Shear wave elasticity imaging: a new ultrasonic technology of medical diagnostics

Sarvazyan, Armen; Руденко, О. В.; Swanson, Scott D.; Fowlkes, J. Brian; Emelianov, Stanislav

doi:10.1016/s0301-5629(98)00110-0

Cited by 1,554 publications

(1,159 citation statements)

References 27 publications

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“…The rate at which tissue responds to an impulsive excitation, including the speed at which shear waves propagate away from the region of excitation (ROE), can be measured to quantify the tissue's shear modulus, as originally proposed by Sarvazyan et al (1998). In contrast to elastographic strain images (Ophir et al, 1991;Hall et al, 2003;Greenleaf et al, 2003) and Acoustic Radiation Force Impulse (ARFI) images ) that show relative structural stiffness compared with adjacent tissues, the ability to quantify an absolute tissue modulus will be useful for different clinical applications.…”

Section: Introductionmentioning

confidence: 99%

Quantifying Hepatic Shear Modulus In Vivo Using Acoustic Radiation Force

Palmeri

Wang

Dahl

et al. 2008

Ultrasound in Medicine & Biology

623

510

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The speed at which shear waves propagate in tissue can be used to quantify the shear modulus of the tissue. As many groups have shown, shear waves can be generated within tissues using focused, impulsive, acoustic radiation force excitations, and the resulting displacement response can be ultrasonically tracked through time. The goals of the work herein are two-fold: first, to develop and validate an algorithm to quantify shear wave speed from radiation force-induced, ultrasonicallydetected displacement data that is robust in the presence of poor displacement signal-to-noise ratio (SNR), and second, to apply this algorithm to in vivo datasets acquired in human volunteers in order to demonstrate the clinical feasibility of using this method to quantify the shear modulus of liver tissue in longitudinal studies. The ultimate clinical application of this work is non-invasive quantification of liver stiffness in the setting of fibrosis and steatosis.In the proposed algorithm, time to peak (TTP) displacement data in response to impulsive acoustic radiation force outside the region of excitation (ROE) are used to characterize the shear wave speed of a material, which is used to reconstruct the material's shear modulus. The algorithm is developed and validated using finite element method (FEM) simulations. Using this algorithm on simulated displacement fields, reconstructions for materials with shear moduli (μ) ranging from 1.3-5 kPa are accurate to within 0.3 kPa, while stiffer shear moduli ranging from 10-16 kPa are accurate to within 1.0 kPa. Ultrasonically tracking the displacement data, which introduces jitter in the displacement estimates, does not impede the use of this algorithm to reconstruct accurate shear moduli.Using in vivo data acquired intercostally in 20 volunteers with body mass indices (BMI) ranging from normal to obese, liver shear moduli have been reconstructed between 0.9 and 3.0 kPa, with an average precision of ±0.4 kPa. These reconstructed liver moduli are consistent with those reported in the literature (μ = 0.75-2.5 kPa) with a similar precision (±0.3 kPa). Repeated intercostal liver shear modulus reconstructions were performed on 9 different days in 2 volunteers over a 105 day period, yielding an average shear modulus of 1.9 ± 0.50 kPa (1.3-2.5 kPa) in the first volunteer, and 1.8 ± 0.4 kPa (1.1-3.0 kPa) in the second volunteer. The simulation and in vivo data to date demonstrate that this method is capable of generating accurate and repeatable liver stiffness measurements and appears promising as a clinical tool for quantifying liver stiffness.

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Section: Introductionmentioning

confidence: 99%

Quantifying Hepatic Shear Modulus In Vivo Using Acoustic Radiation Force

Palmeri

Wang

Dahl

et al. 2008

Ultrasound in Medicine & Biology

623

510

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“…A higher tagging frequency would also hold the approximation in Eq. [5] valid. Equation [5] shows that the resulting SENC image depends on the difference between the tuning frequency and the local spatial frequency, which depends on the local compression of tissue.…”

Section: Senc-tuned Imagingmentioning

confidence: 97%

“…[5] valid. Equation [5] shows that the resulting SENC image depends on the difference between the tuning frequency and the local spatial frequency, which depends on the local compression of tissue. The tuned image, therefore, shows not only a conventional MRI image that depicts morphology, but also the distribution of tissue frequency.…”

Section: Senc-tuned Imagingmentioning

confidence: 97%

“…As shown in Eq. [5], the selection of a tuning frequency will enhance regions in the resulting image, where local frequencies match this tuning frequency.…”

Section: Senc-tuned Imagingmentioning

confidence: 99%

“…To overcome these limitations, other techniques have been suggested to image the distribution of a tissue's mechanical properties, such as elasticity (2). Ultrasound has been used to measure tissue displacement associated with externally applied compressive and cyclic force (2)(3)(4)(5). MRI is another modality used to image elasticity in what is called MR elastography (MRE) (7)(8)(9)(10)(11)(12)(13)(14)(15)(16).…”

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confidence: 99%

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Detecting stiff masses using strain‐encoded (SENC) imaging

Osman

2003

Magnetic Resonance in Med

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A method is proposed for detecting stiff masses using strainencoded (SENC) magnetic resonance imaging (MRI). An object of interest is compressed to produce local strain distribution that depends on local elasticity, where intensities correlate with the local through-imaging-plane strain component. Because the strain is lower inside a stiff mass than in the surrounding soft tissue, an intensity contrast in the resulting images would enable direct detection of the mass without postprocessing. The technique was validated by a phantom experiment in which a gel phantom with a stiff region was used. The advantages of the proposed method include short imaging time and uncomplicated postprocessing. However, in its current form the technique does not measure elasticity.Magn Reson Med 49: 605-608, 2003.

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MR imaging of shear waves generated by focused ultrasound

Felmlee

Greenleaf

et al. 2000

Magn. Reson. Med.

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This study has shown that magnetic resonance elastography (MRE) can detect shear waves excited by focused ultrasound (FUS) in both gel phantoms and ex vivo muscle. Good agreement was shown between the shear modulus measured from MRE images generated using FUS and that using previously reported MRE techniques. The shear wave displacement amplitude at the FUS focus was studied and found to be proportional with both FUS ultrasonic pulse intensity and the FUS modulation pulse period over the range tested. Magn Reson Med 43:111–115, 2000. © 2000 Wiley‐Liss, Inc.

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Shear wave elasticity imaging: a new ultrasonic technology of medical diagnostics

Cited by 1,554 publications

References 27 publications

Quantifying Hepatic Shear Modulus In Vivo Using Acoustic Radiation Force

Quantifying Hepatic Shear Modulus In Vivo Using Acoustic Radiation Force

Detecting stiff masses using strain‐encoded (SENC) imaging

MR imaging of shear waves generated by focused ultrasound

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