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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Shear Wave Speed Measurements Using Crawling Wave Sonoelastography and Single Tracking Location Shear Wave Elasticity Imaging for Tissue Characterization.

Elastography provides tissue stiffness information that attempts to characterize the elastic properties of tissue. However, there is still limited literature comparing elastographic modalities for tissue characterization. This study focuses on two quantitative techniques using different vibration sources that have not been compared to date: crawling wave sonoelastography (CWS) and single tracking location shear wave elasticity imaging (STL-SWEI). To understand each technique's performance, shear wave speed (SWS) was measured in homogeneous phantoms and ex vivo beef liver tissue. Then, the contrast, contrast-to-noise ratio (CNR), and lateral resolution were measured in an inclusion and two-layer phantoms. The SWS values obtained with both modalities were validated with mechanical measurements (MM) which serve as ground truth. The SWS results for the three different homogeneous phantoms (10%, 13%, and 16% gelatin concentrations) and ex vivo beef liver tissue showed good agreement between CWS, STL-SWEI, and MM as a function of frequency. For all gelatin phantoms, the maximum accuracy errors were 2.52% and 2.35% using CWS and STL-SWEI, respectively. For the ex vivo beef liver, the maximum accuracy errors were 9.40% and 7.93% using CWS and STL-SWEI, respectively. For lateral resolution, contrast, and CNR, both techniques obtained comparable measurements for vibration frequencies less than 300 Hz (CWS) and distances between the push beams ( ∆x ) between 3 mm and 5.31 mm (STL-SWEI). The results obtained in this study agree over an SWS range of 1-6 m/s. They are expected to agree in perfectly linear, homogeneous, and isotropic materials, but the SWS overlap is not guaranteed in all materials because each of the three methods have unique features.

In Vivo Estimation of Attenuation and Backscatter Coefficients From Human Thyroids.

Fine-needle aspiration (FNA) remains the gold standard for the diagnosis of thyroid cancer. However, currently, a large number of FNA biopsies result in negative or undetermined diagnosis, which suggests that better noninvasive tools are needed for the clinical management of thyroid cancer. Spectral-based quantitative ultrasound (QUS) characterizations may offer a better diagnostic management as previously demonstrated in mouse cancer models ex vivo. As a first step toward understanding the potential of QUS markers for thyroid disease management, this paper deals with the spectral-based QUS estimation of healthy human thyroids in vivo. Twenty volunteers were inspected by a trained radiologist using two ultrasonic imaging systems, which allowed them to acquire radio-frequency data spanning the 3-16-MHz frequency range. Estimates of attenuation coefficient slope (ACS) using the spectral logarithmic difference method had an average value of [Formula: see text]) with a standard deviation of [Formula: see text]. Estimates of backscatter coefficient (BSC) using the reference-phantom method had an average value of [Formula: see text] over the useful frequency range. The intersubject variability when estimating BSCs was less than 1.5 dB over the analysis frequency range. Further, the effectiveness of three scattering models (i.e., fluid sphere, Gaussian, and exponential form factors) when fitting the experimentally estimated BSCs was assessed. The exponential form factor was found to provide the best overall goodness of fit ( R2 = 0.917), followed by the Gaussian ( R2 = 0.807) and the fluid-sphere models ( R2 = 0.752). For all scattering models used in this study, average estimates of the effective scatterer diameter were between 44 and 56 µm. Overall, an excellent agreement in the estimated attenuation and BSCs with both scanners was exhibited.

Tissue characterization using simultaneous estimation of backscatter coefficient and elastic shear modulus.

Tissue characterization using quantitative ultrasound (QUS) parameters has received significant attention in recent years due to its potential to improve the detection and diagnosis of diseased states. However, the vast majority of studies in QUS tissue typing have used parameters derived from either longitudinal or shear waves in isolation, thereby discarding potentially useful complementary information these parameters may carry. In this study, the simultaneous estimation of backscatter coefficients (derived from longitudinal waves) and shear modulus (derived from shear waves) was implemented on data from a clinical scanner. Both parameters were estimated from five ex vivo porcine kidney samples and used to calculate the anisotropy ratio in the parameters when analyzing the middle and pole regions of the kidneys. For all samples, the estimated parameters were higher in the pole regions than in the middle region, with anisotropy ratios of 1.42±0.11 and 3.07±0.70 for the shear modulus and the backscatter coefficient, respectively. Therefore, these results demonstrate that QUS parameters derived from both longitudinal and shear waves can be estimated simultaneously and may be used in conjunction to track changes in tissue structure and composition.

Effects of phase aberration correction methods on the minimum variance beamformer.

The minimum variance (MV) beamformer is a method that has the potential to enhance the resolution and contrast of ultrasound images. However, it suffers from sensitivity to speed of sound errors and aberration. Although there have been several studies on the application of phase aberration correction (PAC) methods to conventional delay-and-sum (DAS) beamforming, the benefits of PAC methods in mitigating the effects of phase aberration in MV beamformed images are not well understood. A study of this type would be helpful in designing a robust beamformer based on PAC knowledge present in the literature. This study analyzes three PAC algorithms (multi-lag cross-correlation, Rigby's beamsum and scaled covariance matrix) and their impact on the performance of the MV beamformer in the presence of second order phase aberrations. The PAC methods in combination with the MV beamformer were tested on simulated and experimental data corrupted with an electronically created near field phase aberrator. It is shown that all gains in performance of the MV beamformer with respect to DAS is lost at high aberration strengths. For instance, at 60 ns of aberration the lateral resolution of DAS degrades by 22% while MV degrades by 600%. It is also shown that basic PAC methods improve the aberrated MV beamformer. PAC methods reduces degradation in lateral resolution from 600% to 5%. Similar improvements are observed in peak sidelobe level (96% to 27%), contrast (88% to 49% for the simulations and 43% to 15% for experiments) and contrast-to-noise ratio (86% to 42% for the simulations and 68% to 55% for experiments). These enhancements allow the MV beamformer to outperform DAS even in the strongest aberration case.

Automatic pneumonia detection based on ultrasound video analysis.

Pneumonia is a disease which causes high mortality in children under five years old, particularly in developing countries. This paper proposes a novel application of ultrasound video analysis for the detection of pneumonia. This application is based on the processing of small video chunks, in which an image processing algorithm analyzes each frame to get some overall video statistics. Then, based on these quantities, the likeness of presence of pneumonia in the video is determined. The algorithm exploits different geometrical properties of typical anatomical and pathological features that commonly appear in lung sonography and which are already clinically typified in the literature. Our technique has been tested on different transverse thoracic scanning protocols and probe's maneuvers, thus, under a variety of clinical and usage protocols. Then, it can be targeted towards screening applications. We present encouraging results (AUC measure between 0.7851 and 0.9177) based on the analysis of 346 videos with an average duration of eight seconds. The analyzed videos were taken from children who were between three and five years old. Finally, our algorithm can be used directly as a classifier, but we detail how its performance may be enhanced if used as a first stage of a larger pipeline of other complementary pneumonia detection processes.

Evaluation of a frequency-domain ultrasonic imaging attenuation compensation technique.

Ultrasound attenuation is typically compensated for in clinical scanners by using time gain compensation (TGC). However, TGC operates in a frequency-independent fashion and therefore the spatial resolution of the echographic images degrades as the examination depth increases. In the current study, the capability of a multi-band attenuation compensation (MBAC) TGC technique to recover both magnitude and spatial resolution in lossy media was evaluated. Simulations were performed using a 5-MHz transducer for imaging point targets embedded in a medium with attenuation coefficient slope (ACS) of 0.5 dB/(cm.MHz). For performance assessment, the magnitude and spatial resolution of the reflected point spread functions (PSFs) were compared to the ones obtained from point targets embedded in a lossless medium. The results showed a complete recovery of the spectral content when using MBAC for all depths when compared to the lossless case. Both the magnitude and spatial resolution of the compensated PSFs were in agreement with the lossless result (i.e., less than 1 dB and 3 % difference in PSF magnitude and spatial resolution, respectively). The MBAC was then applied to in vivo liver imaging using a scanner equipped with a 5-MHz linear array. Attenuation compensation was performed using ACSs reported in the literature for skin, fat and muscle, and experimentally estimated ACS using the spectral log difference technique for the liver. The lateral and axial extent of the autocorrelation function was estimated in the liver tissue. The experimental MBAC image exhibited only 6 % and 11 % variation in speckle magnitude and lateral autocorrelation length for depths between 2.5 and 4 cm. These results suggest that MBAC technique may enhance speckle uniformity in homogeneous tissue regions.

Effects of data acquisition parameters on the quality of sonoelastographic imaging.

Sonoelastography is an ultrasonic technique that provides qualitative and quantitative images of tissue elasticity. Even though the Kasai variance estimator is a key part of the sonoelastographic image formation, there are no studies that demonstrate that its performance using discrete time signals and finite sized ensemble lengths is optimal. In this work, the influence of the selection of acquisition parameters (pulse repetition frequency or PRF, vibration frequency, and ensemble length) on the quality of the elastograms is studied. Simulations are carried out to define the optimal PRF and ensemble length given a vibration frequency in order to avoid artifacts which can severely degrade image quality. This empirical criterion is supported by sonoelastography experiments performed using two commercial scanners, where the variability increased from 4% to 42% at the worst selection of acquisition parameters. Although a further mathematical proof of the empirical findings is required, these results suggest that careful selection of PRF, vibration frequency and ensemble lengths is required to ensure unbiased sonoelastograms.

Experimental evaluation of spectral-based quantitative ultrasound imaging using plane wave compounding.

Quantitative ultrasound (QUS) based on backscatter coefficient (BSC) estimation has shown potential for tissue characterization. Beamforming using plane wave compounding has advantages for echographic, Doppler, and elastographic imaging; however, to date, plane wave compounding has not been experimentally evaluated for the purpose of BSC estimation. In this study, two BSC-derived parameters (i.e., the BSC midband fit and intercept) were estimated from experimental data obtained using compound plane wave beamforming. For comparison, QUS parameters were also estimated from data obtained using both fixed focus and dynamic receive beamforming. An ultrasound imaging system equipped with a 9-MHz center frequency, 64-element array was used to collect data up to a depth of 45 mm. Two gelatin phantoms with randomly distributed 20-µm inclusions with a homogeneous scatterer concentration and a two-region scatterer concentration were used for assessing the precision and lateral resolution of QUS imaging, respectively. The use of plane wave compounding resulted in accurate QUS estimation (i.e., bias in the BSC parameters of less than 2 dB) and relatively constant lateral resolution (i.e., BSC midband fit 10% to 90% rise distance ranging between 1.0 and 1.5 mm) throughout a 45 mm field of view. Although both fixed focus and dynamic receive beamforming provided the same performance around the focal depth, the reduction in SNR away from the focus resulted in a reduced field of view in the homogeneous phantom (i.e., only 28 mm). The lateral resolution also degraded away from the focus, with up to a 2-fold and 10-fold increase in the rise distance at 20 mm beyond the focal depth for dynamic receive and fixed focus beamforming, respectively. These results suggest that plane wave compounding has the potential to improve the performance of spectral-based quantitative ultrasound over other conventional beamforming strategies.