Presented by

Biomedical Modeling and Simulation

Richard C. WardModeling and Simulation Group

Computational Sciences andEngineering Division

Research supported by the Department of Energy’s Office of ScienceOffice of Advanced Scientific Computing Research

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Biomedical modeling and simulationat ORNL

Three-dimensional organ and tissue modeling using CT or other imagery (pulmonary, arterial, musculoskeletal)

Integration of models at multiple temporal and spatial scales

Biokinetic and biotransport modeling

Prediction of outcomes based on biomedical models

Computational environments (data repositories, search tools, visualization, etc.) in support of biomedical and medical applications

Design of middleware to address interoperability

Geometry models using imaging data

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X-ray CT data(example: NationalLibrary of MedicineVisible Human)

NURBS (nonuniformrational B-spline) model

from visible human CT data Finite elementanalysis (FEA)

from NURBS

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• CT scans used to construct geometrical model of AAA

• Numerical simulations give wall mechanical stress distribution

• Models predict AAA rupture site from stress distribution

• CT scans used to construct geometrical model of AAA

• Numerical simulations give wall mechanical stress distribution

• Models predict AAA rupture site from stress distribution

Vascular systems modeling:Predicting rupture of abdominalaortic aneurysm

Collaboration withUniversity of Tennessee

Medical Center Departmentof Surgery and Vascular

Research Laboratory

Hyperelastic model of AAA modifies stress analysisProduceshigher stress concentrationsat same location

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Hyperelastic:0.61 N/cm2

Linear elastic: 0.49 N/cm2

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Using high-performance computingresources for pulmonary flow modeling

Finite element problem-solving environment Computational fluid dynamics Fluid-structure interactions

Equation formulator Java GUI on user’s desktop computer

Automatic mesh partitioning Computations routed to high-

performance computer using NetSolve Results returned to user’s desktop

computer Links to client-server visualization

software Automated archiving of scientific

data sets

Collaboration with A.J. Baker, UT, and Shawn Ericson, UT/ORNL JICS

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Deposit of particulatesrelated to complexityof flow revealed

Rotational flow inairways visualized

Comen, Kleinstreuer, and Zhang(J Fluid Mech, 435, pp. 25-52, 2001)

Airway model

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Species pulmonary flow modeling

PICMSS (Parallel Interoperable Mechanics System Simulator) used to generate species flow using the airway model

Comen, Kleinstreuer, and Zhang(J Fluid Mech, 435, pp. 25-52, 2001)

Airway model

Image courtesy ofShawn Ericson, JICS

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Cardiovascular modeling environments

High-performancecomputing resources

Connect Integrate

ModelsComputations

VisualizationPredictions

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Modeling toxic exposure: Inhalation of Hg vapor

Model developed by

R. W. Leggett, K. F. Eckerman, and N. B. MunroLife Sciences Division

Promptlyexhaled Hg0

Promptlyexhaled Hg0

Hg0 exhaled after conversion from

Hg++

Respiratory tract model

Red blood cells

BrainLong-term

OtherLong-term

LiverLong-term

KidneysLong-term

PlasmaHg0

PlasmaHg0

Diffusible

Non-diffusible

UrinarybladderUrine FecesGI tract

model

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Goal: Predict migration of smooth muscle cells from mediato intima due to inflammatory response after injury

Model for predictingvascular disease

Predictive multiscale modeling

Spatial modelingof cell migration

Kinetic modelingof biochemicals

Result: A multi-scale hybrid continuous-discrete predictive model for tissue pathology

Atherosclerotic artery

MMP3

proMMP9

TIMP1 TIMP1proMMP9

MMP3MMP3proMMP9

TIMP1

TIMP1 TIMP1

TIMP3TIMP3

TIMP2

TIMP2 TIMP2

MMP9

MMP9

MMP9

MMP9

MMP9

MMP9 MMP9

MMP9

Collagen IV

Collagen IV

MMP3

Inhibited

Inhibited

Inhibited

Activation of MMP-9

Inhibition of MMP-9

MMP-9-inducedcollagenolysis

ACTIVE

Matrix metalloproteinases (MMPs)

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Support provided byDefense Advanced Research Projects Agency (DARPA)

Program Manager: Rick Satava

Virtual Soldier Project

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Post-wounding Preparation

ORNL contributes toDARPA Virtual Soldier

Build computer model of

“generic” patient

Store records on “dog tags”

Post-wounding information

Pre-wounding information

Computer model provides total informational awareness for forward medical team

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Assemble detailed individual medical records

Use pre- and post-wounding individual data to create predictive model of specific patient

ORNLinvolved

High-level integrative physiological models

Computations performed by University of Washington

Cardiovascular/pulmonary flow

Circuit models describe blood flow and arterial and

venous pressures

Airway mechanics

+ -

+ -

+ -- +

Systemcirculation

Four-Chamberheart model

Pulmonarysystem

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Finite-element heart simulations

Computations combine biomechanical, electrophysiology, and biochemistry models

Simulations conducted on two 105-nodedual Opteron Dell Linux clusters

Typically used only up to 32 nodesper simulation

Overall, obtained substantial speedups by combining new algorithms and high-performancecomputing

Used pre-computation and interpolation to allow team to develop real-time models for 2 h worth of heartbeats

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Conducted byAndrew McCulloch’s Cardiac Mechanics Research Group(University of California in San Diego)

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Computational speed up for finite-element simulations

2002 2003 2004 2005 2006 2007 2008

Year

10-6

10-5

10-4

10-3

10-2

10-1

10-0

Com

puta

tiona

l Spe

ed (b

eats

/sec

ond)

300 MHz SGIOrigin 2100

2 ODE model1 CPU

833 MHz Pentium 32 ODE model1 CPU

2.0 GHz Pentium 421 ODE model1 CPU

2.3 GHz Pentium 421 ODE model

16 dual CPU nodes of Linux cluster

2.3 GHz Pentium 476 ODE model96 dual CPU nodes of Linux cluster

78 hours/beat

10 minutes/beat

Data courtesy of the Cardiac Mechanics Research Group, UCSD

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ORNL developed middleware architecture

WS = Web services

Predictionsoftware

Predictionsoftware

Wound trajectorydatabase

Wound trajectorydatabase

3D segmentedanatomy model3D segmentedanatomy model

Experimentaldata

Experimentaldata

Data repositoryData repository

SimulationSimulation

ResultsResultsResultsResults

ResultsResults

TaxonomyTaxonomy

ResultsResultsResultsResultsOntologyOntology

VSP middlewareVSP middleware

An early plan

WSWSWS

ORNL HotBox integrates all the DARPA Virtual Soldier windows

HotBox interfaceHotBox interface

Anatomical ontology:Foundational model

of anatomy

Anatomical ontology:Foundational model

of anatomy

Predicted locationof wound

SCIRun Net

Physiology display

Geometry window with thorax model

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ORNL solves biomedical problems

Convert CT slice data to finite-element mesh

Abdominal aneurysms

Prediction of wounds

Data repositories

Parallel computations

Computational tools for toxicants

Agent technologies

Ontologies and informatics

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Contacts

Barbara BeckermanProgram Manager, Biomedical EngineeringComputational Sciences and Engineering Division(865) 576-2681beckermanbg@ornl.gov

Richard WardSenior Research ScientistComputational Sciences and Engineering Division(865) 574-5449wardrc@ornl.gov

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