A new method of measuring in vivo sound speed in the reflection mode

Hayashi, Nobushige; Tamaki, Nagara; Senda, Michio; Yamamoto, Kazutaka; Yonekura, Yoshiharu; Torizuka, K.; Ogawa, Takeshi; Katakura, Kageyoshi; Umemura, Chinichiro; Kodama, M.

doi:10.1002/jcu.1870160204

Cited by 37 publications

(11 citation statements)

References 7 publications

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“…The average sound-speed estimators include techniques based on the apparent shift from two angles, 19,20 beam tracking, 21 transaxial compression, 22 phase a) Electronic mail: marko.jakovljevic@stanford.edu variance, 23 and echo arrival times at the receive aperture. [24][25][26] These methods have low accuracy in the presence of inhomogeneities, which makes them unsuitable for in vivo measurement through layers of subcutaneous fat and connective tissue. For example, the average SoS estimator by Anderson and Trahey 25 yields highly accurate estimates in homogeneous media (bias less than 0.2% and standard deviation less than 0.52%); however, in a two-layer phantom composed of water and agar-graphite, measured biases in the bottom layer exceeded 30 m/s while the standard deviation was approximately 10 m/s.…”

Section: Introductionmentioning

confidence: 99%

Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach

Jakovljevic

Hsieh

Ali

et al. 2018

The Journal of the Acoustical Society of America

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A model and method to accurately estimate the local speed of sound in tissue from pulse-echo ultrasound data is presented. The model relates the local speeds of sound along a wave propagation path to the average speed of sound over the path, and allows one to avoid bias in the sound-speed estimates that can result from overlying layers of subcutaneous fat and muscle tissue. Herein, the average speed of sound using the approach by Anderson and Trahey is measured, and then the authors solve the proposed model for the local sound-speed via gradient descent. The sound-speed estimator was tested in a series of simulation and ex vivo phantom experiments using two-layer media as a simple model of abdominal tissue. The bias of the local sound-speed estimates from the bottom layers is less than 6.2 m/s, while the bias of the matched Anderson's estimates is as high as 66 m/s. The local speed-of-sound estimates have higher standard deviation than the Anderson's estimates. When the mean local estimate is computed over a 5-by-5 mm region of interest, its standard deviation is reduced to less than 7 m/s.

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Section: Introductionmentioning

confidence: 99%

Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach

Jakovljevic

Hsieh

Ali

et al. 2018

The Journal of the Acoustical Society of America

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“…In the latter report, the mathematical deconvolution operator was used to retrieve a restored image produced by considering an ultrasound system PSF having different mean SoS values. A focusing approach based on the estimation of SoS along the wave propagation path was specifically introduced for the purpose of providing a tissue characterization signature in [ 35 ]. Conceptually, since a mean estimate along the ultrasound beam is obtained with these abovementioned methods [ 34 , 35 ], no local measure within a given ROI of an organ having inhomogeneous SoS can be produced.…”

Section: Speed Of Sound Imagingmentioning

confidence: 99%

“…A focusing approach based on the estimation of SoS along the wave propagation path was specifically introduced for the purpose of providing a tissue characterization signature in [ 35 ]. Conceptually, since a mean estimate along the ultrasound beam is obtained with these abovementioned methods [ 34 , 35 ], no local measure within a given ROI of an organ having inhomogeneous SoS can be produced. Current methods allowing local assessments or images within an ROI are based on spatial coherence [ 36 ] and image compounding [ 37 ] approaches .…”

Section: Speed Of Sound Imagingmentioning

confidence: 99%

Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists

Cloutier

Destrempes

et al. 2021

Insights Imaging

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Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.

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“…In conventional ultrasound diagnostic equipment, an assumed average speed of sound is used for delay and sum beamforming to create a B-mode image that is generated by the RF signal of each received echo line. Conversely, as proposed by Ogawa and Umemura [ 20 ] and Hayashi et al [ 21 ], it is also possible to evaluate the average speed of sound from image quality. In the focusing method, beam focusing is repeated to optimize the local image quality and evaluate the speed of sound at that time.…”

Section: Speed Of Sound Evaluationmentioning

confidence: 99%

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

Yamaguchi

2021

J Med Ultrasonics

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In the field of clinical ultrasound, the full digitalization of diagnostic equipment in the 2000s enabled the technological development of quantitative ultrasound (QUS), followed by multiple diagnostic technologies that have been put into practical use in recent years. In QUS, tissue characteristics are quantified and parameters are calculated by analyzing the radiofrequency (RF) echo signals returning to the transducer. However, the physical properties (and pathological level structure) of the biological tissues responsible for the imaging features and QUS parameters have not been sufficiently verified as there are various conditions for observing living tissue with ultrasound and inevitable discrepancies between theoretical and actual measurements. A major issue of QUS in clinical application is that the evaluation results depend on the acquisition conditions of the RF echo signal as the source of the image information, and also vary according to the model of the diagnostic device. In this paper, typical examples of QUS techniques for evaluating attenuation, speed of sound, amplitude envelope characteristics, and backscatter coefficient in living tissues are introduced. Exemplary basic research and clinical applications related to these technologies, and initiatives currently being undertaken to establish the QUS method as a true tissue characterization technology, are also discussed.

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A new method of measuring in vivo sound speed in the reflection mode

Cited by 37 publications

References 7 publications

Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach

Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach

Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

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