Reported here is a phantom-based comparison of methods for determining the power spectral density of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)=α0fβ, was estimated using a reference phantom method. The power spectral density as estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error. For parameter estimation regions larger than ~34 pulse lengths (~1cm for this experiment), an overall power-law fit error of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here the multitaper method reduced the standard deviation of the α0 and β estimates compared to those using the other techniques. Results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound.
Acoustic properties can be exploited to infer and evaluate tissue microstructure. However, common assumptions are that the medium of interest is homogeneous and isotropic, and that its underlying physical properties cause diffuse scattering. In this paper, we describe how we developed and tested novel parameters designed to address isotropy/anisotropy in backscattered echo signal power in complex biological tissues. Specifically, we explored isotropy/anisotropy in backscattered power in isotropic phantoms (spherical glass beads), an anisotropic phantom (dialysis phantom with rod-like fibers), and an in vivo human tissue with well-described anisotropy (bicep muscle). Our approach uses the Reference Phantom Method to compensate for system-transfer and diffraction losses when electronically beamsteering a linear array transducer. We define three parameters to quantify the presence and orientation of anisotropic scatterers, as well as address magnitude of anisotropy. We found that these parameters can detect and sense the degree of anisotropy in backscatter in both phantoms and bicep muscle. Bias of the summary anisotropy parameters, induced through a speed of sound mismatch of sample media and reference phantom, was less than 0.2 dB if the speed of sound was within ± 20 m/s of the sample media. In summary, these new parameters may be useful for testing the assumption of isotropy as well as providing more detailed information about the underlying microstructural sources of backscatter in complex biological tissues.
Backscatter and attenuation coefficient estimates are needed in many quantitative ultrasound strategies. In clinical applications, these parameters may not be easily obtained because of variations in scattering by tissues overlying a region of interest (ROI). The goal of this study is to assess the accuracy of backscatter and attenuation estimates for regions distal to nonuniform layers of tissue-mimicking materials. In addition, this work compares results of these estimates for “layered” phantoms scanned using different clinical ultrasound machines. Two tissue-mimicking phantoms were constructed, each exhibiting depth-dependent variations in attenuation or backscatter. The phantoms were scanned with three ultrasound imaging systems, acquiring radio frequency echo data for offline analysis. The attenuation coefficient and the backscatter coefficient (BSC) for sections of the phantoms were estimated using the reference phantom method. Properties of each layer were also measured with laboratory techniques on test samples manufactured during the construction of the phantom. Estimates of the attenuation coefficient versus frequency slope, α0, using backscatter data from the different systems agreed to within 0.24 dB/cm-MHz. Bias in the α0 estimates varied with the location of the ROI. BSC estimates for phantom sections whose locations ranged from 0 to 7 cm from the transducer agreed among the different systems and with theoretical predictions, with a mean bias error of 1.01 dB over the used bandwidths. This study demonstrates that attenuation and BSCs can be accurately estimated in layered inhomogeneous media using pulse-echo data from clinical imaging systems.
Shear Wave Elasticity Imaging (SWEI) shows promise for evaluating the pregnant cervix. Changes in shear wave group velocity have been attributed exclusively to changes in stiffness. This assumes homogeneity within the region of interest and purely elastic tissue behavior. However, the cervix is structurally/microstructurally heterogeneous and viscoelastic. We therefore developed strategies to investigate these complex tissue properties. SWEI was performed ex vivo on 14 unripened and 13 misoprostol-ripened cervix specimens from Rhesus macaques. After application of tests of significant and uniform shear wave displacement, as well as reliability of estimates, group velocity decreased significantly from the distal (vaginal) to proximal (uterine) end of unripened, but not ripened, specimens. Viscosity was quantified by the slope of the phase velocity vs. frequency. Dispersion was observed in both groups (median 5.5 m/s/kHz, interquartile range: 1.5–12.0 m/s/kHz), also decreasing towards the proximal cervix. This work suggests that comprehensive assessment of complex tissues such as cervix requires consideration of structural heterogeneity and viscosity.
In vivo estimations of the frequency-dependent acoustic attenuation (α) and backscatter (η) coefficients using radio frequency (RF) echoes acquired with clinical ultrasound systems must be independent of the data acquisition setup and the estimation procedures. In a recent in vivo assessment of these parameters in rodent mammary tumors, overall agreement was observed among α and η estimates using data from four clinical imaging systems. In some cases, particularly in highly attenuating heterogeneous tumors, multi-system variability was observed. This paper compares α and η estimates of a well-characterized rodent-tumor-mimicking homogeneous phantom scanned using 7 transducers with the same four clinical imaging systems: a Siemens Acuson S2000, an Ultrasonix RP, a Zonare Z.one, and a VisualSonics Vevo2100. α and η estimates of lesion-mimicking spheres in the phantom were independently assessed by three research groups, who analyzed their system’s RF echo signals. Imaging-system-based estimates of α and η of both lesion-mimicking spheres were comparable to through-transmission laboratory estimates and to predictions using Faran’s theory, respectively. A few notable variations in results among the clinical systems were observed, but the average and maximum percent difference between α estimates and laboratory-assessed values was 11% and 29%, respectively. Excluding a single outlier dataset, the average and maximum average difference between η estimates for the clinical systems and values predicted from scattering theory was 16% and 33%, respectively. These results were an improvement over previous inter-laboratory comparisons of attenuation and backscatter estimates. Although the standardization of our estimation methodologies can be further improved, this study validates our results from previous rodent breast-tumor model studies.
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