On System-Dependent Sources of Uncertainty and Bias in Ultrasonic Quantitative Shear-Wave Imaging
Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound...
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Published in | IEEE transactions on ultrasonics, ferroelectrics, and frequency control Vol. 63; no. 3; pp. 381 - 393 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.03.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 0885-3010 1525-8955 1525-8955 |
DOI | 10.1109/TUFFC.2016.2524260 |
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Abstract | Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error <; 3% can be expected. |
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AbstractList | Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error <; 3% can be expected. Ultrasonic quantitative shear wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system dependent parameters in ultrasound shear wave speed (SWS) measurements. Each of the eight sources of error are discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2D acoustic propagation simulations and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over an ROI is employed to reduce the sources of uncertainty, a SWS error < 3% can be expected. Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error [Formula Omitted] can be expected. Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error can be expected. Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error can be expected.Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system-dependent parameters in ultrasound shear-wave speed (SWS) measurements. Each of the eight sources of error is discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2-D acoustic propagation simulations, and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency (PRF) and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear-wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over a region of interest (ROI) is employed to reduce the sources of uncertainty, an SWS error can be expected. |
Author | Nightingale, Kathryn R. Palmeri, Mark L. Rouze, Ned C. Yufeng Deng |
Author_xml | – sequence: 1 surname: Yufeng Deng fullname: Yufeng Deng email: yufeng.deng@duke.edu organization: Dept. of Biomed. Eng., Duke Univ., Durham, NC, USA – sequence: 2 givenname: Ned C. surname: Rouze fullname: Rouze, Ned C. email: ned.rouze@duke.edu organization: Dept. of Biomed. Eng., Duke Univ., Durham, NC, USA – sequence: 3 givenname: Mark L. surname: Palmeri fullname: Palmeri, Mark L. email: mark.palmeri@duke.edu organization: Dept. of Biomed. Eng., Duke Univ., Durham, NC, USA – sequence: 4 givenname: Kathryn R. surname: Nightingale fullname: Nightingale, Kathryn R. email: kathy.nightingale@duke.edu organization: Dept. of Biomed. Eng., Duke Univ., Durham, NC, USA |
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Snippet | Ultrasonic quantitative shear-wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating... Ultrasonic quantitative shear wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating... |
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SubjectTerms | Abdomen - diagnostic imaging Acoustics Algorithms Analytical models Bias Frequency measurement Humans Image Processing, Computer-Assisted - methods Imaging Measurement uncertainty Models, Biological Phantoms, Imaging Ultrasonic imaging Ultrasonography - methods Uncertainty |
Title | On System-Dependent Sources of Uncertainty and Bias in Ultrasonic Quantitative Shear-Wave Imaging |
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