ultrasound measurements on tissue penny probert smith institute of biomedical engineering department...
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Ultrasound measurements on tissue
Penny Probert SmithInstitute of Biomedical EngineeringDepartment of Engineering Science University of Oxford
(also Professors Alison Noble, Harvey Burd; Dr Fares Mayia, Russ ShannonChris Haw, Emma Crowley, Jon Dennis)
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Mechanical model of tissue
Viscoelastic properties
Non-linear Almost incompressible G,E<<K
)1(2
EG
)21(3
EK
Kelvin or Voigt model
Maxwell Model
GE 3;5.0
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Why ultrasound?
Possibility of in-vivo measurements Compared with MRI:
Cheaper Faster (so possibility of measurements
during muscle action)
BUT LESS ACCURATE
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Propagation of ultrasound in tissueRelevant material properties
Wave propagation velocity depends mainly on elasticity, density:
Independent of frequency
Attenuation (longitudinal and transverse waves) depends on shear viscosity Also frequency dependent BUT also affected by scattering
Multimode operation
sec/mU
c
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Spectral response
Stokes-Navier eqn inherently non-linear; normally make linear assumption Reasonable assumption for propagation in water Poor assumption in tissue – exploited in e.g.
harmonic imaging. Non-linearity coefficient: B/A
proportion of second to first harmonic excited Depends on tissue composition, orientation Can measure through taking spectrum of echo
signals
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Measurements
Compression, shear velocity measurements – ex vivo Leads to estimation of K,G
Elastography (in-vivo) Strain visualisation
Shear elastography (in- vivo) Leads to estimation of G
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Compression measurements on fish muscle
To assess lipid content
22
21
2
)1(1
c
x
c
x
c
Mixture rule: relates volume fraction, x , to changes in material propertiese.g. velocity
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Experimental rig
sample
flightoftime
LLvelocity calibratesample TX RX
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Correlation with tissue composition
High repeatability in measurement system Good repeatability and correlation with elastic properties
in phantom (normally a gel) or water
Height of water column
Spe
ed o
f so
und
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Fat content (from chemical analysis)
Spe
ed o
f so
und
But not so good in tissue ..
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Causes of error in samples
Region of muscle Region of fat (myosepta)
Structure
Shape and orientationLoading: 0.2% compressive strain - but hard to judge 0% strain
Specimen preparation: Degassing – air bubbles have huge effect
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Velocities in other tissues
Important issue in ultrasound imaging
Fat composition very important Data mixed; poor repeatability
between different people/tissues In-vivo the fat layer causes most
distortion
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Measuring shear velocity – the eye lens
Low frequency vibration excites shear waveTime of flight measurement gives velocity
Pressure from motor? Time dependent effects?
Oscilloscope
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For eye lens ..
High attenuation at ultrasound frequencies Mechanical (or low frequency) wave excitation
Results compare well with other estimates(spinning lens, deformation)
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In-vivo methods
Can monitor the tendon/muscle etc in use and under different (real) loading
Limited in ultrasound windows Signal may be affected by other tissue – eg
fat layer Possible to probe particular parts of the
anatomy
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Elastography
Ultrasound modality becoming standard Designed for in-vivo use – used mainly in
tumour detection Measures tissue displacement – either
through B-mode or r.f. image
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Soft tissue biomechanics Elasticity imaging
P = P0
P = P0+P
Window
Length
Beam Width
Sample Volume
…
vv
Prof. Alison Noble
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Measurements of tissue strain .. in-vivo
No absolute measure of length Measure changes at different strains Correlation of successive traces
Displacement from strain (induced by temperature change in this case)
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Strain estimation
Ultrasound image Strain estimation
(from embedded heat source)
Based on coherent (r.f.) ultrasound data
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Strain imaging – pilot study results
Fibroadenoma
Blue=high strain “ok”
Red =low strain “suspect”
DCIS
CancerCyst
Prof. Alison Noble
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Tendon elastography
Revell et al, IEEE Trans Medical Imaging, 24 6 2006http://www.cs.bris.ac.uk/Research/Digitalmedia/cve/invivo.html
Uses B-mode image; tracks speckle pattern
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BUT ..
Inverse problem (local strain to elastic constants) very hard to solve
Effect of surrounding tissue Orientation – limited number of
ultrasound windows
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Shear measurements
Generate a low frequency shear wave Through differential movement Through interference pattern from two
transducers From ‘pushing pulse’
Watch propagation of wave with hgih frequency ultrasound
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Shear measurements on musclesDifferential movement
Hoyt et al, 2008
Muscle Shear modulus (relaxed) Shear modulus (contracted)Rectus femoris 5.87kPa 11.17kPaBiceps brachii 6.09 8.42
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ARFI (Acoustic Radiation Force) imaging
‘Pushing pulse’ acting locally – can be high frequency for good focal volume control. Longitudinal wave
Excites shear waveHigh speed image acquisition to capture shear velocity
Adapted from Melodelima et al,Ultrasound in Medicine & Biology
Volume 32, Issue 3, March 2006, Pages 387-396 ‘pushing pulse’
Tissue
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Shearwave generation
With thanks to Chris Haw, Alison Noble
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Conclusions
Ex-vivo Holding tissue – end effects? Artificial loading conditions Effect of neighbouring structure
In-vivo Quantitative shear measurements Displays of compression Possibility of measuring under real loading Limitation of viewing windows