Comparison of Acute and Chronic Traumatic Brain Injury Using Semi-Automatic Multimodal

20 Pages·2011·1.71 MB·English

JOURNALOFNEUROTRAUMA28:2287–2306(November2011)
ªMaryAnnLiebert,Inc.
DOI:10.1089/neu.2011.1920
Comparison of Acute and Chronic Traumatic
Brain Injury Using Semi-Automatic
Multimodal Segmentation of MR Volumes
Andrei Irimia,1 Micah C. Chambers,1,2 Jeffry R. Alger,3–5 Maria Filippou,6 Marcel W. Prastawa,7,8
Bo Wang,7,8 David A. Hovda,3 Guido Gerig,7,8 Arthur W. Toga,1,4,5 Ron Kikinis,9
Paul M. Vespa,6 and John D. Van Horn1
Abstract
Althoughneuroimagingisessentialforpromptandpropermanagementoftraumaticbraininjury(TBI),thereis
a regrettable and acute lack of robust methods for the visualization and assessment of TBI pathophysiology,
especially for of the purpose of improving clinical outcome metrics. Until now, the application of automatic
segmentationalgorithmstoTBIinaclinicalsettinghasremainedanelusivegoalbecauseexistingmethodshave,
for the most part, been insufficiently robust to faithfully capture TBI-related changes in brain anatomy. This
articleintroducesandillustratesthe combineduseofmultimodalTBI segmentation andtimepointcomparison
using3DSlicer,awidely-usedsoftwareenvironmentwhoseTBIdataprocessingsolutionsareopenlyavailable.
For three representative TBI cases, semi-automatic tissueclassification and 3D model generation are performed
to perform intra-patient time point comparison of TBI using multimodal volumetrics and clinical atrophy
measures. Identification and quantitative assessment of extra- and intra-cortical bleeding, lesions, edema, and
diffuse axonal injury are demonstrated. The proposed tools allow cross-correlation of multimodal metrics from
structural imaging (e.g., structural volume, atrophy measurements) with clinical outcome variables and other
potentialfactorspredictiveofrecovery.Inaddition,theworkflowsdescribedaresuitableforTBIclinicalpractice
and patient monitoring, particularly for assessing damage extent and for the measurement of neuroanatomical
change over time. With knowledge of general location, extent, and degree of change, such metrics can be
associated with clinical measures and subsequently used to suggest viable treatment options.
Keywords:magneticresonanceimaging;segmentation;TBI;visualization
Introduction neurocognitive function (De Beaumont et al., 2009). More-
over,thelargenumberofrecentTBIcasesinsoldiersreturn-
With an estimated 1.7 million people in the United ing from military conflicts has created a significant clinical
States sustaining a traumatic brain injury (TBI) every challengeforUnitedStatesVeteransAdministrationhospitals
year(Fauletal.,2010),themagnitudeofthismedicalconcern (Taber et al., 2006) and has highlighted the critical need for
to the United States cannot be overstated (Chen and improvementinTBIcareandtreatment.
D’Esposito, 2010). Every year, TBI cases are associated with Promptandproper managementof TBIsequelaecan sig-
1.2 million emergency room visits and over 50,000 deaths nificantlyaltertheircourse,reducemortalityandmorbidity,
(Langloisetal.,2006).InterestinandpublicawarenessofTBI- reducelengthsofhospitalstay,anddecreasehealthcarecosts
causeddiffuseaxonalinjury(DAI)hassurgedwiththepub- (Wattsetal.,2004).NeuroimagingofTBIisthereforevitalfor
lication of studies suggesting that DAI in professional and surgical planning, by providing important information for
amateurathletesmayhavebothacuteandchroniceffectson anatomical localization and surgical navigation, as well as
1Laboratory of Neuro Imaging, and 4Brain Research Institute, Department of Neurology, 2Henri Samueli School of Engineering and
Applied Science, 3Department of Radiological Sciences, 5Division of Brain Mapping, Neuropsychiatric Institute, 6Brain Injury Research
Center,DepartmentsofNeurosurgeryandNeurology,UniversityofCalifornia,LosAngeles,California.
7ScientificComputingandImagingInstitute,8SchoolofComputing,UniversityofUtah,SaltLakeCity,Utah.
9SurgicalPlanningLaboratory,DepartmentofRadiology,HarvardMedicalSchool,Boston,Massachusetts.
2287
2288 IRIMIAET AL.
for guiding decisions regarding the aggressiveness of TBI 3Dbrainmodelgeneration,whilealsohighlightingtheadded
treatment (Chesnut, 1998). Moreover, because TBI often re- clinicalinsightthatthisworkflowcanoffer.
sultsincharacteristicimpairmentsdependentontheareaof
involvement(Warneretal.,2010),lesionanalysiscanassistin Methods
the localization of cognitive processes and in the attempt to
Research participantsand MRIacquisition
obtain novel information on the relationship between brain
anatomy and behavior (Bates et al., 2003). For all these rea- Anonymizedneuroimagingdatafromthreerepresentative
sons,reliableandprecisemethodsofTBIassessmentcanplay TBIsubjectswereacquiredattheBrainInjuryResearchCenter
an essential role during both acute and chronic therapy for oftheUCLAGeffenSchoolofMedicine.Thestudyanddata
thiscondition. acquisition protocol weredesigned andperformed in accor-
Whereas neuroimaging is often critical for proper TBI dancewiththeDeclarationofHelsinkiandwereapprovedby
clinical care, there is a regrettable and acute lack of robust theUCLAInstitutionalReviewBoard.Signedinformedcon-
methods for the exploration, visualization, and quantitative sent was obtained from each patient or from their legally
assessment of TBI-related anatomical insults and patho- authorized representative before any procedure was per-
physiology. Starting 2–3 days after the acute injury, MRI is formed. In Table 1, the age, sex, and types of MR scans ac-
generallyconsideredtobesuperiortoCTforthepurposeof quired from each patient are specified, in addition to the
TBIassessmentandanalysis.WhereasCTisbetteratdetect- numberofdaysafterinjurywhentheacuteandchronicscan
ing the pathology of bones and certain bleeds, MRI can sessions took place. In the case of the first two subjects, the
identify bleeds more easily and more accurately as blood sequences being used are representative of MR acquisition
composition gradually changes following TBI (Dubroff and protocols that are appropriate for patients requiring critical
Newberg,2008).Inthiscontext,theapplicationofautomatic care. In the case of patient 3, we illustrate the use of an ex-
MRIsegmentationalgorithmstotheclinicalinvestigationof tended MR scan protocol involving 12 distinct sequence
TBI cases remains an elusive goal because many existing types. This protocol requires significantly more acquisition
methods are insufficiently robust to accurately capture TBI- timeandcanbeenvisionedasapplicableforTBIpatientsin
relatedchangesinbrainanatomy.Therefore,becausethestate highlystableconditionand/orwhocanwithstandremaining
oftheart in quantitativeMRIanalysisofTBI ofteninvolves motionlessintheMRscannerfortheextendedamountoftime
labor-intensive manual tissue classification, the clinician’s required for the acquisition of images. Both protocols dem-
abilitytogeneraterobustandaccuratethree-dimensional(3D) onstrate the ability of our segmentation environment to ac-
models of neuropathology for TBI diagnosis and treatment commodate,ontheonehand,theuseofalimitednumberof
remains extremely limited. Consequently, despite recent scantypesand,ontheotherhand,theadditionalamountof
progressinthedevelopmentofrobustimageanalysistools,it clinicallyrelevantinformationbeingsuppliedbyamoreen-
remains difficult to quantify TBI-related brain insults either hancedprotocol.Throughoutthearticle,thesetof5sequences
uni- or multi-modally, particularly for the purpose of im- that were used for the imaging of the first two patients is
provingclinicaloutcomemetrics. referredtoasthe‘‘standard’’protocol,whereasthesetof12
To address the need for clinician-friendly TBI analysis sequences usedinthethirdpatientisreferredtoasthe‘‘ex-
tools,wehereproposeandillustratethecombinedtheuseof tended’’protocol.
multimodal,semi-automaticTBIanalysismethodswithin3D MRvolumeswereacquiredat3Tfromeachsubjectusinga
Slicer, a freely available software environment for the seg- SiemensTrioTIMscanner(SiemensAG,Erlangen,Germany).
mentation, registration, visualization, and quantification of ToassessthetimeevolutionofTBIbetweentheacuteandthe
MRimages.Incontrastwithmanyothersegmentationenvi- chronicstage,scanningsessionswereheldbothseveraldays
ronments for TBI that have appeared in the literature (Ding (acutebaseline)aswellasseveralmonths(chronicfollow-up)
etal.,2008),the3DSlicerenvironmentisbothfreelyavailable after the traumatic injury event. To eliminate the effect of
aswellaswidelyusedbyclinicians,scientists,andengineers. different scanner parameters during each scanning session,
To showcase the ability to perform quantitative time point every subject was scanned using the same scanner for both
comparison and assessment of TBI in 3D Slicer, we present acute and chronic time points. The MP-RAGE sequence
threecasesofsemi-automaticTBIvolumesegmentationand (MuglerandBrookeman,1990)wasusedtoacquireT1-weighted
Table1. Case Study SubjectData Specifying theAge,Sex, Cause of Injury,
Dates of ScanningSessions as well asMR ModalitiesAcquiredfrom Each TBIStudy Case
Dayof Dayof
Causeof acute chronic T1pre- T2 GRE T1post- OEF DWI
Patient Age Sex injury scan scan contrast TSE FLAIR T2 SWI Perfusion contrast EPSE DTI DWI1 2 mIP
1 45 M blunttrauma 2 176 O O O O O
2 31 M gunshot 2 201 O O O O O
3 33 M blunttrauma 3 238 O O O O O O O O O O O O
ScanningsessiondatesarespecifiedasthenumberofdaysafteracuteinjurywhentheacuteandchronicMRvolumeswereacquired,
respectively.CheckmarksindicateuseofeachMRscantype(seetextforclarification).
TSE,turbospinecho;FLAIR,fluid-attenuatedinversionrecovery;GRE,gradient-recalledecho;SWI,susceptibility-weightedimaging;OEF,
Oxygenextractionfactor;EP,echo-planar;SE,spinecho;DTI,diffusiontensorimaging;DWI,diffusionweightedimaging;mIP,maximum
intensityprojection.
COMPARISON OFACUTE ANDCHRONIC TBI 2289
images.Inaddition,MRdatawerealsoacquiredusingfluid- obtainedwasconfirmedusingGREimaging.TSET2-weighted
attenuatedinversionrecovery(FLAIR)(DeCoeneetal.,1992), volumes were also used to confirm lesion characterization,
T2-weighted turbo spin echo (TSE), also known as fast spin andDWIvolumeswereexamined,whereavailable,toaddi-
echo(FSE),(Jonesetal.,1992),gradient-recalledecho(GRE) tionallydistinguishvasogenic(increaseddiffusion)fromcy-
T2-weighted images, as well as susceptibility-weighted im- totoxic (restricted diffusion) edema (Huisman et al., 2003;
aging(SWI)(Sehgaletal.,2005).Inthecaseoftheenhanced Warachetal.,1995).Non-hemorrhagicshearinglesionswere
acquisition protocol for Patient 3, seven additional scan definedashyperintenselesionsthatwerevisibleprimarilyon
sequences were also used, including diffusion weighted im- T2-weightedorFLAIRimages.Thismethodofidentification
aging(DWI),diffusiontensorimaging(DTI),andmaximum was adopted because some shearing lesions often do not
intensityprojection(mIP).Acompletelistofthesesequences show substantial amounts of hemorrhage but are primarily
isprovidedforeachpatientinTable1,whereasTable2spe- visibleasareasofhyperintensityonFLAIR,T2-weighted,and
cifiesstandardMRparametersassociatedwitheachsequence. GREimages.
The appearance of hemorrhages in MR imaging is highly
variable across sequences (Greenberg et al., 2009), as it de-
Identification ofpathology
pendsuponanumberofvariables,bothintrinsic(hemoglobin
TBIcomprisesavarietyofcerebrallesiontypes,including oxygenation,erythrocyteintegrity)andextrinsic(e.g.,scanner
hematoma, subarachnoid hemorrhage, contusion, and DAI. field strength, receiver bandwidth, T1 or T2 weighing).
TBI edema,in particular, canfurther becharacterized byits BecauseSWItakesintoaccountMRsignalphaseinformation,
extent and distribution ranging from perifocal (regional) to regionalmagneticfieldalterationscausedbyironconcentra-
diffuse (generalized) (Unterberg et al., 2004). In this study, tiongradientsinthebrainareeasiertocapturewiththistech-
non-hemorrhagic lesions on MRI scanning were coded as nique. As a result, SWI sequences are very useful in TBI
hyperintensitiesonFLAIRimages.Byusingalonginversion imagingbecausesusceptibilityeffectsmakemicro-hemorrhages
time(TI),theFLAIRsequenceachieveshighcontrastbetween moreobviousinSWIcomparedtootherparadigms.Because
lesionsandhealthytissueaswellascerebrospinalfluid(CSF). SWIisthereforegenerallysuperiortoGREandT2-weighted
Inthistypeofneuroimaging,lesionsappearashyperintense imagingindetectinghemorrhagiclesions(Tongetal.,2003),
regions in the white matter (WM), surrounded by normal volumes acquired using this former modality were used to
tissue of lower,moreuniform intensity (Itti et al.,2001). On identify micro-hemorrhages that were poorly detectable or
theotherhand,T2-weightedGREimagingisexcellentforthe undetectable using other sequences. Specifically, following
detectionofacutehemorrhagiclesions,andSWIismuchmore the previous guidelines of Tong and associates (2003), hem-
sensitivethanconventionalT2-GREindetectinghemorrhagic orrhagic lesions were defined as hypointense foci that were
DAI.Bycomparison,thesensitivityofDWIinidentifyingDAI not compatible with vascular, bone, orartifactual structures
lesions is similar to that of FLAIR, and inferior to that of on conventional GRE images. Whenever foci etiology was
T2-GREfordetectinghemorrhage(Huisman,2003).Although doubtful, the lesions in question were not considered to be
GRE images do reveal some micro-hemorrhages, this se- hemorrhagic.
quence is poor at resolving between gray matter (GM) and TBI volume segmentation is greatly improved with the
lesions, on the one hand and WM and lesions, on the other availabilityofMRvolumesacquiredusingvarioussequence
hand,atleastpartlybecauseGMlesionshavehigherrelaxa- typesthataresuitablefortheidentificationofpathology.As
tion times than those of normal WM. For all these reasons, alreadypointedout,althoughFLAIRimagingissuitablefor
brainlesionsadjacenttoCSFweresegmentedfromvolumes theidentificationofCSF-perfusedinjuries,itsabilitytodetect
acquiredusingFLAIR,andthequalityofthesegmentations hemorrhage is greatly superseded in GRE T2 imaging and
Table2. StandardMRAcquisition Parameters Associatedwith Each SequenceTypeSpecified in Table1
parameter
TR TE TI FA ETL Thickness PhaseFOV Sampling Acquisition
Sequence [ms] [ms] [ms] [deg] [mm] [%] [%] type Matrix
pre-contrast T1 1900 3.52 900 9 1 1 100 100 3D 256·256
T2 TSE 3330 89 120 18 5 100 75 2D 512·512
FLAIR 8000 70 2375 130 16 3 75 75 2D 384·512
GRE T2 1500 7 20 1 3 75 80 2D 384·512
SWI 27 20 15 1 1.5 75 95 3D 192·256
Perfusion 2000 32 90 1 6 100 100 2D 128·128
post-contrast T1 1900 3.52 900 9 1 1 100 100 3D 256·256
OEFEP SE 10000 50 90 1 3 100 100 2D 128·128
DTI 8000 95 90 1 3 100 100 2D 128·128
DWI 1 4000 80 90 1 6 100 100 2D 130·130
DWI 2 4000 80 90 1 6 100 100 2D 130·130
mIP 27 20 15 1 12 75 95 3D 256·192
TR,repetitiontime;TE,echotime;TI,inversiontime;FA,flipangle;ETL,echotrainlength;FOV,fieldofview;TSE,turbospinecho;FLAIR,
fluid-attenuatedinversionrecovery;GRE,gradientrecalledecho;SWI,susceptibility-weightedimaging;OEF,oxygenextractionfraction;EP,
echo-planar;SE,spinecho;DTI,diffusiontensorimaging;DWI,diffusionweightedimaging;mIP,maximumintensityprojection.
2290 IRIMIAET AL.
especiallyinSWI,becausethelatterhasimprovedabilitiesto
detectmicro-bleeds.Inthepresentanalysis,itwasfoundthat
non-hemorrhagic lesions were best delineated from FLAIR,
and that the precise identification of hemorrhagic lesions
requiredtheinclusionofGRET2andSWIimagechannelsin
the segmentation. In the absence of these last two sequence
types,thevolumeofnon-hemorrhagicpathologywasfound
to inappropriately include that of hemorrhagic lesions, to
theobviousdetrimentofsegmentationquality.Ontheother
hand, inclusion of both GRE T2 and SWI but not of FLAIR
causednon-hemorrhagic edematobemisclassifiedaseither
healthy-looking GM or WM, which is reasonable to expect
givenSWI’sexcellentsensitivitytothepresenceofironcom-
pounds, although not to that of CSF perfusion of affected
tissues.Finally,forthecasesexaminedhere,exclusionofSWI
resultedintheinabilitytoidentifymicro-bleeds,whichpoints
totheimportantroleofthissequencetypeinidentifyingthe
locationsofsmallfocalinjuries.
Image Processing
Because TBI involves injury to both neuronal cell bodies
andaxonalprocesses,globalatrophyofGMandWMareboth
common in this condition. Partly for this reason, reliable
segmentationofWMandGMlesionsisnecessaryforaccurate
quantitative analysis of TBI lesions. Additionally, accurate
quantificationoftotallesionvolume(lesionload)isessential
for within-subject comparison of TBI volumes acquired at
differenttimepoints.Toaddresstheseclinicalneeds,weused
thesemi-automaticsegmentationtoolsavailablein3DSlicer
software,includingtheAtlasBasedClassification(ABC)and
ExpectationMaximization(EM)segmenters,whichhavebeen
described elsewhere (Pohl et al., 2007; Prastawa and Gerig,
2008;Zoelleietal.,2007)andusedwidelytodetectpathology
inMRscans(Prastawaetal.,2009).Briefly,theABCalgorithm
can perform multimodal registration of MR images (Maes
et al., 1997), tissue classification of the brain (Van Leemput
et al., 1999),as well as lesion segmentation basedon outlier
detection (Prastawa et al., 2003, 2004; Prastawa and Gerig,
2008).TheEMSegmenter,ontheotherhand,isanalgorithm
guided by prior information represented algorithmically
withinatreestructuretoestimateoptimalsegmentationviaa
conventionalclassifier.Inthislattercase,thetreemirrorsthe
hierarchy of anatomical structures and the sub-trees corre-
spondtolimitedsegmentationproblems,asdescribedbyPohl
andassociates(2007).
As opposed to other specialized segmenters to which ac-
cessisoftenrestrictedfromoutsideusers,bothABCandEM
‰
FIG. 1. Sample MR images acquired from Patient 1 using
thestandardprotocol.Thefirstandsecondcolumnscontain
images acquired at acute baseline and chronic follow-up,
respectively.ShownfromtoptobottomareT1-weightedMP-
RAGE images (A), T2-weighted TSE (B), fluid-attenuated in-
version recovery (FLAIR) (C), T2-weighted gradient-recalled
echo (GRE) (D), and susceptibility-weighted imaging
(SWI)(E).Arrowsarecolorcodedtorepresentthefollowing:
red, primary lesion(s); blue,smaller lesion(s); green, micro-
hemorrhage(s);yellow,diffuseaxonalinjury(DAI).Notethat
only representative (i.e., not all) injuries of each type are
indicated by arrows. Color image is available online at
www.liebertonline.com/neu
COMPARISON OFACUTE ANDCHRONIC TBI 2291
segmenters are freely available as segmentation modules in was performed within 3D Slicer. Bias field correction was
3D Slicer. Both methods are automatic and their executions appliedusingafourth-orderpolynomialmodel.Becausethe
requireminimalusersupervision.Inaddition,theABCseg- anatomyofsevereTBIoftendivergesfromhealthyanatomy
menter possesses the ability to perform co-registration of to a very large extent, segmentation errors can frequently
anarbitrarynumberofMRvolumesacquiredusingvarious occur, especially in severe TBI cases. To address this short-
sequences. Thismakesithighlysuitabletothepresent mul- coming, manual review in 3D Slicer by an operator with
timodalTBIimagingparadigms,whereasmanyas12distinct experienceintherecognitionofneurotraumawasperformed
sequencetypesareused.Beforesegmentation,allimagevol- with the purpose of editing and correcting segmentation
umes were co-registered to the pre-contrast MP-RAGE T1- errors. The guidelines of Filippi and associates (1998) for
weightedvolumeacquiredduringtheacutebaselinescanning editingandsegmentationwerefollowed.Nevertheless,when
session. Intensity normalization within and between scans assessing the extent of segmentation error, it is fair to note
FIG.2. Three-dimensionalmodelsofTBIanatomyforPatient1(acutebaselinetimepoint),asgeneratedin3DSlicer.Eachrow
displays one of six canonical views of the brain, whereas each column corresponds to a structure type (ventricles, non-
hemorrhagic lesions, hemorrhagic lesions, and full model). In (A), ventricles are shown as opaque, whereas extracerebral
injuries,graymatter(GM)andwhitematter(WM)volumesareshownastransparenttofacilitatevisualizationofeachstructure
in relationship to cortical landmarks. In (B–D), ventricles are also shown as transparent for similar reasons. Arrows indicate
TBI-relatedpathologyofinterest(seetextforelaboration).Colorimageisavailableonlineatwww.liebertonline.com/neu
2292 IRIMIAET AL.
that,althoughoftenconsideredtobethegoldstandard,even to the volume at the latter time point. In addition to these
manual outlining resulted in both moderate (3–10%) intra- measures, we also report five measures of atrophy, namely
observer error as well as larger inter-operator variabilities thebifrontalindex(HahnandSchapiro,1976),thebicaudate
(Raff et al., 2000). In conclusion, it is reasonable to expect index(Earnestetal.,1979),Evan’sindex(Syneketal.,1976),
thepresenceofsubtlesegmentationinaccuracieseveninthe theventricularindex(Gyldensted,1977)andHuckman’sin-
contextofourrigoroussegmentationparadigm. dex(Huckmanetal.,1975).
Letthe bifrontal horndistancebethe maximumwidthof
the anterior horns of the lateral ventricles (HLV). Then the
Quantitative metrics
bifrontalindexistheratioofthemaximumHLVwidthtothe
Tissue-type segmentation was used to calculate the total inner skull diameter at HLV level. The bicaudate index is
volumeofthreeselectedstructuretypes(ventricularsystem, definedasratiooftheminimumwidthofthelateralventricles
non-hemorrhagiclesions,andhemorrhagiclesions).Thevol- (MLV) to the width of the inner skull at that level. Evan’s
ume change was computed as the ratio of the difference in index is the ratio of the HLV to the maximum inner skull
volumebetweenthefollow-upandacutebaselinetimepoints, diameter (MISD). Finally, the ventricular index is equal to
FIG.3. AsinFigure2,forthechronicfollow-uptimepoint.Colorimageisavailableonlineatwww.liebertonline.com/neu
COMPARISON OFACUTE ANDCHRONIC TBI 2293
MLV/HLVwhereasHuckman’sindexisthesumoftheMLV appreciatethe3DnatureofTBIaswellastheabilitiesof3D
andHLVmeasures. Slicertodynamicallyrenderandcapturethecomplexitiesof
severebrainpathology.
Results
Case1
Becauseneurotraumaoftenexhibitsmultiple,overlapping
formsoffocaland/ordiffuseinjury,insightfromTBIimaging As Figure 1 reveals, Patient 1 exhibits a large deep-brain
canbeenhancedthroughtheuseofmultimodaltechniques.In injurythat ishyperintense in theFLAIRimage(Fig.1C) be-
whatfollows,theresultsofeachsegmentationand3Dmodel causeofperfusionbyCSFfromtheventricularsystem.Con-
generationarereviewedandtheproceduresusedtoperform tralaterallywithrespecttothisinjury,asmallerinsultinthe
tissueclassificationareillustrated.Foreachpatient,wepro- deepWMisalsoapparentinT1-weighted,FLAIRandGRE
vide six canonical views of ventricles and non-hemorrhagic images(Fig.1A,C,andD,respectively).Theposteriorportion
and hemorrhagic lesions, thus allowing the reader to fully oftheleftventricleseemslargerthanthecorrespondingpart
FIG.4. TimepointcomparisonofTBIinPatient1using3DSlicer-generatedvolumesdisplayedinred(fortheacutebaseline
time point), or green (for the chronic follow-up time point). As in Figures 2 and 3, each row displays one of six canonical
viewsofthebrain,withwhitematter(WM)andgraymatter(GM)transparentinCandDtofacilitatevisualizationofeach
structure inrelationship to cortical landmarks.Colorimageis availableonline at www.liebertonline.com/neu
2294 IRIMIAET AL.
Table 3. Longitudinal Analysisof ThreeSelected
Volumetric Structures(Ventricular System,
Non-Hemorrhagic Lesions,and HemorrhagicLesions)
inThree TBI Patients
Volume [cm3]
Structure Patient Acute Chronic D[%]
Brain 1 1142.0 1009.3 -11.6
2 1098.5 978.7 -10.9
3 1111.2 1018.1 -8.4
Ventricular system 1 29.7 30.1 1.3
2 45.8 95.2 107.6
3 20.5 31.4 53.2
Non-Hemorrhagic lesions 1 84.7 19.9 -76.5
2 40.7 14.8 -63.6
3 54.7 0.9 -82.7
Hemorrhagiclesions 1 73.0 17.4 -76.2
2 51.3 <0.1 -99.7
3 22.5 0.3 -88.1
Values are reported for both acute and chronic segmented
volumes, with the change D as a percentage being computed as
(volume at the chronic time point—volume at the acute time
point)·100/volumeattheacutetimepoint.
of the right ventricle, possibly because of local WM inflam-
mation. Additionally, FLAIR seems to reveal some DAI in
the area surrounding the primary injury (yellow arrows),
whereasGREdemonstratesthepresenceofhemorrhageboth
adjacent to and remote from the primary insult (Fig. 1 D,
greenarrows).Therefore,theinclusionofaGREsequenceis
particularlyusefulinthiscasebecauseDAIcanbevisualized
indirectlythroughshearhemorrhagescausedbybloodvessel
lesions(Scheidetal.,2003).Figure1suggeststhattheabilityto
characterize TBI is greatly enhanced by the use of SWI. As
alreadyquantifiedindetailbyotherauthors(Tongetal.,2003,
2008) and illustrated in Figure 1E, this technique is very
sensitive in the detection of extravascular blood products,
which is illustrated by SWI’s identification of significant
hemorrhage surrounding the primary injury, as well as dif-
fuselythroughoutthebrain(Fig.1E).A3Danimationofthe
segmentation for this patient is available in the Supplemen-
tary Material (see online supplementary material at http://
www.liebertonline.com).
InFigure2,theresultsoftheTBIsegmentationforPatient1
areshown.Eachrowdisplaysoneofsixcanonicalviews(left,
right, dorsal, ventral, anterior, and posterior) of the MR-
segmented brain, with every column corresponding to one
particularstructuretype(ventricles,non-hemorrhagiclesions,
hemorrhagiclesions,andthefullmodel).Ineachimage,ex-
tracortical lesions, GM, and WM are transparent, whereas
theventricularsystemisadditionallytransparentinrows2–5
tofacilitatevisualizingtherelativepositionofeachstructure
type with respect to other cortical landmarks. Figure 2A
shows 3D views of the ventricular system, with arrows
drawing attention to anatomical changes caused by pathol-
ogy.AspreviouslypositedbasedonFigure1,thisvolumetric
analysisreflectsthelargeextentoftheprimaryinjury,aswell
asthesignificantamountofbleedingpresentintheWM.The
posterior part of the left ventricle is found to have been FIG. 5. As in Figure1, forPatient 2.Color imageisavail-
slightlyenlargedasaconsequenceofthelesioncompressing able onlineat www.liebertonline.com/neu
COMPARISON OFACUTE ANDCHRONIC TBI 2295
its anterior portion (Fig. 2A). By comparison, the posterior Figure 3 displays the segmentations of volumes acquired
partoftherightventricleappearsthinner,althoughitsante- fromPatient1duringthechronicfollow-upsession.Although
rior portion is larger because of the primary insult being theventricularsystemappearstoexhibitimprovedbilateral
locatedcontralaterallywithrespecttothelatter(Fig.2Band symmetry (Fig. 3A) and the combined volume of bleeds as
C). Figure 2B and C also illustrate the large volume of the extracted from GRE and SWI imaging appears to be much
primaryinjury,whichcoversalargespatialextentmainlyin smaller than in theacute scan (Fig.3C), thelatter cannot be
the left hemisphere and extends from the inferior to the su- statedregardingthevolumeofthescarcausedbytheprimary
periorextremityofthebrain.InFigure2D,standardviewsof injury (Fig. 3B). In fact, the volume of the lesion does not
the full 3D segmentation model are shown in which all appear to have decreased appreciably at follow-up. This is
structuresarevisible,withtheexceptionoftheWMandGM confirmedinFigure4,inwhichavisualtimepointanalysis
models,whichareomittedforvisualclarity.The3Dmodelof of the volumes associated with each structure is performed.
subdural edema is shown as transparent (green color) so as Forthepurposeofthelatter,alllesionsintheacutebaseline
not to obstruct the view of the brain. The full model per- volume (whether hemorrhagic or non-hemorrhagic) are dis-
spective hastheadvantageofallowingonetovisualize and playedjointlyinred,whereasthelesionsandbleedsatfollow-
summarize all forms of TBI-related pathology as displayed up are shown in green. This avoids the highly problematic
intheothercolumns. task of differentiating lesions in the follow-up model
FIG.6. AsinFigure2,forPatient2attheacutebaselinetimepoint.Colorimageisavailableonlineatwww.liebertonline.com/neu
2296 IRIMIAET AL.
FIG. 7. As in Figure 2, for Patient 2 at the chronic follow-up time point. Color image is available online at www
.liebertonline.com/neu
according to their provenience (i.e., from hemorrhagic or thoseimagedatthechronicfollow-uptimepoint,whichagain
non-hemorrhagicregionsintheacutebaselinemodel),while suggestssubstantialdecreaseininjuryextent.Thelongitudi-
still allowing one to perform a visual and quantitative nalanalysisinFigure4suggeststhatPatient1exhibitsonlya
comparisonofthetwotimepoints. small longitudinal change in the volume of the ventricular
InFigure4,resultsofthetimepointcomparisonforPatient system. This is confirmed by the quantitative analysis re-
1aredisplayed.TheleftviewoftheGMvolumerevealsim- ported in Table 3, where it is seen that there is only a 1.3%
portantdecreaseininflammationatthefollow-uptimepoint, increaseinventricularvolumebetweentheacuteandchronic
particularlyoverdorsolateralfrontal,prefrontal,parietal,and time points. By contrast, in agreement with Figure 4, both
superior temporal cortex. Comparison of the acute and hemorrhagic and non-hemorrhagic lesions are found to de-
chronicWMvolumes,ontheotherhand,suggestssubstantial creaseinvolumesubstantially,thatis,byover76%.Among
decrease in inflammation over the entire frontal and pre- the metrics used for quantification of atrophy, Evan’s index
frontalcortex,aswellasmorediffuselyovertheothercortical registers the largest percentage change (11.42%) from the
lobes. In this subject, comparison of the volumes associated acute to the chronic time point. (See Table 4 for numerical
with lesions portrays the acute baseline lesions as encasing valuesofthisandothermeasuresineachsubject.)