An efficient sound speed estimation method to enhance image resolution in ultrasound imaging

Investigation of a method to estimate the average speed of sound using phase variances of element signals for ultrasound compound imaging

PURPOSE

In the receive beamforming of an ultrasonography system, a B-mode image is reconstructed by assuming an average speed of sound (SoS) as a constant value. In our previous studies, we proposed a method for estimating the average SoS based on the coherence factor (CF) and the reciprocal of phase variances of element signals in delay-and-sum (DAS) beamforming. In this paper, we investigate the accuracy of estimation of the average SoS for compound imaging.

METHODS

For this purpose, two numerical simulations were performed with k-Wave software. Also, the estimation methods based on the CF and the reciprocal were applied to in vivo data from the common carotid artery, and B-mode images were reconstructed using the estimated average SoS.

RESULTS

In the first numerical simulation using an inhomogeneous phantom, the relationship between the accuracy and the transmission angles for the estimation was investigated, and the root mean squared errors (RMSEs) of estimates obtained based on the CF and the reciprocal of the phase variance were 1.25 ± 0.09, and 0.765 ± 0.17% at the transmission sequence of steering angles of (- 10°, - 5°, 0°, 5°, 10°), respectively. In the second numerical simulation using a cyst phantom, lateral resolutions were improved by reconstructing the image using the estimates obtained using the proposed strategy (reciprocal). By the proposed strategy, improvement of the continuity of the lumen-intima interface in the lateral direction was observed in the in vivo experiment.

CONCLUSION

Consequently, the results indicated that the proposed strategy was beneficial for estimation of the average SoS and image reconstruction.

Improving diagnostic accuracy of ultrasound texture features in detecting and quantifying hepatic steatosis using various beamforming sound speeds

Objective.While ultrasound image texture has been utilized to detect and quantify hepatic steatosis, the texture features extracted using a single (conventionally 1540 m s-1) beamforming speed of sound (SoS) failed to achieve reliable diagnostic performance. This study aimed to investigate if the texture features extracted using various beamforming SoSs can improve the accuracy of hepatic steatosis detection and quantification.Approach.Patients with suspected non-alcoholic fatty liver disease underwent liver biopsy or MRI proton density fat fraction (PDFF) as part of standard of care, were prospectively enrolled. The radio-frequency data from subjects' right and left liver lobes were collected using 6 beamforming SoSs: 1300, 1350, 1400, 1450, 1500 and 1540 m s-1and analyzed offline. The texture features, i.e. Contrast, Correlation, Energy and Homogeneity from gray-level co-occurrence matrix of normalized envelope were obtained from a region of interest in the liver parenchyma.Main results.Forty-three subjects (67.2%) were diagnosed with steatosis while 21 had no steatosis. Homogeneity showed the area under the curve (AUC) of 0.75-0.82 and 0.58-0.81 for left and right lobes, respectively with varying beamforming SoSs. The combined Homogeneity value over 1300-1540 m s-1from left and right lobes showed the AUC of 0.90 and 0.81, respectively. Furthermore, the combined Homogeneity values from left and right lobes over 1300-1540 m s-1improved the AUC to 0.94. The correlation between texture features and steatosis severity was improved by using the images from various beamforming SoSs. The combined Contrast values over 1300-1540 m s-1from left and right lobes demonstrated the highest correlation (r= 0.90) with the MRI PDFF while the combined Homogeneity values over 1300-1540 m s-1from left and right lobes showed the highest correlation with the biopsy grades (r= -0.81).Significance.The diagnostic accuracy of ultrasound texture features in detecting and quantifying hepatic steatosis was improved by combining its values extracted using various beamforming SoSs.

Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists

Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.

Advances in ultrasonography: image formation and quality assessment

Delay-and-sum (DAS) beamforming is widely used for generation of B-mode images from echo signals obtained with an array probe composed of transducer elements. However, the resolution and contrast achieved with DAS beamforming are determined by the physical specifications of the array, e.g., size and pitch of elements. To overcome this limitation, adaptive imaging methods have recently been explored extensively thanks to the dissemination of digital and programmable ultrasound systems. On the other hand, it is also important to evaluate the performance of such adaptive imaging methods quantitatively to validate whether the modification of the image characteristics resulting from the developed method is appropriate. Since many adaptive imaging methods have been developed and they often alter image characteristics, attempts have also been made to update the methods for quantitative assessment of image quality. This article provides a review of recent developments in adaptive imaging and image quality assessment.

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

In the field of clinical ultrasound, the full digitalization of diagnostic equipment in the 2000s enabled the technological development of quantitative ultrasound (QUS), followed by multiple diagnostic technologies that have been put into practical use in recent years. In QUS, tissue characteristics are quantified and parameters are calculated by analyzing the radiofrequency (RF) echo signals returning to the transducer. However, the physical properties (and pathological level structure) of the biological tissues responsible for the imaging features and QUS parameters have not been sufficiently verified as there are various conditions for observing living tissue with ultrasound and inevitable discrepancies between theoretical and actual measurements. A major issue of QUS in clinical application is that the evaluation results depend on the acquisition conditions of the RF echo signal as the source of the image information, and also vary according to the model of the diagnostic device. In this paper, typical examples of QUS techniques for evaluating attenuation, speed of sound, amplitude envelope characteristics, and backscatter coefficient in living tissues are introduced. Exemplary basic research and clinical applications related to these technologies, and initiatives currently being undertaken to establish the QUS method as a true tissue characterization technology, are also discussed.

A Computationally Efficient Mean Sound Speed Estimation Method Based on an Evaluation of Focusing Quality for Medical Ultrasound Imaging

Generally, ultrasound receive beamformers calculate the focusing time delays of fixed sound speeds in human tissue (e.g., 1540 m/s). However, phase distortions occur due to variations of sound speeds in soft tissues, resulting in degradation of image quality. Thus, an optimal estimation of sound speed is required in order to improve image quality. Implementation of real-time sound speed estimation is challenging due to high computational and hardware complexities. In this paper, an optimal sound speed estimation method with a low-cost hardware resource is presented. In the proposed method, the optimal mean sound speed is determined by measuring the amplitude variance of pre-beamformed radio-frequency (RF) data. The proposed method was evaluated with phantom and in vivo experiments, and implemented on Virtex-4 with Xilinx ISE 12.4 using VHDL. Experiment results indicate that the proposed method could estimate the mean optimal sound speed and enhance spatial resolution with a negligible increase in the hardware resource usage.

Synthetic transmit aperture beamforming for sound velocity estimation using channel-domain differential phase gradient - A phantom study

In medical ultrasound imaging system, degradation of image quality occurs due to mismatch between beamforming sound velocity and propagating sound velocity in tissue. Channel-domain differential phase gradient has been previously utilized to optimize the beamforming sound velocity but its efficacy is limited to transmit focal depth. Specifically, low spatial coherence of channel signal in the non-focal region could lead to over-estimation of beamforming sound velocity. In order to alleviate the estimation bias of beamforming sound velocity, synthetic transmit aperture beamforming is proposed in this study to maintain the spatial coherence of channel data over the entire imaging depth. By combining channel signals from adjacent scanlines to remedy the focusing quality in the non-focal region, the zero of differential phase gradient between the left and right sub-apertures can accurately determine the optimal sound velocity for beamforming. Results indicate that the synthetic transmit aperture beamforming effectively reduces the estimation bias of beamforming sound velocity from 4.3% to 0.1% in the simulations and from 8.8% to 0.1% in phantom measurement. With the optimized sound velocity, the lateral resolution improves by 14.5%. Compared to our previous work, the improved method also exhibits higher robustness of sound velocity estimation in the presence of random noises. The variation of sound velocity estimation decreases from 59.1 m/s with the previous method to 16.9 m/s with the improved method in our simulation when the channel SNR is -25 dB.

Improving image quality of mid-trimester fetal sonography in obese women: role of ultrasound propagation velocity

OBJECTIVE

The quality of ultrasound images is impaired in obese patients. All ultrasound scanners are calibrated for an ultrasound propagation velocity of 1540 m/s, but the propagation in fatty tissue is slower (in the order of 1450 m/s). The main objective of this study was to evaluate the quality of images obtained with different ultrasound propagation velocity settings during the mid-trimester fetal ultrasound examination in obese patients.

METHODS

This was a cross-sectional study using image sets of four recommended scanning planes collected from 32 obese pregnant women during their mid-trimester fetal scan. Each image set comprised three images obtained successively at three different propagation velocity settings (1540 m/s, 1480 m/s and 1420 m/s). A panel of 114 experts assessed the quality of 100 image sets, grading them from A (most acceptable) to C (least acceptable). Scanning-plane-specific indicators of adiposity (fatty layer thickness, probe-to-organ distance) were analyzed for each scanning plane.

RESULTS

The experts had a mean of 18.1 ± 10.2 years of experience. The grade distribution (A, B, C) differed significantly (P < 0.0001) between the three propagation velocity settings tested; at the lower speed of 1480 m/s, images were most often graded A, while at the conventional speed of 1540 m/s, they were most often graded C. Regardless of the scanning plane, the thicker the fatty layer of the abdominal wall in a given plane, the lower the preferred speed (P < 0.0001).

CONCLUSION

The construction of images taking into account ultrasound propagation velocities lower than 1540 m/s can improve significantly the quality of images obtained during mid-trimester fetal ultrasonography in obese women. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Assessment of Coded Excitation Implementation for Estimating Heat-Induced Speed of Sound Changes

Speed of sound (SoS) is an acoustic property that is highly sensitive to changes in tissues. SoS can be mapped non-invasively using ultrasonic through transmission wave tomography. This however, practically limits its clinical use to the breast. A pulse-echo-based method that has broader clinical use and that can reliably measure treatment-induced changes in SoS even under poor signal-to-noise ratio (SNR) is highly desirable. The aim of this study was to evaluate the implementation of coded excitations (CoEs) to improve pulse-echo monitoring of heat-induced changes in the SoS. In this study, a binary phase modulated Barker sequence and a linear frequency-modulated chirp were compared with a common Gaussian pulse transmission. The comparison was conducted using computer simulations, as well as transmissions in both agar-gelatin phantoms and ex vivo bovine liver. SoS changes were experimentally induced by heating the specimens with a therapeutic ultrasound system. The performance of each transmission signal was evaluated by correlating the relative echo shifts to the normalized SoS measured by through transmission. The computer simulations indicated that CoEs are beneficial at very low SNR. The Barker code performed better than both the chirp and Gaussian pulses, particularly at SNRs <10 dB (R² = 0.81 ± 0.06, 0.68 ± 0.07 and 0.55 ± 0.08, respectively, at 0 dB). At high SNRs, the CoEs performed statistically on par with the Gaussian pulse. The experimental findings indicated that both Barker and chirp codes performed better than the Gaussian pulse on ex vivo liver (R² = 0.80 ± 0.15, 0.79 ± 0.15 and 0.54 ± 0.17, respectively) and comparably on agar-gelatin phantoms. In conclusion, CoEs can be beneficial for assessing temperature-induced changes in the SoS using the pulse-echo method under poor SNR.

Adaptive optimization of ultrasound beamforming sound velocity using sub-aperture differential phase gradient

Ultrasound array imaging systems rely on a presumed beamforming sound velocity to calculate the time compensation of each element for receive focusing. The mismatch between the tissue sound velocity and the beamforming sound velocity can degrade the focusing quality due to loss of phase coherence. Since the tissue sound velocity cannot be known in prior, an adaptive optimization of beamforming sound velocity is required to improve the image quality. Differential phase gradient of channel data is proposed to estimate the optimal sound velocity for beamforming. The sound velocity optimization is achieved when the differential phase gradient between the left and the right sub-apertures approaches zero. Channel-domain autocorrelation is utilized for the estimation of phase gradient due to its high rejection to noise interference and low computational complexity. Results indicate that, compared to the conventional phase variance method, the proposed differential phase gradient reduces the standard deviation of sound velocity estimation from 0.5% to 0.2% while the accuracy remains comparable. The contrast ratio of the cyst region achieves the peak when the optimized sound velocity is utilized for beamforming. The lateral resolution of point target also improves by 14.3% after sound velocity optimization. The proposed method increases the robustness of sound velocity optimization. It is suggested to be implemented at transmit focal depth and without beam steering for better performance.

Statistical Characterization of the Medical Ultrasound Echo Signals

Medical ultrasound echo signals provide the basic information for obtaining the ultrasonic image in medical ultrasound technology. The statistics of the ultrasound echo signals reveals the systematic structure of the medical ultrasonic image via analyzing the corresponding statistical distributions. A novel statistical distribution, the ascending order K distribution, was proposed here to model the medical ultrasound echo signals. The ascending order K distribution was developed in light of the statistical analysis of the sequential waveforms in the echo signals. Comparison with the previous statistical distributions was made to verify the superiority of the ascending order K distribution. Further discussion showed the determination of the statistical principles for the ultrasound signals can enhance our understanding of the statistical principles of the ultrasound imaging, and thus, facilitate the optimization of the ultrasound image and the tissue identification in the ultrasound diagnosis.

Variation of ultrasound image lateral spectrum with assumed speed of sound and true scatterer density

One method of estimating sound speed in diagnostic ultrasound imaging consists of choosing the speed of sound that generates the sharpest image, as evaluated by the lateral frequency spectrum of the squared B-mode image. In the current work, simulated and experimental data on a typical (47 mm aperture, 3.3-10.0 MHz response) linear array transducer are used to investigate the accuracy of this method. A range of candidate speeds of sound (1240-1740 m/s) was used, with a true speed of sound of 1490 m/s in simulations and 1488 m/s in experiments. Simulations of single point scatterers and two interfering point scatterers at various locations with respect to each other gave estimate errors of 0.0-2.0%. Simulations and experiments of scatterer distributions with a mean scatterer spacing of at least 0.5 mm gave estimate errors of 0.1-4.0%. In the case of lower scatterer spacing, the speed of sound estimates become unreliable due to a decrease in contrast of the sharpness measure between different candidate speeds of sound. This suggests that in estimating speed of sound in tissue, the region of interest should be dominated by a few, sparsely spaced scatterers. Conversely, the decreasing sensitivity of the sharpness measure to speed of sound errors for higher scatterer concentrations suggests a potential method for estimating mean scatterer spacing.

Timing-error-difference calibration of a two-dimensional array imaging system using the overlapping-subaperture algorithm

Timing errors in the transmitting and receiving electronic channels of an imaging system can generate different transmission and reception phase-aberration profiles. To decide if these two profiles need to be measured separately, an overlapping-subaperture algorithm has been proposed in a previous paper to measure the difference between timing errors in transmitting and receiving channels connected to each element in a two-dimensional array. This algorithm has been used to calibrate a custom built imaging system with a curved linear two-dimensional array, and the results are presented in this paper. The experimental results have demonstrated that the overlapping-subaperture algorithm is capable of calibrating the timing-error-difference profile of this imaging system with a standard deviation of only a few nanoseconds. Experimental results have also shown that the time-error-difference profile of this imaging system is smaller than one tenth of a wavelength and there is no need to measure the transmission and reception phase-aberration profiles separately. The derived average phase-aberration profile using the near-field signal-redundancy algorithm can be used to correct phase aberrations for both transmission and reception.

Correction of tissue-motion effects on common-midpoint signals using reciprocal signals

The near field signal redundancy algorithm for phase-aberration correction is sensitive to tissue motion because several separated transmissions are usually needed to acquire a set of common-midpoint signals. If tissues are moving significantly due to, for example, heart beats, the effects of tissue motion on common-midpoint signals need to be corrected before the phase-aberration profile can be successfully measured. Theoretical analyses in this paper show that the arrival-time difference between a pair of common-midpoint signals due to tissue motion is usually very similar to that between the pair of reciprocal signals acquired using the same two transmissions. Based on this conclusion, an algorithm for correcting tissue-motion effects on the peak position of cross-correlation functions between common-midpoint signals is proposed and initial experimental results are also presented.

Average sound speed estimation using speckle analysis of medical ultrasound data

PURPOSE

Most ultrasound imaging systems assume a pre-determined sound propagation speed for imaging. However, a mismatch between assumed and real sound speeds can lead to spatial shift and defocus of ultrasound image, which may limit the applicability of ultrasound imaging. The estimation of real sound speed is important for improving positioning accuracy and focus quality of ultrasound image.

METHOD

A novel method using speckle analysis of ultrasound image is proposed for average sound speed estimation. Firstly, dynamic receive beam forming technology is employed to form ultrasound images. These ultrasound images are formed by same pre-beam formed radio frequency data but using different assumed sound speeds. Secondly, an improved speckle analysis method is proposed to evaluate focus quality of these ultrasound images. Thirdly, an iteration strategy is employed to locate the desired sound speed that corresponds to the best focus quality image.

RESULTS

For quantitative evaluation, a group of ultrasound data with 20 different structure patterns is simulated. The comparison of estimated and simulated sound speeds shows speed estimation errors to be -0.7 ± 2.54 m/s and -1.30 ± 5.15 m/s for ultrasound data obtained by 128- and 64-active individual elements linear arrays, respectively. Furthermore, we validate our method via phantom experiments. The sound speed estimation error is -1.52 ± 8.81 m/s.

CONCLUSION

Quantitative evaluation proves that proposed method can estimate average sound speed accurately using single transducer with single scan.

In vitro estimation of mean sound speed based on minimum average phase variance in medical ultrasound imaging

Effective receive beamforming in medical ultrasound imaging is important for enhancing spatial and contrast resolution. In current ultrasound receive beamforming, a constant sound speed (e.g., 1540m/s) is assumed. However, the variations of sound speed in soft tissues could introduce phase distortions, leading to degradation in spatial and contrast resolution. This degradation becomes even more severe in imaging fatty tissues (e.g., breast) and with obese patients. In this paper, a mean sound speed estimation method where phase variance of radio-frequency channel data in the region of interest is evaluated is presented for improving spatial and contrast resolution. The proposed estimation method was validated by the Field II simulation and the tissue mimicking phantom experiments. In the simulation, the sound speed of the medium was set to 1450m/s and the proposed method was capable of capturing this value correctly. From the phantom experiments, the -18-dB lateral resolution of the point target at 50mm obtained with the estimated mean sound speed was improved by a factor of 1.3, i.e., from 3.9mm to 2.9mm. The proposed estimation method also provides an improvement of 0.4 in the contrast-to-noise ratio, i.e., from 2.4 to 2.8. These results indicate that the proposed mean sound speed estimation method could enhance the spatial and contrast resolution in the medical ultrasound imaging systems.