System-Independent Ultrasound Attenuation Coefficient Estimation Using Spectra Normalization

Pulse-echo ultrasound attenuation tomography

Objective.We present the first fully two-dimensional attenuation imaging technique developed for pulse-echo ultrasound systems. Unlike state-of-the-art techniques, which use line-by-line acquisitions, our method uses steered emissions to constrain attenuation values at each location with multiple crossing wave paths, essential to resolve the spatial variations of this tissue property.Approach.At every location, we compute normalized cross-correlations between the beamformed images that are obtained from emissions at different steering angles. We demonstrate that their log-amplitudes provide the changes between attenuation-induced amplitude losses undergone by the different incident waves. This allows us to formulate a linear tomographic problem, which we efficiently solve via a Tikhonov-regularized least-squares approach.Main results.The performance of our tomography technique is first validated in numerical examples and then experimentally demonstrated in custom-made tissue-mimicking phantoms with inclusions of varying size, echogenicity, and attenuation. We show that this technique is particularly good at resolving lateral variations in tissue attenuation and remains accurate in media with varying echogenicity.Significance.Based on a similar principle, this method can be easily combined with computed ultrasound tomography in echo mode for speed-of-sound imaging, paving the way towards a multi-modal ultrasound tomography framework characterizing multiple acoustic tissue properties simultaneously.

Recent Advances in Attenuation Estimation

This chapter reviews some of the recent advances in the estimation of the local and the total attenuation, with an emphasis on reducing the bias and variance of the estimates. A special focus is put on describing the effect of power spectrum estimation on bias and variance, the introduction of regularization strategies, as well as on eliminating the need to use reference phantoms for compensating for system dependent effects.

Regularized Ultrasound Phantom-Free Local Attenuation Coefficient Slope (ACS) Imaging in Homogeneous and Heterogeneous Tissues

Attenuation maps or measurements based on the local attenuation coefficient slope (ACS) in quantitative ultrasound (QUS) have shown potential for the diagnosis of liver steatosis. In liver cancers, tissue abnormalities and tumors detected using ACS are also of interest to provide new image contrast to clinicians. Current phantom-based approaches have the limitation of assuming a comparable speed of sound between the reference phantom and insonified tissues. Moreover, these methods present the inconvenience for operators to acquire data on phantoms and patients. The main goal was to alleviate these drawbacks by proposing a methodology for constructing phantom-free regularized (PF-R) local ACS maps and investigate the performance in both homogeneous and heterogeneous media. The proposed method was tested on two tissue-mimicking media with different ACS constructed as homogeneous phantoms, side-by-side and top-to-bottom phantoms, and inclusion phantoms with different attenuations. Moreover, an in vivo proof-of-concept was performed on healthy, steatotic, and cancerous human liver datasets. Modifications brought to previous works include: 1) a linear interpolation of the power spectrum in the log scale; 2) the relaxation of the underlying hypothesis on the diffraction factor; 3) a generalization to nonhomogeneous local ACS; and 4) an adaptive restriction of frequencies to a more reliable range than the usable frequency range. Regularization was formulated as a generalized least absolute shrinkage and selection operator (LASSO), and a variant of the Bayesian information criterion (BIC) was applied to estimate the Lagrangian multiplier on the LASSO constraint. In addition, we evaluated the proposed algorithm when applying median filtering before and after regularization. Tests conducted showed that the PF-R yielded robust results in all tested conditions, suggesting potential for additional validation as a diagnosis method.

Improved Ultrasound Attenuation Estimation with Non-uniform Structure Detection and Removal

Accurate detection of liver steatosis is important for liver disease management. Ultrasound attenuation coefficient estimation (ACE) has great potential in quantifying liver fat content. The ACE methods commonly assume uniform tissue characteristics. However, in vivo tissues typically contain non-uniform structures, which may bias the attenuation estimation and lead to large standard deviations. Here we propose a series of non-uniform structure detection and removal (NSDR) methods to reduce the impact from non-uniform structures during ACE analysis. The effectiveness of NSDR was validated through phantom and in vivo studies. In a pilot clinical study, ACE with NSDR provided more robust in vivo performance as compared with ACE without NSDR, indicating its potential for in vivo applications.

Improving coronary ultrafast Doppler angiography using fractional moving blood volume and motion-adaptive ensemble length

Coronary microperfusion assessment is a key parameter for understanding cardiac function. Currently, coronary ultrafast Doppler angiography is the only non-invasive clinical imaging technique able to assess coronary microcirculation quantitatively in humans. In this study, we propose to use fractional moving blood volume (FMBV), proportional to the red blood cell concentration, as a metric for perfusion. FMBV compares the power Doppler in a region of interest (ROI) inside the myocardium to the power Doppler of a reference area in the heart chamber, fully filled with blood. This normalization gives then relative values of the ROI blood filling. However, due to the impact of ultrasound attenuation and elevation focus on power Doppler values, the reference area and the ROI need to be at the same depth to allow this normalization. This condition is rarely satisfied in vivo due to the cardiac anatomy. Hereby, we propose to locally compensate the attenuation between the ROI and the reference, by measuring the attenuation law on a phantom. We quantified the efficiency of this approach by comparing FMBV with and without compensation on a flow phantom. Compensated FMBV was able to estimate the ground-truth FMBV with less than 5% variation. This method was then adapted to the in vivo case of myocardial perfusion imaging during heart surgery on human neonates. The translation from in vitro to in vivo required an additional clutter filtering step to ensure that blood signals could be correctly identified in the fast-moving myocardium. We applied the singular value decomposition filter on temporal sliding windows whose lengths were a function of myocardium motion. This motion-adaptive temporal sliding window approach was able to improve blood and tissue separation in terms of contrast-to-noise ratio, as compared to well-established constant-length sliding window approaches. Therefore, compensated FMBV and singular value decomposition assisted with motion-adaptive temporal sliding windows improves the quantification of blood volume in coronary ultrafast Doppler angiography.

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.

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

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

Noninvasive, quantitative evaluation of hepatic steatosis of donor livers by reference frequency method: A preliminary study

PURPOSE

Evaluating degree of hepatic steatosis is of great value for prognosis of liver transplantation. There is an urgent need for a non-invasive method to assess hepatic steatosis grade of donor livers. Purpose of our study was to evaluate diagnostic accuracy of attenuation coefficient estimation (ACE) by reference frequency method (RFM) in detecting hepatic steatosis of donor livers.

METHOD

We retrospectively enrolled 62 potential liver donors which underwent ACE by RFM ex-vivo, in-vivo or both. We acquired raw data of B-mode images of liver parenchyma and offline-processes for attenuation estimation. Finally, we calculated and compared diagnostic performance of ACEs for steatosis grade detection and used histological results as the gold standard.

RESULTS

ACEs with none, mild and moderate hepatic steatosis were 0.57, 0.73 and 0.80 dB/cm/MHz in potential donor livers. The cutoff value to diagnose mild hepatic steatosis was 0.63 dB/cm/MHz and 0.77 dB/cm/MHz for moderate hepatic steatosis, and values for the area under the receiver operating characteristic curve for diagnosis of mild and moderate hepatic steatosis were 0.92 and 0.90, respectively.

CONCLUSIONS

According to our results, ACE by RFM is an accurate non-invasive method in detecting hepatic steatosis, which may be of great help for clinical evaluation of donor livers before liver transplantation.

Noise Suppression for Ultrasound Attenuation Coefficient Estimation Based on Spectrum Normalization

Ultrasound attenuation coefficient estimation (ACE) has great diagnostic potential for fatty liver detection and assessment. In a previous study, we proposed a reference phantom-free ACE method, called reference frequency method (RFM), which does not require a calibrated phantom for normalization. The power of each frequency component can be 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). RFM demonstrated accurate ACE in both phantom and in in-vivo liver studies. However, our study also showed that the robustness and penetration of RFM were affected by noise in the ACE signals. Here we propose a noise suppression (NS) and a signal-to-noise ratio (SNR) quality control method to reduce the influence of noise on ACE-RFM performance. The proposed methods were tested in harmonic ACE because harmonic imaging is a more frequently used mode than fundamental imaging for abdominal applications. After applying the NS and SNR control methods, the noise-induced bias for attenuation estimation in harmonic ACE was effectively reduced, leading to significantly improved effective penetration depth. The proposed methods directly measure the noise spectrum of the ultrasound system, which can also be adapted to other spectrum-based ACE methods, such as the reference phantom method and the spectra shift method.

Analytic Global Regularized Backscatter Quantitative Ultrasound

Although a variety of techniques have been developed to reduce the appearance of B-mode speckle, quantitative ultrasound (QUS) aims at extracting the hidden properties of the tissue. Herein, we propose two novel techniques to accurately and precisely estimate two important QUS parameters, namely, the average attenuation coefficient and the backscatter coefficient. Both the techniques optimize a cost function that incorporates data and continuity constraint terms, which we call AnaLytical Global rEgularized BackscatteR quAntitative ultrasound (ALGEBRA). We propose two versions of ALGEBRA, namely, 1-D- and 2-D-ALGEBRA. In 1-D-ALGEBRA, the regularized cost function is formulated in the axial direction, and the QUS parameters are calculated for one line of radio frequency (RF) echo data. In 2-D-ALGEBRA, the regularized cost function is formulated for the entire image, and the QUS parameters throughout the image are estimated simultaneously. This simultaneous optimization allows 2-D-ALGEBRA to "see" all the data before estimating the QUS parameters. In both the methods, we efficiently optimize the cost functions by casting it as a sparse linear system of equations. As a result of this efficient optimization, 1-D-ALGEBRA and 2-D-ALGEBRA are, respectively, 600 and 300 times faster than optimization using the dynamic programming (DP) method previously proposed by our group. In addition, the proposed technique has fewer input parameters that require manual tuning. Our results demonstrate that the proposed ALGEBRA methods substantially outperform least-square and DP methods in estimating the QUS parameters in phantom experiments.

Texture Analysis on Ultrasound: The Effect of Time Gain Compensation on Histogram Metrics and Gray-Level Matrices

Aims:

Texture analysis (TA) is becoming an increasingly used tool in radiological research. Some papers have been published on its use in ultrasound (US), but the way in which the machine settings affect the features has not yet been fully explored. With this research, we analyze how the time gain compensation (TGC) influences the features of the gray-level matrices in the abdominal US setting.

Subjects and Methods:

We analyzed the images acquired from the hepatorenal acoustic window of a healthy 29-year-old volunteer acquired with different TGC settings. TA was carried out using the LifeX software.

Results:

Several both 1^st and 2^nd order gray-level matrices features showed a strong correlation with TGC settings.

Conclusions:

TGC settings must be accounted for when carrying out further TA studies.

Liraglutide reduces attenuation coefficient as a measure of hepatic steatosis during 16 weeks' treatment in nondiabetic obese patients: A pilot trial

Background and Aim

Liraglutide, a long-acting GLP-1 analog, is approved for the treatment of obesity with improvements in fasting blood glucose, hemoglobin A1c, and cardiovascular health. Our aim was to measure the impact of liraglutide dose for obesity on hepatic steatosis measured by ultrasound.

Methods

A single-center, randomized, double-blind, placebo-controlled pilot trial was undertaken in nondiabetic obese, otherwise healthy patients aged 18-65 years. Participants were randomly assigned to receive subcutaneous liraglutide (3.0 mg) or placebo over 16 weeks with dose escalation following US Food and Drug Administration guidelines. Both groups received standardized nutritional and behavioral counseling during the 16 weeks. Hepatic fat content was measured by ultrasound at baseline, 8 weeks, and 16 weeks as an attenuation coefficient (ACE). Effects of treatment were assessed using t-test for the entire groups and for patient subgroup with baseline ACE >0.66 (indicating significant steatosis).

Results

Among 30 patients (93% female) enrolled, 16 were randomized to placebo and 14 to liraglutide. Baseline body mass indices (BMIs) and average age were similar in the two groups. After 16 weeks, the liraglutide group had a significant improvement in steatosis ACE scores (-0.068 ± 0.02 vs -0.0077 ± 0.02 placebo, P = 0.05). Change in steatosis was positively correlated with change in BMI (R² = 0.402, P = 0.0007). Within the liraglutide group, patients with baseline ACE >0.66 had improvement in ACE (-0.134 ± 0.03) compared to those without significant steatosis (-0.041 ± 0.02, P = 0.05).

Conclusions

In this pilot trial, liraglutide, 3.0 mg over 16 weeks, reduced hepatic steatosis; a reduction in hepatic steatosis is correlated with BMI reduction, and effects are particularly evident in those with a significant degree of steatosis by ultrasound imaging.

Ultrasound Attenuation Estimation in Harmonic Imaging for Robust Fatty Liver Detection

Accurate detection of liver steatosis is important for liver disease management. Ultrasound attenuation coefficient estimation (ACE) has great potential in quantifying liver fat content. The commonly used ACE methods (e.g., spectral shift methods, reference phantom methods) assume linear tissue response to ultrasound and were developed in fundamental imaging. However, fundamental imaging may be vulnerable to reverberation clutters introduced by the body wall. The clutters superimposed on liver echoes may bias the attenuation estimation. Here we propose a new ACE technique, the reference frequency method (RFM), in harmonic imaging to mitigate the reverberation bias. The accuracy of harmonic RFM was validated through a phantom study. In a pilot patient study, harmonic RFM performed more robustly in vivo compared with fundamental RFM, illustrating the potential of ACE in harmonic imaging.

Frequency-dependent attenuation reconstruction with an acoustic reflector

Attenuation of ultrasound waves varies with tissue composition, hence its estimation offers great potential for tissue characterization and diagnosis and staging of pathology. We recently proposed a method that allows to spatially reconstruct the distribution of the overall ultrasound attenuation in tissue based on computed tomography, using reflections from a passive acoustic reflector. This requires a standard ultrasound transducer operating in pulse-echo mode and a calibration protocol using water measurements, thus it can be implemented on conventional ultrasound systems with minor adaptations. Herein, we extend this method by additionally estimating and imaging the frequency-dependent nature of local ultrasound attenuation for the first time. Spatial distributions of attenuation coefficient and exponent are reconstructed, enabling an elaborate and expressive tissue-specific characterization. With simulations, we demonstrate that our proposed method yields a low reconstruction error of 0.04 dB/cm at 1 MHz for attenuation coefficient and 0.08 for the frequency exponent. With tissue-mimicking phantoms and ex-vivo bovine muscle samples, a high reconstruction contrast as well as reproducibility are demonstrated. Attenuation exponents of a gelatin-cellulose mixture and an ex-vivo bovine muscle sample were found to be, respectively, 1.4 and 0.5 on average, consistently from different images of their heterogeneous compositions. Such frequency-dependent parametrization could enable novel imaging and diagnostic techniques, as well as facilitate attenuation compensation of other ultrasound-based imaging techniques.

Regularized Estimation of Effective Scatterer Size and Acoustic Concentration Quantitative Ultrasound Parameters Using Dynamic Programming

The objective of quantitative ultrasound (QUS) is to characterize tissue microstructure by parametrizing backscattered radiofrequency (RF) signals from clinical ultrasound scanners. Herein, we develop a novel technique based on dynamic programming (DP) to simultaneously estimate the acoustic attenuation, the effective scatterer size (ESS), and the acoustic concentration (AC) from ultrasound backscattered power spectra. This is achieved through two different approaches: (1) using a Gaussian form factor (GFF) and (2) using a general form factor (gFF) that is more flexible than the Gaussian form factor but involves estimating more parameters. Both DP methods are compared to an adaptation of a previously proposed least-squares (LSQ) method. Simulation results show that in the GFF approach, the variance of DP is on average 88%, 75% and 32% lower than that of LSQ for the three estimated QUS parameters. The gFF approach also yields similar improvements.