human body modeling with ansys software · pdf file1 © 2011 ansys, inc. october 24, 2011...

© 2011 ANSYS, Inc. October 24, 20111

Human Body Modeling with ANSYS Software

Marc Horner, Ph.D.Technical Lead, HealthcareANSYS, Inc.


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.


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






Human Body Modeling




EMAG




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


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


My Flow Patterns

speed

wall shear

pressure


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


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


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.


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


The Westerhof Circuit in Simplorer


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


Insert FLUENT into the Simplorer HBM


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


A Non‐Symmetric Case

velocity

pressure







Human Body Modeling




EMAG



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.


Medical images

CAD/Mesh Finite Element Analysis

FEA loads for activities of daily living

Musculoskeletal Simulation

Optimization

Activities of daily living

Orthopaedic Workflow


Activities of daily living

Boundary conditionsPatient

information

FE-model

Functional Patient‐Specific Modeling


Unique Open Body Model Library


Daily Activity Analysis


Dynamic Physiologic Loads


Thielen et al. 2009

In vivo validation‐ Hip forces


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


Variation in Slide Track Patterns


-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


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


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


Slide Tracks on the Cup‐Walking Profile

Side of cup Top of cup


Slide Tracks on the Cup‐ Cycling Profile



-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


-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


Slide Tracks on the Cup‐ Kinematics



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


Cumulative Wear(after 1 cycle)

walking cycling

wear depth reported in (mm)


Hall et al (Proc Instn Mech Engrs, 1998) measured wear of UHMWPE acetabular components retrieved from 200 patients.

Validation‐ Clinical Data






Human Body Modeling




EMAG




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.


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


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


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


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.


• 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


plasma:

well-perfused compartment:

poorly perfused compartment:

• Patch model extensions:

CFD

Mod

elP

K M

odel

Pharmacokinetic (PK) Analysis of a Fentanyl Patch


• BC between epidermis and dermal vasculature:

)](),[ tCftlcPzcD pu

︵

• The ODE’s for the three compartment PK model are:

)()()(][

)](),[

33312221

1312

tCktCktCkkk

tCftlcdtdC

pel

pup

︵



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






Human Body Modeling




EMAG




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


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


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


Closing Remarks

Coupling detailed simulations to lumped parameter models can provide more rigorous prediction of device performance.


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


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.

human body modeling with ansys software · pdf file1 © 2011 ansys, inc. october 24, 2011...

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