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Related Experiment Videos

Exploiting Ballou's rule for better tissue classification.

Johannes Kvam1, Sverre Holm2, Bjørn A J Angelsen1

  • 1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, P.O. Box 8905, N-7489, Trondheim, Norway.

The Journal of the Acoustical Society of America
|May 4, 2019
PubMed
Summary

Ultrasound tissue characterization using the coefficient of nonlinearity (βn) shows diagnostic potential. New research reveals this coefficient is linked to compressibility, suggesting a combined nonlinear pressure response (βp) is beneficial for tissue analysis.

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Area of Science:

  • Medical physics
  • Acoustics
  • Biomedical engineering

Background:

  • Ultrasound tissue characterization utilizes the coefficient of nonlinearity (βn), which varies significantly with tissue structure.
  • This coefficient (βn = 1 + B/2A) is sensitive to tissue properties but is also correlated with speed of sound and density.

Purpose of the Study:

  • To analyze the empirical and theoretical relationships between the coefficient of nonlinearity and tissue properties.
  • To investigate the potential benefit of estimating the nonlinear pressure response (βp) for improved tissue characterization.

Main Methods:

  • Developed a thermodynamic model and used the Mie intermolecular potential to create a pressure-density relation.
  • Analyzed empirical and theoretical correlations between the coefficient of nonlinearity, speed of sound, density, and compressibility.

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Main Results:

  • The study found that isentropic compressibility (κs) largely determines the coefficient of nonlinearity in many soft tissues.
  • Established a relationship where the nonlinear pressure response (βp = βnκs) is influenced by correlated quantities.

Conclusions:

  • The coefficient of nonlinearity is significantly influenced by tissue compressibility.
  • Estimating the combined nonlinear pressure response (βp) offers a potentially beneficial approach for ultrasound-based tissue characterization due to inherent correlations.