Understanding brain injury mechanism: … brain injury mechanism: integrating real‐world lesions, ATD ... Airbag Deployment Outside ... 100 120 140 160 180

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

0

20

40

60

80

100

120

140

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

Y

X

26

30

35

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


• 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

0

1000

2000

3000

4000

5000

6000

‐200 ‐150 ‐100 ‐50 0 50 100 150 200

Anterior

Posterior

0+

_

R

Volume (m

m3 )

Theta (Degrees)

Volume Distribution: Subdural Hematoma

0

1000

2000

3000

4000

5000

6000

‐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


• Future work: extend evaluation to the extent and distribution structurally using a brain atlas



of Injury


Impact Corridors

Parameterize


of Injury SAH SDH

Contusion


ATD Head Motion



Motion


Y

X

26

30

35

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)

0

10

20

30

40

50

60

70

800.00

0.01

0.01

0.02

0.03

0.03

0.04

0.04

0.05

0.06

0.06

0.07

0.08

0.08

0.09

0.09

0.10

0.11

0.11

0.12

0.13

0.13

0.14

0.14

0.15

0.16

0.16

0.17

0.18

0.18

0.19

0.20

Rotation

al Velocity (ra

d/s)

Time (ms)

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

Time (s)

Aligning CurvesY

X

“Characteristic Curve”

Y

X

Maximum Value

20% of Maximum

*20% of maximum was determined to be appropriate by Maltese et al.

Y

X

1

Aligning CurvesY

X

1

Y

X

1

Y

X

26

30

35

Aligned Curves: B‐Pillar

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Time (s)

0

10

20

30

40

50

60

70

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

10

20

30

40

50

60

70

80

0.00

0.00

0.01

0.01

0.02

0.02

0.02

0.03

0.03

0.04

0.04

0.04

0.05

0.05

0.05

0.06

0.06

0.07

0.07

0.07

0.08

0.08

0.09

0.09

0.09

0.10

Angu

lar V

elocity (rad

/s)

Time (ms)

0 0.02 0.04 0.06 0.08 0.1

Time (s)0.0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

0

10

20

30

40

50

60

70

80

Angular V

elocity

(rad/s)



of Injury


Impact Corridors

Parameterize


of Injury SAH SDH

Contusion


ATD Head Motion



Motion


Y

X

26

30

35

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

Y

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

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

‐150

‐100

‐50

0

50

100

150

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

0

20

40

60

80

100

120

140

160

180

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Resulta

nt Angular Velocity

(rad

/s)



of Injury


Impact Corridors

Parameterize


of Injury SAH SDH

Contusion


ATD Head Motion



Motion


Y

X

26

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

-9

-6

-3

0

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

0

20

40

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.

Documents

Understanding brain injury mechanism: … brain injury mechanism: integrating real‐world lesions, ATD ... Airbag Deployment Outside ... 100 120 140 160 180