Literature DB >> 24726800

Scatterer number density considerations in reference phantom-based attenuation estimation.

Nicholas Rubert1, Tomy Varghese2.   

Abstract

Attenuation estimation and imaging have the potential to be a valuable tool for tissue characterization, particularly for indicating the extent of thermal ablation therapy in the liver. Often the performance of attenuation estimation algorithms is characterized with numerical simulations or tissue-mimicking phantoms containing a high scatterer number density (SND). This ensures an ultrasound signal with a Rayleigh distributed envelope and a signal-to-noise ratio (SNR) approaching 1.91. However, biological tissue often fails to exhibit Rayleigh scattering statistics. For example, across 1647 regions of interest in five ex vivo bovine livers, we obtained an envelope SNR of 1.10 ± 0.12 when the tissue was imaged with the VFX 9L4 linear array transducer at a center frequency of 6.0 MHz on a Siemens S2000 scanner. In this article, we examine attenuation estimation in numerical phantoms, tissue-mimicking phantoms with variable SNDs and ex vivo bovine liver before and after thermal coagulation. We find that reference phantom-based attenuation estimation is robust to small deviations from Rayleigh statistics. However, in tissue with low SNDs, large deviations in envelope SNR from 1.91 lead to subsequently large increases in attenuation estimation variance. At the same time, low SND is not found to be a significant source of bias in the attenuation estimate. For example, we find that the standard deviation of attenuation slope estimates increases from 0.07 to 0.25 dB/cm-MHz as the envelope SNR decreases from 1.78 to 1.01 when estimating attenuation slope in tissue-mimicking phantoms with a large estimation kernel size (16 mm axially × 15 mm laterally). Meanwhile, the bias in the attenuation slope estimates is found to be negligible (<0.01 dB/cm-MHz). We also compare results obtained with reference phantom-based attenuation estimates in ex vivo bovine liver and thermally coagulated bovine liver.
Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Attenuation; Envelope signal-to-noise ratio; Liver; Multi-taper; Reference phantom; Scatterer number density; Thermal ablation

Mesh:

Year:  2014        PMID: 24726800      PMCID: PMC4178544          DOI: 10.1016/j.ultrasmedbio.2014.01.022

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  43 in total

1.  Time-domain calculation of spectral centroid from backscattered ultrasound signals.

Authors:  Hyungsuk Kim; Seo Weon Heo
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2012-06       Impact factor: 2.725

2.  An investigation of the use of transmission ultrasound to measure acoustic attenuation changes in thermal therapy.

Authors:  Neeta Parmar; Michael C Kolios
Journal:  Med Biol Eng Comput       Date:  2006-06-10       Impact factor: 2.602

3.  Attenuation estimation using spectral cross-correlation.

Authors:  Hyungsuk Kim; Tomy Varghese
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2007-03       Impact factor: 2.725

4.  Dependence of ultrasonic attenuation on bone mass and microstructure in bovine cortical bone.

Authors:  Magali Sasso; Guillaume Haïat; Yu Yamato; Salah Naili; Mami Matsukawa
Journal:  J Biomech       Date:  2007-10-29       Impact factor: 2.712

5.  Evaluation of the impact of backscatter intensity variations on ultrasound attenuation estimation.

Authors:  Eenas A Omari; Tomy Varghese; Ernest L Madsen; Gary Frank
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

6.  Ultrasound attenuation estimation in soft tissue using the entropy difference of pulsed echoes between two adjacent envelope segments.

Authors:  H S Jang; T K Song; S B Park
Journal:  Ultrason Imaging       Date:  1988-10       Impact factor: 1.578

7.  Ultrasonic attenuation and absorption in liver tissue.

Authors:  K J Parker
Journal:  Ultrasound Med Biol       Date:  1983 Jul-Aug       Impact factor: 2.998

8.  Method of data reduction for accurate determination of acoustic backscatter coefficients.

Authors:  E L Madsen; M F Insana; J A Zagzebski
Journal:  J Acoust Soc Am       Date:  1984-09       Impact factor: 1.840

9.  Simultaneous backscatter and attenuation estimation using a least squares method with constraints.

Authors:  Kibo Nam; James A Zagzebski; Timothy J Hall
Journal:  Ultrasound Med Biol       Date:  2011-10-02       Impact factor: 2.998

10.  Quantitative assessment of in vivo breast masses using ultrasound attenuation and backscatter.

Authors:  Kibo Nam; James A Zagzebski; Timothy J Hall
Journal:  Ultrason Imaging       Date:  2013-04       Impact factor: 1.578

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  3 in total

1.  Low Variance Estimation of Backscatter Quantitative Ultrasound Parameters Using Dynamic Programming.

Authors:  Zara Vajihi; Ivan M Rosado-Mendez; Timothy J Hall; Hassan Rivaz
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2018-09-12       Impact factor: 2.725

2.  Evaluation of ultrasonic scattering in agar-based phantoms using 3D printed scattering molds.

Authors:  Antria Filippou; Christakis Damianou
Journal:  J Ultrasound       Date:  2022-01-08

3.  Analysis of Coherent and Diffuse Scattering Using a Reference Phantom.

Authors:  Ivan M Rosado-Mendez; Lindsey C Drehfal; James A Zagzebski; Timothy J Hall
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2016-03-25       Impact factor: 2.725

  3 in total

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