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Initial phantom study on estimation of speed of sound in medium using coherence among received echo signals

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Abstract

Purpose

Ultrasound beamforming is required to obtain clinical ultrasound images. In the beamforming procedure, the distance between the receiving focal point and each transducer element is determined based on the assumed speed of sound in the tissue. However, the actual speed of sound in tissue is unknown and varies depending on the tissue type. To improve the performance of an ultrasonic beamformer by evaluating its focusing quality, the coherence factor (CF) was introduced in medical ultrasound imaging. The CF may be used to estimate the speed of sound in tissue because it can identify focusing errors in beamforming. In the present study, the feasibility of CF for estimating the speed of sound was examined through phantom experiments.

Method

To evaluate the dependency of CF on the assumed speed of sound in ultrasound beamforming, beamformed ultrasonic radio frequency (RF) signals and CFs were obtained at different assumed speeds of sound. CF is highest when the assumed speed of sound matches the true speed of sound in the medium. Therefore, the speed of sound in the medium was determined as the assumed speed of sound, which gives the highest CF. The proposed method was validated in a conventional line-by-line sequence with a focused transmit beam and ultrafast plane wave imaging.

Results

A homogeneous phantom (diffuse scattering medium) with a known speed of sound of 1540 m/s was used for validating the proposed method. Beamformed ultrasonic RF signals and CFs were obtained at an assumed speed of sound from 1480 to 1600 m/s varied at a pitch of 5 m/s. In the line-by-line sequence, CF reached the maximum at an assumed speed of sound of 1525.0 m/s (0.97% difference from the true value) when CFs at all spatial points in the region of interest (ROI) were averaged. On the other hand, the speed of sound was determined to be 1528.5 m/s (0.75% difference) when CFs at spatial points with CF-weighted echo amplitudes were larger than 20% of the maximum value. In plane wave imaging, the speed of sound was estimated to be 1544.5 m/s (0.29% difference) using CFs with CF-weighted echo amplitudes larger than 20% of the maximum value.

Conclusion

The speed of sound of a homogeneous medium could be determined by the proposed method with errors of less than 1% using CFs obtained from ultrasonic echo signals selected based on the CF-weighted echo amplitudes, i.e., when echo signals with better signal-to-noise ratios (SNRs) were used.

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References

  1. O’Donnell M, Flax SW. Phase aberration measurements in medical ultrasound. Ultrason Imaging. 1988;10:1–11.

    Article  PubMed  Google Scholar 

  2. Li Y. Phase aberration correction using near-field signal redundancy. I. Principles. IEEE Trans Ultrason Ferroelectr Freq Control. 1997;44:355–71.

    Article  CAS  PubMed  Google Scholar 

  3. Fontanarosa D, van der Meer S, Harris E, et al. A CT based correction method for speed of sound aberration for ultrasound based image guided radiotherapy. Med Phys. 2011;38:2665–73.

    Article  PubMed  Google Scholar 

  4. Greenleaf JF, Johnson A, Bahn RC, et al. Quantitative crosssectional imaging of ultrasound parameters. Ultrason Symp Proc. New York, NY:IEEE; 1977. p. 989–95.

  5. Greenleaf JF, Bahn RC. Clinical imaging with transmissive ultrasonic computerized to- mography. IEEE Trans Biomed Eng. 1981;28:177–85.

    Article  CAS  PubMed  Google Scholar 

  6. Scherzinger AL, Belgam RA, Carson PL, et al. Assessment of ultrasonic computed tomography in symptomatic breast patients by discriminant analysis. Ultrasound Med Biol. 1989;15:21–8.

    Article  CAS  PubMed  Google Scholar 

  7. Li C, Duric N, Littrup P, et al. In vivo breast sound-speed imaging with ultrasound tomography. Ultrasound Med Biol. 2009;35:1615–28.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Terada T, Yamanaka K, Suzuki A, et al. Highly precise acoustic calibration method of ring-shaped ultrasound transducer array for plane-wave- based ultrasound tomography. Jpn J Appl Phys. 2017;56:07JF07.

    Article  Google Scholar 

  9. Ophir J, Yazdi Y. A transaxial compression technique (TACT) for localized pulse-echo estimation of sound speed in biological tissues. Ultrason Imaging. 1990;12:35–46.

    Article  CAS  PubMed  Google Scholar 

  10. Nitta N, Aoki T, Hyodo K, et al. Direct measurement of speed of sound in cartilage in situ using ultrasound and magnetic resonance images. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:6063–6.

    CAS  PubMed  Google Scholar 

  11. Pereira FR, Machado JC, Pereira WCA. Ultrasonic speed measurement using the time- delay profile of rf-backscattered signals: simulation and experimental results. J Acoust Soc Am. 2002;111:1445–53.

    Article  PubMed  Google Scholar 

  12. Onodera G, Taki H, Kanai H. Estimation of sound velocity distribution from time delay received at each element of ultrasonic probe. In: Proceedings of Symposium on Ultrasonic Electronics. vol. 37; 2016, p. 1P5–7.

  13. Imbault M, Faccinetto A, Osmanski B, et al. Robust sound speed estimation for ultrasound-based hepatic steatosis assess- ment. Phys Med Biol. 2017;62:3582–98.

    Article  PubMed  Google Scholar 

  14. Mallart R, Fink M. Adaptive focusing in scattering media through sound-speed inhomogeneities: the van Cittert Zernike approach and focusing criterion. J Acoust Soc Am. 1994;96:3721–32.

    Article  Google Scholar 

  15. Dahl JJ, Hyun D, Lediju M, et al. Lesion detectability in diagnostic ultrasound with short-lag spatial coherence imaging. Ultrason Imaging. 2011;33:119–33.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Lediju BMA, Goswami R, Kisslo JA, et al. Short-lag spatial coher- ence imaging of cardiac ultrasound data: initial clinical results. Ultrasound Med Biol. 2013;39:1861–74.

    Article  Google Scholar 

  17. Hollman KW, Rigby KW, O’Donnell M. Coherence factor of speckle from a multi-row probe. In: Proceedings of the IEEE Ultrasonics Symposium. IEEE; 1999, p. 1257–60.

  18. Li P, Li M. Adaptive imaging using the generalized coherence factor. IEEE Trans Ultrason Ferroelectr Freq Control. 2003;50:128–41.

    Article  PubMed  Google Scholar 

  19. Yoon C, Kang J, Han S, et al. Enhancement of photoacoustic image quality by sound speed correction: ex vivo evaluation. Opt Express. 2012;20:3082–90.

    Article  PubMed  Google Scholar 

  20. Cho S, Kang J, Kang J, et al. Phantom and in vivo evaluation of sound speed estimation methods: preliminary results. In: IEEE International Ultrasonics Symposium. Chicago, IL, USA: IEEE; 2014, p. 1678-81.

  21. Montaldo G, Tanter M, Fink M. Time reversal of speckle noise. Phys Rev Lett. 2011;106:054301.

    Article  CAS  PubMed  Google Scholar 

  22. Hasegawa H. Improvement of penetration of modified amplitude and phase estimation beamformer. J Med Ultrason. 2017;44:3–11.

    Article  Google Scholar 

  23. Hasegawa H. Improvement of range spatial resolution of medical ultrasound imaging by element-domain signal processing. Jpn J Appl Phys. 2017;56:07JF02.

    Article  Google Scholar 

  24. Mozumi M, Nagaoka R, Hasegawa H. Improvement of high range resolution imaging method by considering change in ultrasonic waveform during propagation. Jpn J Appl Phys. 2018;57:07LF23.

    Article  Google Scholar 

  25. Hasegawa H, Nagaoka R. Investigation on improvement of performance of ultrasonic beamformer. IEICE Technical Report. November 2018 (in press).

  26. Hasegawa H. Apodized adaptive beamformer. J Med Ultrason. 2017;44:155–65.

    Article  Google Scholar 

  27. Jensen J, Stuart MB, Jensen JA. Optimized plane wave imaging for fast and high-quality ultrasound imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2016;63:1922–34.

    Article  PubMed  Google Scholar 

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Acknowledgements

This study was partly supported by JSPS KAKENHI Grant number JP17H03276.

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Authors and Affiliations

  1. Graduate School of Science and Engineering, University of Toyama, Toyama, 930-8555, Japan

    Hideyuki Hasegawa & Ryo Nagaoka

Authors
  1. Hideyuki Hasegawa
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  2. Ryo Nagaoka
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Correspondence to Hideyuki Hasegawa.

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Hasegawa, H., Nagaoka, R. Initial phantom study on estimation of speed of sound in medium using coherence among received echo signals. J Med Ultrasonics 46, 297–307 (2019). https://doi.org/10.1007/s10396-019-00936-4

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  • DOI: https://doi.org/10.1007/s10396-019-00936-4

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