Skip to main content

Advertisement

SpringerLink
Log in

Assessment of the frequency dependence of acoustic properties on material, composition, and scatterer size of the medium

  • Original Article–Physics & Engineering
  • Published:
Journal of Medical Ultrasonics Aims and scope Submit manuscript

Abstract

Purpose

The aim of this study was to elucidate the frequency dependence of the speed of sound (SoS) and attenuation coefficients in phantoms with controlled attenuation properties (scatterer density, scatterer size, absorption control material) and rat livers.

Methods

The frequency dependence of SoS and attenuation coefficients were evaluated with ultrasound (1–15 MHz) by observing multiple phantoms with different scatterer sizes, densities, and presence or absence of evaporated milk as absorbing media. Normal and fatty model rat livers were examined with the same protocol.

Results

The phantom results revealed that the scatterer density and SoS of the base media were the dominant factors causing the changes in SoS. Frequency dependence was not observed in SoS. Assessment of the attenuation coefficient showed that the frequency dependence was mainly affected by absorption attenuation when the scatterer was as small as a hepatocyte (i.e. ≤ 10 µm). Scattering attenuation was also observed to affect frequency dependence when the scatterer was as large as lipid droplets (i.e. ≤ 40 µm).

Conclusion

Assuming a consistent size of the main scatterers in the evaluation medium, the frequency dependence of the SoS and attenuation coefficients may provide insight into the scatterer density and the contribution of absorption and scattering attenuation. Further studies in the higher frequency band (up to about 50 MHz) are expected to advance the clinical application of high-frequency ultrasound.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Yamaguchi T. Basic concept and clinical applications of quantitative ultrasound (QUS) technologies. J Med Ultrason. 2021;48:391–402.

    Article  Google Scholar 

  2. Ophir J, Céspedes I, Ponnekanti H, et al. Elastography: A quantitative method for imaging the elasticity of biological tissues. Ultrason Imaging. 1991;13:111–34.

    Article  CAS  PubMed  Google Scholar 

  3. Harada N, Shirabe K, Ijichi H, et al. Acoustic radiation force impulse imaging predicts postoperative ascites resulting from curative hepatic resection for hepatocellular carcinoma. Surgery. 2012;151:837–43.

    Article  PubMed  Google Scholar 

  4. Zhang P, Zhou P, Tian SM, et al. Application of acoustic radiation force impulse imaging for the evaluation of focal liver lesion elasticity. Hepatobiliary Pancreat Dis Int. 2013;12:165–70.

    Article  PubMed  Google Scholar 

  5. Kitazaki T, Kondo K, Yamakawa M, et al. Shear wavelength estimation based on inverse filtering and multiple-point shear wave generation. Jpn J Appl Phys. 2016. https://doi.org/10.7567/JJAP.55.07KF10.

    Article  Google Scholar 

  6. Zhi H, Xiao XY, Ou B, et al. Could ultrasonic elastography help the diagnosis of small (≤2 cm) breast cancer with the usage of sonographic BI-RADS classification? Eur J Radiol. 2012;81:3216–21.

    Article  PubMed  Google Scholar 

  7. Choi WJ, Kim HH, Cha JH, et al. Predicting prognostic factors of breast cancer using shear wave elastography. Ultrasound Med Biol. 2014;40:269–74.

    Article  PubMed  Google Scholar 

  8. Feleppa E, Kalisz A, Sokil-Melgar JB, et al. Typing of prostate tissue by ultrasonic spectrum analysis. IEEE Trans Ultrason Ferroelectr Freq Control. 1996;43:609–19.

    Article  Google Scholar 

  9. Mamou J, Coron A, Oelze ML, et al. Three-dimensional high-frequency backscatter and envelope quantification of cancerous human lymph nodes. Ultrasound Med Biol. 2011;37:345–57.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Oelze ML, O’Brien WD, Blue JP, et al. Differentiation and characterization of rat mammary fibroadenomas and 4T1 mouse carcinomas using quantitative ultrasound imaging. IEEE Trans Med Imaging. 2004;23:764–71.

    Article  PubMed  Google Scholar 

  11. Higuchi T, Hirata S, Yamaguchi T, et al. Liver tissue characterization for each pixel in ultrasound image using multi-Rayleigh model. Jpn J Appl Phys. 2014. https://doi.org/10.7567/JJAP.53.07KF27.

    Article  Google Scholar 

  12. Igarashi Y, Ezuka H, Yamaguchi T, et al. Quantitative estimation method for liver fibrosis based on combination of Rayleigh distributions. Jpn J Appl Phys. 2010. https://doi.org/10.1143/JJAP.49.07HF06.

    Article  Google Scholar 

  13. Nakajima S, Shibuya K, Kamiyama N, et al. Comparison of ultrasound colored image views produced by application of statistical analysis of radio-frequency signals and histological findings in patients with chronic hepatitis C. J Med Ultrason. 2010;37:51–8.

    Article  Google Scholar 

  14. Ricci P, Marigliano C, Cantisani V, et al. Valutazione ecografica della fibrosi epatica: esperienza preliminare con acoustic structure quantification (ASQ). Radiol Medica. 2013;118:995–1010.

    Article  Google Scholar 

  15. Yamaguchi T, Hachiya H. Proposal of a parametric imaging method for quantitative diagnosis of liver fibrosis. J Med Ultrason. 2010;37:155–66.

    Article  Google Scholar 

  16. Yu I, Yamaguchi T, Hachiya H. Stability of quantitative evaluation method of liver fibrosis using amplitude distribution model of fibrotic liver. Jpn J Appl Phys. 2011. https://doi.org/10.7567/JJAP.50.07HF17.

    Article  Google Scholar 

  17. Fujii Y, Taniguchi N, Takano R, et al. Texture analysis with a new method in which the region of interest is segmented into multiple layers for radiofrequency amplitude histogram analysis of fibrous rat livers. J Med Ultrason. 2004;31:13–20.

    Article  Google Scholar 

  18. Kaltenbach TEM, Gruener B, Akinli AS, et al. Acoustic structure quantification (ASQ): a new tool in sonographic examination of liver lesions in hepatic alveolar echinococcosis. J Med Ultrason. 2014;41:445–53.

    Article  Google Scholar 

  19. Ghoshal G, Lavarello RJ, Kemmerer JP, et al. Ex vivo study of quantitative ultrasound parameters in fatty rabbit livers. Ultrasound Med Biol. 2012;38:2238–48.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Tamura K, Mamou J, Yoshida K, et al. Ultrasound-based lipid content quantification using double Nakagami distribution model in rat liver steatosis. Jpn J Appl Phys. 2020. https://doi.org/10.35848/1347-4065/ab918e.

    Article  Google Scholar 

  21. Sasso M, Audière S, Kemgang A, et al. Liver steatosis assessed by controlled attenuation parameter (CAP) measured with the XL probe of the fibroscan: a pilot study assessing diagnostic accuracy. Ultrasound Med Biol. 2016;42:92–103.

    Article  PubMed  Google Scholar 

  22. Audière S, Labourdette A, Miette V, et al. Improved ultrasound attenuation measurement method for the non-invasive evaluation of hepatic steatosis using fibroscan. Ultrasound Med Biol. 2021;47:3181–95.

    Article  PubMed  Google Scholar 

  23. Tamaki N, Koizumi Y, Hirooka M, et al. Novel quantitative assessment system of liver steatosis using a newly developed attenuation measurement method. Hepatol Res. 2018;48:821–8.

    Article  PubMed  Google Scholar 

  24. Weijers G, Starke A, Thijssen JM, et al. Transcutaneous vs. intraoperative quantitative ultrasound for staging bovine hepatic steatosis. Ultrasound Med Biol. 2012;38:1404–13.

    Article  PubMed  Google Scholar 

  25. Ogawa T, Yoshida K, Yamaguchi T. Speed of sound evaluation considering spatial resolution in a scanning acoustic microscopy system capable of observing wide spatial area. Jpn J Appl Phys. 2020. https://doi.org/10.35848/1347-4065/ab83da.

    Article  Google Scholar 

  26. Abe K, Arakawa M, Kanai H. Estimation method for sound velocity distribution for high-resolution ultrasonic tomographic imaging. J Med Ultrason. 2019;46:27–33.

    Article  Google Scholar 

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

    Article  PubMed  Google Scholar 

  28. Tsujimoto Y, Matsuda D, Minamiguchi K, et al. Measurement of temperature dependence of sound velocity in biological tissues. Jpn J Appl Phys. 2019. https://doi.org/10.7567/1347-4065/ab12cb.

    Article  Google Scholar 

  29. Hasegawa H, Nagaoka R. Initial phantom study on estimation of speed of sound in medium using coherence among received echo signals. J Med Ultrason. 2019;46:297–307.

    Article  Google Scholar 

  30. Goss SA, Johnston RL, Dunn F. Comprehensive compilation of empirical ultrasonic properties of mammalian tissues. J Acoust Soc Am. 1978;64:423–57.

    Article  CAS  PubMed  Google Scholar 

  31. Hachiya H, Ohtsuki S, Tanaka M. Relationship between speed of sound in and density of normal and diseased rat livers. Jpn J Appl Phys. 1994;33:3130–3.

    Article  Google Scholar 

  32. Hachiya H, Yamaguchi T. Acoustic characteristics of the tissue and the ultrasonic B-mode Image. Med Imaging Technol. 2003;21:95–100 ([in japanese]).

    Google Scholar 

  33. Irie S, Inoue K, Yoshida K, et al. Speed of sound in diseased liver observed by scanning acoustic microscopy with 80 MHz and 250 MHz. J Acoust Soc Am. 2016;139:512–9.

    Article  CAS  PubMed  Google Scholar 

  34. Strohm EM, Moore MJ, Kolios MC. Single cell photoacoustic microscopy: a review. IEEE J Sel Top Quantum Electron. 2016;22:137–51.

    Article  Google Scholar 

  35. Drakos T, Antoniou A, Evripidou N, et al. Ultrasonic attenuation of an agar, silicon dioxide, and evaporated milk gel phantom. J Med Ultrasound. 2021;29:239–49.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Drakos T, Giannakou M, Menikou G, et al. An improved method to estimate ultrasonic absorption in agar-based gel phantom using thermocouples and MR thermometry. Ultrasonics. 2020;103: 106089.

    Article  CAS  PubMed  Google Scholar 

  37. Omura M, Yoshida K, Akita S, et al. Verification of echo amplitude envelope analysis method in skin tissues for quantitative follow-up of healing ulcers. Jpn J Appl Phys. 2018. https://doi.org/10.7567/JJAP.57.07LF15.

    Article  Google Scholar 

  38. Schwartz M. Estimating the acoustic attenuation coefficient slope for liver from reflected ultrasound signals. IEEE Trans Sonics Ultrason. 1979;26:353–61.

    Article  Google Scholar 

  39. Brewin MP, Pike LC, Rowland DE, et al. The acoustic properties, centered on 20 MHZ, of an IEC agar-based tissue-mimicking material and its temperature, frequency and age dependence. Ultrasound Med Biol. 2008;34:1292–306.

    Article  CAS  PubMed  Google Scholar 

  40. Sun C, Pye SD, Browne JE, et al. The speed of sound and attenuation of an IEC agar-based tissue-mimicking material for high frequency ultrasound applications. Ultrasound Med Biol. 2012;38:1262–70.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Matsukawa M, Akimoto T, Ueba S, et al. Ultrasonic wave properties in the particle compounded agarose gels. Ultrasonics. 2002;40:323–7.

    Article  CAS  PubMed  Google Scholar 

  42. Matsukawa M, Sasaki K, Akimoto T, et al. Application of a suspension theory to particle-dispersed agarose gels. Jpn J Appl Phys. 2002;41:3163–7.

    Article  CAS  Google Scholar 

  43. Farrer AI, Odéen H, de Bever J, et al. Characterization and evaluation of tissue-mimicking gelatin phantoms for use with MRgFUS. J Ther Ultrasound. 2015;3:1–11.

    Article  Google Scholar 

  44. Inglis S, Ramnarine KV, Plevris JN, et al. An anthropomorphic tissue-mimicking phantom of the oesophagus for endoscopic ultrasound. Ultrasound Med Biol. 2006;32:249–59.

    Article  PubMed  Google Scholar 

  45. Sato T, Watanabe Y. High sensitivity estimation of red blood cell aggregation with ultrasonic peak frequency. IEEE International Ultrasonics Symposium (IUS). 2013. pp 868–71.

  46. Madsen EL, Frank GR, Dong F. Liquid or solid ultrasonically tissue-mimicking materials with very low scatter. Ultrasound Med Biol. 1998;24:535–42.

    Article  CAS  PubMed  Google Scholar 

  47. Browne JE, Ramnarine KV, Watson AJ, et al. Assessment of the acoustic properties of common tissue-mimicking test phantoms. Ultrasound Med Biol. 2003;29:1053–60.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was partly supported by JSPS Core-to-Core Program JPJSCCA20170004, and KAKENHI Grant Number 19H04482. We also acknowledge financial support from the Institute for Global Prominent Research at Chiba University.

Author information

Authors and Affiliations

  1. Graduate School of Science and Engineering, Chiba University, 1-33 Yayoicho, Inage, Chiba, 2638522, Japan

    Mai Ino

  2. Center for Frontier Medical Engineering, Chiba University, 1-33 Yayoicho, Inage, Chiba, 2638522, Japan

    Kenji Yoshida, Shinnosuke Hirata & Tadashi Yamaguchi

  3. Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei, Tokyo, 1848588, Japan

    Kazuyo Ito

  4. Singapore Eye Research Institute, Singapore National Eye Centre, Duke-NUS Medical School, The Academia, 20 College Road, Discovery Tower Level 6, Singapore, 169856, Singapore

    Kazuyo Ito

Authors
  1. Mai Ino
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kenji Yoshida
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shinnosuke Hirata
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kazuyo Ito
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tadashi Yamaguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Mai Ino or Tadashi Yamaguchi.

Ethics declarations

Conflict of interest

The authors declare that there are no conflicts of interest.

Ethical statements

All institutional and national guidelines for the care and use of laboratory animals were followed.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

10396_2022_1235_MOESM1_ESM.docx

Supplementary file1 Table 1. Phantom specifications. Table 2. Profiles and measurement/evaluation conditions of five single-element concave transducers (DOCX 37 kb)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ino, M., Yoshida, K., Hirata, S. et al. Assessment of the frequency dependence of acoustic properties on material, composition, and scatterer size of the medium. J Med Ultrasonics 49, 569–578 (2022). https://doi.org/10.1007/s10396-022-01235-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10396-022-01235-1

Keywords

Search

Navigation