Attenuation estimation using spectral cross-correlation

Reliability and stability of ultrasound-guided attenuation parameter in evaluating hepatic steatosis

PURPOSE

This study aimed to explore the reliability and stability of ultrasound-guided attenuation parameter (UGAP) values obtained by two measuring methods and different measuring times.

METHODS

Patients who underwent liver UGAP examinations in our hospital from September 2022 to December 2022 were retrospectively analyzed. The clinical data and UGAP measurements results were collected. Two different measuring methods: static single-frame multi-point measuring and dynamic multi-frame single-point measuring, were performed for each patient, and 10 UGAP values of each measuring method were recorded. The medians of the UGAP values of the 1st-3rd, 1st-5th, 1st-7th and 1st-10th by each measuring method were taken as the final UGAP values of measuring 3, 5, 7 and 10 times. The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 or 10 times) were compared.

RESULTS

206 patients were included in this study. There was no statistical difference between UGAP values measured by static single-frame multi-point measuring and dynamic multi-frame single-point measuring (P = 0.689, P = 0.270, P = 0.298, P = 0.091), regardless of measuring times (3, 5, 7, 10 times). No significant difference between the UGAP values obtained by 3, 5, 7 and 10 measurements was found (P = 0.554, P = 0.916).

CONCLUSION

The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 and 10 times) are stable and reliable. Additionally, 3 times of UGAP measurements might be enough for each patient in clinical practice.

Protocol of quantitative ultrasound techniques for noninvasive assessing of hepatic steatosis after bariatric surgery

Introduction

Roux-en-Y gastric bypass surgery can effectively improve steatosis, necroinflammatory activity, and hepatic fibrosis in individuals diagnosed with morbid obesity or nonalcoholic steatohepatitis (NASH). Common methods such as body mass index (BMI) to evaluate the postoperative effect of clinical bariatric surgery cannot differentiate subcutaneous fats from visceral fats and muscles. Several Quantitative ultrasound (QUS)-based approaches have been developed to quantify hepatic steatosis. QUS techniques (tissue attenuation imaging (TAI), tissue scatter distribution imaging (TSI)) from radio frequency (RF) data analysis as a means for the detection and grading of hepatic steatosis has been posited as an objective and noninvasive approach. The implementation and standardization of QUS techniques (TAI, TSI) in assessing hepatic steatosis quantitatively after bariatric surgery is of high-priority. Our study is aimed to assess hepatic steatosis with QUS techniques (TAI, TSI) in morbidly obese individuals before and after bariatric surgery, and to compare with anthropometric measurements, laboratory assessments and other imaging methods.

Methods and analysis

The present investigation, a self-discipline examination of navigational capacity devoid of visual cues, is designed as a single-site, forward-looking evaluation of efficacy with the imprimatur of the institutional review board. The duration of the study has been provisionally determined to span from 1 January 2023 through 31 December 2025. Our cohort shall encompass one hundred participants, who was scheduled to undergo Roux-en-Y gastric bypass (RYGB) at Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. All patients will undergo anthropometric measurements, blood-based biochemical analyses, ultrasonic examination and magnetic resonance imaging proton density fat fraction (MRI-PDFF). The primary endpoint is the analysis of evaluating the efficacy of QUS techniques assessing hepatic steatosis compared to other methods before and after bariatric surgery.

Results

Prior to the fomal study, we recruited 21 obese Chinese participants who received ultrasonic examination (TAI, TSI) and MRI-PDFF. AC-TAI showed moderate correlations with MRI-PDFF (adjusted r = 0.632; P < 0.05). For MRI-PDFF ≥10%, SC-TSI showed moderate correlations with MRI-PDFF (adjusted r = 0.677; P < 0.05).

Conclusion

Our pre-experiment results signified that using QUS techniques for postoperative evaluation of bariatric surgery is promising. QUS techniques will be signed a widespread availability, real-time functionality, and low-cost approach for assessing hepatic steatosis before and after bariatric surgery in obese individuals, thus is capable for subsequent scale-up liver fat quantification.

Ethics and dissemination

The present research endeavor has been bestowed with the imprimatur of the Ethics Committee of the Hospital, as indicated by its Approval Number: 2023-KY-015. In due course, upon completion of the study, we intend to disseminate our findings by publishing them in a suitable academic journal, thereby facilitating their widespread utilization.

Registration

The trial is duly registered with the Chinese Clinical Trial Registry, and with a unique Trial Registration Number, ChiCTR2300069892, approved on March 28, 2023.

Quantitative ultrasound fatty liver evaluation in a pediatric population: comparison with magnetic resonance imaging of liver proton density fat fraction

BACKGROUND

Biopsy remains the gold standard for the diagnosis of hepatic steatosis, the leading cause of pediatric chronic liver disease; however, its costs call for less invasive methods.

OBJECTIVE

This study examined the diagnostic accuracy and reliability of quantitative ultrasound (QUS) for the assessment of liver fat content in a pediatric population, using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the reference standard.

MATERIALS AND METHODS

We enrolled 36 patients. MRI-PDFF involved a 3-dimensional T2*-weighted with Dixon pulse multiple-echo sequence using iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL IQ). QUS imaging relied on the ultrasound system "RS85 A" (Samsung Medison, Seoul, South Korea) and the following software: Hepato-Renal Index with automated region of interest recommendation (EzHRI), Tissue Attenuation Imaging (TAI), and Tissue Scatter Distribution Imaging (TSI). For each QUS index, receiver operating characteristic (ROC) curve analysis against MRI-PDFF was used to identify the associated cut-off value and the area under the ROC curve (AUROC). Concordance between two radiologists was assessed by intraclass correlation coefficients (ICCs) and Bland-Altman analysis.

RESULTS

A total of 61.1% of the sample (n=22) displayed a MRI-PDFF ≥ 5.6%; QUS cut-off values were TAI=0.625 (AUROC 0.90, confidence interval [CI] 0.77-1.00), TSI=91.95 (AUROC 0.99, CI 0.98-1.00) and EzHRI=1.215 (AUROC 0.98, CI 0.94-1.00). Inter-rater reliability was good-to-excellent for EzHRI (ICC 0.91, 95% C.I. 0.82-0.95) and TAI (ICC 0.94, 95% C.I. 0.88-0.97) and moderate to good for TSI (ICC 0.73; 95% C.I. 0.53-0.85).

CONCLUSION

Our results suggest that QUS can be used to reliably assess the presence and degree of pediatric hepatic steatosis.

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.

Two-dimensional Convolutional Neural Network Using Quantitative US for Noninvasive Assessment of Hepatic Steatosis in NAFLD

Background Quantitative US (QUS) using radiofrequency data analysis has been recently introduced for noninvasive evaluation of hepatic steatosis. Deep learning algorithms may improve the diagnostic performance of QUS for hepatic steatosis. Purpose To evaluate a two-dimensional (2D) convolutional neural network (CNN) algorithm using QUS parametric maps and B-mode images for diagnosis of hepatic steatosis, with the MRI-derived proton density fat fraction (PDFF) as the reference standard, in patients with nonalcoholic fatty liver disease (NAFLD). Materials and Methods: Consecutive adult participants with suspected NAFLD were prospectively enrolled at a single academic medical center from July 2020 to June 2021. Using radiofrequency data analysis, two QUS parameters (tissue attenuation imaging [TAI] and tissue scatter-distribution imaging [TSI]) were measured. On B-mode images, hepatic steatosis was graded using visual scoring (none, mild, moderate, or severe). Using B-mode images and two QUS parametric maps (TAI and TSI) as input data, the algorithm estimated the US fat fraction (USFF) as a percentage. The correlation between the USFF and MRI PDFF was evaluated using the Pearson correlation coefficient. The diagnostic performance of the USFF for hepatic steatosis (MRI PDFF ≥5%) was evaluated using receiver operating characteristic curve analysis and compared with that of TAI, TSI, and visual scoring. Results Overall, 173 participants (mean age, 51 years ± 14 [SD]; 96 men) were included, with 126 (73%) having hepatic steatosis (MRI PDFF ≥5%). USFF correlated strongly with MRI PDFF (Pearson r = 0.86, 95% CI: 0.82, 0.90; P < .001). For diagnosing hepatic steatosis (MRI PDFF ≥5%), the USFF yielded an area under the receiver operating characteristic curve of 0.97 (95% CI: 0.93, 0.99), higher than those of TAI, TSI, and visual scoring (P = .015, .006, and < .001, respectively), with a sensitivity of 90% (95% CI: 84, 95 [114 of 126]) and a specificity of 91% (95% CI: 80, 98 [43 of 47]) at a cutoff value of 5.7%. Conclusion A deep learning algorithm using quantitative US parametric maps and B-mode images accurately estimated the hepatic fat fraction and diagnosed hepatic steatosis in participants with nonalcoholic fatty liver disease. ClinicalTrials.gov registration nos. NCT04462562, NCT04180631 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sidhu and Fang in this issue.

Attenuation Compensation and Estimation

Estimating the loss of ultrasound signal with propagation depth as a function of frequency is essential for quantifying tissue properties. Specifically, ultrasound attenuation is used to correct for spectral distortion prior to estimating quantitative ultrasound parameters to assess the tissue. Ultrasound attenuation can also be used independently to characterize the tissue. In this chapter, we review the primary algorithms for estimating both the local attenuation within a region of interest as well as the total attenuation between a region of interest and an ultrasound source. The strengths and weaknesses of each algorithm are also discussed.

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

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an estimated prevalence of up to 30% in the general population and higher in people with type 2 diabetes. The assessment of liver fat content is essential to help identify patients with or who are at risk for NAFLD and to follow their disease over time. The American Institute of Ultrasound in Medicine-RSNA Quantitative Imaging Biomarkers Alliance Pulse-Echo Quantitative Ultrasound Initiative was formed to help develop and standardize acquisition protocols and to better understand confounding factors of US-based fat quantification. The three quantitative US parameters explored by the initiative are attenuation, backscatter coefficient, and speed of sound. The purpose of this review is to present the current state of attenuation imaging for fat quantification and to provide expert opinion on examination performance and interpretation. US attenuation methods that need further study are outlined.

Fast linear least-squares method for ultrasound attenuation and backscatter estimation

The ultrasonic attenuation and backscatter coefficients of tissues are relevant acoustic parameters due to their wide range of clinical applications. In this paper, a linear least-squares method for the estimation of these coefficients in a homogeneous region of interest based on pulse-echo measurements is proposed. The method efficiently fits an ultrasound backscattered signal model to the measurements in both the frequency and depth dimension simultaneously at a low computational cost. It is demonstrated that the inclusion of depth information has a positive effect particularly on the accuracy of the estimated attenuation. The sensitivity of the attenuation and backscatter coefficients' estimates to several predefined parameters such as the window length, window overlap and usable bandwidth of the spectrum is also studied. Comparison of the proposed method with a benchmark approach based on dynamic programming highlights better performance of our method in estimating these coefficients, both in terms of accuracy and computation time. Further analysis of the computation time as a function of the predefined parameters indicates our method's potential to be used in real-time clinical settings.

Spectral Shift Originating from Non-linear Ultrasonic Wave Propagation and Its Effect on Imaging Resolution

An amplitude-dependent downshift in the fundamental wave spectrum of a propagating ultrasonic pulse caused by non-linear wave propagation is described. The effects of non-linearity and the associated downshift on spatial resolution are also studied. The amounts of downshift and spatial resolution are extracted from the numerically simulated beam profile based on the KZK equation. Results for a 25-MHz transducer reveal that non-linear effects can lead to 58% additional downshift in the centre frequency of a pulse compared with a linear case with downshift caused only by attenuation. This additional downshift causes about 50% degradation in axial resolution. However, as the beam becomes narrower from the non-linear effects, the overall effect of non-linearity still leads to improved lateral resolution (≤26%). Therefore, as non-linearity increases with wave pressure, it is concluded that the increase in source pressure improves lateral resolution and degrades axial resolution.

Quantitative Ultrasound Radiofrequency Data Analysis for the Assessment of Hepatic Steatosis in Nonalcoholic Fatty Liver Disease Using Magnetic Resonance Imaging Proton Density Fat Fraction as the Reference Standard

Objective

To investigate the diagnostic performance of quantitative ultrasound (US) parameters for the assessment of hepatic steatosis in patients with nonalcoholic fatty liver disease (NAFLD) using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the reference standard.

Materials and Methods

In this single-center prospective study, 120 patients with clinically suspected NAFLD were enrolled between March 2019 and January 2020. The participants underwent US examination for radiofrequency (RF) data acquisition and chemical shift-encoded liver MRI for PDFF measurement. Using the RF data analysis, the attenuation coefficient (AC) based on tissue attenuation imaging (TAI) (AC-TAI) and scatter-distribution coefficient (SC) based on tissue scatter-distribution imaging (TSI) (SC-TSI) were measured. The correlations between the quantitative US parameters (AC and SC) and MRI-PDFF were evaluated using Pearson correlation coefficients. The diagnostic performance of AC-TAI and SC-TSI for detecting hepatic fat contents of ≥ 5% (MRI-PDFF ≥ 5%) and ≥ 10% (MRI-PDFF ≥ 10%) were assessed using receiver operating characteristic (ROC) analysis. The significant clinical or imaging factors associated with AC and SC were analyzed using linear regression analysis.

Results

The participants were classified based on MRI-PDFF: < 5% (n = 38), 5–10% (n = 23), and ≥ 10% (n = 59). AC-TAI and SC-TSI were significantly correlated with MRI-PDFF (r = 0.659 and 0.727, p < 0.001 for both). For detecting hepatic fat contents of ≥ 5% and ≥ 10%, the areas under the ROC curves of AC-TAI were 0.861 (95% confidence interval [CI]: 0.786–0.918) and 0.835 (95% CI: 0.757–0.897), and those of SC-TSI were 0.964 (95% CI: 0.913–0.989) and 0.935 (95% CI: 0.875–0.972), respectively. Multivariable linear regression analysis showed that MRI-PDFF was an independent determinant of AC-TAI and SC-TSI.

Conclusion

AC-TAI and SC-TSI derived from quantitative US RF data analysis yielded a good correlation with MRI-PDFF and provided good performance for detecting hepatic steatosis and assessing its severity in NAFLD.

Clinical Feasibility of Quantitative Ultrasound Imaging for Suspected Hepatic Steatosis: Intra- and Inter-examiner Reliability and Correlation with Controlled Attenuation Parameter

This study was aimed at investigating the clinical feasibility of quantitative ultrasound (QUS) imaging in the evaluation of suspected hepatic steatosis through assessment of the reliability of measurements and its correlation with the controlled attenuation parameter (CAP). This retrospective study included 117 patients who underwent liver B-mode ultrasound (US) with QUS imaging with a clinical US machine (RS85, Samsung Medison, Seoul, Korea) and CAP measurements between December 2019 and March 2020. For QUS examination, tissue attenuation imaging (TAI) and tissue scatter-distribution imaging (TSI) parameters were obtained. Intra- and inter-examiner reliability were assessed using intra-class correlation coefficients (ICCs), and QUS imaging parameters were correlated with CAP measurements using Spearman's correlation analysis. TAI and TSI revealed excellent intra- and inter-examiner reliability with ICCs of 0.994 and 0.975 and 0.991 and 0.947, respectively. Both TAI and TSI were significantly positively correlated with CAP values. QUS imaging provided good intra-and inter-observer reliability and correlated well with CAP in assessing suspected hepatic steatosis.

Evaluation method of the degree of red blood cell aggregation considering ultrasonic propagation attenuation by analyzing ultrasonic backscattering properties

PURPOSE

Red blood cell (RBC) aggregation is one of the main factors that determines blood viscosity and an important indicator for evaluating blood properties. As a noninvasive and quantitative method for diagnosing blood properties, our research group estimated the size of RBC aggregates by fitting the scattered power spectrum from the blood vessel lumen with the theoretical scattering characteristics to evaluate the degree of RBC aggregation. However, it was assumed that the propagation attenuation of ultrasound in the vascular lumen was the same regardless of whether RBCs were aggregated or not, which caused systematic errors in the estimated size.

METHODS

To improve the size estimation accuracy, we calculated and corrected the attenuation of the blood vessel lumen during RBC aggregation and non-aggregation. The attenuation in the blood vessel lumen was calculated with the spectra acquired from two different depths.

RESULTS

In the basic experiments using microparticles, the estimation accuracy decreased as the concentration increased in the case of the conventional method, but the estimated size tended to approach the true size irrespective of the concentration, removing the propagation attenuation component with the proposed method. In the in vivo experiment on the human hand dorsal vein, the size was estimated to be larger during RBC aggregation and smaller during non-aggregation using the proposed method.

CONCLUSION

These results suggest that the proposed method can provide precise size estimation by considering the propagation attenuation component regardless of differences in blood conditions such as RBC concentration and degree of aggregation.

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.

Signal-Processing Framework for Ultrasound Compressed Sensing Data: Envelope Detection and Spectral Analysis

Acquisition times and storage requirements have become increasingly important in signal-processing applications, as the sizes of datasets have increased. Hence, compressed sensing (CS) has emerged as an alternative processing technique, as original signals can be reconstructed using fewer data samples collected at frequencies below the Nyquist sampling rate. However, further analysis of CS data in both time and frequency domains requires the reconstruction of the original form of the time-domain data, as traditional signal-processing techniques are designed for uncompressed data. In this paper, we propose a signal-processing framework that extracts spectral properties for frequency-domain analysis directly from under-sampled ultrasound CS data, using an appropriate basis matrix, and efficiently converts this into the envelope of a time-domain signal, avoiding full reconstruction. The technique generates more accurate results than the traditional framework in both time- and frequency-domain analyses, and is simpler and faster in execution than full reconstruction, without any loss of information. Hence, the proposed framework offers a new standard for signal processing using ultrasound CS data, especially for small and portable systems handling large datasets.

Attenuation Coefficient Parameter Computations for Tissue Composition Assessment of Carotid Atherosclerotic Plaque in Vivo

Quantitative ultrasound has been used to assess carotid plaque tissue composition. Here, we compute the attenuation coefficient (AC) in vivo with the optimum power spectral shift estimator (OPSSE) and reference phantom method (RPM), extract AC parameters and form parametric maps. Differences between OPSSE and RPM AC parameters are computed. Relationships between AC parameters, surgical scores and histopathology assessments are examined. Kendall's τ correlations between OPSSE AC and surgical scores are significant, including those between cholesterol and Standard Deviation (adjusted p = 0.038); thrombus and Minimum (adjusted p = 0.002), Maximum (adjusted p = 0.021) and Standard Deviation (adjusted p = 0.001); ulceration and Average (adjusted p = 0.033), Median (unadjusted p = 0.013), Maximum (unadjusted p = 0.039) and Mode (adjusted p = 0.009). The strongest correlations with histopathology are percentage cholesterol and Median OPSSE (unadjusted p = 0.007); percentage hemorrhage and Minimum OPSSE (adjusted p < 0.001); hemosiderin score and Median OPSSE (adjusted p = 0.010); and percentage calcium and Percentage Non-physical RPM Pixels (unadjusted p = 0.014). Kruskal-Wallis H and Dunn's post hoc tests have the ability to distinguish between groups (p < 0.05). Results suggest AC parameters may assist in vivo evaluation of carotid plaque vulnerability.

Quantitative ultrasound radiofrequency data analysis for the assessment of hepatic steatosis using the controlled attenuation parameter as a reference standard

Purpose

This study was aimed to investigate the value of quantitative ultrasound (US) parameters from radiofrequency (RF) data analysis for assessing hepatic steatosis, using controlled attenuation parameter (CAP)-based steatosis grades as the reference standard.

Methods

We analyzed 243 participants with both B-mode liver US with RF data acquisition and CAP measurements. On B-mode US images, hepatic steatosis was visually scored (0/1/2/3, none/mild/moderate/severe), and the hepatorenal index (HRI) was calculated. From the RF data analysis, the tissue scatter-distribution imaging parameter (TSI-p) and tissue attenuation imaging parameter (TAI-p) of the liver parenchyma were measured. US parameters were correlated with CAP-based steatosis grades (S0/1/2/3, none/mild/moderate/severe) and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Multivariate linear regression analysis was performed to identify determinants of TSI-p and TAI-p.

Results

Participants were classified as having S0 (n=152), S1 (n=54), S2 (n=14), and S3 (n=23) on CAP measurements. TSI-p and TAI-p were significantly correlated with steatosis grades (ρ =0.593 and ρ=-0.617, P<0.001 for both). For predicting ≥S1, ≥S2, and S3, the areas under the ROC curves (AUCs) of TSI-p were 0.827/0.914/0.917; TAI-p, 0.844/0.914/0.909; visual scores, 0.659/0.778/0.794; and HRI, 0.629/0.751/0.759, respectively. TSI-p and TAI-p had significantly higher AUCs than did visual scores or HRI for ≥S1 or ≥S2 (P≤0.003). In the multivariate analysis, the transient elastography-based fibrosis grade (P=0.034) and steatosis grade (P<0.001) were independent determinants of TSI-p, while steatosis grade (P<0.001) was an independent determinant of TAI-p.

Conclusion

TSI-p and TAI-p derived from US RF data may be useful for detecting hepatic steatosis and assessing its severity.

Attenuation Coefficient Estimation of Normal Placentas

Attenuation coefficient estimation has the potential to be a useful tool for placental tissue characterization. A current challenge is the presence of inhomogeneities in biological tissue that result in a large variance in the attenuation coefficient estimate (ACE), restricting its clinical utility. In this work, we propose a new Attenuation Estimation Region Of Interest (AEROI) selection method for computing the ACE based on the (i) envelope signal-to-noise ratio deviation and (ii) coefficient of variation of the transmit pulse bandwidth. The method was first validated on a tissue-mimicking phantom, for which an 18%-21% reduction in the standard deviation of ACE and a 14%-24% reduction in the ACE error, expressed as a percentage of reported ACE, were obtained. A study on 59 post-delivery clinically normal placentas was then performed. The proposed AEROI selection method reduced the intra-subject standard deviation of ACE from 0.72 to 0.39 dB/cm/MHz. The measured ACE of 59 placentas was 0.77 ± 0.37 dB/cm/MHz, which establishes a baseline for future studies on placental tissue characterization.

Attenuation estimation by repeatedly solving the forward scattering problem

Estimation of the attenuation is important in medical ultrasound not only for correct time-gain compensation but also for tissue characterization. In this paper, the feasibility of a new method for attenuation estimation is tested. The proposed method estimates the attenuation by repeatedly solving the forward wave propagation problem and matching the simulated signals to the measured ones. This approach allows avoiding common assumptions made by other methodologies and potentially allows to account and correct for other acoustic effects that may bias the attenuation estimate. The performance of the method was validated on simulated data and on data recorded in tissue mimicking phantoms with known attenuation properties, and was compared to the spectral-shift and spectral-difference methods. Simulation results showed the different methods to have good accuracy when noise-free signals were considered (the average relative error of the attenuation estimation did not exceed 15%). However, the accuracy of the conventional methods decreased rapidly in the presence of measurement noise and varying scatterer concentration, while the relative error of the proposed method remained below 15%. Furthermore, the proposed method outperformed conventional attenuation estimators in the experimental phantom study, where its average error was 8%, while the average error of the spectral-shift and spectral-difference methods was 26% and 32%, respectively. In summary, these findings demonstrate the feasibility of the proposed approach and motivate us to refine the method for solving more general problems.

Lower Bound on Estimation Variance of the Ultrasonic Attenuation Coefficient Using the Spectral-Difference Reference-phantom Method

Ultrasonic attenuation is one of the primary parameters of interest in Quantitative Ultrasound (QUS). Non-invasive monitoring of tissue attenuation can provide valuable diagnostic and prognostic information to the physician. The Reference Phantom Method (RPM) was introduced as a way of mitigating some of the system-related effects and biases to facilitate clinical QUS applications. In this paper, under the assumption of diffuse scattering, a probabilistic model of the backscattered signal spectrum is used to derive a theoretical lower bound on the estimation variance of the attenuation coefficient using the Spectral-Difference RPM. The theoretical lower bound is compared to simulated and experimental attenuation estimation statistics in tissue-mimicking (TM) phantoms. Estimation standard deviation (STD) of the sample attenuation in a region of interest (ROI) of the TM phantom is measured for various combinations of processing parameters, including Radio-Frequency (RF) data block length (i.e., window length) from 3 to 17 mm, RF data block width from 10 to 100 A-lines, and number of RF data blocks per attenuation estimation ROI from 3 to 10. In addition to the Spectral-Difference RPM, local attenuation estimation for simulated and experimental data sets was also performed using a modified implementation of the Spectral Fit Method (SFM). Estimation statistics of the SFM are compared to theoretical variance predictions from the literature.1 Measured STD curves are observed to lie above the theoretical lower bound curves, thus experimentally verifying the validity of the derived bounds. This theoretical framework benefits tissue characterization efforts by isolating processing parameter ranges that could provide required precision levels in estimation of the ultrasonic attenuation coefficient using Spectral Difference methods.

Multifeature analysis of an ultrasound quantitative diagnostic index for classifying nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease related to metabolic syndrome. This study applied an integrated analysis based on texture, backscattering, and attenuation features in ultrasound imaging with the aim of assessing the severity of NAFLD. Ultrasound radiofrequency data obtained from 394 clinical cases were analyzed to extract three texture features (autocorrelation, sum average, and sum variance), the signal-to-noise ratio (SNR), and the slope of the center-frequency downshift (CFDS slope). The texture, SNR, and CFDS slope were combined to produce a quantitative diagnostic index (QDI) that ranged from 0 to 6. We trained the QDI using training data and then applied it to test data to assess its utility. In training data, the areas (AUCs) under the receiver operating characteristic curves for NAFLD and severe NAFLD were 0.81 and 0.84, respectively. In test data, the AUCs were 0.73 and 0.81 for NAFLD and severe NAFLD, respectively. The QDI was able to distinguish severe NAFLD and a normal liver from mild NAFLD, and it was significantly correlated with metabolic factors. This study explored the potential of using the QDI to supply information on different physical characteristics of liver tissues for advancing the ability to grade NAFLD.

Tissue Attenuation Estimation by Mean Frequency Downshift and Bandwidth Limitation

Attenuation of ultrasound in tissue can be estimated from the propagating pulse center frequency downshift. This method assumes that the envelope of the emitted pulse can be approximated by a Gaussian function and that the attenuation linearly depends on frequency. The resulting downshift of the mean frequency depends not only on attenuation but also on pulse bandwidth and propagation distance. This kind of approach is valid for narrowband pulses and shallow penetration depth. However, for short pulses and deep penetration, the frequency downshift is rather large and the received spectra are modified by the limited bandwidth of the receiving system. In this paper, the modified formula modeling the mean frequency of backscattered echoes is presented. The equation takes into account the limitation of the bandwidth due to bandpass filtration of the received echoes. This approach was applied to simulate the variation of the mean frequency of the pulse propagating for both weakly and strongly attenuating media and for narrowband and wideband pulses. The behavior of both the standard and modified estimates of attenuation has been validated using RF data from a tissue-mimicking phantom. The ultrasound attenuation of the phantom, determined with a corrected equation, was close to its true value, while the result obtained using the original formula was lower by as much as 50% at a depth of 8 cm.

Optimum Diffraction-Corrected Frequency-Shift Estimator of the Ultrasonic Attenuation Coefficient

The ultrasonic attenuation coefficient is an important parameter that has been studied extensively in Quantitative Ultrasound and Tissue Characterization. There are various methods described in the literature that estimate this parameter by measuring either spectral difference (i.e., decay) or spectral shift of the backscattered echo signal. Under ideal conditions, i.e., in the absence of abrupt changes in tissue backscattering, Spectral Difference methods can produce estimates with high accuracy and precision. On the other hand, diffraction-corrected Spectral Shift methods (e.g., the Hybrid method) are better suited for application in practical settings using clinical ultrasound scanners. However, current Spectral Shift methods use inefficient frequency shift estimators that ultimately degrade the quality of attenuation coefficient estimates. In this paper, a probabilistic model of the backscattered radiofrequency (RF) echo is used to derive the Cramér-Rao lower bound (CRLB) on estimation variance of the spectral centroid. Next, an efficient correlation-based shift estimator is presented that achieves the CRLB. Used in conjunction with a well-characterized reference phantom to correct for diffraction and other system-related effects, this estimator greatly improves the accuracy and precision of Spectral- Shift attenuation estimation. A theoretical analysis of this method is provided, and its performance is quantitatively compared with that of the Hybrid method using simulated and experimental phantom studies. A minimum of 3-fold reduction in the standard deviation of attenuation coefficient estimates is observed using the new method.

Ultrasound coefficient of nonlinearity imaging

Imaging the acoustical coefficient of nonlinearity, β, is of interest in several healthcare interventional applications. It is an important feature that can be used for discriminating tissues. In this paper, we propose a nonlinearity characterization method with the goal of locally estimating the coefficient of nonlinearity. The proposed method is based on a 1-D solution of the nonlinear lossy Westerfelt equation, thereby deriving a local relation between β and the pressure wave field. Based on several assumptions, a β imaging method is then presented that is based on the ratio between the harmonic and fundamental fields, thereby reducing the effect of spatial amplitude variations of the speckle pattern. By testing the method on simulated ultrasound pressure fields and an in vitro B-mode ultrasound acquisition, we show that the designed algorithm is able to estimate the coefficient of nonlinearity, and that the tissue types of interest are well discriminable. The proposed imaging method provides a new approach to β estimation, not requiring a special measurement setup or transducer, that seems particularly promising for in vivo imaging.

Performance evaluation of the spectral centroid downshift method for attenuation estimation

Estimation of frequency-dependent ultrasonic attenuation is an important aspect of tissue characterization. Along with other acoustic parameters studied in quantitative ultrasound, the attenuation coefficient can be used to differentiate normal and pathological tissue. The spectral centroid downshift (CDS) method is one the most common frequencydomain approaches applied to this problem. In this study, a statistical analysis of this method's performance was carried out based on a parametric model of the signal power spectrum in the presence of electronic noise. The parametric model used for the power spectrum of received RF data assumes a Gaussian spectral profile for the transmit pulse, and incorporates effects of attenuation, windowing, and electronic noise. Spectral moments were calculated and used to estimate second-order centroid statistics. A theoretical expression for the variance of a maximum likelihood estimator of attenuation coefficient was derived in terms of the centroid statistics and other model parameters, such as transmit pulse center frequency and bandwidth, RF data window length, SNR, and number of regression points. Theoretically predicted estimation variances were compared with experimentally estimated variances on RF data sets from both computer-simulated and physical tissue-mimicking phantoms. Scan parameter ranges for this study were electronic SNR from 10 to 70 dB, transmit pulse standard deviation from 0.5 to 4.1 MHz, transmit pulse center frequency from 2 to 8 MHz, and data window length from 3 to 17 mm. Acceptable agreement was observed between theoretical predictions and experimentally estimated values with differences smaller than 0.05 dB/cm/MHz across the parameter ranges investigated. This model helps predict the best attenuation estimation variance achievable with the CDS method, in terms of said scan parameters.

Optimization of the autocorrelation weighting function for the time-domain calculation of spectral centroids

Spectral centroid from the backscattered ultrasound provides important information about the attenuation properties of soft tissues and Doppler effects of blood flows. Because the spectral centroid is originally determined from the power spectrum of backscattered ultrasound signals in the frequency domain, it is natural to calculate it after converting time-domain signals into spectral domain signals, using the fast Fourier transform (FFT). Recent research, however, derived the time-domain equations for calculating the spectral centroid using a Parseval's theorem, to avoid the calculation of the Fourier transform. The work only presented the final result, which showed that the computational time of the proposed time-domain method was 4.4 times faster than that of the original FFT-based method, whereas the average estimation error was negligible. In this paper, we present the optimal design of the autocorrelation weighting function, which is used for the timedomain spectral centroid estimation process, to reduce the computational time significantly. We also carry out a comprehensive analysis of the computational complexities of the FFTbased and time-domain methods with respect to the length of ultrasound signal segments. The simulation results using numerical phantoms show that, with the optimized autocorrelation weighting function, we only need approximately 3% of the full set of data points. In addition to that, because the proposed optimization technique requires a fixed number of data points to calculate the spectral centroid, the execution time is constant as the length of the data segment increases, whereas the execution time of the conventional FFT-based method is increased. Analysis of the computational complexities between the proposed method and the conventional FFT-based method presents O(N) and O(Nlog2N), respectively.

Scatterer number density considerations in reference phantom-based attenuation estimation

Attenuation estimation and imaging have the potential to be a valuable tool for tissue characterization, particularly for indicating the extent of thermal ablation therapy in the liver. Often the performance of attenuation estimation algorithms is characterized with numerical simulations or tissue-mimicking phantoms containing a high scatterer number density (SND). This ensures an ultrasound signal with a Rayleigh distributed envelope and a signal-to-noise ratio (SNR) approaching 1.91. However, biological tissue often fails to exhibit Rayleigh scattering statistics. For example, across 1647 regions of interest in five ex vivo bovine livers, we obtained an envelope SNR of 1.10 ± 0.12 when the tissue was imaged with the VFX 9L4 linear array transducer at a center frequency of 6.0 MHz on a Siemens S2000 scanner. In this article, we examine attenuation estimation in numerical phantoms, tissue-mimicking phantoms with variable SNDs and ex vivo bovine liver before and after thermal coagulation. We find that reference phantom-based attenuation estimation is robust to small deviations from Rayleigh statistics. However, in tissue with low SNDs, large deviations in envelope SNR from 1.91 lead to subsequently large increases in attenuation estimation variance. At the same time, low SND is not found to be a significant source of bias in the attenuation estimate. For example, we find that the standard deviation of attenuation slope estimates increases from 0.07 to 0.25 dB/cm-MHz as the envelope SNR decreases from 1.78 to 1.01 when estimating attenuation slope in tissue-mimicking phantoms with a large estimation kernel size (16 mm axially × 15 mm laterally). Meanwhile, the bias in the attenuation slope estimates is found to be negligible (<0.01 dB/cm-MHz). We also compare results obtained with reference phantom-based attenuation estimates in ex vivo bovine liver and thermally coagulated bovine liver.

Signal to noise ratio comparisons for ultrasound attenuation slope estimation algorithms

PURPOSE

Attenuation imaging has a promising role in the detection of tissue abnormalities. The authors have previously compared three different frequency domain ultrasound attenuation estimation methods, for accuracy and bias. The mean estimated attenuation value in a region of interest has been the determining factor of how well a method performs; however, the noise level has not been quantified for attenuation estimated using different methods.

METHODS

The authors compare three different frequency domain ultrasound attenuation estimation methods [the reference phantom method (RPM), the centroid downshift method (CEN), and the hybrid method (HYB)] using the signal to noise ratio (SNR) metric. Both simulated and experimental tissue-mimicking phantoms are used in the performance comparison study, evaluating the impact of the variation in acoustical properties.

RESULTS

For attenuation estimation in a tissue-mimicking phantom with a known attenuation coefficient of 0.5 dB/cm/MHz, all the three methods estimated the attenuation coefficient to be ≈ 0.49 dB/cm/MHz for a transmit center frequency of 6 MHz, however, the signal to noise ratio obtained was found to be 8.5, 5.7, and 2.2 for the HYB, RPM, and CEN methods, respectively. These results demonstrate the need for the SNR metric in the comparison of different algorithms and to evaluate the impact of varying different ultrasound system and tissue parameters.

CONCLUSIONS

In this paper, the authors demonstrate that although the estimated mean attenuation value with a region of interest may be closely estimated using different methods, the signal to noise ratio obtained of the estimates can vary significantly. The centroid downshift method presented with the lowest signal-to-noise ratio of the methods compared. The hybrid method was the least susceptible to changes in the acoustical properties and provided unbiased attenuation coefficient estimates with the highest signal-to-noise ratios.

Evaluation of the impact of backscatter intensity variations on ultrasound attenuation estimation

PURPOSE

Quantitative ultrasound based approaches such as attenuation slope estimation can be used to determine underlying tissue properties and eventually used as a supplemental diagnostic technique to B-mode imaging. The authors investigate the impact of backscatter intensity and frequency dependence variations on the attenuation slope estimation accuracy.

METHODS

The authors compare three frequency domain based attenuation slope estimation algorithms, namely, a spectral difference method, the reference phantom method, and two spectral shift methods: a hybrid method and centroid downshift method. Both the reference phantom and hybrid method use a tissue-mimicking phantom with well-defined acoustic properties to reduce system dependencies and diffraction effects. The normalized power spectral ratio obtained is then filtered by a Gaussian filter centered at the transmit center frequency in the hybrid method. A spectral shift method is then used to estimate the attenuation coefficient from the normalized and filtered spectrum. The centroid downshift method utilizes the shift in power spectrum toward lower frequencies with depth. Numerical phantoms that incorporate variations in the backscatter intensity from -3 to 3 dB, by varying the scatterer number density and variations in the scatterer diameters ranging from 10 to 100 μm are simulated. Experimental tissue mimicking phantoms with three different scatterer diameter ranges (5-40, 75-90, and 125-150 μm) are also used to evaluate the accuracy of the estimation methods.

RESULTS

The reference phantom method provided accurate results when the acoustical properties of the reference and the sample are well matched. Underestimation occurs when the reference phantom possessed a higher sound speed than the sample, and overestimation occurs when the reference phantom had a lower sound speed than the sample. The centroid downshift method depends significantly on the bandwidth of the power spectrum, which in turn depends on the frequency dependence of the backscattering. The hybrid method was the least susceptible to changes in the sample's acoustic properties and provided the lowest standard deviation in the numerical simulations and experimental evaluations.

CONCLUSIONS

No significant variations in the estimation accuracy of the attenuation coefficient were observed with an increase in the scatterer number density in the simulated numerical phantoms for the three methods. Changes in the scatterer diameters, which result in different frequency dependence of backscatter, do not significantly affect attenuation slope estimation with the reference phantom and hybrid approaches. The centroid method is sensitive to variations in the scatterer diameter due to the frequency shift introduced in the power spectrum.

Task-oriented comparison of power spectral density estimation methods for quantifying acoustic attenuation in diagnostic ultrasound using a reference phantom method

Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0 f (β), was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

Mean scatterer spacing estimation using multi-taper coherence

It has been hypothesized that estimates of mean scatterer spacing are useful indicators for pathological changes to the liver. A commonly employed estimator of the mean scatterer spacing is the location of the maximum of the collapsed average of coherence of the ultrasound radio-frequency signal. To date, in ultrasound, estimators for this quantity have been calculated with a single taper. Using frequency-domain Monte Carlo simulations, we demonstrate that multi-taper estimates of coherence are superior to single-taper estimates for predicting mean scatterer spacing. Scattering distributions were modeled with Gamma-distributed scatterers for fractional standard deviations in scatterer spacings of 5, 10, and 15% at a mean scatterer spacing of 1 mm. Additionally, we demonstrate that we can distinguish between ablated liver tissue and unablated liver tissue based on signal coherence. We find that, on the average, signal coherence is elevated in the liver relative to signal coherence of received echoes from thermally ablated tissue. Additionally, our analysis indicates that a tissue classifier utilizing the multi-taper estimate of coherence has the potential to distinguish between ablated and unablated tissue types better than a single-taper estimate of coherence. For a gate length of 5 mm, we achieved an error rate of only 8.7% when sorting 23 ablated and 23 unablated regions of interest (ROIs) into classes based on multi-taper calculations of coherence.

Using nearest neighbors for accurate estimation of ultrasonic attenuation in the spectral domain

Attenuation is a key diagnostic parameter of tissue pathology change and thus may play a vital role in the quantitative discrimination of malignant and benign tumors in soft tissue. In this paper, two novel techniques are proposed for estimating the average ultrasonic attenuation in soft tissue using the spectral domain weighted nearest neighbor method. Because the attenuation coefficient of soft tissues can be considered to be a continuous function in a small neighborhood, we directly estimate an average value of it from the slope of the regression line fitted to the 1) modified average midband fit value and 2) the average center frequency shift along the depth. To calculate the average midband fit value, an average regression line computed from the exponentially weighted short-time Fourier transform (STFT) of the neighboring 1-D signal blocks, in the axial and lateral directions, is fitted over the usable bandwidth of the normalized power spectrum. The average center frequency downshift is computed from the maximization of a cost function defined from the normalized spectral cross-correlation (NSCC) of exponentially weighted nearest neighbors in both directions. Different from the large spatial signal-block-based spectral stability approach, a costfunction- based approach incorporating NSCC functions of neighboring 1-D signal blocks is introduced. This paves the way for using comparatively smaller spatial area along the lateral direction, a necessity for producing more realistic attenuation estimates for heterogeneous tissue. For accurate estimation of the attenuation coefficient, we also adopt a reference-phantombased diffraction-correction technique for both methods. The proposed attenuation estimation algorithm demonstrates better performance than other reported techniques in the tissue-mimicking phantom and the in vivo breast data analysis.

Time-domain calculation of spectral centroid from backscattered ultrasound signals

Spectral centroid estimation from backscattered ultrasound RF signals is the preliminary step for quantitative ultrasound analysis in many medical applications. The traditional approach of estimating the spectral centroid in the frequency domain takes a long time because discrete Fourier transform (DFT) processing for each RF segment is required. To avoid this, we propose time-domain methods to estimate the spectral centroid in this paper. First, we derive the continuous-time-domain equations for the spectral centroid estimation using Parseval's theorem and Hilbert transform theory. Then, we extend the method to the discrete-time domain to ease the implementation while maintaining the same accuracy as the calculation in the frequency domain. From the result, we observe that it is not practical to apply the discrete-time equations directly, because a high sampling rate is needed to approximate the time derivative in the discrete-time domain. Therefore, we also derive the feasible version of the discrete-time equations using a circular autocorrelation function, which has no constraints on the sampling rate for real RF signals acquired from pulse-echo ultrasound systems. Simulation results using numerical phantoms show that the time-domain calculation is approximately 4.4 times faster on average than the frequency-domain method when the software's built-in functions were used. The average estimation error compared with that of the frequency-domain method using DFT is less than 0.2% for the entire propagation depths. The proposed time-domain approach to estimate the spectral centroid can be easily implemented in real-time ultrasound systems.

Theoretical and phantom based investigation of the impact of sound speed and backscatter variations on attenuation slope estimation

Quantitative ultrasound features such as the attenuation slope, sound speed and scatterer size, have been utilized to evaluate pathological variations in soft tissues such as the liver and breast. However, the impact of variations in the sound speed and backscatter due to underlying fat content or fibrotic changes, on the attenuation slope has not been addressed. Both numerical and acoustically uniform tissue-mimicking experimental phantoms are used to demonstrate the impact of sound speed variations on attenuation slope using clinical real-time ultrasound scanners equipped with linear array transducers. Radiofrequency data at center frequencies of 4 and 5 MHz are acquired for the experimental and numerical phantoms respectively. Numerical phantom sound speeds between 1480 and 1600 m/s in increments of 20 m/s for attenuation coefficients of 0.3, 0.4, 0.5, 0.6, and 0.7 dB/cm/MHz are simulated. Variations in the attenuation slope when the backscatter intensity of the sample is equal, 3 dB higher, and 3 dB lower than the reference is also evaluated. The sound speed for the experimental tissue-mimicking phantoms were 1500, 1540, 1560 and 1580 m/s respectively, with an attenuation coefficient of 0.5 dB/cm/MHz. Radiofrequency data is processed using three different attenuation estimation algorithms, i.e. the reference phantom, centroid downshift, and a hybrid method. In both numerical and experimental phantoms our results indicate a bias in attenuation slope estimates when the reference phantom sound speed is higher (overestimation) or lower (underestimation) than that of the sample. This bias is introduced via a small spectral shift in the normalized power spectra of the reference and sample with different sound speeds. The hybrid method provides the best estimation performance, especially for sample attenuation coefficient values lower than that of the reference phantom. The performance of all the methods deteriorates when the attenuation coefficient of the reference phantom is lower than that of the sample. In addition, the hybrid method is the least sensitive to sample backscatter intensity variations.

A theoretical comparison of attenuation measurement techniques from backscattered ultrasound echoes

Accurate characterization of tissue pathologies using ultrasonic attenuation is strongly dependent on the accuracy of the algorithm that is used to obtain the attenuation coefficient estimates. In this paper, computer simulations were used to compare the accuracy and the precision of the three methods that are commonly used to estimate the local ultrasonic attenuation within a region of interest (ROI) in tissue; namely, the spectral log difference method, the spectral difference method, and the hybrid method. The effects of the inhomgeneities within the ROI on the accuracy of the three algorithms were studied, and the optimal ROI size (the number of independent echoes laterally and the number of pulse lengths axially) was quantified for each method. The three algorithms were tested for when the ROI was homogeneous, the ROI had variations in scatterer number density, and the ROI had variations in effective scatterer size. The results showed that when the ROI was homogeneous, the spectral difference method had the highest accuracy and precision followed by the spectral log difference method and the hybrid method, respectively. Also, when the scatterer number density varied, the spectral difference method completely failed, while the log difference method and hybrid method still gave good results. Lastly, when the scatterer size varied, all of the methods failed.

A novel power spectrum calculation method using phase-compensation and weighted averaging for the estimation of ultrasound attenuation

An estimation of ultrasound attenuation in soft tissues is critical in the quantitative ultrasound analysis since it is not only related to the estimations of other ultrasound parameters, such as speed of sound, integrated scatterers, or scatterer size, but also provides pathological information of the scanned tissue. However, estimation performances of ultrasound attenuation are intimately tied to the accurate extraction of spectral information from the backscattered radiofrequency (RF) signals. In this paper, we propose two novel techniques for calculating a block power spectrum from the backscattered ultrasound signals. These are based on the phase-compensation of each RF segment using the normalized cross-correlation to minimize estimation errors due to phase variations, and the weighted averaging technique to maximize the signal-to-noise ratio (SNR). The simulation results with uniform numerical phantoms demonstrate that the proposed method estimates local attenuation coefficients within 1.57% of the actual values while the conventional methods estimate those within 2.96%. The proposed method is especially effective when we deal with the signal reflected from the deeper depth where the SNR level is lower or when the gated window contains a small number of signal samples. Experimental results, performed at 5MHz, were obtained with a one-dimensional 128 elements array, using the tissue-mimicking phantoms also show that the proposed method provides better estimation results (within 3.04% of the actual value) with smaller estimation variances compared to the conventional methods (within 5.93%) for all cases considered.

Estimating the total ultrasound attenuation along the propagation path by applying multiple filters to backscattered echoes from a single spherically focused source

Quantifying the correlation length of the tissue microstructure has shown potential for differentiating between benign and malignant tumors. To implement these advances in the clinic, the total frequency-dependent attenuation along the propagation path must be determined on a patient specific basis. Previously, an algorithm was developed to estimate this attenuation using echoes from multiple sources. In this study, the developed algorithm was extended to echoes from a single source by filtering the echoed signal into multiple frequency bands. This step was needed because it would be challenging to scan exactly the same tissue region using multiple sources in the clinic. Computer simulations and phantom experiments were conducted to verify the attenuation could be determined by filtering the echoes from a single source. The simulations utilized a spherically focused single-element source (5 cm focal length, f/4, 14 MHz center frequency, 50% bandwidth) exposing a homogeneous tissue region (Gaussian scattering structures with effective radii of 5 to 55 mum at a density of 250/mm(3), attenuation of 0.1 to 0.9 dB/cm.MHz). The phantom experiments utilized a spherically focused single-element source (5.08 cm focal length, f/4, 7.5 MHz center frequency) exposing a 0.5 dB/cm.MHz homogeneous glass bead phantom. The computer simulations and phantom experiment confirmed that the total attenuation along the propagation path can be determined by appropriately applying multiple filters to the backscattered echoes from a single source.

Trade-offs in data acquisition and processing parameters for backscatter and scatterer size estimations

By analyzing backscattered echo signal power spectra and thereby obtaining backscatter coefficient vs. frequency data, the size of subresolution scatterers contributing to echo signals can be estimated. Here we investigate trade-offs in data acquisition and processing parameters for reference phantom-based backscatter and scatterer size estimations. RF echo data from a tissue-mimicking test phantom were acquired using a clinical scanner equipped with linear array transducers. One array has a nominal frequency bandwidth of 5 to 13 MHz and the other 4 to 9 MHz. Comparison of spectral estimation methods showed that the Welch method provided spectra yielding more accurate and precise backscatter coefficient and scatterer size estimations than spectra computed by applying rectangular, Hanning, or Hamming windows and much reduced computational load than if using the multitaper method. For small echo signal data block sizes, moderate improvements in scatterer size estimations were obtained using a multitaper method, but this significantly increases the computational burden. It is critical to average power spectra from lateral A-lines for the improvement of scatterer size estimation. Averaging approximately 10 independent A-lines laterally with an axial window length 10 times the center frequency wavelength optimized trade-offs between spatial resolution and the variance of scatterer size estimates. Applying the concept of a time-bandwidth product, this suggests using analysis blocks that contain at least 30 independent samples of the echo signal. The estimation accuracy and precision depend on the ka range where k is the wave number and a is the effective scatterer size. This introduces a region-of-interest depth dependency to the accuracy and precision because of preferential attenuation of higher frequency sound waves in tissuelike media. With the 5 to 13 MHz, transducer ka ranged from 0.5 to 1.6 for scatterers in the test phantom, which is a favorable range, and the accuracy and precision of scatterer size estimations were both within approximately 5% using optimal analysis block dimensions. When the 4- to 9-MHz transducer was used, the ka value ranged from 0.3 to 0.8 to 1.1 for the experimental conditions, and the accuracy and precision were found to be approximately 10% and 10% to 25%, respectively. Although the experiments were done with 2 specific models of transducers on the test phantom, the results can be generalized to similar clinical arrays available from a variety of manufacturers and/or for different size of scatterers with similar ka range.

Measurements of attenuation coefficient for evaluating the hardness of a cataract lens by a high-frequency ultrasonic needle transducer

A cataract is a clouding of the lens in the eye that affects vision. Phacoemulsification is the mostly common surgical method for treating cataracts, and determining that the optimal phacoemulsification energy is dependent on measuring the hardness of the lens. This study explored the use of an ultrasound needle transducer for invasive measurements of ultrasound attenuation coefficient to evaluate the hardness of the cataract lens. A 47 MHz high-frequency needle transducer with a diameter of 0.9 mm was fabricated by a polarized PMN-33%PT single crystal in the present study. The attenuation coefficients at different stages of an artificial porcine cataract lens were measured using the spectral shift approach. The hardness of the cataract lens was also evaluated by mechanical measurement of its elastic properties. The results demonstrated that the ultrasonic attenuation coefficient was increased from 0.048 +/- 0.02 to 0.520 +/- 0.06 dB mm(-1) MHz(-1) corresponding to an increase in Young's modulus from 6 +/- 0.4 to 96 +/- 6.2 kPa as the cataract further developed. In order to evaluate the feasibility of combining needle transducer and phacoemulsification probe for real-time measurement during cataract surgery, the needle transducer was mounted on the phacoemulsification probe for a vibration test. The results indicated that there was no apparent damage to the tip of the needle transducer and the pulse-echo test showed that a good performance in sensitivity was maintained after the vibration test.

Hybrid spectral domain method for attenuation slope estimation

Attenuation estimation methods for medical ultrasound are important because attenuation properties of soft tissue can be used to distinguish between benign and malignant tumors and to detect diffuse disease. The classical spectral shift method and the spectral difference method are the most commonly used methods for the estimation of the attenuation; however, they both have specific limitations. Classical spectral shift approaches for estimating ultrasonic attenuation are more sensitive to local spectral noise artifacts and have difficulty in compensating for diffraction effects because of beam focusing. Spectral difference approaches, on the other hand, fail to accurately estimate attenuation coefficient values at tissue boundaries that also possess variations in the backscatter. In this paper, we propose a hybrid attenuation estimation method that combines the advantages of the spectral difference and spectral shift methods to overcome their specific limitations. The proposed hybrid method initially uses the spectral difference approach to reduce the impact of system-dependent parameters including diffraction effects. The normalized power spectrum that includes variations because of backscatter changes is then filtered using a Gaussian filter centered at the transmit center frequency of the system. A spectral shift method, namely the spectral cross-correlation algorithm is then used to compute spectral shifts from these filtered power spectra to estimate the attenuation coefficient. Ultrasound simulation results demonstrate that the estimation accuracy of the hybrid method is better than the centroid downshift method (spectral shift method), in uniformly attenuating regions. In addition, this method is also stable at boundaries with variations in the backscatter when compared with the reference phantom method (spectral difference method). Experimental results using tissue-mimicking phantom also illustrate that the hybrid method is more robust and provides accurate attenuation estimates in both uniformly attenuating regions and across boundaries with backscatter variations. The proposed hybrid method preserves the advantages of both the spectral shift and spectral difference approaches while eliminating the disadvantages associated with each of these methods, thereby improving the accuracy and robustness of the attenuation estimation.

In vivo ultrasonic attenuation slope estimates for detecting cervical ripening in rats: Preliminary results

To effectively postpone preterm birth, cervical ripening needs to be detected and delayed. As the cervix ripens, the spacing between the collagen fibers increases and fills with water, hyaluronan, decorin, and enzymes suggesting that the ultrasonic attenuation of the cervix should decrease. The decrease in ultrasonic attenuation may be detectable, leading to an effective means of detecting cervical ripening. Herein, the traditional attenuation slope-estimation algorithm based on measuring the downshift in center frequency of the ultrasonic backscattered signal with propagation depth was modified and applied to the cervix of rats. The modified algorithm was verified using computer simulations and an ex vivo tissue sample before being evaluated in in vivo animal studies. Spherically-focused f/3 transducers with 33-MHz center frequencies and with 9-mm focal lengths were used in both the simulations and experiments. The accuracy was better than 15% in the simulations, and the attenuation slope of the cervix in the ex vivo experiment was 2.6+/-0.6 dB/cm-MHz, which is comparable to 2.5+/-0.4 dB/cm-MHz measured using a through-transmission insertion loss technique. For the in vivo experiments, a statistically significant effect of ultrasonic attenuation with gestational age was not observed. The large variances in the in vivo results were most likely due to the natural variation in attenuation for biological tissue between animals.