Scatterer Size Images Research Articles

Improving biomedical ultrasonic imaging systems through coded excitation and pulse compression.

Coded excitation and pulse compression techniques are being employed in biomedical ultrasonic imaging systems in order to improve image quality. Traditionally, the rationale for using coded excitation techniques in biomedical ultrasonic imaging was to increase the signal‐to‐noise ratio (SNR) of backscattered signals without increasing the pressure amplitudes above the thresholds predicted to produce bioeffects. Furthermore, coding schemes combined with pulse compression would allow the spatial resolution to be preserved. Recently, unique coded excitation schemes have been developed [i.e., the resolution enhancement compression (REC) technique] that not only produce a significant increase in SNR but also a doubling of the bandwidth of the ultrasonic imaging system. In conventional ultrasound B‐mode imaging, the increased bandwidth provided by the REC technique could be used to improve the axial resolution of the ultrasonic imaging system or traded off to improve the contrast resolution of the ultrasonic imaging system through frequency compounding. In quantitative imaging techniques using spectral analysis (e.g., scatterer size imaging), the increased bandwidth from REC could be used to increase the trade‐off between spatial resolution and estimate variance. An overview of these coded excitation techniques and their application to biomedical ultrasonic imaging will be presented. [This work is supported by NIH EB006741.]

Acoustic backscatter and effective scatterer size estimates using a 2D CMUT transducer

Compared to conventional piezoelectric transducers, new capacitive microfabricated ultrasonic transducer (CMUT) technology is expected to offer a broader bandwidth, higher resolution and advanced 3D/4D imaging inherent in a 2D array. For ultrasound scatterer size imaging, a broader frequency range provides more information on frequency-dependent backscatter, and therefore, generally more accurate size estimates. Elevational compounding, which can significantly reduce the large statistical fluctuations associated with parametric imaging, becomes readily available with a 2D array. In this work, we show phantom and in vivo breast tumor scatterer size image results using a prototype 2D CMUT transducer (9 MHz center frequency) attached to a clinical scanner. A uniform phantom with two 1 cm diameter spherical inclusions of slightly smaller scatterer size was submerged in oil and scanned by both the 2D CMUT and a conventional piezoelectric linear array transducer. The attenuation and scatterer sizes of the sample were estimated using a reference phantom method. RF correlation analysis was performed using the data acquired by both transducers. The 2D CMUT results indicate that at a 2 cm depth (near the transmit focus for both transducers) the correlation coefficient reduced to less than 1/e for 0.2 mm lateral or 0.25 mm elevational separation between acoustic scanlines. For the conventional array this level of decorrelation requires a 0.3 mm lateral or 0.75 mm elevational translation. Angular and/or elevational compounding is used to reduce the variance of scatterer size estimates. The 2D array transducer acquired RF signals from 140 planes over a 2.8 cm elevational direction. If no elevational compounding is used, the fractional standard deviation of the size estimates is about 12% of the mean size estimate for both the spherical inclusion and the background. Elevational compounding of 11 adjacent planes reduces it to 7% for both media. Using an experimentally estimated attenuation of 0.6 dB cm−1 MHz−1, scatterer size estimates for an in vivo breast tumor also demonstrate improvements using elevational compounding with data from the 2D CMUT transducer.

Initial Clinical Experience Imaging Scatterer Size and Strain in Thyroid Nodules

This article describes a new research ultrasound scanner that can be programmed to produce elastograms and backscatter parametric images in real time. Its performance was evaluated in a clinical setting. Radio frequency data were acquired from 13 patients with thyroid nodules and from 4 normal thyroids, along with reference phantom data. Scatterer size was deduced by measuring the backscatter versus frequency and fitting data to a model. Strain was obtained by a cross-correlation method, comparing precompression and postcompression radio frequency signals. Scatterer size contrast was defined as the observed contrast between the "normal" and "abnormal" tissue in the same gland or, when considering diffuse conditions, by comparing with normal values. Strain contrast was estimated if abnormal and normal tissue was captured in the same palpation, that is, excluding diffuse disease, which was the case for 9 subjects. On scatterer size images, 4 nodules exhibited positive contrast versus the adjacent normal parenchyma, indicating larger scatterers. Five nodules were isoechoic, and 4 had negative contrast. Four nodules exhibited positive strain contrast, indicating that they were softer than the normal parenchyma. Two nodules had the same brightness, and 3 were darker than the background thyroid tissue on strain images. Contrast was observed between nodules and thyroid parenchymal tissue for both types of parametric images. Further work is needed to determine whether the diagnostic importance of these parameters in characterizing thyroid nodules might be worthwhile. Both modes must be of a sufficient frame rate to provide real-time feedback to operators, which will require further work.

Improved parametric imaging of scatterer size estimates using angular compounding

The feasibility of estimating and imaging scatterer size using backscattered ultrasound signals and spectral analysis techniques was demonstrated previously. In many cases, size estimation, although computationally intensive, has proven to be useful for monitoring, diagnosing, and studying disease. However, a difficulty that is encountered in imaging scatterer size is the large estimator variance caused by statistical fluctuations in echo signals from random media. This paper presents an approach for reducing these statistical uncertainties. Multiple scatterer size estimates are generated for each image pixel using data acquired from several different directions. These estimates are subsequently compounded to yield a single estimate that has a reduced variance. In this feasibility study, compounding was achieved by translating a sectored-array transducer in a direction parallel to the acquired image plane. Angular compounding improved the signal-to-noise ratio (SNR) in scatterer size images. The improvement is proportional to the square root of the effective number of statistically independent views available for each image pixel.

Bayesian and least squares approaches to ultrasonic scatterer size image formation

Scatterer size images can be used to describe renal microstructure and function in vivo. Such information may facilitate early detection of disease processes. When high range resolution is required, however, it is necessary to analyze short data segments. Periodogram-based maximum likelihood (ML) techniques for scatterer size estimation are limited in these situations by noise and range-gate artifacts. Moreover, when the input signal-to-noise ratio (SNR) of the echo signal is small, performance is further degraded. If accurate prior information about the approximate properties of the object is available, it can be incorporated into the solution to improve the estimates by reducing the number of possible solutions. In this paper, use of prior knowledge in scatterer size image formation is investigated. A maximum a posteriori (MAP) estimator, based on a random-object model, and an iterative constrained least squares (CLS) estimator, based on a deterministic-object model, are designed. Their performances and that of a Wiener filter are compared with the ML technique as a function of gate duration and SNR.

Autoregressive spectral estimation in ultrasonic scatterer size imaging.

An autoregressive (AR) spectral estimation method was considered for the purpose of estimating scatterer size images. The variance and bias of the resulting estimates were compared with those using classical FFT periodograms for a range of input signal-to-noise ratios and echo-signal durations corresponding to various C-scan image slice thicknesses. The AR approach was found to produce images of significantly higher quality for noisy data and when thin slices were required. Several images reconstructed with the two techniques are presented to demonstrate difference in visual quality. Task-specific guidelines for empirical selection of the AR model order are also proposed.

Autoregressive Spectral Estimation in Ultrasonic Scatterer Size Imaging

An autoregressive (AR) spectral estimation method was considered for the purpose of estimating scatterer size images. The variance and bias of the resulting estimates were compared with those using classical FFT periodograms for a range of input signal-to-noise ratios and echo-signal durations corresponding to various C-scan image slice thicknesses. The AR approach was found to produce images of significantly higher quality for noisy data and when thin slices were required. Several images reconstructed with the two techniques are presented to demonstrate difference in visual quality. Task-specific guidelines for empirical selection of the AR model order are also proposed.

Parametric ultrasound imaging from backscatter coefficient measurements: Image formation and interpretation

A broadband method for measuring backscatter coefficients σ b and other acoustic parameters is described. From the σ b measurements, using a commercially-available imaging system, four high-resolution parametric ultrasound images are formed in a C-scan image plane. Scatterer size images are computed from the frequency dependence of σ b and a correlation model function that describes the structure and elastic properties of the medium. Scattering strength images are computed from the absolute magnitude of σ b . Chi-square images are generated to display how well the correlation model represents the interrogated medium. Integrated backscatter coefficient images are formed over the transducer bandwidth. All four images are generated simultaneously and compared with the corresponding B-mode image. Test samples with known physical properties were used to demonstrate experimentally that accurate parametric images are possible if an accurate correlation model is used. Local variations in attenuation, the center frequency and bandwidth of the transducer, and the distribution of scatterer sizes greatly influence the accuracy of estimates and the appearance of the image, thus demonstrating the importance of these factors in parametric image interpretation.

Parametric Ultrasound Imaging from Backscatter Coefficient Measurements: Image Formation and Interpretation

A broadband method for measuring backscatter coefficients sigma b and other acoustic parameters is described. From the sigma b measurements, using a commercially-available imaging system, four high-resolution parametric ultrasound images are formed in a C-scan image plane. Scatterer size images are computed from the frequency dependence of sigma b and a correlation model function that describes the structure and elastic properties of the medium. Scattering strength images are computed from the absolute magnitude of sigma b. Chi-square images are generated to display how well the correlation model represents the interrogated medium. Integrated backscatter coefficient images are formed over the transducer bandwidth. All four images are generated simultaneously and compared with the corresponding B-mode image. Test samples with known physical properties were used to demonstrate experimentally that accurate parametric images are possible if an accurate correlation model is used. Local variations in attenuation, the center frequency and bandwidth of the transducer, and the distribution of scatterer sizes greatly influence the accuracy of estimates and the appearance of the image, thus demonstrating the importance of these factors in parametric image interpretation.

Quantitative scatterer size imaging: M.F. Insana, K.S. Hensley, S.J. Rosenthal and G.G. Cox, Department of Diagnostic Radiology, University of Kansas Medical Center, Kansas City, KS 66103

Quantitative scatterer size imaging: M.F. Insana, K.S. Hensley, S.J. Rosenthal and G.G. Cox, Department of Diagnostic Radiology, University of Kansas Medical Center, Kansas City, KS 66103