Brain Imaging of Veterans and Se

Members with Chronic Mild T

Harvey Levin, PhD

Supported by CDMRP Grants W81XWH‐08‐2‐0125 and 0133, 

Veterans Affairs Merit Review and Center of Excellence for Tra

Brain Injury, Injury, and NINDS P01 NS056202 NS056202
,

Acknowledgement: Imaging Core, Neuron

Networks Networks Center of Excellence Excellence

• Rajan Agarwal, MD‐neuroradiologist• Shalini Mukhi, MD‐neuroradiologist• Mary Newsome, Newsome, PhD‐fMRI, resting resting state• Randall Scheibel, PhD‐task‐related fMRI• Brian Taylor, PhD‐MR physicist physicist• Elisabeth Wilde, PhD‐structural MRI, DT• Xiaodi Li, BA‐Image d t a a anal t ys• Vanessa Abadia, M Ed‐Image data analy
os s o te e es o se t t o

Challenges in Diagnosing Chronic mTB

OEF/OIF/OND Veterans

• Diagnosis often relies on self‐report witho

acute medical records; co‐morbidPTSD/depression partially overlap in sx wimTBI. Substance abuse could affect MRI f 

i

• Lack of reference data to identify subtle co

atrophy and reduced b i ra n region volume

MRI; DTI metrics have similar issue.

• DTI metrics metrics are potentially potentially robust imaging imaging

biomarkers for mTBI, but center differenceeq p ui ment, software, Q , A and method of 
DTI Data from Ongoing Merit Re

Project of Chronic mTBI in Vete

• Used tract based spatial spatial statistics statistics (TBSS

compare mTBI (n=19) with post‐deploygroup without TBI (n=13) who were not

exposed to blast.

• Fractional anisotropy (FA), a metric whi

reflects preferential diffusion of water pto tract, shows areas of reduced integri

microstructure i l di nc u ng corpus callosu

brain stem, and cerebellum.


Preliminary fcMRI Finding

• Four male Veterans Veterans who sustained sustained mTBI due to b

• Four male Veterans who were not exposed to bl

had no history of TBI served as control subjects.

• These small groups did not differ in age or educa

• In the scanner, subjects were i t ns ructed to close 

eyes but not fall asleep.
Default Mode Network (DMN

mTBI>Controls

Note the atypical atypical lateral lateral region outside outside of the DMN reported reported in civilian

civilian

subacute mTBI (Mayer et al., 2011).
Altered brain activation in military personne

TBI from blast. Scheibel et al (JINS 2012, 18

• Compared OEF/OIF groups with TBI (n=15

TBI on stimulus‐response compatibility ta

• TBI was co‐morbid with high PTSD sympto• Pressed button on side pointed to by blue 

but opposite of red arrow direction

• TBI group had more activation activation in mesial

prefrontal cortex, anterior cingulate gyrus 

posterior regions after statistically control

group differences in PTSD, depression and 

• PTSD dampened frontal‐temporal activatio

Figure 2 Modulation of cognitive control activation by PTSD symptom severity. Im

depict areas where veterans veterans with lower scores on the PCL‐C had greater greater Arrows 

relative to veterans with higher PCL‐C scores. Figures on the right indicate brain 

veterans with lower PCL‐C scores had significant activation during the Arro

(Scheibel et al., 2011)
est state a d tas e ated 

Summary

• DTI, resting state fMRI and task‐related fM

sensitive to chronic effects of predominan

TBI primarily due to blast

• Co‐morbid PTSD clearly affects task‐relate

but effects on resting state and task fMRI under investigation.

• DTI effects may be more specific to axona

than PTSD

• Cautious interpretation of findings becaus

studies studies are still in progress progress



Making the invisible injury visible: MEG 

frequency source imaging for mild and mo

Traumatic Brain Injury (TBI)

Mingxiong Huang, Ph.D., Roland R. Lee M.D

mxhuang@ucsd.edu, rrlee@ucsd.edu 

VA San Diego Healthcare System, San Diego, CA 

Dep artment of Radiology, University of California, San Dieg o
Mild TBI is often referred as invisible injuries: Detecting 

Challenging Challenging using Conventional Conventional Neuroimaging Neuroimaging Met

Met

• Traumatic brain injury (TBI) is a leading cause of sustained

impairment in veterans, military personnel, and civilian

M

populations.

• Mild TBI (mTBI): injuries are difficult to detect (injuries

visible on only 10% of conventional MRIs or CTs).

• Axonal injury is a leading factor in mTBI. Conventional CT

and MRI are mainly sensitive to blood product, and less

sensitive to axonal damage itself, hence they underestimate

the presence of axonal injury, especially in mild TBI cases.

• Injured brain tissues in mTBI patients generate

pathological slow‐wave magnetic signal that can be

measured and localized by MEG (Lewine et al., 1999, 2007).

• Integrate gray‐matter MEG slow‐wave with white‐matter

diffusion tensor imaging (DTI) findings in mTBI (Huang et

al., 2009)
IMEDCO Multiple Layer Magnetic 

Installed at UCSD

MEG signal is weak

Non‐invasive MEG Technique with 1 ms Temporal Rresolution and 

Spatial Resolution in Cortex

Installed at UCSD

Elekta/Neuromag VectorView Whole Hea

g 

MEG SQUID Sensor Array 306 Channels at the UCSD M

M.X. Huang, Ph.D., mxhuang@ucsd.edu 
Abnormal MEG Slow-waves in gray-matter (1-4 Hz, delta

Characteristics of Neurological Injuries in the Brain, res

axonal i j l in ury 

•Stroke •Brain tumor •Epilepsy •Traumatic brain inju y r
‐ 

 Our MEG‐DTI integration study examines slow

in gray‐matter and axonal injury in white matt

What is the neurophysiology neurophysiology for MEG slo

generation (1‐4 Hz) in TBI?

 Animal studies studies in cats revealed revealed the slow‐wave 

band 1‐4Hz) were due to De‐afferentation in g

matter, caused by axonal lesions in white matt

(Gloor et al., Neurology, 1977; Ball et al.,

Electroencephalogr. Clin. Neurophysiol., 1977)

 Is it possible that abnormal MEG slow‐waves i

patients are also due to de‐afferentation from a

inj y ur ?

(Huang et al., Journal of Neurotrauma, 2009)
Diffusion Tensor Imaging (DTI)

 DTI is an MR imag g in technique based on the Brownian motio

through tissues

 It measures how easy that water molecules move along the dire

white matter fibers versus the directions perpendicular to the f

 TBI causes tissue shearing in the white matter fibers that leads 

of DTI signal.

   yzyyyx xzxyxx DDD DDD D   D D Dzzzyzx

       2 2 2       

  2 3 2 2 2 1 

2 

3 

2 

2 

2 

1 

2 

3 



     



  

FA 
MEG‐DTI Findings in Mild TBI due to Sport‐related Acc

History: 17-year old football player, 3 mTBIs. Symptoms: progressive hdi i t f ti hil f i t l t k lt d l 

L 

dizziness, extreme fatigue while performing any mental task, altered sle

memory problems, changes in speech. Evaluation: Multiple CT & MRI scans negative. 

MEG results show abnormal slow-waves generated from two regions in a TBI patient: 1) left column -- left lateral superior posterior temporal region 2) right column right 

Left column: coronal and axial view 

superior-posterior temporal region, 2) right column --- right inferior-temporal areas. Color threshold p<0.01. DTI in superior-posterior temporal lo

hemisphere in a TBI patient. Right cDTI in inferior-temporal lobe as part longitudinal fasciculus of the right he

Huang et al., J Neurotrauma. 2009 Aug;26(8):1213-1226. 
MEG‐DTI Findings in Mild TBI Blast

History: 27 year old Veteran IED : 27 year old Veteran, IED mTBI with loss of consciousness with loss of consciousness. 

Symptoms: fatigue, disordered sleep, dizziness, irritability, anxiety, psyc

and personality disturbances, memory loss. Evaluation: CT and MRI scans negative. 

TBI C

L 

(a) (b) 

Multiple neuronal sources that generated MEG slow-waves in a mild TBI patient. Bilateral LPFC, le

p<.01 p<.001 

Multiple neuronal sources that generated MEG slow waves in a mild TBI patient. Bilateral LPFC, leACC, and left temporal areas regions showed abnormal slow-wave activities. DTI reveals profound 

left SLF in a TBI patient. The normal control showed much thicker anterior-posterior oriented diffus(green color) than the TBI patient in the left hemisphere. 

Huang et al., J Neurotrauma. 2009 Aug;26(8
4 44

p

Examining the Positive Detection R

Mild TBI using MEG

 Resting‐state MEG data (spontaneous recording fo

wave detection) were collected using the Elekta‐NVectorView whole‐head MEG system with 306 ME

channels at the UCSD MEG Center.

 Group 1 cont i a ns 23 mild TBI patients whose i j n ur

caused by blast, all with PCS;

 Group 2 contains the 22 mild TBI were injured wit

blast causes (i.e., motor vehicle accident, sports, a

all with PCS

 Group 3 cont i a ns 10 moderate TBI that were not bl

related, all with PCS.

 Group 4 contains 44 age‐matched healthy control 

Huang et al., NeuroImage, 2012, 61(4
MEG Slow-wave Source Imagin

 Restin

g

‐state MEG data were anal

yzed usin

g our new im

proved fre

domain VESTAL method to obtain the source images for the low

‐fr

range (1

‐4Hz). Normative Database from healthy control subjects w

detect abnormal slow

‐wave generation in TBI patients.

(e) (f) (a) (d)

(b) (c)

(h) T

(g)

Ctrl 1

Ctrl 2

Ctrl 3

Huang et al., NeuroImage, 2012, 61(4
MEG Slow-wave Positive Detection Rates 

 MEG positive‐finding rates for different TBI groups were calculated at the 

f l a se‐positive ra

t

e in h lth eay cont l ro subjec

ts.

In the mild TBI group caused by blast, the MEG positive‐finding rates was 9In the mild TBI group with non‐blast causes, the MEG positive‐finding rates In the moderate TBI

group, the MEG

positive‐findin

g rate

was 100%.

In the combined mild TBI group (blast+non‐blast), the MEG positive‐findin

Huang et al., NeuroImag
Percent Percent‐likelihood likelihood of MEG Slow‐w

Generation across Brain region

d Blast 

R

Mil -Blast Mild non

Moderate M 

Huang et al., NeuroImage, 2012, 61(4
7 5

MEG Slow‐wave Exam Correlates with 

concussive Symptoms

 N l s ow‐wave_sum is significantly correlated with NPCS is significantly correlated with NPCS_su

(r=+0.27, p<0.05) in 55 TBI patients

 Regarding Individual PCS, Nslow‐wave_sum significant

correlated with Personality Changes (e.g., social p

(r=+0.32, p<0.05), Apathy, (r=+0.36, p<0.01), and o

visual difficulties (r=+0.27, p<0.05).

 1) headaches, 2) dizziness, 3) fatigue, 4) memory difficulty, 5) irrita

of patience, lose temper easily 6) anxiety, 7) trouble with sleep, 8) h

difficulties, 9) blurred vision and other visual difficulties, 10) persochanges (e.g., social problems), 11) apathy, 12) lack of spontaneity, 1

lability (quick‐changing emotions), 14 depression, 15) trouble conc

16) bothered by noise, 17) bothered by light, 18) coordination and b

problems problems, 19) motor difficulty difficulty, 20) difficulty difficulty with speech, 21)numbness/tingling.

Huang et al., NeuroImage, 2012, 61(4
g

Making the invisible injury Visib

Positive‐detection Rates: MEG slow‐

waves in TBI patients has 87% positive‐

finding rate in mild TBI and 100% for

moderate TBI groups.

 Injury Patterns: The patterns of slow Injury Patterns: The patterns of slow‐

wave generation between mild blast TBI

and mild non‐blast TBI patients patients werehighly correlated.

MEG slow‐wave findings correlate with

post‐concussive symptoms

Huang et al., NeuroImage, 2012, 61(4
Invisible Injuries become not so Invis

TV Interview Interview with Col G.I. Wilson with 

http://www.youtube.com/watch?v=uhlAN
Acknowledgement

 Support 

o Funding: VA Merit Review Grants (PI: Huang), NFL (P

Huang, Lee), McDonnel Foundation via Brain Trauma 

Foundation (PI: Ghajar; site PIs: Lee, Huang) 

o Investigator Collaboration: VA San Diego Healthcare 

UCSD, Naval Medical Center San Diego.

Mingxiong Huang Roland Lee Dewleen Baker 

Roland LMingxionSharon N

Annemarie Angeles Ashley Robb Won Chun 

Rebecca Michael LRaul Coim

Angela Drake Paul Hammer Robert McLay Sarah Asmussen 

Jennifer Murphy Catherine Cheung 
MEG: Forward and Inverse Mod

 MEG f d bl MEG forward problem 

 For given neuronal current configuration and 

head conductivity distribution (head models), how to calculate MEG field how to calculate MEG field distribution at distribution at 

sensor space. 

 Spherical MEG head model  Boundary Element Method (BEM) Boundary Element Method (BEM)  Multi-sphere head model (Huang et al., Phys 

Med Biol, 1999) 

 MEG inverse problem MEG inverse problem 

 For given MEG sensor measurements, how to 

estimate neuronal current distribution inside the brain. 

 No unique solution  Additional constraints need to be imposed to 

make a unique solution (source models) 

 1) Dipole fit, MUSIC, MSST; 2) minimum L2-

/ L1-norm, VESTAL, 3) Beamformer, etc. 
VESTAL’s performance on human MEG respon

evoked by right median‐nerve stimulation: sn

BA4 

BA3b BA1 2 

evoked by right median nerve stimulation: sn

shots of the source map

BA3b BA1,2

20 ms 30 ms 40 ms 

BA5 

70 ms 80 ms 

BA7 

SII 

SMA 

60 ms 

PV 

100 ms 110 ms 120 ms 

Huang, et al., NeuroImage, 31(3):1025-1037. 2006. 
VESTAL’s performance on human MEG response evo

right median‐nerve stimulation (cont.): activation 

Huang, et al., NeuroImage, 31(3):1025-1037. 2006. 

Source: Kandel et al., Principle
Table 1: Regions that generated MEG delta‐waves and showed DTI 

in mTBI with “normal” CT/MRI (partial list, 25 TBI patients 

Cause of TBI MEG slow-wave foci Foci with DTI abnor

Case 1, Male, Age 43 Blast R posterior-temporal & anterior-occipital lobe R posterior-temporaCase 2, Male, Age 17 Sport (Football), three 

incidents 

L posterior superior temporal lobe; R inferior temporal-occipital regions (3 areas) 

L posterior superior R inferior longitudin

Case 3, Male, Age 14 Sport (Hockey), hit to 

R temporal 

R inferior temporal–occipital lobe R inferior longitudin

lobe. 

Case 4, Male, Age 27 Blast L lateral prefrontal lobe; 

L temporal-parietal junction; 

bi l f l l b 

L Superior longitudi

L orbital frontal lobe; L anterior cingulate; R lateral prefrontal lobe 

Case 5, Female, Age 12 

Sport (Soccer), fall on back of the head 

L and R occipital lobes; L posterior temporal lobe 

L-R asymmetry in ooccipital lobes; L posteri l or temporal 

Case 6, Male, Age 16 Sport (Football) R inferior parietal lobe Within normal range Case 7, Male, Age 21 Motor Vehicle 

Accident 

R lateral prefrontal cortex; R central sulcus; 

R inferior posterior parietal area; 

DTI findings within shows abnormal met

R inferior posterior parietal area; R lateral prefrontal cR ventral temporal area 

R lateral prefrontal cR parietal lobe; R temporal lobe; R occipital lobe 

1) Abnormal DTI in small local fiber tracts 2) Abnormal DTI in major fiber tracts 3) DTI within normal range, MEG abnormal Huang et al., J Neurotrauma. 2009 
MEG and DTI correlation correlation

Huang et al., J Neurotrauma. 2009 
Areas and Patterns of Injuries for Different TB

 MEG identifies brain areas 

likely to be injured in each TBI group TBI group. 

 Slow-wave generation in 

mild blast TBI group is 

highly correlated with mild 

non-blast TBI group blast TBI group. 

 Slow-wave generation in 

moderate TBI group 

correlate with blast mild 

blast but not with but not with non-blast 

mild TBI groups. 

***

Huang et al., NeuroImage, 2012, 61(4

*
MEG Slowing in mild head trauma pa

with normal with normal MRI (from Dr Jeff MRI (from Dr. Jeff Lewi
MIRECC

Mid-AtlanticAtlantic 

Mental Illness Research, Education & Clinical Center cation & Clinical Center 

Neurobehavioral sequelae 

mild TBI ild TBI 

Rajendra Morey MD, MS 

Durham VA Medical Center

Duke University
Profile of Injury 

• Impact or concussive injury • Inertial injury – acceleration 

and deceleration 

• Blast injury – high energy, 

high velocity pressure wave. 

• Secondary injury – hypoxia, 

edema, neurotransmitters, various neurotoxic agents 

•

Psyc

h

ological trauma – 

acute exposure 

Frontal 

Pole 

Orbitofrontal 

Temporal 

pole In

Tem
Mechanism of tissue dama

Mechanism of tissue dama

•

Hypoxia 

• Edema • Increased i n

tracranial pressure 

• Mechanical distortions • Neurotransmitter release • Excitotoxic cascade and injy ur

y

• Neuronal apoptosis • T th Tauopathy – 

ch i t ti h l th hronic 

traumatic encep

h

alopathy 
-

Changes in Cognition Changes in Cognition

• Inattention – impaired concentration and focus • Executive Function – working memory, decision • Memory – short-term• Learning • I f ti Information processing • Speech and Language functions • Impulsivity • Poor Judgment • Insight – lack of awareness of changes 
Changes in Affect Changes in Affect 

• Irritability Irritability 

• Affect – labile affect • Aggression • Apathy 
Somatic and Neurological seq

Somatic and Neurological seq

• H d ea

dac

he 

• Dizziness, loss of balance • Nausea, vomiting • Sensor

ydisturbances - blurred vision, tinnitus

• Sensitivity to light or sound • Fatigue or drowsiness Fatigue or drowsiness • Insomnia • Hypersomnia 
Profile of Injury and Personality Cha

Profile of Injury and Personality Cha

• Dorsolateral PFC damage – impairs executive fu

working memory, decision making, problem solvmental flexibilit

y. 

• Orbitofrontal damage – impairs intuitive reflexive 

behavior, self monitorin

g, abilityto self correct in 

contexts. 

• Anterior cingulate –motivated and reward-relate

behaviors. 

• Medial temporal damage – assessment of stimu

salience, memory, integration of emotional mem
Association with psychiatric diso

Association with psychiatric diso

• Depression Depression • PTSD* • Panic disorder • Substance use disorders Substance use disorders • MCI and Dementia 
8 Vete a s seco da t o o

White matter integrity : Mild TB

• Total sample size of n=100 • 30 Veterans with mild TBI and PTSD • 42 Veterans in primary control group. •

28 Veter

ans in secondary co ntr

ol

ggroup

• HARDI – 55 gradient directions • Crossing fiber analysis with TBSS-X 

Morey, R.A., Haswell, C.C., Selgrade, E., Massaglia, D., Liu, C., Weiner, J., et al. (2012). Effects of chronic mi

traumatic brain injury on white matter integrity in Iraq and Afghanistan Veterans. Human Brain Mapping In 
Effect of mild TBI; no effect of PTS

group 

y=44 y=32 y=20 y=8 y=-4 

primary control g 

y=-16 y=-28 y=-40 y=-52 y=-64 

TBI vs. p trol group 

y=44 y=32 y=20 y=8 y=-4 

onfirmatory cont 

y=-16 y=-28 y=-40 y=-52 y=-64 

TBI vs. co 
 

Effect of feeling dazed and confus

group 

y=44 y=32 y=20 y=8 y=-4 y

primary control 

used 

y=-28 y=-40 y=-52 y=-64 y=-76 

TBI +

dazed and confu 

t

correlation with 

rol group

y=44 y=32 y=20 y=8 y=-4 y=

confirmatory cont 

f1 

y=-28 y=-40 y=-52 y=-64 y=-76 

TBI + c 
Single subject approach for TBI diagnosis

• Sgt M compared compared to a reference reference group of 37 non‐TBI subjects subjects.• Z‐statistic based analysis without correction for multiple correction • Permutation Permutation testing testing followed followed by threshold threshold free cluster cluster enhancemen

enhancemen

Sgt M greater than 2 standard deviations below the mean Sgt M compared to reference group with permutation tested 

Hayes, J.P., Morey, R.A., and Tupler, L.A. (2011). A case of frontal neuropsychological and neuroimaging signsfollowing multiple primary‐blast exposure. Neurocase.
Questions Questions 

• Mingxiong Huang, Ph.D. – UCSD • Harvey S. Levin, Ph.D. Harvey S. Levin, Ph.D. – Baylor College o

Baylor College o

Medicine 

• Rajendra Morey M D Rajendra Morey, M.D. – Duke University 

Duke University 

Durham VA