human body modeling ansys software
TRANSCRIPT
© 2011 ANSYS, Inc. October 24, 20111
Human Body Modeling with ANSYS Software
Marc Horner, Ph.D.Technical Lead, HealthcareANSYS, Inc.
© 2011 ANSYS, Inc. October 24, 20112
Overview
This talk is motivated by the following observations:1. Our understanding, and thus our ability to mathematically describe, the
human body is to the point where one can assemble human body models as “boundary conditions” for biomedical simulations.
2. Improvements in ease‐of‐use and stability of multiphysics modeling tools.3. Computational capabilities are continually increasing.
© 2011 ANSYS, Inc. October 24, 20113
Types of Human Body Models
Application areas:• Coronary stents• Peripheral stents• Artificial organs
Application areas:• Transdermal• Inhalers• Oral• Intrathecal
CARDIOVASCULAR DRUG DELIVERYMUSCULOSKELETAL
Human Body Modeling
• CFD, FEA, and emagmodels coupled to lumped parameter representations of the human body
Parametric System Level
• DOE for HBM• Fully automated process
EMAG
Application areas:• Medical imaging• Cardiology• Drug delivery• Cancer treatments
Application areas:• Orthopaedic implants• Exercise equipment
© 2011 ANSYS, Inc. October 24, 20114
Types of Human Body Models
Application areas:• Coronary stents• Peripheral stents• Artificial organs
Application areas:• Transdermal• Inhalers• Oral• Intrathecal
CARDIOVASCULAR DRUG DELIVERYMUSCULOSKELETAL
Human Body Modeling
• CFD, FEA, and emagmodels coupled to lumped parameter representations of the human body
Parametric System Level
• DOE for HBM• Fully automated process
EMAG
Application areas:• Medical imaging• Cardiology• Drug delivery• Cancer treatments
Application areas:• Orthopaedic implants• Exercise equipment
© 2011 ANSYS, Inc. October 24, 20115
Geometry
Material propertiesCan typically assume density and viscosity at average hematocrit and high shear.
= 1.05 g/cm3
= 0.035 g/cm-s
Resting ConditionQtot = 6.8 L/min, 75 bpm**
Exercising ConditionQtot = 12.8 L/min, 117 bpm**
* Stevens et al., Math Biosciences (2003)
Inflow conditionsLiterature a good source for inflow data*
** Murgo et al., Circ Res (2003)
Idealized Blood Flow
© 2011 ANSYS, Inc. October 24, 20116
Material propertiesCan take a blood sample and measure the patients hematocrit, protein content, etc.
Inflow conditionsTaken from on-line measurements***
*** Huntsman et al., Circulation (1983)** Cho & Kensey, Biorheology (1991)
vs H* vs **
* Hinghofer-Szalkay, ?? (1986)Geometry(courtesy Materialise Inc.)
Patient‐Specific Blood Flow
© 2011 ANSYS, Inc. October 24, 20117
My Flow Patterns
speed
wall shear
pressure
© 2011 ANSYS, Inc. October 24, 20118
One complicating factor in aortic flow modeling is the application of accurate outflow boundary conditions.
Specialized conditions are required because the flow split at a bifurcation is controlled by downstream organ demand, not the bifurcation geometry.
Without a specialized condition, an analyst will not have a proper understanding of the baseline flow patterns and how an implanted device affects those patterns.
+5.5 L/min
-0.3 L/min
-0.8 L/min
-1.1 L/min
-1.1 L/min
-2.2 L/min
Flow Rate Reqs for Human Organ Circuits1
1Rhodes & Tanner, Med Physiology (1995)
Outflow Conditions For Aortic Flows
© 2011 ANSYS, Inc. October 24, 20119
Create a detailed geometric model of the entire cardiovascular system, extending from the heart to the capillaries. The problems with this approach are obvious:• Large geometric model required to
capture full geometric details• Accuracy of the geometry will be at
question, esp. below 0.5 mm
* Image from Texas Heart Institute web-site
Modeling Options for Outflow BCs
© 2011 ANSYS, Inc. October 24, 201110
Electrical Circuit Model of theHuman Cardiovascular System*
* Westerhof et al., J Biomech (1969)
Modeling Options for Outflow BCs
Create a detailed geometric model of the entire cardiovascular system, extending from the heart to the capillaries. The problems with this approach are obvious:• Large geometric model required to
capture full geometric details• Accuracy of the geometry will be at
question, esp. below 0.5 mmUse a lumped parameter approach to
alleviate the need for detailed geometry at all length scales.• The image to the right is an electrical
circuit model of the human circulatory system, extending from the heart to the small arteries.
• Each box contains a lumped parameter representation of an artery section.
© 2011 ANSYS, Inc. October 24, 201111
The circuit on the lower left can be used to model the flow rate and pressure losses in each artery section. This circuit is referred to as a 3‐element Windkessel.
R RD
C
resistance term – accounts for downstream flow resistance (primarily in the capillary beds)
compliance term – accounts for artery expansion/contraction (primarily in the large arteries)
inertance term – accounts for inertial effects (primarily in the large arteries)
Lumped Parameter Model Details
© 2011 ANSYS, Inc. October 24, 201112
The Westerhof Circuit in Simplorer
© 2011 ANSYS, Inc. October 24, 201113
0.00 2.00 4.00 6.00 8.00 10.00 12.00 0.00
100.00
200.00
300.00
400.00
500.00
mag
(1/E
1.I)
Ansoft LLC total input imedance magnitudeCurve Info
mag(1/E1.I)AC
Impedance Comparison
Westerhof Model Simplorer Model(Inverted L Network)
0.00 2.00 4.00 6.00 8.00 10.00 12.00F [kHz]
-75.00
-50.00
-25.00
0.00
25.00
-ang
_deg
(E1.
I) [d
eg]
Ansoft LLC total input imedance phaseCurve Info-ang_deg(E1.I)
AC
© 2011 ANSYS, Inc. October 24, 201114
Insert FLUENT into the Simplorer HBM
© 2011 ANSYS, Inc. October 24, 201115
The Windkessel boundary condition was applied to an idealized representation of the abdominal aorta. Transient values for the inlet flow rate and outlet pressures were culled from a literature source*. The geometry and boundary conditions were symmetric in this case. As seen in the figure on the right, there was excellent agreement between published and computational results for the outlet pressure.
Qin
Pout
Iliac RCR parameters
RD = 3.22 mm Hg-s/cc
R = 0.55 mm Hg-s/cc
C = 0.001 cc/mm Hg
* Wan et al. (preprint)
Outlet pressure from SI[mplorerr compared well with the results of Taylor
Validation‐ Flow Past a Symmetric Bifurcation
© 2011 ANSYS, Inc. October 24, 201116
A Non‐Symmetric Case
velocity
pressure
© 2011 ANSYS, Inc. October 24, 201117
Types of Human Body Models
Application areas:• Coronary stents• Peripheral stents• Artificial organs
Application areas:• Orthopaedic implants• Exercise equipment
Application areas:• Transdermal• Inhalers• Oral• Intrathecal
CARDIOVASCULAR DRUG DELIVERYMUSCULOSKELETAL
Human Body Modeling
• CFD, FEA, and emagmodels coupled to lumped parameter representations of the human body
Parametric System Level
• DOE for HBM• Fully automated process
EMAG
Application areas:• Medical imaging• Cardiology• Drug delivery• Cancer treatments
© 2011 ANSYS, Inc. October 24, 201118
Anybody for Implant Loads
AnyBody: Determine spine kinematics
ANSYS: FEM analysis of a
spine implant based on the
spine kinematics
AnyBody provides a detailed description of the loads and joint forces occurring in the human body in daily activity. ANSYS Mechanical can import loads from Anybody,
providing critical information for testing orthopaedic implants and the like.
© 2011 ANSYS, Inc. October 24, 201119
Medical images
CAD/Mesh Finite Element Analysis
FEA loads for activities of daily living
Musculoskeletal Simulation
Optimization
Activities of daily living
Orthopaedic Workflow
© 2011 ANSYS, Inc. October 24, 201120
Activities of daily living
Boundary conditionsPatient
information
FE-model
Functional Patient‐Specific Modeling
© 2011 ANSYS, Inc. October 24, 201121
Unique Open Body Model Library
© 2011 ANSYS, Inc. October 24, 201122
Daily Activity Analysis
© 2011 ANSYS, Inc. October 24, 201123
Dynamic Physiologic Loads
© 2011 ANSYS, Inc. October 24, 201124
Thielen et al. 2009
In vivo validation‐ Hip forces
© 2011 ANSYS, Inc. October 24, 201125
A Hip Simulator
video from: http://edp.tkk.fi/en/research/tribology/research_projects/biotribology/
© 2011 ANSYS, Inc. October 24, 201126 Upper fig: Calonius and Saikko, Acta Polytechnica (2003)
waveforms whole head patterns flattened patterns
- Slide tracks represent the relative motion of the ball and cup
Slide tracks on the head are determined by mounting pens to fixed points on the cup and vice versa for slide tracks on the cup.
Lower fig: Calonius and Saikko, J Biomech (2002)
Slide Track Patterns
© 2011 ANSYS, Inc. October 24, 201127
Variation in Slide Track Patterns
© 2011 ANSYS, Inc. October 24, 201128
-27
-17
-7
3
13
23
2.84 3.84 4.84
Ang
le in
Deg
rees
Time (S)
HipAbduction
HipFlexion
HipExternalRotation
Walking
Model Inputs
Geometry • Femur and implant provided in STL format
• Acetabular cup was created in ANSYS Mechanical
-20
0
20
40
60
80
100
120
140
0 0.5 1
Flexion
Abduction
Ext. Rotation
Cycling
Initial STL geometry Implant and cup assembly
• Kinematic joint conditions provided by AnyBody:
dhead = 20 mmdcup = 22 mm
© 2011 ANSYS, Inc. October 24, 201129
Implementation
Geometry• Head, cup (rigid), and stem
Material properties• Default material properties used for all parts
Boundary Conditions• Angular data entered as displacement BC’s for the cup in tabular format
Solver• ANSYS Mechanical 12.1 transient solver• Rigid‐flexible contact maintained between the head and the cup
Post‐processing• Slide tracks are calculated using an APDL script which is inserted as a command object
cup
headstem
© 2011 ANSYS, Inc. October 24, 201130
Creating Slide Tracks using APDL
Choose location of the “pen”
Get the node number for the pen location
Track the node during the transient cycle
Report (x,y,z) vs time for the node at the end of simulation
Use point locations to create keypoints
Join keypoints to form a spline
Display the spline with initial geometry to see the slide tracks
© 2011 ANSYS, Inc. October 24, 201131
Slide Tracks on the Cup‐Walking Profile
Side of cup Top of cup
© 2011 ANSYS, Inc. October 24, 201132
Slide Tracks on the Cup‐ Cycling Profile
Side of cup Top of cup
© 2011 ANSYS, Inc. October 24, 201133
-1500
-1000
-500
0
500
1000
1500
2000
2500
3000
3500
2 2.2 2.4 2.6 2.8 3 3.2
MediolateralForce ProximoDistalForce
AnteroPosteriorForce
29
5064
6987
Force vs time data
Slide track with time-step locations
Slide Tracks on the Cup‐Walking Forces
© 2011 ANSYS, Inc. October 24, 201134
-1500
-1000
-500
0
500
1000
1500
2000
2500
3000
3500
2 2.2 2.4 2.6 2.8 3 3.2
MediolateralForce ProximoDistalForce
AnteroPosteriorForce
147
168182
187205
Force vs time data
Slide track with time-step locations
Slide Tracks on the Cup‐Walking Forces
© 2011 ANSYS, Inc. October 24, 201135
Slide Tracks on the Cup‐ Kinematics
Side of cup Top of cup
© 2011 ANSYS, Inc. October 24, 201136
Archard’s Law defines the effect of sliding distance (v) and contact pressure () on the per cycle wear depth (w):
Which can be approximated as:
• where,– kw is the wear coef. (which is material and surface dependent) = 1.066E‐6
– is the contact stress, and– S is the sliding distance
dttvtkwcycle
),,(),,(),(
cycle
w Skw
Wear Calculation
© 2011 ANSYS, Inc. October 24, 201137
Cumulative Wear(after 1 cycle)
walking cycling
wear depth reported in (mm)
© 2011 ANSYS, Inc. October 24, 201138
Hall et al (Proc Instn Mech Engrs, 1998) measured wear of UHMWPE acetabular components retrieved from 200 patients.
Validation‐ Clinical Data
© 2011 ANSYS, Inc. October 24, 201139
Types of Human Body Models
Application areas:• Coronary stents• Peripheral stents• Artificial organs
Application areas:• Transdermal• Inhalers• Oral• Intrathecal
CARDIOVASCULAR DRUG DELIVERYMUSCULOSKELETAL
Human Body Modeling
• CFD, FEA, and emagmodels coupled to lumped parameter representations of the human body
Parametric System Level
• DOE for HBM• Fully automated process
EMAG
Application areas:• Medical imaging• Cardiology• Drug delivery• Cancer treatments
Application areas:• Orthopaedic implants• Exercise equipment
© 2011 ANSYS, Inc. October 24, 201140
Pharmacokinetic (PK) Modeling
• PK models utilize a compartmentalized approach to model drug distribution in the body over time. The compartments represent organs and other drug depots.
• PK models simulate drug/chemical:• Absorption• Distribution• Metabolism• Excretion
• Coupling the PK model to the drug delivery model enables the designer to further refine the delivery system to work together with the human body, understand dependence on patient variability, disease state, etc.
© 2011 ANSYS, Inc. October 24, 201141
The system consists of a cylindrical patch applied to the skin. The drug reservoir (in the patch) contains a mixture of drug and permeation enhancer. Diffusion is the only mode of transport out of the patch and through the skin. The far boundary of the skin is the inlet to the microcirculation, which acts as a drug sink.
• Two boundary conditions are tested at the far wall:1. zero flux condition – which
assumes the plasma is an infinite sink
2. PK condition – to account for drug build‐up in plasma
patch
skin
microcirculation
Transdermal Delivery Model
© 2011 ANSYS, Inc. October 24, 201142
Axisymmetry is assumed
Drug and enhancer are modeled as user‐defined scalars in FLUENT
A transient diffusion equation models transport through the skin and patch:
, where i = drug, permeation enhancer
iii cDtc
Kcc patchdrugskindrug ,, /skiniskinipatchipatchi cDcD ,,,,
r = 0.925 cm
50.8 m
50.8 m
patch
skin
r = 0.9 cm
• The interfacial conditions at the patch‐skin interface are continuity of flux and a partitioning (jump) condition:
, where K is the partition coefficient
Transdermal Model Details
© 2011 ANSYS, Inc. October 24, 201143
The permeation enhancer increases the drug flux through the skin. The level of enhancement is typically a function of the local enhancer concentration. Two typical situations are:
Ddrug,skin = Ddrug,0+*Cpe Kdrug,skin = Kdrug,0+*Cpe
The permeation enhancer increases the diffusivity of drug in the skin
The permeation enhancer increases drug solubility in the skin
increasing increasing
Transdermal Model Details‐ Formulation Effects
© 2011 ANSYS, Inc. October 24, 201144
Validation Case‐ Fentanyl Patch, No PK Model
0.0
0.5
1.0
1.5
2.0
2.5
0 10 20 30 40 50 60
simulation
experiment
reference
Time (hr)
Drug
Flux (µ
g cm
‐2hr
‐1)
Comparison of drug flux through lower boundary of epidermis. Initial concentration of drug and enhancer 0.06, 0.04(gm cm‐3). dt=100, ncells=58400, µ=1.8e‐4, η=0.0
0.0
0.5
1.0
1.5
2.0
2.5
0 10 20 30 40 50 60
simulation
experiment
reference
Time (hr)
Drug
Flux (µ
g cm
‐2hr
‐1)
Comparison of drug flux through lower boundary of epidermis. Initial concentration of drug and enhancer 0.06, 0.04(gm cm‐3). dt=100, ncells=58400, µ=0.0, η=19.0
flux when Ddrug=f(Cenhancer) flux when K = f(Cdrug)
Reference: Rim et al., Annals of BME, (2005)
Rim et al. examined the effect of enhancement type on drug flux. These plots compare FLUENT results to their experimental and computational results.
© 2011 ANSYS, Inc. October 24, 201145
• BC between epidermis and dermal vasculature:
)](),[ tCftlcPzcD pu
︵
• The ODE’s for the three compartment PK model are:
MOTIVATION: Understand/optimize patch performance by including the physiologic processing of drug.
)()()(][
)](),[
33312221
1312
tCktCktCkkk
tCftlcdtdC
pel
pup
︵
)(/)( 2212122 tCktCkdtdC p
)(/)( 3313133 tCktCkdtdC p
plasma:
well-perfused compartment:
poorly perfused compartment:
• Patch model extensions:
CFD
Mod
elP
K M
odel
Pharmacokinetic (PK) Analysis of a Fentanyl Patch
© 2011 ANSYS, Inc. October 24, 201146
• BC between epidermis and dermal vasculature:
)](),[ tCftlcPzcD pu
︵
• The ODE’s for the three compartment PK model are:
)()()(][
)](),[
33312221
1312
tCktCktCkkk
tCftlcdtdC
pel
pup
︵
)(/)( 2212122 tCktCkdtdC p
)(/)( 3313133 tCktCkdtdC p
plasma:
well-perfused compartment:
poorly perfused compartment:
• Patch model extensions:
Pharmacokinetic (PK) Analysis of a Fentanyl Patch
MOTIVATION: Understand/optimize patch performance by including the physiologic processing of drug.
CFD
Mod
elP
K M
odel
© 2011 ANSYS, Inc. October 24, 201147
Types of Human Body Models
Application areas:• Coronary stents• Peripheral stents• Artificial organs
Application areas:• Transdermal• Inhalers• Oral• Intrathecal
CARDIOVASCULAR DRUG DELIVERYMUSCULOSKELETAL
Human Body Modeling
• CFD, FEA, and emagmodels coupled to lumped parameter representations of the human body
Parametric System Level
• DOE for HBM• Fully automated process
EMAG
Application areas:• Medical imaging• Cardiology• Drug delivery• Cancer treatments
Application areas:• Orthopaedic implants• Exercise equipment
© 2011 ANSYS, Inc. October 24, 201148
HFSS‐Workbench Link for Modeling Cancer Treatment
Hyperthermia cancer treatment used to accelerate effects of chemotherapy
RF power applied to tumor using phased array antenna• Eight strip dipole antennas connected in parallel pairs and printed on inner surface of cylindrical plastic shell
MRI Cross Section of Lower Leg with Tumor (Courtesy Duke University Medical Center)
HFSS Model of Patient with Phased Array Applicator on Lower Leg
© 2011 ANSYS, Inc. October 24, 201149
HFSS Model of RF Phased Array Applicator
Device operates at 138 MHz• Element excitations optimized to concentrate power inside tumor
HFSS Model of Applicator on Leg Tumor (shown in green)HFSS Model of RF Phased Array
Applicator
Electric Field Magnitude with Optimized Array Weights
Local Specific Absorption Rate (SAR) with Optimized Array Weights
© 2011 ANSYS, Inc. October 24, 201150
Transient Thermal Analysis in ANSYS Workbench
• Electromagnetic power is a function of time
– 28 W used to reach desired temperature and 9 W to maintain temperature
• Transient analysis used to determine temperature rise inside tumor
– Reaches 47° C in 6 minutes and is maintained there for 14 minutes
Geometry in ANSYS Workbench
Results of Transient Thermal Analysis(max/min temperature in the tumor)
Results of Transient Thermal Analysis
© 2011 ANSYS, Inc. October 24, 201151
Closing Remarks
Coupling detailed simulations to lumped parameter models can provide more rigorous prediction of device performance.
© 2011 ANSYS, Inc. October 24, 201152
Closing Remarks
Coupling detailed simulations to lumped parameter models can provide more rigorous prediction of device performance.
V&V is possible.
0.0
0.5
1.0
1.5
2.0
2.5
0 10 20 30 40 50 60
simulation
experiment
reference
Time (hr)
Drug
Flux (µ
g cm
‐2hr
‐1)
, µ , η
Pout
© 2011 ANSYS, Inc. October 24, 201153
Closing Remarks
ANSYS provides flexible and open solutions that can be adapted to solve even the most challenging problems facing the biomedical engineers of today.
The ANSYS vision for this industry includes collaborating with other software vendors to enable one‐way and/or cosimulationwith the highest fidelity models available.