Comparison of theoretical scattering results and ultrasonic data from clinical liver examinations.

A theoretical analysis of soft-tissue ultrasonic scattering has been used to formulate specific results describing spectral parameters for tissue characterization. Results are applicable to clinical liver examinations. Three spectral parameters are mathematically expressed in terms of acoustic attenuation and the effective sizes, concentrations, and relative acoustic impedances of tissue scatters. Results from a clinical data base are shown to agree well with analytical results for each spectral parameter. Agreement is found for: spectral shapes; effects of attenuation; and correlations between parameters. Images of three spectral parameters are presented and their gray-scale features are evaluated with reference to analytical results.

[1]  Ernest J. Feleppa,et al.  Liver-Tissue Characterization by Digital Spectrum and Cepstrum Analysis , 1981 .

[2]  F. L. Lizzi,et al.  Power Spectra Measurements of Ultrasonic Backscatter from Ocular Tissues , 1975 .

[3]  D. Nicholas,et al.  EVALUATION OF BACKSCATTERING COEFFICIENTS FOR EXCISED HUMAN TISSUES: RESULTS, INTERPRETATION AND ASSOCIATED MEASUREMENTS , 1982 .

[4]  E. Feleppa,et al.  Focal and diffuse liver disease studied by quantitative microstructural sonography. , 1985, Radiology.

[5]  E J Feleppa,et al.  Diagnostic spectrum analysis in ophthalmology: a physical perspective. , 1986, Ultrasound in medicine & biology.

[6]  E. Feleppa,et al.  Theoretical framework for spectrum analysis in ultrasonic tissue characterization. , 1983, The Journal of the Acoustical Society of America.

[7]  E. Feleppa,et al.  Relationship of Ultrasonic Spectral Parameters to Features of Tissue Microstructure , 1987, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  P A Narayana,et al.  On the validity of the linear approximation in the parametric measurement of attenuation in tissues. , 1983, Ultrasound in medicine & biology.

[9]  J. G. Miller,et al.  The relationship between collagen and ultrasonic attenuation in myocardial tissue. , 1979, The Journal of the Acoustical Society of America.

[10]  R. F. Wagner,et al.  Pattern Recognition Methods for Optimizing Multivariate Tissue Signatures in Diagnostic Ultrasound , 1986, Ultrasonic imaging.

[11]  Kevin J. Parker,et al.  Measurement of Ultrasonic Attenuation Within Regions Selected from B-Scan Images , 1983, IEEE Transactions on Biomedical Engineering.