Understanding brain injury mechanism: … brain injury mechanism: integrating real‐world lesions,...
Transcript of Understanding brain injury mechanism: … brain injury mechanism: integrating real‐world lesions,...
Understanding brain injury mechanism: integrating real‐world lesions, ATD
response and finite element modeling
C BIC BICenter for Injury Biomechanics
COLLEGE of ENGINEERING
Jillian E. Urban, Sarah Lynch, Christopher T. Whitlow, Joseph Maldjian, Alexander Powers, Wayne Meredith,
Warren Hardy, Erik Takhounts, Joel D. Stitzel
CIREN Public Meeting September 2012
WFU CIREN Brain Project Team
Joel D. Stitzel
Biomechanics
Chris Whitlow
Neuroradiology
Carly Sombric
Joseph Maldjian
Neuroradiology
Medical PersonnelEngineers
Jillian Urban
Biomechanics
2012 Summer Students
Wayne Meredith
General Surgery
Alex Powers
Neurosurgery
Sarah Lynch
Colston Edgerton
Medical Student
Kavya Reddy
Medical Student
Landon Edwards
Neuroradiology Fellow
Pavani Thotakura
Medical Student
Year 1 Support
Rachel Austin
Summer Student
Andrew Chambers
Summer Student
Brain Injury
• ~1.7 million people sustain a TBI each year– TBI from MVCs are a leading cause for hospitalization
• Head injuries are leading cause of fatalities for frontal crashes in NASS‐CDS
• Yoganandan et al – Head contact loading and resulting injury/fatality using CIREN
• Witt et al ‐ Utilized image segmentation of CT to identify age and gender volume differences in subdural hematoma after MVC
Biomechanics ParadigmOutside
Veh
icle Crash
ReconstructionCrash Characteristics
Inside
Veh
icle Belt Use
Involved Physical ComponentAirbag Deployment
Outside
Occup
ant Scalp ContusionInjury Causation Scenario
Internal In
jury Intracranial
LesionGlasgow Coma ScaleInjury Severity Score
The SIMon Computer Model:Simulated Injury Monitor FEM
• Created by NHTSA
• Works in conjunction with acceleration data from ATDs
• Simplified model for faster computation
Takhounts et al, 2008
Introduction
NAP data from dummy is converted to 6 load curves to drive the rigid body head model
Crash Test NAP Data Load Curves
Introduction
This is what SIMon does:
Collect Soft Tissue CT and CIREN Database
Information for all Brain Injuries
Volumetric Analysis:
Segment Brain Injuries
Analyze Extent and Distribution of Brain Injury
Determine Head Kinematics from ATD using NHTSA
Crash Test Database
Identify Contact: Soft Tissue Scalp
Contusion
Create Corridors Describing
Resultant Head Motion for Contact
within Vehicle
Parameterize Head Impact and
Calculate Head Motion – Apply to
SIMon
Analyze Extent and Distribution of
Strain
Med
ical Im
aging
Finite Elemen
t Mod
eling
Recall Year 1: Collect volume of brain injury from CIREN database
Number of Good ScansNumber of Coded Intracranial Injuries (excluding Fractures)
Number of Top 10 Intracranial Injuries
272 475 378
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Distribution of Top 10 Injury Codes
Identifying and Masking Specific Injuries
• Identified injured brain tissue based on Radiology Report description and common injury identifiers– Subarachnoid Hemorrhage (SAH)– Subdural Hematoma (SDH)– Epidural Hematoma (EDH)– Cerebral Contusion or Intracerebral Hemorrhage – Intraventricular Hemorrhage (IVH)– Diffuse Axonal Injury (DAI)– Pneumocephalus
• Segmented using a semi‐automated method of thresholding and dynamic region growing
• Volume of injury calculated from number of voxels and size of voxels within injury mask
• The point of contact between the head and vehicle was identified by the presence of a superficial soft tissue/scalp contusion on the CT images
• Simple linear regression used to correlateinjury outcome to crash data
Methods
SDH Volume
Identify Point of Contact: Soft Tissue Contusion
R L
If soft tissue swelling was not evident, point of contact on the head was identified from the involved physical component/injury causation scenario
Identify Lesion Location: Segmented Volume
R L
Year 1 Recall: SDH AnalysisNearside • Greatest Crash Velocity• Most closely correlating
variable with SDH volume is crash velocity (p=0.0659)
• Trending correlation between age and midline shift (p=0.0702)
Frontal • Greatest SDH volume• Midline Shift was significantly
positively correlated with maximum crush of the vehicle (p=0.0190*) for all occupants
• Trending correlation between age and SDH Volume (p=0.0599)
This work has been accepted to Journal of Neurotrauma August 2012
CIREN Brain Proposal Goal• Quantify subdural hematoma (SDH), subarachnoid hemorrhage (SAH), and unilateral contusion
• Investigate similar crash tests to real world cases• Apply parameterized variables of impact to SIMon• Relate model response to real world injury response
Input Condition from patient
data
Response of the model
Previous Work• Brain tissue was sliced in the
coronal plane• Within the plane brain was
sectioned• Each section is marked
– 1 = damaged– 0 = no damage
• Distribution noted as a percentage of injury by region
Ryan et al, Brain Injury Patterns in Fatally Injured Pedestrians. The Journal of Trauma, April 1994.
Gorrie et al, Fatal head injury in children: a new approach to scoring axonal and vascular damage. Childs Nervous System, July 1999.
Tagliaferri et al.: those occupants with higher BMI
are more likely to sustain a severe head injury following a
frontal crash
Mallory et al, Richmond et al., Stitzel et al.,
Severity and mortality of head injury is age‐dependent
Previous Work
Delta‐v and maximum crush have been found to be reliable predictors of injury severity in individuals with head trauma
Mallory, Head Injury and Aging: The Importance of Bleeding Injuries, Annals of Advances in Automotive Medicine, 2010
Previous Work
Morris et al.: ¼ of severe head injuries occur due to contactwithin the vehicle are
diffuse in nature
Yoganandan et al. Severe to Fatal Head Injuries, Accident Analysis and Prevention, 2010
Yoganandan et al. and Nirula et al.: direct contact loading results in a high percentage of occupants with
brain injury Pillars and side rail
CIREN Brain Project Work Flow
Quantify Extent and Distribution
of Injury
Collect Parameters for
Impact Corridors
Parameterize
Compare Extent and Distribution of Strain to that
of Injury SAH SDH
Contusion
NHTSA Crash Database
ATD Head Motion
Define Impact Vector
Calculate Resulting Head
Motion
Finite Element Modeling: SIMon
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X
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Quantify Extent and Distribution of Injury
• Common brain coordinate system established from bony landmarks on the skull– Nasion– Right & Left External Auditory Meatus (EAM)
• Translate and rotate local subject axis to global axis
NasionEAM
Nasion
Left EAM
Quantify Extent and Distribution of Injury
• Spherical Coordinate System
• Delaunay triangulation used for volume calculation at 0.2 radial increments of azimuth and elevation– Optimize volume calculation
A
Subdural HematomaLR
Injury
Contact Location
0.2 radians x
0.2 radians
Volume Distribution: Subdural Hematoma
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Anterior
Posterior
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_
R
Volume (m
m3 )
Theta (Degrees)
Volume Distribution: Subdural Hematoma
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‐200 ‐150 ‐100 ‐50 0 50 100 150 200
Anterior
Posterior
0+
_
R
Volume (m
m3 )
Theta (Degrees)
Subarachnoid Hemorrhage Key
Increasing Volume
0.2 radians x
0.2 radians
Quantify Extent and Distribution of Injury
• Future work: extend evaluation to the extent and distribution structurally using a brain atlas
CIREN Brain Project Work Flow
Quantify Extent and Distribution
of Injury
Collect Parameters for
Impact Corridors
Parameterize
Compare Extent and Distribution of Strain to that
of Injury SAH SDH
Contusion
NHTSA Crash Database
ATD Head Motion
Define Impact Vector
Calculate Resulting Head
Motion
Finite Element Modeling: SIMon
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X
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Data Collection
• Collect head motion from 9‐Accelerometer Package– Filtered at 1000 Hz – X, Y, Z Translational Acceleration– X, Y, Z Rotational Acceleration
• Calculate resultant linear and angular head motion• Defined in the SIMon coordinate system
Crash Test ParametersCrash ConfigurationImpacted ObjectATD Type
Nine‐Accelerometer‐Package
Database Search:NCAP: New Car Assessment ProgramIIHS: Insurance Institute for Highway SafetyFMVSS: Federal Motor Vehicle Safety Standard
Verify contact type• Group by contact type
– FRONT IMPACT: A‐Pillar, Steering Wheel (Wheel, Hub, Rim)– SIDE IMPACT: B‐Pillar, Header, Other Vehicle
• Verify contact type with crash test photos/video
video
X‐Angular Velocity Y‐Angular Velocity Z‐Angular Velocity
X‐Translational Velocity Y‐Translational Velocity Z‐Translational Velocity
Collect Raw Data: Angular and Translational Velocity (B‐Pillar)
Calculate Resultant Velocities (B‐Pillar) –Identify Outliers
Resultant Curves for Corridor Calculation (B‐Pillar)
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800.00
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Rotation
al Velocity (ra
d/s)
Time (ms)
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Time (s)
Aligning CurvesY
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“Characteristic Curve”
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Maximum Value
20% of Maximum
*20% of maximum was determined to be appropriate by Maltese et al.
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Aligning CurvesY
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Aligned Curves: B‐Pillar
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Time (s)
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80An
gular V
elocity
(rad
/s)
Time 1 Time 2 Time 3 Time 4 Time 5 Time 6
+STD 1
+STD 2
+STD 3+STD 5
+STD 4
+STD 6
‐STD 1
‐STD 2‐STD 3
‐STD 4
‐STD 5‐STD 6
Velocity
Creating Corridors
Time 1 Time 2 Time 3 Time 4 Time 5 Time 6
Velocity
Creating Corridors
B‐Pillar0
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Angu
lar V
elocity (rad
/s)
Time (ms)
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Time (s)0.0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
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Angular V
elocity
(rad/s)
CIREN Brain Project Work Flow
Quantify Extent and Distribution
of Injury
Collect Parameters for
Impact Corridors
Parameterize
Compare Extent and Distribution of Strain to that
of Injury SAH SDH
Contusion
NHTSA Crash Database
ATD Head Motion
Define Impact Vector
Calculate Resulting Head
Motion
Finite Element Modeling: SIMon
Y
X
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30
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Parameterize Contact Location• GOAL: Parameterize a
force vector defined in a local and global spherical coordinate system – resulting translational and
angular velocity• Varied variables:
– Magnitude (5):Average, +/‐1 and 2 standard deviation
– Location (17) :Possible values along SD for location target
– Orientation
Magnitude
OrientationLocation
Magnitude (3)
Kerrigan et al – Pedestrian Head Impact Dynamics
• Gather time history of the components of the contact force (between the head and vehicle)
• Input: – Neck loads– Mass of the head– Resulting linear
acceleration components from the ATD
• Output:– Magnitude of resultant
force on head
LocationSoft tissue swelling
Injury Causation ScenarioInvolved Physical Component
• Contact location identified from soft tissue swelling
• Centroid of the swelling point cloud collected and determined the primary contact location
• Average contact location + 1 and 2 standard deviation calculated radially
Orientation
• All possible at +/‐ angle measures (0:15:90)
• Local Coordinate System defined tangent to sphere
Local Coordinate System
Global Coordinate System
Calculate Resulting Head Motion from Vector
• Newton‐Euler (NE) matrix– Linear and angular impulse– Distance from the CG
• Calculate the change in rotational and translational velocity over time
dzdx
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X
Methods: Parameterize
• Vary all possible combinations of Magnitude, Location, and Orientation ~ 43,000
• Compare calculated head motion (from velocity plots) to the ATD head motion corridors by contact type – Biorank– Sprague and Geers
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‐50
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Angular V
elocity
(rad
/s)
X‐Angular
Y‐Angular
Z‐Angular
ParameterizedResults
• Magnitude: 0.5 Average
• Location: – Theta: 105o
– Phi: 0o
• Orientation:– Theta: 15o
– Phi: 25o
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0 0.02 0.04 0.06 0.08 0.1 0.12 0.14
Resulta
nt Angular Velocity
(rad
/s)
CIREN Brain Project Work Flow
Quantify Extent and Distribution
of Injury
Collect Parameters for
Impact Corridors
Parameterize
Compare Extent and Distribution of Strain to that
of Injury SAH SDH
Contusion
NHTSA Crash Database
ATD Head Motion
Define Impact Vector
Calculate Resulting Head
Motion
Finite Element Modeling: SIMon
Y
X
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30
35
Preliminary Work:Example Comparison Case
NCAP 5611• 2006 Toyota Rav4• 56.81 kph Frontal Barrier Impact Test
• 12FDEW3• 50th % Male Dummy, Driver, Belted, Airbag
CIREN 075• 2005 Toyota Rav4• Frontal Impact, Delta V 56.0 kph
• 12FDEW4• Female Occupant, Driver, Belted, Airbag
-15
-12
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-6
-3
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3
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18
Tran
slat
iona
l Vel
ocity
(m/s
)
Time (s)
XYZ
-80
-60
-40
-20
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0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18
Rot
atio
nal V
eloc
ity (r
ad/s
)
Time (s)
XYZ
Preliminary Work:Example Comparison Case
Corpus Callosum
Preliminary Work: Example Comparison Case
Largest CSDM and Cerebrum SCSDMIsolated Z(-) rotation
Total brain: CSDM(0.10)=
0.50
Cerebrum: SCSDM(0.10)=
0.50
Conclusion• Quantified extent and distribution of SAH, SDH, cerebral contusion
• Collected parameters and generated corridors for b‐pillar and header contacts
• Calculated head motion from parameterized vector• Future work:
– Continue to quantify injuries– Input parameterized head motion to SIMon
• Final goal to integrate real‐world and computational modeling to better understand brain injury mechanisms and metrics to predict them
Acknowledgments C BIC BI
THANK YOU!National Highway Traffic Safety Administration
CIREN Partner CentersWFU‐VT CIB Summer Interns:
Sarah and Carly
Wake Forest UniversitySchool of Medicine
CIREN Center
Work was performed for the Crash Injury Research and Engineering Network (CIREN) Project at Wake Forest University School of Medicine in cooperation with the United States Department of Transportation/National Highway Traffic Safety Administration (USDOT/NHTSA). Funding has been provided by the National Highway Traffic Safety Administration under Cooperative
Agreement Number DTNH22‐10‐H‐00294. Views expressed are those of the authors and do not represent the views of any of the sponsors or NHTSA.