US Backscatter for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative.

Nonalcoholic fatty liver disease (NAFLD) is believed to affect one-third of American adults. Noninvasive methods that enable detection and monitoring of NAFLD have the potential for great public health benefits. Because of its low cost, portability, and noninvasiveness, US is an attractive alternative to both biopsy and MRI in the assessment of liver steatosis. NAFLD is qualitatively associated with enhanced B-mode US echogenicity, but visual measures of B-mode echogenicity are negatively affected by interobserver variability. Alternatively, quantitative backscatter parameters, including the hepatorenal index and backscatter coefficient, are being investigated with the goal of improving US-based characterization of NAFLD. The American Institute of Ultrasound in Medicine and Radiological Society of North America Quantitative Imaging Biomarkers Alliance are working to standardize US acquisition protocols and data analysis methods to improve the diagnostic performance of the backscatter coefficient in liver fat assessment. This review article explains the science and clinical evidence underlying backscatter for liver fat assessment. Recommendations for data collection are discussed, with the aim of minimizing potential confounding effects associated with technical and biologic variables.

A Locally Adaptive Phase Aberration Correction (LAPAC) Method for Synthetic Aperture Sequences.

Phase aberration is a phenomenon caused by heterogeneity of the speed of sound in tissue, in which the actual speed of sound of the tissue is different than the assumed speed of sound used for beamforming. It reduces the quality and resolution of ultrasonic images and impairs clinical diagnostic capabilities. Although phase aberration correction (PAC) methods can reduce these detrimental effects, most practical implementations of PAC methods are based on the near field phase screen model, which have limited ability to represent the true aberration induced by inhomogeneous tissue. Accordingly, we propose a locally adaptive phase aberration correction (LAPAC) method that is applied through the use of synthetic aperture. The method is tested using full-wave simulations of models of human abdominal wall, experiments with tissue aberrators, and in vivo carotid images. LAPAC is compared with conventional phase aberration correction (cPAC) where aberration profiles are computed at a preselected depth and applied to the beamformer's time delays. For all experiments, LAPAC shows an average of 1 to 2 dB higher contrast than cPAC, and enhancements of 3 to 7 dB with respect to the uncorrected cases. We conclude that LAPAC may be a viable option to enhance ultrasound image quality images even in the presence of clinically relevant aberrating conditions.

Effects of Phase Aberration and Phase Aberration Correction on the Minimum Variance Beamformer.

The minimum variance (MV) beamformer has the potential to enhance the resolution and contrast of ultrasound images but is sensitive to steering vector errors. Robust MV beamformers have been proposed but mainly evaluated in the presence of gross sound speed mismatches, and the impact of phase aberration correction (PAC) methods in mitigating the effects of phase aberration in MV beamformed images has not been explored. In this study, an analysis of the effects of aberration on conventional MV and eigenspace MV (ESMV) beamformers is carried out. In addition, the impact of three PAC algorithms on the performance of MV beamforming is analyzed. The different beamformers were tested on simulated data and on experimental data corrupted with electronic and tissue-based aberration. It is shown that all gains in performance of the MV beamformer with respect to delay-and-sum (DAS) are lost at high aberration strengths. For instance, with an electronic aberration of 60 ns, the lateral resolution of DAS degrades by 17% while MV degrades by 73% with respect to the images with no aberration. Moreover, although ESMV shows robustness at low aberration levels, its degradation at higher aberrations is approximately the same as that of regular MV. It is also shown that basic PAC methods improve the aberrated MV beamformer. For example, in the case of electronic aberration, multi-lag reduces degradation in lateral resolution from 73% to 28% and contrast loss from 85% to 25%. These enhancements allow the combination of MV and PAC to outperform DAS and PAC and ESMV in moderate and strong aberrations. We conclude that the effect of aberration on the MV beamformer is stronger than previously reported in the literature and that PAC is needed to improve its clinical potential.

Temporal artifact minimization in sonoelastography through optimal selection of imaging parameters.

Sonoelastography is an ultrasonic technique that uses Kasai's autocorrelation algorithms to generate qualitative images of tissue elasticity using external mechanical vibrations. In the absence of synchronization between the mechanical vibration device and the ultrasound system, the random initial phase and finite ensemble length of the data packets result in temporal artifacts in the sonoelastography frames and, consequently, in degraded image quality. In this work, the analytic derivation of an optimal selection of acquisition parameters (i.e., pulse repetition frequency, vibration frequency, and ensemble length) is developed in order to minimize these artifacts, thereby eliminating the need for complex device synchronization. The proposed rule was verified through experiments with heterogeneous phantoms, where the use of optimally selected parameters increased the average contrast-to-noise ratio (CNR) by more than 200% and reduced the CNR standard deviation by 400% when compared to the use of arbitrarily selected imaging parameters. Therefore, the results suggest that the rule for specific selection of acquisition parameters becomes an important tool for producing high quality sonoelastography images.

Simultaneous imaging of ultrasonic relative backscatter and attenuation coefficients for quantitative liver steatosis assessment.

Prevalence of liver disease is continuously increasing and nonalcoholic fatty liver disease (NAFLD) is the most common etiology. We present an approach to detect the progression of liver steatosis based on quantitative ultrasound (QUS) imaging. This study was performed on a group of 55 rats that were subjected to a control or methionine and choline deficient (MCD) diet known to induce NAFLD. Ultrasound (US) measurements were performed at 2 and 6 weeks. Thereafter, animals were humanely euthanized and livers excised for histological analysis. Relative backscatter and attenuation coefficients were simultaneously estimated from the US data and envelope signal-to-noise ratio was calculated to train a regression model for: (1) fat fraction percentage estimation and (2) performing classification according to Brunt's criteria in grades (0 <5%; 1, 5-33%; 2, >33-66%; 3, >66%) of liver steatosis. The trained regression model achieved an [Formula: see text] of 0.97 (p-value < 0.01) and a RMSE of 3.64. Moreover, the classification task reached an accuracy of 94.55%. Our results suggest that in vivo QUS is a promising noninvasive imaging modality for the early assessment of NAFLD.

Estimating concentration of ultrasound contrast agents with backscatter coefficients: experimental and theoretical aspects.

Ultrasound contrast agents (UCAs) have been explored as a means to enhance therapeutic techniques. Because the effectiveness of these techniques relies on the UCA concentration at a target site, it would be beneficial to estimate UCA concentration noninvasively. In this study, a noninvasive method for estimating UCA concentration was developed in vitro. Backscatter coefficients (BSCs) estimated from measurements of Definity(®) UCAs were fitted to a theoretical scattering model in the 15-25 MHz range using a Levenberg-Marquardt regression technique. The model was defined by the UCA size distribution and concentration, and therefore concentration estimates were extracted directly from the fit. Calculation of the BSC was accomplished using planar reference measurements from the back wall of a Plexiglas(®) chamber and an average of 500 snapshots of ultrasonic backscatter from UCAs flowing through the chamber. In order to verify the ultrasonically derived UCA concentration estimates, a sample of the UCAs was extracted from the flow path and the concentration was estimated with a hemacytometer. UCA concentrations of 1, 2, and 5 times the dose recommended by the manufacturer were used in experiments. All BSC-based estimates were within one standard deviation of hemacytometer based estimates for peak rarefactional pressures of 100-400 kPa.

Cross-imaging system comparison of backscatter coefficient estimates from a tissue-mimicking material.

A key step toward implementing quantitative ultrasound techniques in a clinical setting is demonstrating that parameters such as the ultrasonic backscatter coefficient (BSC) can be accurately estimated independent of the clinical imaging system used. In previous studies, agreement in BSC estimates for well characterized phantoms was demonstrated across different laboratory systems. The goal of this study was to compare the BSC estimates of a tissue mimicking sample measured using four clinical scanners, each providing RF echo data in the 1-15 MHz frequency range. The sample was previously described and characterized with single-element transducer systems. Using a reference phantom for analysis, excellent quantitative agreement was observed across the four array-based imaging systems for BSC estimates. Additionally, the estimates from data acquired with the clinical systems agreed with theoretical predictions and with estimates from laboratory measurements using single-element transducers.

On the estimation of backscatter coefficients using single-element focused transducers.

The ultimate goal of quantitative ultrasound (QUS) imaging methods based on backscatter coefficient (BSC) estimates is to obtain system-independent structural information about samples. In the current study, three BSC estimation methods were compared and evaluated using the same backscattered pressure datasets in order to assess their consistency. BSC estimates were obtained from two phantoms with embedded glass spheres and compared to theoretical BSCs calculated using size distributions estimated using optical microscopy. Effective scatterer diameter and concentration estimates of the glass spheres were also obtained from the estimated BSCs. One estimation method needed to be compensated by more than an order of magnitude in amplitude in order to produce BSCs comparable to the other two methods. All calibration methods introduced different frequency-dependent effects, which could have noticeable effects on the bias of QUS estimates derived from experimental BSCs. Although in most cases the experimental QUS estimates obtained with all three methods were observed to differ by less than 10%, larger differences are expected depending on both the pressure focusing gain of the transducer (proportional to the ratio of the square of the aperture radius to the product of the wavelength and focal length) and ka range used in the estimation.

Total attenuation compensation for backscatter coefficient estimation using full angular spatial compounding.

The backscatter coefficient (BSC) quantifies the frequency-dependent reflectivity of tissues. Accurate estimation of the BSC is only possible with the knowledge of the attenuation coefficient slope (ACS) of the tissues under examination. In this study, the use of attenuation maps constructed using full angular spatial compounding (FASC) is proposed for attenuation compensation when imaging integrated BSCs. Experimental validation of the proposed approach was obtained using two cylindrical physical phantoms with off-centered inclusions having different ACS and BSC values than the background, and in a phantom containing an ex vivo chicken breast sample embedded in an agar matrix. With the phantom data, three different ACS maps were employed for attenuation compensation: (1) a ground truth ACS map constructed using insertion loss techniques, (2) the estimated ACS map using FASC attenuation imaging, and (3) a uniform ACS map with a value of 0.5 dBcm\protect \relax \special {t4ht=-}1MHz\protect \relax \special {t4ht=-}1, which is commonly used to represent attenuation in soft tissues. Comparable results were obtained when using the ground truth and FASC-estimated ACS maps in term of inclusion detectability and estimation accuracy, with averaged fractional error below 2.8 dB in both phantoms. Conversely, the use of the homogeneous ACS map resulted in higher levels of fractional error (>10 dB), which demonstrates the importance of an accurate attenuation compensation. The results with the ex vivo tissue sample were consistent with the observations using the physical phantoms, with the FASC-derived ACS map providing comparable BSC images to those formed using the ground truth ACS map and more accurate than those BSC images formed using a uniform ACS. These results suggest that BSCs can be reliably estimated using FASC when a self-consistent attenuation compensation stemming from prior estimation of an accurate ACS map is used.

Scattering by an arrangement of eccentric cylinders embedded on a coated cylinder with applications to tomographic density imaging.

The solution to the scattering of an incident pressure wave by an arrangement of eccentric cylinders embedded inside a pair of concentric cylinders is derived here using a combination of T-matrix and mode-matching approaches. This method allows the generation of synthetic data from relatively complex structures to be used for the validation of acoustic tomography methods. An application of the solution derived here is illustrated by reconstructing sound speed and density profiles from a complex phantom using inverse scattering.

Density imaging using inverse scattering.

Inverse scattering is considered one of the most robust and accurate ultrasonic tomography methods. Most inverse scattering formulations neglect density changes in order to reconstruct sound speed and acoustic attenuation. Some studies available in literature suggest that density distributions can also be recovered using inverse scattering formulations. Two classes of algorithms have been identified. (1) The separation of sound speed and density contributions from reconstructions using constant density inverse scattering algorithms at multiple frequencies. (2) The inversion of the full wave equation including density changes. In this work, the performance of a representative algorithm for each class has been studied for the reconstruction of circular cylinders: the dual frequency distorted Born iterative method (DF-DBIM) and the T-matrix formulation. Root mean square error values lower than 30% were obtained with both algorithms when reconstructing cylinders up to eight wavelengths in diameter with moderate density changes. However, in order to provide accurate reconstructions the DF-DBIM and T-matrix method required very high signal-to-noise ratios and significantly large bandwidths, respectively. These limitations are discussed in the context of practical experimental implementations.

A study on the reconstruction of moderate contrast targets using the distorted born iterative method.

Previous tomographic methods using ultrasound for reconstructing sound speed and attenuation images suffered from convergence issues for targets with moderate speed of sound contrast. Convergence problems can be overcome by the use of the multiple frequency, distorted Born iterative method (DBIM). The implementation of DBIM for measurement configurations in which receiver positions are fixed was studied, and a novel regularization scheme was developed. The regularization parameter needed to stabilize the inversion process initially was found through the Rayleigh quotient iteration, then relaxed according to the relative residual error between the measured and estimated scattered fields. The DBIM was successfully stabilized for both full and partial receiver angular coverage without a significant loss in spatial resolution. The effects of variable density in the reconstructions were briefly explored through simulations. The ability to reconstruct targets with moderate contrast was validated through experimental measurements. Speed of sound profiles for balloons filled with saline in a background of water were reconstructed using multiple frequency DBIM techniques. The mean squared error for speed of sound reconstructions of the balloon phantoms with 16.4% sound speed contrast was 1.1%.

Regularized Spectral Log Difference Technique for Ultrasonic Attenuation Imaging.

The attenuation coefficient slope (ACS) has the potential to be used for tissue characterization and as a diagnostic ultrasound tool, hence complementing B-mode images. The ACS can be valuable for the estimation of other ultrasound parameters such as the backscatter coefficient. There is a well-known tradeoff between the precision of the estimated ACS values and the data block size used in the spectral-based techniques such as the spectral-log difference (SLD). This tradeoff limits the practical usefulness of the spectral-based attenuation imaging techniques. In this paper, the regularized SLD (RSLD) technique is presented in detail, and evaluated with simulations and experiments with physical phantoms, ex vivo and in vivo. The RSLD technique allowed decreasing estimation variance when using small data block sizes, i.e., fivefold reduction in the standard deviation of percentage error when using data block sizes larger than and more than a tenfold reduction when using data blocks. The precision improvement was obtained without sacrificing estimation accuracy (i.e., estimation bias improved in 70% of the cases by 10% of the ground truth-value on average while degraded in 30% of the cases by 3% of the ground truth-value on average). The improvements in precision allowed for better differentiation of inclusions especially when using small data blocks (i.e., smaller than ) where the contrast-to-noise ratio improved by an order of magnitude on average. The results suggest that the RSLD allows for the reconstruction of attenuation coefficient images with an improved tradeoff between spatial resolution and estimation precision.

In vivo estimation of the Young's modulus in normal human dermis.

Skin elastic properties change during a cutaneous disorder or in the aging process. Deep knowledge of skin layers helps monitoring and diagnosing structural changes. High frequency ultrasound (HF-US) has been recently introduced to diagnose and evaluate some dermatological disorders in the clinical practice. US elastography adds elasticity information of the analyzed tissue. In particular, harmonic elastography estimates the speed of shear waves produced by external vibration sources, in order to relate the shear wave speed to the Young's modulus. In the epidermis and dermis layers, shear waves are not generated; in contrast, surface acoustic waves (SAWs) exist as they propagate in the top of the tissue. This study uses crawling wave sonoelastography for the estimation of SAWs in human thigh dermis in vivo. Experiments were performed in ten volunteers in the range of 200 - 500 Hz. As other studies suggest, SAW speed needs to be compensated to reach shear wave speed, for calculating the Young's modulus. Thus, the SAW speed estimated was corrected when it propagates in solidUS gel interface. Specifically, the elasticity modulus found was $18.35 \pm 1.04$ KPa for a vibration frequency of 200 Hz. Results suggest that the elasticity modulus can be estimated in vivo using crawling wave HF-US for skin application and shows potential for future application in skin disorders.

H-scan analysis of thyroid lesions.

The H-scan analysis of ultrasound images is a matched-filter approach derived from analysis of scattering from incident pulses in the form of Gaussian-weighted Hermite polynomial functions. This framework is applied in a preliminary study of thyroid lesions to examine the H-scan outputs for three categories: normal thyroid, benign lesions, and cancerous lesions within a total group size of 46 patients. In addition, phantoms comprised of spherical scatterers are analyzed to establish independent reference values for comparison. The results demonstrate a small but significant difference in some measures of the H-scan channel outputs between the different groups.

Experimental Implementation of a Pulse Compression Technique Using Coherent Plane-Wave Compounding.

The axial resolution of an ultrasound imaging system is inversely proportional to the bandwidth of the emitted signal. When conventional pulsing (CP) is used, the impulse response of the transducer and the excitation signal determine together the shape of the emitted pulse and its bandwidth. A way to increase the ultrasound image resolution is to increase the transducer's limited passband. The resolution enhancement compression (REC) is a coding technique that boosts the signal energy in the transition frequency bands, where the energy transduction of the ultrasound probe is less efficient. Consequently, image quality metrics including axial resolution, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) can be improved. In this paper, the objective is to combine REC with coherent plane-wave compounding (CPWC) in order to achieve better image quality at an ultrafast acquisition rate. Promising results are obtained from both wire and cyst phantoms using an excitation signal designed to provide a 54% increase in bandwidth over the one obtained with a broadband pulse excitation at -6 dB. The experimental bandwidth measured from the backscattered echoes was improved by 49% for the wire phantom, when using the CPWC-REC technique compared to CPWC-CP. Furthermore, the axial resolution as derived from the modulation transfer function of the envelope of the wire target was enhanced by 29%. The CNR and SNR were improved up to 9 and up to 4 dB, respectively, in the cyst phantom. These results reveal that CPWC-REC is able to achieve higher spatial resolution, compared to CPWC-CP, with better SNR and CNR. Moreover, experimental results show that an effective implementation on a research scanner of REC using plane-wave imaging is possible. Consistent in vivo acquisition results on rabbit are presented and discussed.

Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ultrasound has proved to be a useful tool to detect lung consolidation as evidence of pneumonia. However, diagnosis of pneumonia by ultrasound has limitations: it is operator-dependent, and it needs to be carried out and interpreted by trained personnel. Pattern recognition and image analysis is a potential tool to enable automatic diagnosis of pneumonia consolidation without requiring an expert analyst. This paper presents a method for automatic classification of pneumonia using ultrasound imaging of the lungs and pattern recognition. The approach presented here is based on the analysis of brightness distribution patterns present in rectangular segments (here called "characteristic vectors") from the ultrasound digital images. In a first step we identified and eliminated the skin and subcutaneous tissue (fat and muscle) in lung ultrasound frames, and the "characteristic vectors"were analyzed using standard neural networks using artificial intelligence methods. We analyzed 60 lung ultrasound frames corresponding to 21 children under age 5 years (15 children with confirmed pneumonia by clinical examination and X-rays, and 6 children with no pulmonary disease) from a hospital based population in Lima, Peru. Lung ultrasound images were obtained using an Ultrasonix ultrasound device. A total of 1450 positive (pneumonia) and 1605 negative (normal lung) vectors were analyzed with standard neural networks, and used to create an algorithm to differentiate lung infiltrates from healthy lung. A neural network was trained using the algorithm and it was able to correctly identify pneumonia infiltrates, with 90.9% sensitivity and 100% specificity. This approach may be used to develop operator-independent computer algorithms for pneumonia diagnosis using ultrasound in young children.

Sound scattering from two concentric fluid spheres (L).

The solution to the problem of plane wave and point source scattering by two concentric fluid spheres is derived. The effect of differences in sound speed, density, and absorption coefficient is taken into account. The scattered field is then found in the limit as the outer sphere becomes an infinitely thin shell and compared to the solution for a single fluid sphere for verification. A simulation is then performed using the concentric fluid sphere solution as an approximation to the human head and compared to the solution of a single fluid sphere with the properties of either bone or water. The solutions were found to be similar outside of the spheres but differ significantly inside the spheres.

Measurement of surface acoustic waves in high-frequency ultrasound: Preliminary results.

Skin lesions change elastic properties near the surface. In the last decades, several non-invasive elastography techniques have been developed for detecting the mechanical properties of tissue. In particular, harmonic elastography is characterized for inducing shear wave propagation by an external vibrator in order to estimate shear modulus. However, near the boundary region, propagation is governed by surface acoustic waves (SAW). This paper combines crawling waves elastography with a high-frequency ultrasound (HFUS) system for the estimation of the SAW-to-shear compensation factor when ultrasound (US) gel is used as coupling interface. Experiments explore the SAWspeed in a homogeneous phantom with a solid-water interface in order to corroborate theoretical findings. Subsequently, experiments in a solid-US gel interface are conducted in order to find the correct compensation factor. Preliminary results suggest that SAW propagation can be detected using HFUS, and shear velocity maps can be generated by applying the estimated empirical correction factor. This study will potentially avoid the underestimation of shear modulus when using SAW-based HFUS elastography which is promising for the better diagnosis of skin diseases.

A regularized inverse approach to ultrasonic pulse-echo imaging.

An inverse-theoretic approach to ultrasonic pulse-echo imaging based on nonquadratic regularization is presented, and its effectiveness is investigated computationally by: 1) evaluating the quality of the reconstruction of speckle-based images as a function of the transmit-receive bandwidth and focal number of the transducer; 2) comparing the reconstructed images with those obtained by using conventional B-mode imaging. The L-curve and the generalized cross-validation methods were evaluated as automatic regularization parameter selection techniques. The inversion using regularization produced better results than conventional B-mode imaging for high signal-to-noise ratios (SNRs). A lower bound of 30 dB for the SNR was found for this study, below which several of the image features were lost during the reconstruction process in order to control the distortion due to the noise.