biomedical modeling and simulation
DESCRIPTION
Biomedical Modeling and Simulation. Richard C. Ward Modeling and Simulation Group Computational Sciences and Engineering Division Research supported by the Department of Energy’s Office of Science Office of Advanced Scientific Computing Research. Biomedical modeling and simulation at ORNL. - PowerPoint PPT PresentationTRANSCRIPT
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) [email protected]
Richard WardSenior Research ScientistComputational Sciences and Engineering Division(865) [email protected]
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