wilde et al., 2008). Incontrast to reports of lower FA in chronic mild TBI patients(Kraus et al., 2007), DTI within the first week (Bazarian et al.,2007; Chu et al., 2010; Wilde et al., 2008; Wu et al., 2009) aftermild TBI showed increased FA and lower ADC consistentwith cytotoxic edema, a potentially reversible condition. Therelationship of DTI variables to cognitive measures has beenfound to be different in civilians with chronic mild TBI com-pared with uninjured subjects, but between-group differences

in FA have not been consistent across brain regions (Niogiet al., 2008). Some issues in the interpretation of these DTIstudies have been inclusion of patients with structural lesions(Benson et al., 2007; Inglese et al., 2005; Niogi et al., 2008), andunavailability of acute imaging findings (Kraus et al., 2007).

We evaluated the integrity of brain WM in veterans andservice members who screened positive for mild to moderateblast-related TBI. We postulated that severity of WM injury onDTI would be positively related to injury severity and post-concussion symptoms, but negatively related to cognitivefunctioning and health-related quality of life (HRQOL). Withthe high rate of comorbid PTSD and depression in OEF=OIFveterans (Hoge et al., 2008; Invisible Wounds of War, 2008;Schneiderman et al., 2008; Seal et al., 2009) with blast-relatedmild TBI, we also analyzed these conditions and generalemotional distress.

Methods

Study design

This prospective, dual-cohort design recruited two groupsof post-deployment OEF=OIF veterans and service members,including a group with self-report of mild to moderate TBIdue to blast, and a comparison group without blast exposurewho sustained injury to other body regions or had no injury.This comparison group controlled for the adverse effects ofdeployment-related stress on sustained attention, memory,and negative affect (Vasterling et al., 2006).

Participants

The study was approved by the Institutional Review Boardand the Michael E. DeBakey Veterans Affairs Medical Center(MEDVAMC) Research and Development Board, and par-ticipants provided written informed consent. Recruitmentwas done through physician referral, research databasesearch at the MEDVAMC, and through advertisement in thenewspaper of a regional Army post. Eligibility criteria for theTBI group included diagnosis of blast-related TBI by a phy-sician, and self-reported injury features consistent with TBIdue to blast (i.e., one or more blast injuries associated with orwithout loss of consciousness [LOC]), provided that there wasa period of confusion, and=or post-traumatic amnesia (PTA)immediately after the blast (French and Parkinson, 2008). Aspart of the clinical assessment of these patients, an interviewwith a physician identified loss or alteration of consciousnessat the time of injury associated with blast. This interview alsoqueried the patient regarding loss of memory for events priorto and following the injury. Other eligibility criteria in bothgroups were age 18–54 years; within 42 months post-injury(for all injured subjects); right-handedness; no history of se-vere neurological disorders, schizophrenia, or bipolar disor-der; no pre-deployment hospitalization for TBI; no currentsubstance abuse; and no contraindications to undergoingMRI. All participants were screened for previous and currentsubstance abuse (Maisto et al., 2000; Saunders et al., 1993;Skinner, 1982). Of 236 veterans and service members screenedfor this study, 182 individuals were excluded: 60 had post-injury intervals longer than 42 months, 42 declined or lackedcontact information, 30 reported exposure to blasts, butwithout altered consciousness, 21 had history of TBI, but notdue to blast, 15 had alcohol or=and drug abuse problems,

684 LEVIN ET AL.

9 were diagnosed with severe neurological=or psychiatricdisorders, and 5 could not participate due to claustrophobia.

Fifty-four service members and veterans who served in Iraqor Afghanistan were recruited for this study, including 37whose self-report of LOC and PTA associated with blast wereconsistent with mild to moderate TBI. Seventeen servicemembers and veterans were recruited for the comparisongroup, who reported no history of TBI and no exposure toblast or LOC, including eight who reported at least one ex-tracranial injury during deployment, and nine who wereuninjured (Table 1). Two subjects from the comparison groupwere excluded due to incidental MRI findings (see below).Imaging data from one of the TBI subjects were not analyzeddue to technical difficulties.

Brain imaging

Magnetic resonance imaging. Unsedated MRI was ac-quired on a 3.0 T Philips Achieva scanner (Cleveland, OH) atthe MEDVAMC using an 8-channel SENSE headcoil. Anato-mical series to assess neuropathology included T1-weighted3D-turbo field echo (9.9 msec repetition time [TR], 4.6 msececho time [TE], 1.0 mm axial slices, 0 mm gap, 132 slices,240 mm field of view [FOV], 88 flip angle), T2-weighted gra-dient echo (2500 msec TR, 32 msec TE, 5.0 mm axial slices,0 mm gap, 25 slices, 224 mm FOV, 30–408 flip angle), T2-weighted fluid attenuated inversion recovery (FLAIR)(11000 msec TR, 105 msec TE, 5.0 mm axial slices, 1 mm gap,25 slices, 240 mm FOV, 908 flip angle), and T2-weighted gra-dient spin echo (GRASE) imaging (2141 msec TR, 80 msec TE,5.0 mm axial slices, 0 mm gap, 25 slices, 230 mm FOV, 908 flipangle).

Diffusion tensor imaging. Transverse multi-slice spinecho, single shot, echo planar imaging (EPI) sequences wereused (7341 msec TR, 70 msec TE, 2.0 mm axial slices, 0 mmgap). A 224 mm FOV was used with a measured voxel size of2.0�2.0�2.0 mm, and a reconstructed voxel size of 1.75�1.75�2.0 mm. Diffusion was measured along 32 direc-tions (number of b-value¼ 2, low b-value¼ 0, and high b-value¼ 1000 sec=mm2). To improve signal-to-noise ratio,high-b images were acquired twice and averaged in mostcases. Each acquisition took approximately 4 min 44 sec, and70 slices were acquired.

Review of magnetic resonance imaging findings. MRIimages were reviewed by a board-certified neuroradiologistat the MEDVAMC independently of group identification oroutcome data. The presence, location, and pathology of eachlesion were documented, and the presence and severity of

diffuse pathology such as atrophy were also coded. This re-view disclosed the presence of a small gliotic lesion in the rightinferior frontal gyrus of one comparison participant, andmultiple areas of shearing injury within the frontal lobes ofanother. These findings were interpreted as evidence of oldtraumatic injury and both subjects were later excluded fromthe overall analysis. Five veterans with TBI had MRI findingsconsistent with brain trauma, and their neuropathology issummarized in Table 2. One TBI participant had a Chiari typeI malformation as an incidental finding.

Diffusion tensor imaging analysis. Selection of sites foranalysis was guided by the literature on the neuropathologyof TBI documenting vulnerability of parasagittal regions toaxonal injury (Adams et al., 1982; Meythaler et al., 2001), andthe robustness of fiber tracts permitting reliable measurement.We measured FA and ADC for both manually-traced regionsof interest (ROIs) on a slice-by-slice basis, and quantitativefiber tractography to assess WM integrity, as these methodshave different advantages and limitations.

Diffusion tensor imaging data preprocessing. The PhilipsDTI registration tool (release 0.4; Netsch and van Muiswinkel,2004) for Philips Research Integrated Development Environ-ment V4 was used, with the following parameters: affinetransformation, 10% local correlation, maximum number ofsteps¼ 20, minimum distance 50 mm, removal of motion andeddy current artifacts, and averaging two acquisitions forbetter signal-to-noise ratio.

Diffusion tensor imaging quantitative fiber tracto-graphy. Operators who analyzed the DTI data were notgiven any information concerning the group identification oroutcome data. The Philips fiber tracking software (Hoogen-raad, 2002) was utilized to determine fiber tracts passingthrough ROIs, and mean FA and ADC of the identified fiberswas used as the quantitative measure for DTI variables. Themethodology and quantitative tractography protocols for thecorpus callosum (including genu, body, splenium, and total),arcuate fasciculus, inferior longitudinal fasciculus, inferiorfronto-occipital fasciculus, uncinate fasciculus, cingulatebundle, and anterior and posterior limbs of the internal cap-sule have been previously published (Levin et al., 2008; Wa-kana et al., 2007; Wilde et al., 2006; Wilde et al., 2009). Figure 1illustrates the quantitative tractography method used for thecorpus callosum and cingulate regions in a subject with blast-related DTI. Corticospinal tracts were measured with a mul-tiple ROI method in the axial plane, with one ROI placed atthe level of the colliculi, and the other placed at the WM justsuperior to the roof of the lateral ventricles. The fornix was

Table 1. Demographic Features in the TBI and Comparison Groups

TBI (n¼ 37) Comparison (n¼ 15)

Mean SD Mean SD Wilcoxon Z scores p Value

Age (years) 31.5 7.2 31.4 5.4 0.2424 .809Education (years) 13.5 1.4 13.6 1.4 0.2076 .836Pre-injury IQ 102.9 5.3 101.6 7.1 �0.8916 .373Post-injury interval to scan (days) 871.5 343.1 919.5 455.1 0.3117 .755

TBI, traumatic brain injury; SD, standard deviation; IQ, intelligence quotient using the Barona et al. (1984) method of estimation.

DTI IN BLAST INJURY 685

measured using two seed point ROIs placed along the fornixin two different coronal slices where the fornix body is visibleas one bundle.

Standard (non-tractography) diffusion tensor imagingregions of interest. Non-tractography ROI protocols in-cluded the total corpus callosum (including genu, body,splenium, and total), and the right and left anterior and pos-terior limbs of the internal capsule. The total corpus callosumand its subregions were measured on the mid-sagittal slice,using the same boundaries as the quantitative tractographymeasurement (Wilde et al., 2006). The boundaries used for the

internal capsule were also applied in a similar fashion to ob-tain non-tractography ROI measurement. Measurement of theFA and ADC within the defined ROI on one slice was per-formed. The location and boundaries of regions involved inthe ROI method are illustrated in Figure 1.

Intra-rater and inter-rater agreement. To examine intra-rater agreement, analysis of each region was performed twicefor each participant for both quantitative tractography andstandard ROI measurement; intra-class correlation coeffi-cients (ICCs) exceeded 0.95 for all DTI indices. Inter-rateragreement was also assessed by measurement of each proto-

Table 2. Durations of LOC=PTA and MRI Pathology in TBI Participants

SubjectLOC

(yes=no=uncertain)Durationof LOC

Durationof confusion

Durationof PTA Lesion location and pathology

1 No — < 30 min < 30 min Chiari type I malformation2 Uncertain — < 30 min — —3 Uncertain — < 30 min — —4 Yes < 1 min 30 min–24 hours < 30 min —5 No — < 30 min < 30 min —6 Uncertain — < 30 min — —7 Yes 6–24 hours 30 min–24 hours — —8 No — < 30 min — —9 Yes < 1 min 24 hours–7 days 30 min–24 hours —

10 No — < 30 min — —11 Yes 1–30 min < 30 min — —12 Yes 1–30 min 24 hours–7 days 30 min–24 hours —13 Uncertain — < 30 min — —14 Uncertain — 30 min–24 hours 30 min–24 hours —15 No — 30 min–24 hours 30 min–24 hours MDBA16 Yes < 1 min < 30 min — (R=L) SFG and (R) FLWM

and MFG shearing injuryof WM and G=WJ

17 Yes < 1 min 7 days–1 month 7 days–1 month —18 No — < 0 min — —19 Yes < 1 min < 30 min < 30 min —20 Yes < 1 min 30 min–24 hours < 30 min —21 Yes 1–30 min < 30 min — MDBA, (R=L) FLWM, SFG,

and PG shearing injuryof WM and G=WJ

22 Uncertain — < 30 min < 30 min —23 Yes 1–30 min < 30 min 30 min–24 hours —24 No — — 30 min–24 hours (R=L) FLWM, SFG,

and MFG gliosis of WMand G=WMJ

25 Yes 1–30 min — — —26 No — < 30 min — —27 Uncertain — < 30 min 30 min–24 hours —28 Yes 1–30 min 24 h–7 days 24 h–7 days —29 Yes 1–30 min 24 h–7 days < 30 min (R=L) SFG and IFG, (L)

PL encephalomalacia andshearing injury of G=WMJ

30 Yes < 1 min 24 h–7 days > 3 months —31 Uncertain — 24 h–7 days 24 h–7 days —32 Yes 1–30 min 30 min–24 hours < 30 min —33 Uncertain — < 30 min 30 min–24 hours —34 Uncertain — — < 30 min —35 No — < 30 min < 30 min —36 Yes < 1 min < 30 min > 3 months —37 No — < 30 min — —

MDBA, mild diffuse brain atrophy; FLWM, frontal lobe white matter; SFG, superior frontal gyrus; MFG, middle frontal gyrus; IFG, inferiorfrontal gyrus; PG, precentral gyrus; PL, parietal lobe; WM, white matter; G=WMJ, grey=white matter junction; R, right; L, left; LOC, loss ofconsciousness; PTA, post-traumatic amnesia; TBI traumatic brain injury; MRI, magnetic resonance imaging.

686 LEVIN ET AL.

col by two different raters in five cases in each group; ICCsagain exceeded 0.95.

Voxel-based analysis. The preprocessed DTI data wereloaded into DTI Studio ( Johns Hopkins University, Baltimore,MD) to compute and export DTI index maps including ADCand FA. To achieve better inter-subject registration, the pointof intersection of the anterior commissure with the mid-sagittal plane was selected as the landmark and manuallyreset as the origin of each exported map image. The FA andADC maps were calculated with the background noisethreshold of 10, which excluded pixels with lower intensity onthe b¼ 0 image. In addition, b¼ 0 images were also exported.The b¼ 0 image for one control participant was used to createa template in Montreal Neurological Institute space. All DTIindex maps were subsequently normalized to the template andthen smoothed with a gaussian filter of full width at halfmaximum of 8 mm. After data preparation, the voxel-basedanalysis (VBA) was performed using SPM2 (Wellcome De-partment of Imaging Neuroscience, London, U.K.) running onMATLAB 6 (MathWorks, Natick, MA). The Student’s unpairedt-test was performed between TBI and comparison groups toevaluate any difference in FA and ADC. In these analyses, acluster threshold of 10 and a p value of 0.01 were used.

Outcome measures

Participants in both groups underwent outcomes assess-ment at the MEDVAMC on the day of imaging or within1 week.

Symptom and quality-of-life scales. Post-concussionsymptoms were evaluated in both groups by the Neurobe-havioral Symptom Inventory (NSI) (Cicerone and Kalmar,1995), a self-report symptom inventory of 22 post-concussionsymptoms. Inclusion of the non-TBI group provided an esti-mate of the level of symptoms such as headache in a group ofpost-deployment veterans. The participant rated the presenceand severity of each symptom for the past 2 weeks on a five-point scale of severity. Cluster analysis (Cicerone and Kalmar,1995) of the NSI has revealed physical, cognitive, affective,and somatic symptom clusters. The reliability and validity of

the NSI have been supported in previous studies (Ciceroneand Kalmar, 1995). We administered the PTSD Checklist-Civilian Version (PCL-C) (Blanchard et al., 1996), a self-reportsymptom inventory of 17 PTSD symptoms which the partic-ipant rated on a five-point scale of severity based on the pastmonth. The reliability and validity of the PCL-C have beenfound to be satisfactory (Blanchard et al., 1996). The totalPTSD severity score of the PCL-C was analyzed. From theBrief Symptom Inventory (BSI) (Derogatis, 1982) we analyzedthe Global Severity Index and the depression scale. HRQOLwas measured by the Mental and Physical Summary scores ofSF-12, a brief version of the Medical Outcomes Study Short-Form (SF-36) which is supported by reliability and validitydata (Ware et al., 1996).

Cognitive assessment. Episodic memory was evaluatedusing the Verbal Selective Reminding Test (VSRT; Buschke,1973), and the Nonverbal Selective Reminding Test (NSVRT;Fletcher, 1985). The verbal version tested consistent long-termretrieval (CLTR) of 12 words over six trials, followed by adelayed recall trial administered 30 min later. The NonverbalSelective Reminding Test (Fletcher, 1985) measured CLTR ofthe spatial location for eight dots over eight trials followed bya 30-min delayed recall. Total number of items recalled con-sistently across trials and the delayed recall score were ana-lyzed for both tests. To measure decision making in relation torewards and penalties over trials, we administered the IowaGambling Task (Bechara et al., 1994), in which the participantwas asked on each of 100 trials to select a card from one of fourdecks. The participant was free to select a card from any of thedecks on each trial in response to rewards or penalties whichwere unpredictable and followed each card selection. Impetusfor this task was the somatic marker hypothesis that emo-tional signals bias selection of advantageous responses andinhibition of disadvantageous responses (Damasio, 1996).Bechara and associates (2000) postulated that a neural systemconsisting of ventral medial prefrontal cortex, amygdala, andventral striatum mediates the capacity to shift preference toadvantageous responses as experience accrues with rewardsand penalties. A rival postulation (Rolls, 1999) differs, mainlyby implicating the lateral orbital frontal cortex rather than theventral medial region. The decks differed in the schedule and

FIG. 1. From left to right: Axial diffusion tensor imaging (DTI) fractional anisotropy (FA) color map of a subject withmoderate blast-induced TBI (reportedly> 30 min duration of post-injury confusion), demonstrating both the quality of DTIdata acquisition and the protocol used for the anterior and posterior limbs of the internal capsule using the region-of-interest(ROI) analysis method (boundaries are outlined in white). Next, the DTI FA color map for the same individual is portrayed inthe sagittal plane, and boundaries used for the subregions of the corpus callosum (genu, body, and splenium) using the ROIanalysis method are illustrated (boundaries are outlined in white). Third, a sagittal view of the tractography of the totalcorpus callosum is overlaid on the same subject’s T1-weighted image, again illustrating the excellent quality of the tracto-graphy results, as well as the characteristic fiber pattern that emerges using the quantitative tractography method of analysis.Finally, we see a sagittal view of the tractography of the left cingulum bundle overlaid on the subject’s T1-weighted image.Note that the tractography fiber patterns for this individual with a history of moderate blast-induced traumatic brain injurydo not qualitatively differ from the expected pattern observed in control subjects, consistent with the lack of quantitativedifference in the DTI metrics obtained.

DTI IN BLAST INJURY 687

amount of rewards and penalties given for selecting a card.Following each card selection, the participant was informed ofthe magnitude of reward (or penalty) of play money. Selectinga card from two of the decks (C and D) resulted in largerewards on early trials, followed by costly penalties on latertrials (disadvantageous decks), whereas selection of cardsfrom the other two decks (A and B) produced consistent, al-beit smaller, rewards, but no large penalties. Overall, selectionof cards from the advantageous decks generated larger netgains over many trials. The difference between the sum ofcards selected from decks A and B and decks C and D was thedependent measure. With a dichotomous variable of cardsselected from advantageous versus disadvantageous decks,we also analyzed the distribution of this difference score andidentified outliers.

Statistical analysis

Because of the small sample size and because some of theoutcome variables had a non-normal distribution, we used thenormal approximation continuity-corrected z statistic for thenon-parametric Wilcoxon rank sum two-sample test to com-pare the TBI and comparison groups on continuous variables.The non-parametric Kruskal-Wallis test was used to comparethe mild TBI, moderate TBI, and comparison groups on con-tinuous variables. A repeated-measures analysis was used tocompare consistent long-term retrieval scores between the TBIand comparison groups on the Verbal Selective Remindingand the Nonverbal Selective Reminding tests, which werecomposed of six trials, and eight trials, respectively. Forbetween-group comparisons of categorical variables, we usedFisher’s exact test for 2�2 tables, and chi-square test forcomparison of variables with more than two categories. Stu-dent’s t-tests were used to test between-group differences inthe VBA of DTI variables. Correlation of imaging data withthe outcome measures was performed using the Spearmanrank-order statistic. p Values< 0.01 were considered signifi-cant.

Results

Demographic and clinical features

The groups did not significantly differ in age, education,pre-injury IQ estimated from demographic features (Baronaet al., 1984), or the time from the date of injury (or end ofdeployment for uninjured veterans in the comparison group;Table 1).

As seen in Table 2, 17 (46%) of the TBI participants reportedsome LOC, including one whose LOC was longer than 30 min.

Eight TBI participants (22%) reported durations of PTA orconfusion longer than 24 h, for a total of nine participants(24%) whose duration of LOC, altered consciousness, or PTAwas consistent with moderate TBI. The remaining 28 TBIparticipants reported durations of LOC or altered conscious-ness indicative of mild TBI. For the 27 TBI participants whoreported exposure to more than one blast, PTA and LOC forthe most severe injury are represented in Table 2.

Post-concussion and symptoms of post-traumaticstress disorder

Participants with TBI reported significantly more severepost-concussion symptoms than the comparison group for thephysical, cognitive, and sensory clusters, but not for the af-fective cluster, of the NSI (Table 3). The mean total PTSDsymptom score on the PCL-C was also significantly higher inthe TBI group (Table 4).

According to an established criterion T-score >50 on thePCL-C, 22 of 37 (59.5%) of the TBI participants had scoresconsistent with the diagnosis of PTSD, compared with 4 of 15(28.6%) of the comparison group (Fisher’s exact test p¼ 0.064).Total PTSD and the sum of the post-concussion symptomscores (Table 3) were also highly correlated within the TBI(Spearman r¼ 0.89, p< 0.0001) and comparison (r¼ 0.94,p< 0.001) groups. When we adjusted the PTSD total score forthe sum of the post-concussion symptom cluster scores on theNSI, the between-group difference was eliminated. Similarly,adjusting the sum of the NSI cluster scores for the PTSD to-tal score mitigated the between-group difference in post-concussion symptoms.

Emotional distress, depression, and health-relatedquality of life

Global emotional distress and depression as measured bythe BSI were more severe in the TBI group than the compar-ison group (Table 4). According to a criterion T score of 63 orhigher on the Global Severity Index of the BSI, 36 of the 37(97.3%) TBI participants had generalized emotional distress,compared with 9=15 (60.0%) of the comparison group(Fisher’s exact probability¼ 0.0014). The groups did not sig-nificantly differ in the Physical or Mental Summary scores ofthe SF-12 (Table 4).

Cognitive findings

Between-group analysis of total CLTR across trials dis-closed that verbal learning and memory on the Verbal Selec-tive Reminding Test was less efficient in the TBI group than

Table 3. Mean Post-Concussion Cluster Scores for Neurobehavioral Symptom Inventory

TBI (n¼ 37) Comparison (n¼ 15)

Mean SD Range Mean SD Range Wilcoxon statistic p Value

Physical 1.33 0.73 0.00–2.83 0.72 0.73 0.00–2.66 �2.75 0.006Cognitive 2.23 0.90 1.20–4.00 1.43 1.21 0.00–3.80 �2.43 0.015Affective 2.24 0.99 0.25–4.00 1.38 1.13 0.00–3.75 �1.54 0.013Sensory 1.82 1.05 0.00–3.50 0.83 1.06 0.00–3.50 �2.49 0.004Sum of mean cluster scores 7.64 3.02 0.45–13.33 4.36 3.69 0.00–13.71 �2.88 0.003

TBI, traumatic brain injury; SD, standard deviation.

688 LEVIN ET AL.

the comparison participants (F (1,51)¼ 22.92, p< 0.0001). Asseen in Figure 2, delayed recall of the word list was also lowerin the TBI group than the comparison group (F (1,51)¼ 14.18,p¼ 0.0004). In contrast, nonverbal learning and memory(CLTR) for the spatial location of dots across trials (F (1,43)¼2.23, p¼ 0.143), and recall after a delay (F (1,43)¼ 0.91,p¼ 0.345) did not differ between the groups.

Spearman correlations between the verbal memory vari-ables and the total PTSD score were non-significant, includingthe total number of words consistently retrieved across trials(r¼ –0.111, p¼ 0.52), and delayed recall (r¼�0.202, p¼ 0.23).For Nonverbal Selective Reminding, correlations with totalPTSD score were r¼�0.293 ( p¼ 0.10) for consistent retrieval,and r¼�0.317 ( p¼ 0.08) for delayed recall of spatial loca-tions.

Decision-making performance on the Iowa Gambling Task,as measured by the difference in the number of cards selectedfrom advantageous and disadvantageous decks over 100 tri-als, did not differ between the TBI (mean¼ 3.65, SD¼ 23.74)and the comparison (mean¼ 8.0, SD¼ 26.33) groups (F(1,47)¼ 0.33, p¼ 0.570), and no between-group differences inperformance were present on any of the five blocks of 20 trials.

Diffusion tensor imaging findings

Distributions of FA and ADC as measured by fiber tracto-graphy or the ROI method were similar for the TBI andcomparison groups. For example, fiber tractography dis-closed a mean FA for the total corpus callosum of 0.50(SD¼ 0.02, range¼ 0.46–0.54) for the TBI group, and 0.50(SD¼ 0.02, range¼ 0.45–0.53) for the comparison group,Wilcoxon statistic¼�1.06, p¼ 0.48. Corresponding ADCvalues for the TBI group (mean¼ 0.84, SD¼ 0.03, range¼0.79–0.89) did not differ from those of the comparison group(mean¼ 0.85, SD¼ 0.06, range¼ 0.77–0.97), Wilcoxon statis-tic¼ 0.71, p¼ 0.48.

Consistent with this pattern, no between-group differenceswere found on either ADC or FA using either fiber tracto-graphy or non-tractography methods, including a single-sliceROI approach and a VBA.

To further examine the possibility that the lack of groupdifferences on DTI parameters may have been attributable tothe relatively mild nature of the blast-injury exposure, werepeated analysis of DTI variables for both quantitative trac-tography and ROI methods by comparing the data of the 27subjects with mild TBI with findings for nine subjects withmoderate TBI in whom severity of injury was defined byduration of LOC, altered consciousness, or PTA (Table 2),relative to the 15 subjects in the comparison group usingKruskal-Wallis tests. For quantitative tractography, therewere no significant differences found among these groups onany DTI variable. Using the ROI method, the FA of the totalcorpus callosum marginally differed among the groups (w2

(2)¼ 6.16, p¼ 0.05), but contrary to expectations, the moder-ate TBI group demonstrated a higher mean FA in this regionthan either the mild TBI or the comparison group.

Correlation of diffusion tensor imagingfindings with outcome measures

We found no significant correlations between the outcomemeasures and DTI variables within the comparison group ofveterans and service members who did not sustain a TBI andwere not exposed to blast. As described below, the direction,magnitude, and consistency of these brain–behavior correla-tions within the TBI group varied with the outcome domainand whether DTI data were processed by fiber tracking or ROImethods.

Table 4. Mean Scores for GSI and Depression on the BSI, PTSD on PCL-C, and SF-12

TBI (n¼ 37) Comparison (n¼ 15)

Mean SD Range Mean SD Range Wilcoxon statisticb p Value

GSI (BSI)a 76.00 7.52 46.00–81.00 64.20 14.99 35.00–81.00 �2.88 0.004Depression Scale (BSI)a 69.51 10.49 44.00–81.00 60.40 12.89 43.00–81.00 �2.37 0.018PTSD score (PCL-C) 55.57 15.64 23.00–84.00 40.07 19.59 17.00–77.00 �2.55 0.011SF-12

Physical summary 40.59 12.29 18.67–65.94 45.78 10.64 23.46–59.08 1.44 0.149Mental summary 36.61 11.32 18.60–63.26 42.52 13.42 20.33–62.84 1.61 0.107

aThe BSI variables are T-scores for non-patient norms.bThe value for the Wilcoxon statistic is the normal approximation continuity-corrected z statistic.TBI, traumatic brain injury; SD, standard deviation; BSI, Brief Symptom Inventory; GSI, Global Severity Index; PTSD, post-traumatic stress

disorder; PCL-C, Posttraumatic Stress Disorder Checklist-Civilian Version; SF-12, Medical Outcomes Study Short Form (SF-12) Physical andMental Summary Scores.

FIG. 2. Number of words consistently recalled over sixtrials on the Verbal Selective Reminding Test, and followinga 30-min delay, for both the traumatic brain injury (TBI) andcomparison groups (CLTR, consistent long-term retrieval).

DTI IN BLAST INJURY 689

Symptom measures. Spearman rank-order correlationsbetween the DTI variables of FA and ADC and the total post-concussion symptom score on the NSI and the total PTSDsymptom score on the PCL-C were calculated for the TBIgroup. Using fiber tracking, total corpus callosum FA wasnegatively correlated with both the mean post-concussionsymptom cluster score (r¼�0.40, p¼ 0.02), and the meantotal PTSD score (r¼�0.30, p¼ 0.07). However, there were nosignificant correlations of ADC with the symptom measures,and no significant correlations of either FA or ADC using theROI method.

Episodic memory. As seen in the fiber tracking data inTable 5, the most consistent correlations with verbal memoryon the selective reminding tests were obtained for the unci-nate, internal capsule, and corticospinal tract. FA values in-dicating integrity of WM microstructure were positivelyrelated to consistent verbal recall across trials, whereas ADCvalues reflecting increased diffusivity were negatively relatedto recall (Fig. 3). However, the corresponding correlations fornonverbal selective reminding did not conform to this pattern,

as both FA and ADC values were positively correlated withconsistency of recall and delayed recall, respectively (Table 5).

For the ROI method in the TBI group, Table 6 shows pos-itive correlations between FA in the splenium of the corpuscallosum and the number of words consistently retrievedacross trials and after a delay, consistent with the expectedpattern in which higher FA is related to better performance(Fig. 3). Negative correlations were found between the totalnumber of words consistently retrieved and ADC in the leftposterior limb and the right anterior limb of the internalcapsule. Again this was consistent with the expected patternin which higher ADC was related to poorer verbal memory.No significant correlations were found between DTI variablesobtained with the ROI method and either consistent recallacross trials or delayed recall on the NVSRT.

Decision making. Significant correlations between per-formance on the Iowa Gambling Task and DTI variableswere limited to the quantitative fiber tracking method, in-cluding right uncinate FA (r¼ 0.426, p¼ 0.003), right posteriorinternal capsule FA (r¼ 0.325, p¼ 0.024), and right inferior

Table 5. Correlations of FA and ADC Measured by Fiber Tracking and Verbal and Nonverbal

Selective Reminding Tests

Total CLTR VSRT Total CLTR NVSRT 30 min delayed recall NVSRT

r p r p r p

Right PIC FA 0.350 0.037 0.350 0.054 0.240 0.194Left PIC FA 0.365 0.029 0.366 0.043 0.242 0.191Left CST FA 0.335 0.046 0.400 0.030 0.256 0.165Right uncinate ADC �0.342 0.041 0.114 0.541 0.125 0.504Left uncinate ADC �0.331 0.049 0.328 0.071 0.380 0.035Left PIC ADC �0.391 0.019 0.024 0.899 0.121 0.517Left AIC ADC �0.292 0.084 0.194 0.297 0.365 0.044CC genu ADC 0.091 0.596 0.467 0.008 0.383 0.033CC splenium ADC 0.195 0.254 0.373 0.039 0.114 0.541CC total ADC 0.111 0.521 0.460 0.009 0.279 0.129Right IFOF ADC �0.078 0.651 0.390 0.030 0.322 0.078

FA, fractional anisotropy; ADC, apparent diffusion coefficient; AIC, anterior limb of the internal capsule; CC, corpus callosum; CST,corticospinal tract; IFOF, inferior fronto-occipital fasciculus; PIC, posterior limb of the internal capsule; CLTR, consistent long-term retrieval;NVSRT, Nonverbal Selective Reminding Test; VSRT, Verbal Selective Reminding Test.

FIG. 3. Scatterplots of consistent retrieval of words on the Verbal Selective Reminding Test plotted by fractional anisotropy(FA) and apparent diffusion coefficient (ADC) as measured by diffusion tensor imaging using fiber tracking (FT) and region-of-interest (ROI) methods. Correlation coefficients are shown in Tables 5 and 6 (CLTR, consistent long-term retrieval).

690 LEVIN ET AL.

frontal occipital fasciculus FA (r¼ 0.325, p¼ 0.024). There wereno significant correlations with ADC or using ROI measures.

Discussion

Post-concussion and symptoms of post-traumaticstress disorder

Our outcome data replicate those of previous studies (Hogeet al., 2008; Schneiderman et al., 2008), showing that OEF=OIFveterans and service members with a history of blast-inducedmild to moderate TBI report more severe post-concussion andPTSD symptoms than veterans without TBI. Based on the NSI,veterans with TBI had more severe post-concussion symptomsthan the comparison group, a finding that was confirmed forphysical, cognitive, and sensory clusters of post-concussionsymptoms. However, the groups did not significantly differ onthe affective symptom cluster of the NSI. Nearly 60% of par-ticipants with TBI had elevated total PCL-C scores consistentwith the diagnosis of PTSD, compared with a previously re-ported rate of 50% using the same diagnostic criterion amongOEF=OIF returnees who sustained mild blast-related TBI withLOC (Hoge et al., 2008; Schneiderman et al., 2008). Similarly toprevious studies, we found that OEF=OIF veterans with mildTBI had PTSD symptoms that were more severe than veteranswho had been deployed but had no TBI or exposure to blast.The linear relation between severity of post-concussion andPTSD symptoms in our TBI participants implicates substantialoverlap and raises the possibility of a common, unifyingmechanism. This overlap of symptoms is consistent with self-report data collected from a large cohort of veterans who hadsustained blast-induced TBI, predominantly in the mild rangeof severity (Hoge et al., 2008). Similarly to Hoge and associates(2008), we found that increased post-concussion symptoms inthe TBI group relative to the comparison group were mitigatedby adjusting for severity of PTSD symptom scores. Con-versely, adjusting for post-concussion symptoms eliminatedthe between-group difference in PTSD symptom scores. Ourfindings are consistent with the interpretation by Hoge andcolleagues (2008), that blast-induced mild TBI and PTSD arefrequently comorbid in OEF=OIF veterans and service mem-bers. In comparison with civilian mild TBI, blast-related mildTBI in the OEF=OIF population is often associated with an-ticipatory emotional arousal and exposure to deaths and in-juries among other service members, enemy combatants, ornoncombatants, thus increasing the risk for PTSD (Vander-ploeg et al., 2009; Vasterling et al., 2006). Moreover, thistraumatic exposure may be repetitive, further increasing therisk for PTSD in OEF=OIF veterans with mild TBI.

Global distress and health-related quality of life

Global emotional distress as measured by the BSI was alsomore severe in the TBI group relative to the comparisongroup. However, the groups differed only marginally on thedepression scale score of the BSI, as clinically elevateddepression scores were obtained in more than half of theparticipants in the comparison group, thus mitigating a sig-nificant between-group difference. This marginal finding isconsistent with other reports (Invisible Wounds of War, 2008;Seal et al., 2009) of generally high rates of depression inOEF=OIF veterans. In contrast, we found no between-groupdifference in HRQOL as measured by self-perceived physicalhealth and mental health concerns on the SF-12. The dissoci-ation in findings between measures of symptoms, distress,and HRQOL, suggests that the increased symptoms associ-ated with TBI were disproportionately severe for the post-concussion and post-traumatic stress domains.

Cognitive findings

We found that group differences in cognition were specificto the VSRT (Buschke, 1973), a measure of episodic memorythat involves learning a list of 12 words and resistance tointerference. Following the first trial, in which all 12 words arepresented, the examiner presented only those words that theparticipant failed to recall on the preceding trial. This selectivereminding thus potentially interferes with recall of thosewords that were correctly recalled on the previous trial andthus not represented by the examiner. Veterans and servicemembers with blast-related TBI recalled fewer words acrossthe six trials and following a 30-min delay than the compar-ison group. However, we found no between-group differ-ences in visual recall of the spatial location of dots using aselective reminding procedure (Fletcher, 1985). This dissoci-ation is in accord with the sensitivity of the VSRT to civilianmild TBI (Levin et al., 1987). The finding of poor verbalmemory more than a year after blast-related mild TBI con-trasts with the recovery typically found on this test within 1–3months after civilian mild TBI (Levin et al., 1987). With theexception of sports-related mild TBI (Guskiewicz et al., 2003),civilians typically sustain a single injury, whereas repetitiveexposure to blast is common in OEF=OIF service members,especially those undergoing multiple deployments (Vasterl-ing et al., 2006). The potentially cumulative effects of repeti-tive exposure to blast further differentiate the injuriessustained by OEF=OIF veterans from civilian mild TBI. Theassociation of PTSD with problems in initial registration ofinformation, vulnerability to interference, and sustainedattention may also explain our finding that the mild TBI grouphad poor verbal memory using a selective reminding proce-dure. This postulation is also congruent with the report(Brewin et al., 2010) that verbal memory is more vulnerablethan visual memory to PTSD (Vanderploeg et al., 2009), andthe view (Vanderploeg et al., 2009) that mild TBI due to blastand PTSD independently contribute to cognitive deficits.

Administration of the Iowa Gambling Task (Bechara et al.,1994) to evaluate decision making in relation to incentive andpenalties disclosed no between-group difference in the rela-tive preference for selecting cards from advantageous decksacross trials. Moreover, the distributions of the differencebetween total cards selected from advantageous versus dis-advantageous decks did not differ, and outliers were no more

Table 6. Correlations of FA and ADC as Measured

by ROI and the Verbal Selective Reminding Test

Total CLTR 30-Min delayed recall

r p r p

CC splenium FA 0.356 0.033 0.348 0.038Left PIC ADC �0.432 0.008 �0.242 0.161Right AIC ADC �0.463 0.005 �0.025 0.888

FA, fractional anisotropy; ADC, apparent diffusion coefficient;AIC, anterior limb of internal capsule; CC, corpus callosum; PIC,posterior limb of internal capsule; CLTR, consistent long-termretrieval; ROI, region of interest.

DTI IN BLAST INJURY 691

frequent in the mild TBI group than the comparison group.Without evidence for a deficiency in deferring reward tomaximize gains over trials, our data provide no support fordysfunction in the neural system involving the ventral pre-frontal cortex, amygdala, ventral striatum, and nucleus ac-cumbens in OEF=OIF veterans with mild TBI due to blast.

Diffusion tensor imaging findings

Using manual measurement of single-slice ROIs, quanti-tative tractography, and VBA methods of DTI analysis, wefound no between-group differences in the integrity of WMmicrostructure. Moreover, the distributions of FA and ADCwere quite similar in the two groups across neuroanatomicregions of WM known to be vulnerable to axonal injury, andcorrelations between the DTI data and post-concussionsymptoms were generally weak. The lack of between-groupdifferences in DTI indices may be attributed to the WM injuryhaving been of subthreshold severity for detection by thisimaging technique. With the exception of nine participantswho reported duration of LOC longer than 30 min, or dura-tions of PTA or confusion longer than 24 h, our sample of TBIparticipants had LOC and PTA consistent with mild TBI.However, we found no consistent difference in DTI variablesbetween the mild and moderate TBI subgroups. Moreover,correlation of the DTI variables with the symptom scale scoresdisclosed no consistent pattern, including both post-concussion and PTSD symptoms. We also evaluated whetherhigh FA, reflecting integrity of WM microstructure, waspositively correlated with cognitive performance within theTBI group. As a convergent analysis, we determined whetherincreased diffusivity as reflected by higher ADC values wasnegatively correlated with cognitive performance. Althoughthe direction of correlations for the VSRT was consistent withexpectations, and reflected increased memory problems withlower FA and higher ADC, this was not the case for theNVSRT, for which the direction of the correlations was in-consistent and at times in an unanticipated direction. We alsofound no significant correlation between DTI variables andseverity of PTSD symptoms, indicating that post-traumaticstress could not explain the relation of verbal memory to DTIindices. Despite the lack of a correlation between decisionmaking on the Iowa Gambling Task and ADC, performanceof the TBI group was positively related to FA in tracts con-necting the prefrontal and temporal regions, and extendingfrom the prefrontal to occipital regions. Consistent with evi-dence of greater sensitivity of right than left ventral medialprefrontal lesions to poor decision making on this task (Be-chara, 2004), the positive correlations with FA were found forthe right uncinate, right inferior frontal occipital fasciculus,and the posterior limb of the right internal capsule in the TBIgroup. Consequently, we suggest that further investigation ofthis cognitive measure in relation to DTI may be informative.

Late DTI findings of reduced FA and increased ADC in-dicative of WM injury in civilian TBI have generally beenconfined to participants with moderate to severe injury. Al-though a recent study (Niogi et al., 2008) has disclosed subtlealteration of the relation between DTI indices and cognition inchronic civilian mild TBI participants, between-group differ-ences in FA were not consistent across ROIs. The subthresholdinjury severity interpretation of our DTI data could be testedin future DTI studies by including veterans with clinician-

confirmed moderate to severe blast-induced TBI, in additionto those with mild TBI. Longitudinal imaging, including pre-deployment DTI, and repeated DTI within a week after mildTBI (Bazarian et al., 2007; Wilde et al., 2008) due to blastwould also contribute to identifying subtle WM alterations(Bazarian et al., 2007; Wilde et al., 2008) that may resolve overtime. Comparison with prospective civilian TBI patientswould also elucidate whether the negative DTI findings in thepresent study are specific to mild blast-induced TBI. Neuro-pathology studies support a continuum of WM injury incivilian TBI (Blumbergs et al., 1994; Oppenheimer, 1968), butthe pattern seen in blast-related TBI remains to be elucidated.

Limitations of this study

In our sample of veterans and service members withchronic blast-related TBI, assessment of acute injury variablesdepended in part on self-report data concerning alteration orloss of consciousness and PTA. However, the diagnosis of TBIwas based on a clinical interview with a physician, similar tothe approach used in other studies of veterans with TBI due toblast (Belanger et al., 2009; Terrio et al., 2009). We acknowl-edge the small sample size of OEF=OIF veterans and servicemembers whom we recruited prospectively from a traumaregistry, from clinical services at the MEDVAMC, and fromadvertising in the newspaper of a regional Army post. Al-though recruitment involved cooperation with several clinicalservices, study brochures were widely distributed and en-rollment was not based on patients referred by clinicians be-cause of more severe or persistent symptoms (Terrio et al.,2009). Despite the small sample size, the behavioral findingswere consistent with those of previous studies (Hoge et al.,2008; Schneiderman et al., 2008) using similar self-reportmeasures of post-concussion and PTSD symptoms. Also,medical records documenting acute injury were not available.Our comparison group of post-deployment OEF=OIF veter-ans unexposed to blast was divided between those who sus-tained extracranial injury and those who were uninjured.Inclusion of uninjured veterans in the comparison group mayhave accentuated the group differences in reported symp-toms. The cross-sectional design of this study is a furtherlimitation. Recruitment through the trauma registry, clinics,and Army base provided access to veterans and servicemembers with chronic, but not acute TBI. Although ourneuropsychological assessment lacked a measure of symptomvalidity, group differences in cognitive performance werespecific to verbal recall. A dichotomous variable measuringdecision making over trials in relation to rewards and pen-alties showed similar distributions of data for the TBI andcomparison groups. We also found no between-group dif-ference in self-perceived health status, a finding inconsistentwith symptom amplification or malingering in the TBI group.Although we acknowledge the lack of adjustment for multiplestatistical tests, we view the correlation analyses between DTIvariables and outcome measures as exploratory in this initialDTI study of blast-related TBI.

Conclusions

Further investigation of blast-induced TBI using DTI isnevertheless encouraged, because this noninvasive imagingtechnique is generally sensitive to civilian TBI injury due toclosed head trauma, and it provides a measure of WM

692 LEVIN ET AL.

integrity independent of self-report or behavioral data. Sup-plementation of DTI with volumetric MRI (Bagley et al., 2000),and other advanced MR techniques such as magnetizationtransfer imaging (Bagley et al., 2000; Kimura et al., 1996; Smithet al., 1995), and susceptibility-weighted imaging (Tong et al.,2002) may improve the detection of pathology associated withmild blast-induced TBI and the concomitant effects of PTSD.Moreover, longitudinal investigation with repeat imagingwould be more sensitive to the subtle changes that occurfollowing these injuries.

Acknowledgments

This research was supported by grant B4596 by the De-partment of Veterans Affairs, Veterans Health Administra-tion, Rehabilitation Research and Development Service; theMental Illness Research, Education and Clinical Centers(MIRECC); and by the Houston VA HSR&D Center of Ex-cellence (HFP90-020). We gratefully acknowledge the assis-tance of Stacey K. Martin and Stephen R. McCauley, Ph.D. fortheir assistance in manuscript preparation. We are also in-debted to the veterans and service members who participatedin the study.

Author Disclosure Statement

No competing financial interests exist.

References

Adams, J.H., Graham, D.I., Murray, L.S., and Scott, G. (1982).Diffuse axonal injury due to nonmissile head injury in hu-mans: an analysis of 45 cases. Ann. Neurol. 12, 557–563.

Bagley, L.J., McGowan, J.C., Grossman, R.I., Sinson, G., Ko-tapka, M., Lexa, F.J., Berlin, J.A., and McIntosh, T.K. (2000).Magnetization transfer imaging of traumatic brain injury. J.Magn. Reson. Imaging 11, 1–8.

Barona, A., Reynolds, C.R., and Chastain, R. (1984). A demo-graphically based index of premorbid intelligence for theWAIS-R. J Consult. Clin. Psychol. 5, 885–887.

Bazarian, J.J., Zhong, J., Blyth, B., Zhu, T., Kavcic, V., and Pe-terson, D. (2007). Diffusion tensor imaging detects clinicallyimportant axonal damage after mild traumatic brain injury: apilot study. J. Neurotrauma 24, 1447–1459.

Bechara, A. (2004). The role of emotion in decision-making: ev-idence from neurological patients with orbitofrontal damage.Brain Cogn. 55, 30–40.

Bechara, A., Damasio, A.R., Damasio, H., and Anderson, S.W.(1994). Insensitivity to future consequences following damageto human prefrontal cortex. Cognition 50, 7–15.

Bechara, A., Tranel, D., and Damasio, H. (2000). Characteriza-tion of the decision-making deficit of patients with ventro-medial prefrontal cortex lesions. Brain 123, 2189–2202.

Belanger, H.G., Kretzmer, T., Yoash-Gantz, R., Pickett, T., and Tu-pler, L.A. (2009). Cognitive sequelae of blast-related versus othermechanisms of brain trauma. J. Int. Neuropsychol. Soc. 15, 1–8.

Benson, R.R., Meda, S.A., Vasudevan, S., Kou, Z., Govindarajan,K.A., Hanks, R.A., Millis, S.R., Makki, M., Latif, Z., Coplin, W.,Meythaler, J., and Haacke, E.M. (2007). Global white matteranalysis of diffusion tensor images is predictive of injury se-verity in traumatic brain injury. J. Neurotrauma 24, 446–459.

Blanchard, E.B., Jones-Alexander, J., Buckley, T.C., and Forneris,C.A. (1996). Psychometric properties of the PTSD Checklist(PCL). Behav. Res. Ther. 34, 669–673.

Blumbergs, P.C., Scott, G., Manavis, J., Wainwright, H., Simp-son, D.A., and McLean, A.J. (1994). Staining of amyloid pre-cursor protein to study axonal damage in mild head injury.Lancet 344, 1055–1056.

Brewin, C.R., Gregory, J.D., Lipton, M.L., and Burgess, N. (2010).Intrusive images in psychological disorders: Characteristics,neural mechanisms, and treatment implications. Psychol. Rev.117, 210–232.

Buschke, H. (1973). Selective reminding for analysis of memoryand learning. J. Verbal Learning Verbal Behav. 12, 543–550.

Cernak, I., and Noble-Haeusslein, L.J. (2009). Traumatic braininjury: an overview of pathobiology with emphasis on mili-tary populations. J. Cereb. Blood Flow Metab. 30, 255–266.

Champion, H.R., Holcomb, J.B., and Young, L.A. (2009). Injuriesfrom explosions: physics, biophysics, pathology, and requiredresearch focus. J. Trauma 66, 1468–1477; discussion 1477.

Chu, Z., Wilde, E.A., Hunter, J.V., McCauley, S.R., Bigler, E.D.,Troyanskaya, M., Yallampalli, R., Chia, J.M., and Levin, H.S.(2010). Voxel-based analysis of diffusion tensor imaging inmild traumatic brain injury in adolescents. AJNR Am. J.Neuroradiol. 31, 340–346.

Cicerone, K.D., and Kalmar, K. (1995). Persistent postconcussionsyndrome: The structure of subjective complaints after mildtraumatic brain injury. J. Head Trauma Rehabil. 10, 1–17.

Damasio, A.R. (1996). The somatic marker hypothesis and thepossible functions of the prefrontal cortex. Philos. Trans. R.Soc. Lond. B Biol. Sci. 351, 1413–1420.

Derogatis, L.R. 1982. The Brief Symptom Inventory: Adminis-tration, Scoring, and Procedures Manual. Johns HopkinsUniversity School of Medicine: Baltimore.

Fletcher, J.M. (1985). Memory for verbal and nonverbal stimuliin learning disability subgroups: analysis by selective re-minding. J. Exp. Child Psychol. 40, 244–259.

French, L.M., and Parkinson, G.W. (2008). Assessing and treat-ing veterans with traumatic brain injury. J. Clin. Psychol. 64,1004–1013.

Galarneau, M.R., Woodruff, S.I., Dye, J.L., Mohrle, C.R., andWade, A.L. (2008). Traumatic brain injury during OperationIraqi Freedom: findings from the United States Navy-MarineCorps Combat Trauma Registry. J. Neurosurg. 108, 950–957.

Guskiewicz, K.M., McCrea, M., Marshall, S.W., Cantu, R.C.,Randolph, C., Barr, W., Onate, J.A., and Kelly, J.P. (2003).Cumulative effects associated with recurrent concussion incollegiate football players: the NCAA Concussion Study.JAMA 290, 2549–2555.

Hoge, C.W., McGurk, D., Thomas, J.L., Cox, A.L., Engel, C.C.,and Castro, C.A. (2008). Mild traumatic brain injury in U.S.Soldiers returning from Iraq. N. Engl. J. Med. 358, 453–463.

Hoogenraad, F. (2002). Multi-center evaluation of in-vivo fiber-tracking. Philips Medical Systems.

Inglese, M., Makani, S., Johnson, G., Cohen, B.A., Silver, J.A.,Gonen, O., and Grossman, R.I. (2005). Diffuse axonal injury inmild traumatic brain injury: a diffusion tensor imaging study.J. Neurosurg. 103, 298–303.

Invisible Wounds of War: Psychological and Cognitive Injuries,Their Consequences, and Services to Assist Recovery. (2008).T. Tanielian, and L.H. Jaycox, (eds), RAND Corporation: SantaMonica, CA.

Kimura, H., Meaney, D.F., McGowan, J.C., Grossman, R.I., Len-kinski, R.E., Ross, D.T., McIntosh, T.K., Gennarelli, T.A., andSmith, D.H. (1996). Magnetization transfer imaging of diffuseaxonal injury following experimental brain injury in the pig:characterization by magnetization transfer ratio with histo-pathologic correlation. J. Comput. Assist. Tomogr. 20, 540–546.

DTI IN BLAST INJURY 693

Kraus, M.F., Susmaras, T., Caughlin, B.P., Walker, C.J., Sweeney,J.A., and Little, D.M. (2007). White matter integrity and cog-nition in chronic traumatic brain injury: a diffusion tensorimaging study. Brain. 130, 2508–2519.

Levin, H.S., Mattis, S., Ruff, R.M., Eisenberg, H.M., Marshall,L.F., Tabaddor, K., High, W.M., Jr., and Frankowski, R.F.(1987). Neurobehavioral outcome following minor head inju-ry: a three-center study. J. Neurosurg. 66, 234–243.

Levin, H.S., Wilde, E.A., Chu, Z., Yallampalli, R., Hanten, G.R.,Li, X., Chia, J., Vasquez, A.C., and Hunter, J.V. (2008). Diffu-sion tensor imaging in relation to cognitive and functionaloutcome of traumatic brain injury in children. J. Head TraumaRehabil. 23, 197–208.

Maisto, S.A., Carey, M.P., Carey, K.B., Gordon, C.M., andGleason, J.R. (2000). Use of the AUDIT and the DAST-10 toidentify alcohol and drug use disorders among adults with asevere and persistent mental illness. Psychol. Assess. 12, 186–192.

Meythaler, J.M., Peduzzi, J.D., Eleftheriou, E., and Novack, T.A.(2001). Current concepts: diffuse axonal injury-associatedtraumatic brain injury. Arch. Phys. Med. Rehabil. 82, 1461–1471.

Netsch, T., and van Muiswinkel, A. (2004). Quantitative evalu-ation of image-based distortion correction in diffusion tensorimaging. IEEE Trans. Med. Imaging 23, 789–798.

Niogi, S.N., Mukherjee, P., Ghajar, J., Johnson, C.E., Kolster, R.,Lee, H., Suh, M., Zimmerman, R.D., Manley, G.T., andMcCandliss, B.D. (2008). Structural dissociation of attentionalcontrol and memory in adults with and without mild trau-matic brain injury. Brain 131, 3209–3221.

Oppenheimer, D.R. (1968). Microscopic lesions in the brain fol-lowing head injury. J. Neurol. Neurosurg. Psychiatry 31, 299–306.

Owens, B.D., Kragh, J.F., Jr., Wenke, J.C., Macaitis, J., Wade,C.E., and Holcomb, J.B. (2008). Combat wounds in OperationIraqi Freedom and Operation Enduring Freedom. J. Trauma64, 295–299.

Povlishock, J.T., and Katz, D.I. (2005). Update of neuropathologyand neurological recovery after traumatic brain injury. J. HeadTrauma Rehabil. 20, 76–94.

Rolls, E.T. 1999. The Brain and Emotion. Oxford University Press:Oxford.

Saunders, J.B., Aasland, O.G., Babor, T.F., de la Fuente, J.R., andGrant, M. (1993). Development of the Alcohol Use DisordersIdentification Test (AUDIT): WHO Collaborative Project onEarly Detection of Persons with Harmful Alcohol Consump-tion—II. Addiction 88, 791–804.

Schneiderman, A.I., Braver, E.R., and Kang, H.K. (2008). Un-derstanding sequelae of injury mechanisms and mild trau-matic brain injury incurred during the conflicts in Iraq andAfghanistan: persistent postconcussive symptoms and post-traumatic stress disorder. Am. J. Epidemiol. 167, 1446–1452.

Seal, K.H., Metzler, T.J., Gima, K.S., Bertenthal, D., Maguen, S.,and Marmar, C.R. (2009). Trends and risk factors for mentalhealth diagnoses among Iraq and Afghanistan veterans usingDepartment of Veterans Affairs health care, 2002–2008. Am. J.Public Health. 99, 1651–1658.

Skinner, H.A. (1982). The drug abuse screening test. AddictBehav. 7, 363–371.

Smith, D.H., Meaney, D.F., Lenkinski, R.E., Alsop, D.C., Gross-man, R., Kimura, H., McIntosh, T.K., and Gennarelli, T.A.(1995). New magnetic resonance imaging techniques for the

evaluation of traumatic brain injury. J. Neurotrauma 12, 573–577.

Terrio, H., Brenner, L.A., Ivins, B.J., Cho, J.M., Helmick, K., Schwab,K., Scally, K., Bretthauer, R., and Warden, D. (2009). Traumaticbrain injury screening: preliminary findings in a US Army Bri-gade Combat Team. J. Head Trauma Rehabil. 24, 14–23.

Tong, K., Holshouser, B., Shutter, L., Chiou, P., Herigauk, G.,and Haacke, E. (2002). High resolution susceptibility weightedimaging (SWI) improves detection of hemorrhagic lesions inadults with traumatic brain injury: correlation with severity ofinjury and outcome, in: Proceedings of ISMRM 10th ScientificMeeting, p. 46.

Vanderploeg, R.D., Belanger, H.G., and Curtiss, G. (2009). Mildtraumatic brain injury and posttraumatic stress disorder andtheir associations with health symptoms. Arch. Phys. Med.Rehabil. 90, 1084–1093.

Vasterling, J.J., Proctor, S.P., Amoroso, P., Kane, R., Heeren, T.,and White, R.F. (2006). Neuropsychological outcomes of armypersonnel following deployment to the Iraq war. JAMA 296,519–529.

Wakana, S., Caprihan, A., Panzenboeck, M.M., Fallon, J.H.,Perry, M., Gollub, R.L., Hua, K., Zhang, J., Jiang, H., Dubey,P., Blitz, A., van Zijl, P., and Mori, S. (2007). Reproducibility ofquantitative tractography methods applied to cerebral whitematter. Neuroimage 36, 630–644.

Warden, D. (2006). Military TBI during the Iraq and Afghanistanwars. J. Head Trauma Rehabil. 21, 398–402.

Ware, J., Jr., Kosinski, M., and Keller, S.D. (1996). A 12-ItemShort-Form Health Survey: construction of scales and pre-liminary tests of reliability and validity. Med. Care. 34, 220–233.

Wilde, E.A., Chu, Z., Bigler, E.D., Hunter, J.V., Fearing, M.A.,Hanten, G., Newsome, M.R., Scheibel, R.S., Li, X., and Levin,H.S. (2006). Diffusion tensor imaging in the corpus callosum inchildren after moderate to severe traumatic brain injury. J.Neurotrauma 23, 1412–1426.

Wilde, E.A., McCauley, S.R., Chu, Z., Hunter, J.V., Bigler, E.D.,Yallampalli, R., Wang, Z.J., Hanten, G., Li, X., Ramos, M.A.,Sabir, S.H., Vasquez, A.C., Menefee, D., and Levin, H.S.(2009). Diffusion tensor imaging of hemispheric asymmetriesin the developing brain. J. Clin. Exper. Neuropsychol. 31, 205–218.

Wilde, E.A., McCauley, S.R., Hunter, J.V., Bigler, E.D., Chu, Z.,Wang, Z.J., Hanten, G.R., Troyanskaya, M., Yallampalli, R., Li,X., Chia, J., and Levin, H.S. (2008). Diffusion tensor imaging ofacute mild traumatic brain injury in adolescents. Neurology70, 948–955.

Wu, T., Wilde, E.A., Bigler, E.D., Yallampalli, R., McCauley,S.R., Troyanskaya, M., Chu, Z., Li, X., Hanten, G., Hunter, J.V.,and Levin, H.S. (2009). Evaluating the relation betweenmemory functioning and cingulum bundles in acute mildtraumatic brain injury using diffusion tensor imaging. J.Neurotrauma 27, 303–307.

Address correspondence to:Harvey S. Levin, Ph.D.

Baylor College of Medicine1709 Dryden Road, Suite 1200

Houston, TX 77030

E-mail: hlevin@bcm.edu

694 LEVIN ET AL.