2002 symposium 1

Craig Goodrich

2002 MIRL Symposium

COMPUTER SIMULATION

CAROTID

ATHEROSCLEROTIC

PLAQUE IMAGING

2002 symposium 3

Topics of Discussion

Why do a computer simulation? Carotid anatomy Atherosclerotic disease Magnetic resonance imaging Implementation of model Results

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Why do a computer simulation?

Truth standard difficult for human imaging

Animal models User determines truth with

computer model

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Arterial wall anatomy Tunica Interna

layer of endothelial cells and elastic fibers

Tunica Mediasmooth muscle cells (SMC) in framework of loose connective tissue

Tunica Externa (adventitia) connective

tissue sheath mostly collagen, with scattered elastin and SMC – blends with adjacent tissues anchoring vessel to them

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Atherosclerotic development High lipid levels in artery -> monocytes become filled

with lipids (now called foam cells) Foam cells attach to endothelium and release growth

factors causing SMC to grow. Monocytes invade, migrating between endothelial

cells. Monocytes, SMC, endothelial cells begin phagocytization of fat resulting in plaque (which projects into lumen).

Endothelial cells become swollen with lipids and gaps appear in endothelial lining. Platelets begin sticking to exposed collagen fibers which leads to clot.

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atherosclerotic disease

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Magnetic Resonance Imaging

Proton magnetic moment Precession depends on field

strength Appropriate manipulation of field

(i.e. linear field gradients) -> image Image contrast depends on proton

density, relaxation, acquisition timing

Motion degrades image quality

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Example MRA images

T1 weighted

Proton density weighted (PD)

Time-of-flight (TOF)

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20 phase/heartbeat phase contrast MRA

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Modeled anatomy

Lumen – determined from phase contrast images

Endothelium – 1 pixel layer Tunica Interna – 6 pixel layers Tunica Media - 21 pixel layers Tunica Externa – 9 pixel layers

(probably should be thicker)

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Proton Density Anatomical Computer model

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Modeling disease

Foam cells Lipid layer Fibrous

plaque Thrombus

13.5%

62% 132%

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MRI simulationusing IDL

Read imaging parametersTR, TE, K_fill, fnecho_lim, theta

Read tissue parametersT1, T2, PD

Read masks for tissue typesbackground (assume muscle)vessel wall components

Determine type of imaging sequence and call subroutine

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Spin echo subroutine1. T1 & T2 correct each tissue mask2. multiply each mask by PD3.For loop for each time phase

a) cut hole in neck mask for vessel structure b) add all tissue masks c) FFT assembled anatomy d) truncate 40962 array to 5122 array (simulates continuous -> discrete) e) store in temporary Kspace array (kx,ky,t)

4. Sequentially fill Kspace as function of TR & HR

5. Add T2* attenuation6. Inverse FFT for final image and return image

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Results

Simulatedphase artifact

Anatomy model Simulated PD images

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Future Work Determine thickening threshold for plaque detection Other contrast models

T2 weightedT1 weightedTOF

Add other anatomy (including movement) Add blood flow Add other k-space trajectories Coil sensitivities Noise, better PD, T2, T1 estimates ……….. Etc.