Ultrasonic fat fraction quantification using in vivo adaptive sound speed estimation

Real-Time Speed-of-Sound Estimation In Vivo via Steered Plane Wave Ultrasound

Speed-of-sound (SoS) is an intrinsic acoustic property of human tissues and has been regarded as a potential biomarker of tissue health. To foster the clinical use of this emerging biomarker in medical diagnostics, it is important for SoS estimates to be derived and displayed in real time. Here, we demonstrate that concurrent global SoS estimation and B-mode imaging can be achieved live on a portable ultrasound scanner. Our innovation is hinged upon the design of a novel pulse-echo SoS estimation framework that is based on steered plane wave imaging. It has accounted for the effects of refraction and imaging depth when the medium SoS differs from the nominal value of 1540 m/s that is conventionally used in medical imaging. The accuracy of our SoS estimation framework was comparatively analyzed with through-transmit time-of-flight measurements in vitro on 15 custom agar phantoms with different SoS values (1508-1682 m/s) and in vivo on human calf muscles ( N = 9 ; SoS range: 1560-1586 m/s). Our SoS estimation framework has a mean signed difference (MSD) of - 0.6 ± 2.3 m/s in vitro and - 2.2 ± 11.2 m/s in vivo relative to the reference measurements. In addition, our real-time system prototype has yielded simultaneous SoS estimates and B-mode imaging at an average frame rate of 18.1 fps. Overall, by realizing real-time tissue SoS estimation with B-mode imaging, our innovation can foster the use of tissue SoS as a biomarker in medical ultrasound diagnostics.

A New Method of Plane-Wave Ultrasound Imaging Based on Reverse Time Migration

Coherent plane-wave compounding technique enables rapid ultrasound imaging with comparable image quality to traditional B-mode imaging that relies on focused beam transmission. However, existing methods assume homogeneity in the imaged medium, neglecting the heterogeneity in sound velocities and densities present in real tissues, resulting in noise reverberation. This study introduces the Reverse Time Migration (RTM) method for ultrasound plane-wave imaging to overcome this limitation, which is combined with a method for estimating the speed of sound in layered media. Simulation results in a homogeneous background demonstrate that RTM reduces side lobes and grating lobes by approximately 30 dB, enhancing the contrast-to-noise ratio by 20% compared to conventional delay and sum (DAS) beamforming. Moreover, RTM achieves superior imaging outcomes with fewer compounding angles. The lateral resolution of the RTM with 5-9 angle compounding is able to achieve the effectiveness of the DAS method with 15-19 angle compounding, and the CNR of the RTM with 11-angle compounding is almost the same as that of the DAS with 21-angle compounding. In a heterogeneous background, experimental simulations and in vitro wire phantom experiments confirm RTM's capability to correct depth imaging, focusing reflected waves on point targets. In vitro porcine tissue experiments enable accurate imaging of layer interfaces by estimating the velocities of multiple layers containing muscle and fat. The proposed imaging procedure optimizes velocity estimation in complex media, compensates for the impact of velocity differences, provides more reliable imaging results.

Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound

In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current state-of-the-art methods relate the tissue speed of sound to local echo shifts computed between images that are beamformed using restricted transmit and receive apertures. However, the aperture limitation affects the robustness of phase-shift estimations and, consequently, the accuracy of reconstructed speed-of-sound maps. Here, we propose a method based on the Radon transform of image patches able to estimate local phase shifts from full-aperture images. We validate our technique on simulated, phantom and in-vivo data acquired on a liver and compare it with a state-of-the-art method. We show that the proposed method enhances the stability to changes of beamforming speed of sound and to a reduction of the number of insonifications. In particular, the deployment of pulse-echo speed-of-sound estimation methods onto portable ultrasound devices can be eased by the reduction of the number of insonifications allowed by the proposed method.

Ultrasonic Sound Speed Estimation for Liver Fat Quantification: A Review by the AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative

Non-alcoholic fatty liver disease (NAFLD) is a significant cause of diffuse liver disease, morbidity and mortality worldwide. Early and accurate diagnosis of NALFD is critical to identify patients at risk of disease progression. Liver biopsy is the current gold standard for diagnosis and prognosis. However, a non-invasive diagnostic tool is desired because of the high cost and risk of complications of tissue sampling. Medical ultrasound is a safe, inexpensive and widely available imaging tool for diagnosing NAFLD. Emerging sonographic tools to quantitatively estimate hepatic fat fraction, such as tissue sound speed estimation, are likely to improve diagnostic accuracy, precision and reproducibility compared with existing qualitative and semi-quantitative techniques. Various pulse-echo ultrasound speed of sound estimation methodologies have been investigated, and some have been recently commercialized. We review state-of-the-art in vivo speed of sound estimation techniques, including their advantages, limitations, technical sources of variability, biological confounders and existing commercial implementations. We report the expected range of hepatic speed of sound as a function of liver steatosis and fibrosis that may be encountered in clinical practice. Ongoing efforts seek to quantify sound speed measurement accuracy and precision to inform threshold development around meaningful differences in fat fraction and between sequential measurements.

Excluding Echo Shift Noise in Real-Time Pulse-Echo Speed-of-Sound Imaging

Computed ultrasound tomography in echo mode (CUTE) allows real-time imaging of the tissue speed of sound (SoS) using handheld ultrasound. The SoS is retrieved by inverting a forward model that relates the spatial distribution of the tissue SoS to echo shift maps detected between varying transmit and receive angles. Despite promising results, in vivo SoS maps often show artifacts due to elevated noise in echo shift maps. To minimize artifacts, we propose a technique where an individual SoS map is reconstructed for each echo shift map separately, as opposed to a single SoS map from all echo shift maps simultaneously. The final SoS map is then obtained as a weighted average over all SoS maps. Due to the partial redundancy between different angle combinations, artifacts that appear only in a subset of the individual maps can be excluded via the averaging weights. We investigate this real-time capable technique in simulations using two numerical phantoms, one with a circular inclusion and one with two layers. Our results demonstrate that the SoS maps reconstructed using the proposed technique are equivalent to the ones using simultaneous reconstruction when considering uncorrupted data but show significantly reduced artifact level for data that are corrupted by noise.

Sound Speed Estimation for Distributed Aberration Correction in Laterally Varying Media

Spatial variation in sound speed causes aberration in medical ultrasound imaging. Although our previous work has examined aberration correction in the presence of a spatially varying sound speed, practical implementations were limited to layered media due to the sound speed estimation process involved. Unfortunately, most models of layered media do not capture the lateral variations in sound speed that have the greatest aberrative effect on the image. Building upon a Fourier split-step migration technique from geophysics, this work introduces an iterative sound speed estimation and distributed aberration correction technique that can model and correct for aberrations resulting from laterally varying media. We first characterize our approach in simulations where the scattering in the media is known a-priori. Phantom and in-vivo experiments further demonstrate the capabilities of the iterative correction technique. As a result of the iterative correction scheme, point target resolution improves by up to a factor of 4 and lesion contrast improves by up to 10.0 dB in the phantom experiments presented.

Speed-of-sound estimation in ultrasound propagation medium by considering size of target scatterer

PURPOSE

Accurate speed-of-sound (SoS) estimation in an ultrasound propagation medium improves imaging quality and contributes to better diagnosis of diseases. In conventional time-delay-based SoS estimation approaches studied by several groups, a received wave is assumed to be scattered from an ideal point scatterer. In these approaches, the SoS is overestimated when the target scatterer has a non-negligible size. In this paper, we propose the SoS estimation method that considers target size.

METHODS

In the proposed method, the error ratio of the estimated SoS using the conventional time-delay-based approach is determined from measurable parameters using the geometric relationship between the received elements and target. Subsequently, the SoS erroneously estimated using conventional estimation, assuming the ideal point scatterer as a target, is corrected by the determined estimation error ratio. To validate the proposed method, the SoS in water was estimated for several wire sizes.

RESULTS

The SoS in the water was overestimated using the conventional SoS estimation method, with a maximum positive error of 38 m/s. The proposed method corrected the SoS estimates, and the errors were suppressed to within 6 m/s, irrespective of the wire diameter.

CONCLUSION

The present results demonstrate that the proposed method can estimate the SoS by considering the target size without using information on the true SoS, true target depth, and true target size, which is applicable to in vivo measurements.

Ultrasound-based hepatic fat quantification: current status and future directions

Non-alcoholic fatty liver disease (NAFLD) is a spectrum of disease from fatty accumulation (steatosis), necro-inflammation though to fibrosis. It is of increasing global prevalence as a hepatic manifestation of the metabolic syndrome. Although accurate histopathology and magnetic resonance imaging techniques for hepatic fat quantification exist, these are limited by invasiveness and availability, respectively. Ultrasonography is potentially ideal for assessing and monitoring hepatic steatosis given the examination is rapid and readily available. Traditional ultrasound methods include qualitative B-mode for imaging markers, such as increased hepatic parenchymal echogenicity compared to adjacent renal cortex are commonplace; however, there is acknowledged significant interobserver variability and they are suboptimal for detecting mild steatosis. Recently quantitative ultrasound metrics have been investigated as biomarkers for hepatic steatosis. These methods rely on changes in backscatter, attenuation, and speed of sound differences encountered in a steatotic liver. Prospective studies using quantitative ultrasound parameters show good diagnostic performance even at low steatosis grades and in NAFLD. This review aims to define the clinical need for ultrasound-based assessments of liver steatosis, to describe briefly the physics that underpins the various techniques available, and to assess the evidence base for the effectiveness of the techniques that are available commercially from various ultrasound vendors.

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.

In vivoadaptive focusing for clinical contrast-enhanced transcranial ultrasound imaging in human

Objective. Imaging the human brain vasculature with high spatial and temporal resolution remains challenging in the clinic today. Transcranial ultrasound is still scarcely used for cerebrovascular imaging, due to low sensitivity and strong phase aberrations induced by the skull bone that only enable the proximal part major brain vessel imaging, even with ultrasound contrast agent injection (microbubbles).Approach. Here, we propose an adaptive aberration correction technique for skull bone aberrations based on the backscattered signals coming from intravenously injected microbubbles. Our aberration correction technique was implemented to image brain vasculature in human adults through temporal and occipital bone windows. For each subject, an effective speed of sound, as well as a phase aberration profile, were determined in several isoplanatic patches spread across the image. This information was then used in the beamforming process.Main results. This aberration correction method reduced the number of artefacts, such as ghost vessels, in the images. It improved image quality both for ultrafast Doppler imaging and ultrasound localization microscopy (ULM), especially in patients with thick bone windows. For ultrafast Doppler images, the contrast was increased by 4 dB on average, and for ULM, the number of detected microbubble tracks was increased by 38%.Significance. This technique is thus promising for better diagnosis and follow-up of brain pathologies such as aneurysms, arterial stenoses, arterial occlusions, microvascular disease and stroke and could make transcranial ultrasound imaging possible even in particularly difficult-to-image human adults.

Optimization of reconstruction time of ultrasound computed tomography with a piecewise homogeneous region-based refract-ray model

In this article, a novel ultrasound computed tomography (USCT) reconstruction algorithm for breast imaging is proposed. This algorithm is based on an ultrasound propagation model, the refract-ray model (RRM). In this model, the field of imaging is assumed as piecewise homogenous and is divided into several regions. The ultrasound propagation paths are considered polylines that only refract at the borders of the regions. The edge information is provided by B-mode imaging. Both simulations and experiments are implemented to validate the proposed algorithm. Compared with the traditional bent-ray model (BRM), the time of reconstructions using RRM decreases by over 90 %. In simulations, the imaging qualities for RRM and BRM are comparable, in terms of the root mean square error, the Tenengrad value, and the deformation of digital phantom. In the experiments, a cylindrical agar phantom is imaged using a customized imaging system. When imaging using RRM, the estimate of the phantom radius is about 0.1 mm in error, while it is about 0.3 mm in error using BRM. Moreover, the Tenengrad value of the result using RRM is much higher than that using BRM (9.76 compared to 0.79). The results show that the proposed algorithm can better delineate the phantom within a water bath. In future work, further experimental work is required to validate the method for improving imaging quality under breast-mimicking imaging conditions.

Pulse-Echo Quantitative US Biomarkers for Liver Steatosis: Toward Technical Standardization

Excessive liver fat (steatosis) is now the most common cause of chronic liver disease worldwide and is an independent risk factor for cirrhosis and associated complications. Accurate and clinically useful diagnosis, risk stratification, prognostication, and therapy monitoring require accurate and reliable biomarker measurement at acceptable cost. This article describes a joint effort by the American Institute of Ultrasound in Medicine (AIUM) and the RSNA Quantitative Imaging Biomarkers Alliance (QIBA) to develop standards for clinical and technical validation of quantitative biomarkers for liver steatosis. The AIUM Liver Fat Quantification Task Force provides clinical guidance, while the RSNA QIBA Pulse-Echo Quantitative Ultrasound Biomarker Committee develops methods to measure biomarkers and reduce biomarker variability. In this article, the authors present the clinical need for quantitative imaging biomarkers of liver steatosis, review the current state of various imaging modalities, and describe the technical state of the art for three key liver steatosis pulse-echo quantitative US biomarkers: attenuation coefficient, backscatter coefficient, and speed of sound. Lastly, a perspective on current challenges and recommendations for clinical translation for each biomarker is offered.

Carbon nanotube-based, serially connected terahertz sensor with enhanced thermal and optical efficiencies

Owing to their high thermal and optical performances, carbon nanotube (CNT) films are used in various photo-thermo-electric (PTE) applications, such as terahertz (THz) sensing and energy harvesting. To improve the performance of PTE devices, a device structure should be designed based on a deep understanding of the thermal and optical responses of the CNT film. However, the optical properties of CNT films in the THz frequency region remain unclear because of the difficulties associated with device processing and measurements. Herein, we report our findings on the thermal and optical characteristics of CNT films. The shape of the CNT film that maximizes the product of the thermal and optical factors (optimal structure of the PTE sensor) depends on the frequency of the irradiating electromagnetic wave. The optimal film thickness and width values for THz irradiation range from 300-600 nm and 50-70 µm, respectively. Subsequently, we fabricated a serially connected, multi-element PTE sensor with an optimal device structure and enhanced the detection sensitivity by approximately 13 times compared with a single-element PTE sensor. In addition, we demonstrated the first THz spectroscopy application using a PTE sensor. The findings of this study, thermal/optical factor enhancement, and micro-sized CNT film processing technology can be used to improve the performance of all CNT-based photothermal devices, including PTE sensors and thermoelectric generators.

Conventional and artificial intelligence-based imaging for biomarker discovery in chronic liver disease

Chronic liver diseases, resulting from chronic injuries of various causes, lead to cirrhosis with life-threatening complications including liver failure, portal hypertension, hepatocellular carcinoma. A key unmet medical need is robust non-invasive biomarkers to predict patient outcome, stratify patients for risk of disease progression and monitor response to emerging therapies. Quantitative imaging biomarkers have already been developed, for instance, liver elastography for staging fibrosis or proton density fat fraction on magnetic resonance imaging for liver steatosis. Yet, major improvements, in the field of image acquisition and analysis, are still required to be able to accurately characterize the liver parenchyma, monitor its changes and predict any pejorative evolution across disease progression. Artificial intelligence has the potential to augment the exploitation of massive multi-parametric data to extract valuable information and achieve precision medicine. Machine learning algorithms have been developed to assess non-invasively certain histological characteristics of chronic liver diseases, including fibrosis and steatosis. Although still at an early stage of development, artificial intelligence-based imaging biomarkers provide novel opportunities to predict the risk of progression from early-stage chronic liver diseases toward cirrhosis-related complications, with the ultimate perspective of precision medicine. This review provides an overview of emerging quantitative imaging techniques and the application of artificial intelligence for biomarker discovery in chronic liver disease.

Spatial Coherence in Medical Ultrasound: A Review

Traditional pulse-echo ultrasound imaging heavily relies on the discernment of signals based on their relative magnitudes but is limited in its ability to mitigate sources of image degradation, the most prevalent of which is acoustic clutter. Advances in computing power and data storage have made it possible for echo data to be alternatively analyzed through the lens of spatial coherence, a measure of the similarity of these signals received across an array. Spatial coherence is not currently explicitly calculated on diagnostic ultrasound scanners but a large number of studies indicate that it can be employed to describe image quality, to adaptively select system parameters and to improve imaging and target detection. With the additional insights provided by spatial coherence, it is poised to play a significant role in the future of medical ultrasound. This review details the theory of spatial coherence in pulse-echo ultrasound and key advances made over the last few decades since its introduction in the 1980s.

Reverberation clutter signal suppression in ultrasound attenuation estimation using wavelet-based robust principal component analysis

Objective. Ultrasound attenuation coefficient estimation (ACE) has diagnostic potential for clinical applications such as quantifying fat content in the liver. Previously, we have proposed a system-independent ACE technique based on spectral normalization of different frequencies, called the reference frequency method (RFM). This technique does not require a well-calibrated reference phantom for normalization. However, this method may be vulnerable to severe reverberation clutter introduced by the body wall. The clutter superimposed on liver echoes may bias the estimation. Approach. We proposed to use robust principal component analysis, combined with wavelet-based sparsity promotion, to suppress the severe reverberation clutters. The capability to mitigate the reverberation clutters was validated through phantom and in vivo studies. Main Results. In the phantom studies with added reverberation clutters, higher normalized cross-correlation and smaller mean absolute errors were attained as compared to RFM results without the proposed method, demonstrating the capability to reconstruct tissue signals from reverberations. In a pilot patient study, the correlation between ACE and proton density fat fraction (PDFF), a measurement of liver fat by MRI as a reference standard, was investigated. The proposed method showed an improvement of the correlation (coefficient of determination, R = 0.82) as compared with the counterpart without the proposed method (R = 0.69). Significance: The proposed method showed the feasibility of suppressing the reverberation clutters, providing an important basis for the development of a robust ACE with large reverberation clutters.

Distributed Aberration Correction Techniques Based on Tomographic Sound Speed Estimates

Phase aberration is widely considered a major source of image degradation in medical pulse-echo ultrasound. Traditionally, near-field phase aberration correction techniques are unable to account for distributed aberrations due to a spatially varying speed of sound in the medium, while most distributed aberration correction techniques require the use of point-like sources and are impractical for clinical applications where diffuse scattering is dominant. Here, we present two distributed aberration correction techniques that utilize sound speed estimates from a tomographic sound speed estimator that builds on our previous work with diffuse scattering in layered media. We first characterize the performance of our sound speed estimator and distributed aberration correction techniques in simulations where the scattering in the media is known a priori. Phantom and in vivo experiments further demonstrate the capabilities of the sound speed estimator and the aberration correction techniques. In phantom experiments, point target resolution improves from 0.58 to 0.26 and 0.27 mm, and lesion contrast improves from 17.7 to 23.5 and 25.9 dB, as a result of distributed aberration correction using the eikonal and wavefield correlation techniques, respectively.

A Preliminary Study of Liver Fat Quantification Using Reported Ultrasound Speed of Sound and Attenuation Parameters

The quantification of liver fat as a diagnostic assessment of steatosis remains an important priority for non-invasive imaging systems. We derive a framework in which the unknown fat volume percentage can be estimated from a pair of ultrasound measurements. The precise estimation of ultrasound speed of sound and attenuation within the liver is found to be sufficient for estimating fat volume assuming a classic model of the properties of a composite elastic material. In this model, steatosis is represented as a random dispersion of spherical fat vacuoles with acoustic properties similar to those of edible oils. Using values of speed of sound and attenuation from the literature in which normal and steatotic livers were studied near 3.5 MHz, we describe agreement of the new estimation method with independent measures of fat. This framework holds the potential for translation to clinical scanners with which the two ultrasound measurements can be made and used for improved quantitative assessment of steatosis.

Local Sound Speed Estimation for Pulse-Echo Ultrasound in Layered Media

Our previous methodology in local sound speed estimation utilized time delays measured by the cross correlation of delayed full-synthetic aperture channel data to estimate the average speed of sound. However, focal distortions in this methodology lead to biased estimates of the average speed of sound, which, in turn, leads to biased estimates of the local speed of sound. Here, we demonstrate the bias in the previous methodology and introduce a coherence-based average sound speed estimator that eliminates this bias and is computationally much cheaper in practice. Because this coherence-based approach estimates the average sound speed in the medium over an equally spaced grid in depth rather than time, we derive a refined model that relates the local and average speeds of sound as a function of depth in layered media. A fast, closed-form inversion of this model yields highly accurate local sound speed estimates. The root-mean-square (rms) error of local sound speed reconstruction in simulations of two-layer media is 4.6 and 2.5 m/s at 4 and 8 MHz, respectively. This work examines the impact of frequency, f -number, aberration, and reverberation on sound speed estimation. Phantom and in vivo experiments in rats further validate the coherence-based sound speed estimator.

Noninvasive estimation of local speed of sound by pulse-echo ultrasound in a rat model of nonalcoholic fatty liver

Objective. Speed of sound has previously been demonstrated to correlate with fat concentration in the liver. However, estimating speed of sound in the liver noninvasively can be biased by the speed of sound of the tissue layers overlying the liver. Here, we demonstrate a noninvasive local speed of sound estimator, which is based on a layered media assumption, that can accurately capture the speed of sound in the liver. We validate the estimator using an obese Zucker rat model of non-alcoholic fatty liver disease and correlate the local speed of sound with liver steatosis.Approach.We estimated the local and global average speed of sound noninvasively in 4 lean Zucker rats fed a normal diet and 16 obese Zucker rats fed a high fat diet for up to 8 weeks. The ground truth speed of sound and fat concentration were measured from the excised liver using established techniques.Main Results. The noninvasive, local speed of sound estimates of the livers were similar in value to their corresponding 'ground truth' measurements, having a slope ± standard error of the regression of 0.82 ± 0.15 (R²= 0.74 andp< 0.001). Measurement of the noninvasive global average speed of sound did not reliably capture the 'ground truth' speed of sound in the liver, having a slope of 0.35 ± 0.07 (R²= 0.74 andp< 0.001). Decreasing local speed of sound was observed with increasing hepatic fat accumulation (approximately -1.7 m s^-1per 1% increase in hepatic fat) and histopathology steatosis grading (approximately -10 to -13 m s^-1per unit increase in steatosis grade). Local speed of sound estimates were highly correlated with steatosis grade, having Pearson and Spearman correlation coefficients both ranging from -0.87 to -0.78. In addition, a lobe-dependent speed of sound in the liver was observed by theex vivomeasurements, with speed of sound differences of up to 25 m s^-1(p< 0.003) observed between lobes in the liver of the same animal.Significance.The findings of this study suggest that local speed of sound estimation has the potential to be used to predict or assist in the measurement of hepatic fat concentration and that the global average speed of sound should be avoided in hepatic fat estimation due to significant bias in the speed of sound estimate.

The SVD beamformer with diverging waves: a proof-of-concept for fast aberration correction

The rise of ultrafast ultrasound imaging-with plane or diverging waves - paved the way to new applications of ultrasound in biomedical applications. However, propagation through complex layers (typically fat, muscle, and bone) hinder considerably the image quality, especially because of sound speed heterogeneities. In difficult-to-image patients, in the case of the hepatic steatosis for instance, a good image and a reliable sound speed quantification are crucial to provide a powerful non-invasive diagnosis tool. In this work, we proposed to adapt the singular value decomposition (SVD) beamformer method for diverging waves and thus present a novel aberration correction approach for widely used curved arrays. We probed its efficiency experimentally bothin vitroandin vivo. Besides the proposed matrix formalism, we explored the physical meaning of the SVD of ultrafast data. Finally, we demonstrated the ability of the technique to improve the image quality and offer new perspectives particularly in quantitative liver imaging.

Exogenous Drug Disposition as a Diagnostic Biomarker Strategy for Non-Alcoholic Steatohepatitis

Non-alcoholic steatohepatitis (NASH) is the progressive form of non-alcoholic fatty liver disease (NAFLD) and is diagnosed by a liver biopsy. Due to the invasiveness of a biopsy, the majority of patients with NASH are undiagnosed. Additionally, the prevalence of NAFLD and NASH creates the need for a simple screening method to differentiate patients with NAFLD versus NASH. Non-invasive strategies for diagnosing NAFLD versus NASH have been developed, typically relying on imaging techniques and endogenous biomarker panels. However, each technique has limitations, and none can accurately predict the associated functional impairment of drug metabolism and disposition. The function of several drug metabolizing enzymes and drug transporters have been described in NASH that impacts drug pharmacokinetics. The aim of this review is to give an overview of the existing non-invasive strategies to diagnose NASH, and to propose a novel strategy based on altered pharmacokinetics using an exogenous biomarker whose disposition and elimination pathways are directly impacted by disease progression. Altered disposition of safe and relatively inert exogenous compounds may provide the sensitivity and specificity needed to differentiate patients with NAFLD and NASH to facilitate a direct indication of hepatic impairment on drug metabolism and prevent subsequent adverse drug reactions. Significance Statement This review provides an overview of the main non-invasive techniques (imaging and panels of biomarkers) used to diagnose non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) along with a biopsy. Pharmacokinetic changes have been identified in NASH and this review proposes a new approach to predict NASH and the related risk of adverse drug reactions, based on the assessment of drug elimination disruption using exogenous biomarkers.

Speed of sound and shear wave speed for calf soft tissue composition and nonlinearity assessment

Background

The purpose of this study was threefold: (I) to study the correlation of speed-of-sound (SoS) and shear-wave-speed (SWS) ultrasound (US) in the gastrocnemius muscle, (II) to use reproducible tissue compression to characterize tissue nonlinearity effects, and (III) to compare the potential of SoS and SWS for tissue composition assessment.

Methods

Twenty gastrocnemius muscles of 10 healthy young subjects (age range, 23-34 years, two females and eight males) were prospectively examined with both clinical SWS (GE Logiq E9, in m/s) and a prototype system that measures SoS (in m/s). A reflector was positioned opposite the US probe as a timing reference for SoS, with the muscle in between. Reproducible tissue compression was applied by reducing probe-reflector distance in 5 mm steps. The Ogden hyperelastic model and the acoustoelastic theory were used to characterize SoS and SWS variations with tissue compression and extract novel metrics related to tissue nonlinearity. The body fat percentage (BF%) of the subjects was estimated using bioelectrical impedance analysis.

Results

A weak negative correlation was observed between SWS and SoS (r=-0.28, P=0.002). SWS showed an increasing trend with increasing tissue compression (P=0.10) while SoS values decayed nonlinearly (P<0.001). The acoustoelastic modeling showed a weak correlation for SWS (r=-0.36, P<0.001) but a very strong correlation for SoS (r=0.86, P<0.001), which was used to extract the SoS acoustoelastic parameter. SWS showed higher variability between both calves [intraclass correlation coefficient (ICC) =0.62, P=0.08] than SoS (ICC =0.91, P<0.001). Correlations with BF% were strong and positive for SWS (r=0.60, P<0.001), moderate and negative for SoS (r=-0.43, P=0.05), and moderate positive for SoS acoustoelastic parameter (r=0.48, P=0.03).

Conclusions

SWS and SoS provide independent information about tissue elastic properties. SWS correlated stronger with BF% than SoS, but measurements were less reliable. SoS enabled the extraction of novel metrics related to tissue nonlinearity with potential complementary information.

The quantification of liver fat from wave speed and attenuation

A framework is developed for estimating the volume fraction of fat in steatotic livers from viscoelastic measures of shear wave speed and attenuation. These measures are emerging on clinical ultrasound systems' elastography options so this approach can become widely available for assessing and monitoring steatosis. The framework assumes a distribution of fat vesicles as spherical inhomogeneities within the liver and uses a composite rheological model (Christensen 1969J. Mech. Phys. Solids1723-41) to determine the shear modulus as a function of increasing volume of fat within the liver. We show that accurate measurements of shear wave speed and attenuation provide the necessary and sufficient information to solve for the unknown fat volume and the underlying liver stiffness. Extension of the framework to compression wave measurements is also possible. Data from viscoelastic phantoms, human liver studies, and steatotic animal livers are shown to provide reasonable estimates of the volume fraction of fat.

Comparison of ultrasound speed-of-sound of the lower extremity and lumbar muscle assessed with computed tomography for muscle loss assessment

To compare the speed of propagation of ultrasound (US) waves (SoS) of the lower leg with the clinical reference standard computed tomography (CT) at the level of lumbar vertebra 3 (L3) for muscle loss assessment. Both calf muscles of 50 patients scheduled for an abdominal CT were prospectively examined with ultrasound. A plexiglas-reflector located on the opposite side of the probe with the calf in between was used as a timing reference for SoS (m/s). CT measurements were performed at the level of L3 and included area (cm2) and attenuation (HU) of the psoas muscle, abdominal muscles, subcutaneous fat, visceral fat and abdominal area. Correlations between SoS, body mass index (BMI) and CT were determined using Pearson's correlation coefficient. Based on reported CT sarcopenia threshold values, receiver operating characteristic (ROC) analysis was performed for SoS. Inter-examiner agreement was assessed with the median difference, inter-quartile range (IQR) and intraclass correlation coefficients. SoS of the calf correlated moderately with abdominal muscle attenuation (r = 0.48; P < .001), psoas muscle attenuation (r = 0.40; P < .01), abdominal area (r = -0.44; P < .01) and weakly with subcutaneous fat area (r = -0.37; P < .01). BMI correlated weakly with psoas attenuation (r = -0.28; P < .05) and non-significantly with abdominal muscle attenuation. Normalization with abdominal area resulted in moderate correlations with abdominal muscle area for SoS (r = 0.43; P < .01) and BMI (r = -0.46; P < .001). Based on sarcopenia threshold values for skeletal muscle attenuation (SMRA), area under curve (AUC) for SoS was 0.724. Median difference between both examiners was -3.4 m/s with IQR = 15.1 m/s and intraclass correlation coefficient = 0.794. SoS measurements of the calf are moderately accurate based on CT sarcopenia threshold values, thus showing potential for muscle loss quantification.

MRI and muscle imaging for idiopathic inflammatory myopathies

Although idiopathic inflammatory myopathies (IIM) are a heterogeneous group of diseases nearly all patients display muscle inflammation. Originally, muscle biopsy was considered as the gold standard for IIM diagnosis. The development of muscle imaging led to revisiting not only the IIM diagnosis strategy but also the patients' follow-up. Different techniques have been tested or are in development for IIM including positron emission tomography, ultrasound imaging, ultrasound shear wave elastography, though magnetic resonance imaging (MRI) remains the most widely used technique in routine. Whereas guidelines on muscle imaging in myositis are lacking here we reviewed the relevance of muscle imaging for both diagnosis and myositis patients' follow-up. We propose recommendations about when and how to perform MRI on myositis patients, and we describe new techniques that are under development.

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.

CohereNet: A Deep Learning Architecture for Ultrasound Spatial Correlation Estimation and Coherence-Based Beamforming

Deep fully connected networks are often considered "universal approximators" that are capable of learning any function. In this article, we utilize this particular property of deep neural networks (DNNs) to estimate normalized cross correlation as a function of spatial lag (i.e., spatial coherence functions) for applications in coherence-based beamforming, specifically short-lag spatial coherence (SLSC) beamforming. We detail the composition, assess the performance, and evaluate the computational efficiency of CohereNet, our custom fully connected DNN, which was trained to estimate the spatial coherence functions of in vivo breast data from 18 unique patients. CohereNet performance was evaluated on in vivo breast data from three additional patients who were not included during training, as well as data from in vivo liver and tissue mimicking phantoms scanned with a variety of ultrasound transducer array geometries and two different ultrasound systems. The mean correlation between the SLSC images computed on a central processing unit (CPU) and the corresponding DNN SLSC images created with CohereNet was 0.93 across the entire test set. The DNN SLSC approach was up to 3.4 times faster than the CPU SLSC approach, with similar computational speed, less variability in computational times, and improved image quality compared with a graphical processing unit (GPU)-based SLSC approach. These results are promising for the application of deep learning to estimate correlation functions derived from ultrasound data in multiple areas of ultrasound imaging and beamforming (e.g., speckle tracking, elastography, and blood flow estimation), possibly replacing GPU-based approaches in low-power, remote, and synchronization-dependent applications.

In vivo Ultrafast Quantitative Ultrasound and Shear Wave Elastography Imaging on Farm-Raised Duck Livers during Force Feeding

Shear wave elastography (speed and dispersion), local attenuation coefficient slope and homodyned-K parametric imaging were used for liver steatosis grading. These ultrasound biomarkers rely on physical interactions between shear and compression waves with tissues at both macroscopic and microscopic scales. These techniques were applied in a context not yet studied with ultrasound imaging, that is, monitoring steatosis of force-fed duck livers from pre-force-fed to foie gras stages. Each estimated feature presented a statistically significant trend along the feeding process (p values <10^-3). However, whereas a monotonic increase in the shear wave speed was observed along the process, most quantitative ultrasound features exhibited an absolute maximum value halfway through the process. As the liver fat fraction in foie gras is much higher than that seen clinically, we hypothesized that a change in the ultrasound scattering regime is encountered for high-fat fractions, and consequently, care has to be taken when applying ultrasound biomarkers to grading of severe states of steatosis.

System-Independent Ultrasound Attenuation Coefficient Estimation Using Spectra Normalization

Ultrasound attenuation coefficient estimation (ACE) has diagnostic potential for clinical applications such as differentiating tumors and quantifying fat content in the liver. The two commonly used ACE methods in the ultrasound array imaging system are the spectral shift method and the reference-phantom-based methods. The spectra shift method estimates the central frequency downshift along depth, whereas the reference-phantom-based methods use a well-calibrated phantom to cancel system dependent effects in attenuation estimation. In this study, we propose a novel system-independent ACE technique based on spectra normalization of different frequencies. This technique does not require a reference phantom for normalization. The power of each frequency component is normalized by the power of an adjacent frequency component in the spectrum to cancel system-dependent effects, such as focusing and time gain compensation (TGC). This method is referred to as the reference frequency method (RFM), and its performance has been evaluated in phantoms and in vivo liver studies. The RFM technique can be applied to various transducer geometries (e.g., linear or curved arrays) with different beam patterns (e.g., focused or unfocused).