Ultrasound measurements on tissue Penny Probert Smith Institute of Biomedical Engineering Department of Engineering Science University of Oxford (also Professors Alison Noble, Harvey Burd; Dr Fares Mayia, Russ Shannon Chris Haw, Emma Crowley, Jon Dennis)

Mechanical model of tissue  Viscoelastic properties  Non-linear  Almost incompressible  G,E<<K Kelvin or Voigt model Maxwell Model

Why ultrasound?  Possibility of in-vivo measurements  Compared with MRI: Cheaper Faster (so possibility of measurements during muscle action) BUT LESS ACCURATE

Propagation of ultrasound in tissue Relevant 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

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

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

Compression measurements on fish muscle To assess lipid content Mixture rule: relates volume fraction, x, to changes in material properties e.g. velocity

Experimental rig sample TXRX

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 Speed of sound

Fat content (from chemical analysis) Speed of sound But not so good in tissue..

Causes of error in samples Region of muscle Region of fat (myosepta) Structure Shape and orientation Loading: 0.2% compressive strain - but hard to judge 0% strain Specimen preparation: Degassing – air bubbles have huge effect

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

Measuring shear velocity – the eye lens Low frequency vibration excites shear wave Time of flight measurement gives velocity Pressure from motor? Time dependent effects? Oscilloscope

For eye lens..  High attenuation at ultrasound frequencies  Mechanical (or low frequency) wave excitation Results compare well with other estimates (spinning lens, deformation)

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

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

Soft tissue biomechanics Elasticity imaging P = P 0 P = P 0 +P Window Length Beam Width Sample Volume … v v Prof. Alison Noble

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)

Strain estimation Ultrasound image Strain estimation (from embedded heat source) Based on coherent (r.f.) ultrasound data

Strain imaging – pilot study results Fibroadenoma Blue=high strain “ok” Red =low strain “suspect” DCIS Cancer Cyst Prof. Alison Noble

Tendon elastography Revell et al, IEEE Trans Medical Imaging, /Digitalmedia/cve/invivo.html Uses B-mode image; tracks speckle pattern

BUT..  Inverse problem (local strain to elastic constants) very hard to solve  Effect of surrounding tissue  Orientation – limited number of ultrasound windows

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

Shear measurements on muscles Differential movement Hoyt et al, 2008 Muscle Shear modulus (relaxed) Shear modulus (contracted) Rectus femoris 5.87kPa 11.17kPa Biceps brachii

ARFI (Acoustic Radiation Force) imaging ‘ Pushing pulse’ acting locally – can be high frequency for good focal volume control. Longitudinal wave Excites shear wave High speed image acquisition to capture shear velocity Adapted from Melodelima et al, Ultrasound in Medicine & Biology Volume 32, Issue 3Ultrasound in Medicine & Biology Volume 32, Issue 3, March 2006, Pages ‘ pushing pulse’ Tissue

Shearwave generation With thanks to Chris Haw, Alison Noble

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