Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions.

Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns, such as scatterer concentrations and arrangements. In this study, we proposed a machine learning approach to integrate the strength of multimodality quantitative ultrasound envelope statistics imaging techniques and applied it to detecting microwave ablation induced thermal lesions in porcine liver ex vivo. The quantitative ultrasound parameters included were homodyned-K α which is a scatterer clustering parameter related to the effective scatterer number per resolution cell, Nakagami m which is a shape parameter of the envelope probability density function, and Shannon entropy which is a measure of signal uncertainty or complexity. Specifically, the homodyned-K log10(α), Nakagami-m, and horizontally normalized Shannon entropy parameters were combined as input features to train a support vector machine (SVM) model to classify thermal lesions with higher scatterer concentrations from normal tissues with lower scatterer concentrations. Through heterogeneous phantom simulations based on Field II, the proposed SVM model showed a classification accuracy above 0.90; the area accuracy and Dice score of higher-scatterer-concentration zone identification exceeded 83% and 0.86, respectively, with the Hausdorff distance <26. Microwave ablation experiments of porcine liver ex vivo at 60-80 W, 1-3 min showed that the SVM model achieved a classification accuracy of 0.85; compared with single log10(α),m, or hNSE parametric imaging, the SVM model achieved the highest area accuracy (89.1%) and Dice score (0.77) as well as the smallest Hausdorff distance (46.38) of coagulation zone identification. We concluded that the proposed multimodality quantitative ultrasound envelope statistics imaging based SVM approach can enhance the capability to characterize tissue scatterer distribution patterns and has the potential to detect the thermal lesions induced by microwave ablation.

Normative ultrasound values for Achilles tendon thickness in the general population and patients with Achilles tendinopathy: A large international cross-sectional study.

The objective of the study was to obtain adjusted ultrasonographic reference values of the Achilles tendon thickness (maximum anterior-posterior distance) in adults without (previous) Achilles tendinopathy (AT) and to compare these reference values with AT patients. Six hundred participants were consecutively included, comprising 500 asymptomatic individuals and 100 patients with clinically diagnosed chronic AT. The maximum tendon thickness was assessed using Ultrasound Tissue Characterization. A multiple quantile regression model was developed, incorporating covariates (personal characteristics) that were found to have a significant impact on the maximum anterior-posterior distance of the Achilles tendon. A 95% reference interval (RI) was derived (50th, 2.5th-97.5th percentile). In asymptomatic participants median (95% RI) tendon thickness was 4.9 (3.8-6.9) mm for the midportion region and 3.7 (2.8-4.8) mm for the insertional region. Age, height, body mass index, and sex had a significant correlation with maximum tendon thickness. Median tendon thickness for the midportion region was calculated with the normative equation -2.1 + AGE × 0.021 + HEIGHT × 0.032+ BMI × 0.028 + SEX × 0.05. For the insertional region, the normative equation was -0.34 + AGE × 0.010+ HEIGHT × 0.018 + BMI × 0.022 + SEX × -0.05. In the equations, SEX is defined as 0 for males and 1 for females. Mean (95% CI) difference in tendon thickness compared to AT patients was 2.7 mm (2.3-3.2, p < 0.001) for the midportion and 1.4 mm (1.1-1.7, p < 0.001) for the insertional region. Compared to the asymptomatic population 73/100 (73%) AT patients exhibited increased tendon thickening, with values exceeding the 95% RI. This study presents novel reference values for the thickness of midportion and insertional region of the Achilles tendon, which were adjusted for personal characteristics. Our novel web-based openly accessible calculator for determining normative Achilles tendon thickness (www.achillestendontool.com) will be a useful resource in the diagnostic process. Trial registration number: This trial is registered in the Netherlands Trial Register (NL9010).

Measuring Ultrasonographic Thickness of the Achilles Tendon Insertion Is Less Reliable Than the Midportion in Healthy Tendons and Patients With Tendinopathy.

INTRODUCTION: Ultrasound is the preferred imaging method in the diagnostic process of Achilles tendinopathy (AT). Ultrasound tissue characterization (UTC) is a frequently used, standardized and valid method to assess tendon geometry in AT patients. It is unknown whether UTC is reliable for measuring Achilles tendon thickness. The aim of the study was to assess intra- and inter-rater reliability of Achilles tendon thickness measurements using UTC in both asymptomatic individuals and patients with AT, and to evaluate if the reliability of thickness measurements differs between the midportion and insertional area. METHODS: Exactly 50 patients with AT and 50 asymptomatic individuals were included. Using the conventional US and standardized UTC procedure maximum thickness was measured in the midportion and insertion region. To determine inter- and intra-rater reliabilities, the intraclass correlation coefficient (ICC) was used. RESULTS: The ICC values for inter- and intra-rater reliability were classified as "excellent," for the AT group (0.93 [95% CI: 0.88-0.96] and 0.95 [0.92-0.97]) and asymptomatic participants (0.91 [0.87-0.94] and 0.94 [0.92-0.96]). The reliability of measuring tendon thickness in the midportion region was "excellent," with both inter-rater (0.97 [0.95-0.98]) and intra-rater (0.98 [0.96-0.99]) ICC values indicating high levels of agreement. In the insertional region, ICC values for inter-rater (0.79 [0.69-0.87]) and intra-rater (0.89 [0.84-0.93]) reliability were "moderate to good." CONCLUSION: We showed excellent reliability for measuring the US thickness of the midportion and good reliability of measuring the insertional region in patients with AT. Significantly lower ICCs were observed for the reliability of thickness measurements in the insertional region when compared with the midportion.

Ultrasound Entropy Imaging Based on the Kernel Density Estimation: A New Approach to Hepatic Steatosis Characterization.

In this paper, we present the kernel density estimation (KDE)-based parallelized ultrasound entropy imaging and apply it for hepatic steatosis characterization. A KDE technique was used to estimate the probability density function (PDF) of ultrasound backscattered signals. The estimated PDF was utilized to estimate the Shannon entropy to construct parametric images. In addition, the parallel computation technique was incorporated. Clinical experiments of hepatic steatosis were conducted to validate the feasibility of the proposed method. Seventy-two participants and 204 patients with different grades of hepatic steatosis were included. The experimental results show that the KDE-based entropy parameter correlates with log10 (hepatic fat fractions) measured by magnetic resonance spectroscopy in the 72 participants (Pearson's r = 0.52, p < 0.0001), and its areas under the receiver operating characteristic curves for diagnosing hepatic steatosis grades ≥ mild, ≥moderate, and ≥severe are 0.65, 0.73, and 0.80, respectively, for the 204 patients. The proposed method overcomes the drawbacks of conventional histogram-based ultrasound entropy imaging, including limited dynamic ranges and histogram settings dependence, although the diagnostic performance is slightly worse than conventional histogram-based entropy imaging. The proposed KDE-based parallelized ultrasound entropy imaging technique may be used as a new ultrasound entropy imaging method for hepatic steatosis characterization.

Quadriceps strength, patellar tendon quality, relative load exposure, and knee symptoms in male athletes before the anterior cruciate ligament reconstruction.

Introduction: Anterior cruciate ligament (ACL) injuries cause knee instability, knee pain, weight-bearing adjustments, and functional deficits but their association to patellar tendon quality is unknown. Our purpose was to investigate quadriceps strength, patellar tendon quality, relative load exposure, perceived knee stability, knee pain, extension angle, and time from ACL injury; in addition to examining their relative associations. Methods: Injured and uninjured legs of 81 male athletes of different sports with a unilateral ACL injury (18-45 years) were examined. Participants reported location and intensity of knee pain and their perceived stability using a numerical rating scale (NRS 0-10). Strength was tested with an isokinetic device. Tendon quality was measured using ultrasound tissue characterization. Means ± standard deviation (SD) of perceived knee stability, knee extension angle, knee pain, isokinetic quadriceps strength in relation to body mass, proportion of echo-types (I-IV), tendon volume, and number of days from ACL injury to assessment are reported. Values of effect sizes (ES) and correlations (rs) were calculated. Results: ACL injured leg demonstrated reduced reported knee stability (6.3 ± 2.5), decreased knee extension angle (-0.7 ± 3.1° vs. -2.7 ± 2.2°; ES = 0.7; P < 0.001), greater knee pain (NRS 3.1 ± 2.2 vs. 0.0 ± 0.1; ES = 2.0; P < 0.001), and 22% lower quadriceps strength (228.0 ± 65.0 vs. 291.2 ± 52.9 Nm/kg: ES = 1.2; P < 0.001) as compared to the uninjured leg. However, patellar tendons in both legs displayed similar quality. Quadriceps strength was associated with stability (rs = -0.54; P < 0.001), pain (rs = -0.47; P < 0.001), extension angle (rs = -0.39; P < 0.001), and relative load exposure (rs = -0.34; P < 0.004). Echo-types distribution was beneficially associated with time from ACL injury (rs range: -0.20/ -0.32; P < 0.05). Discussion: ACL injured athletes displayed knee pain, extension deficit, and weaker quadriceps in the injured leg. While there were no differences in patellar tendon quality between legs, longer time from ACL injury showed better tendon quality.

Review of Envelope Statistics Models for Quantitative Ultrasound Imaging and Tissue Characterization.

The homodyned K-distribution and the K-distribution, viewed as a special case, as well as the Rayleigh and the Rice distributions, viewed as limit cases, are discussed in the context of quantitative ultrasound (QUS) imaging. The Nakagami distribution is presented as an approximation of the homodyned K-distribution. The main assumptions made are (1) the absence of log-compression or application of nonlinear filtering on the echo envelope of the radiofrequency signal and (2) the randomness and independence of the diffuse scatterers. We explain why other available models are less amenable to a physical interpretation of their parameters. We also present the main methods for the estimation of the statistical parameters of these distributions. We explain why we advocate the methods based on the X-statistics for the Rice and the Nakagami distributions and the K-distribution. The limitations of the proposed models are presented. Several new results are included in the discussion sections, with proofs in the appendix.

MBR-Net: A multi-branch residual network based on ultrasound backscattered signals for characterizing pediatric hepatic steatosis.

The evaluation of pediatric hepatic steatosis and early detection of fatty liver in children are of critical importance. In this paper, a deep learning model based on the convolutional neural network (CNN) of ultrasound backscattered signals, multi-branch residual network (MBR-Net), was proposed for characterizing pediatric hepatic steatosis. The MBR-Net was composed of three convolutional branches. Each branch used different sizes of convolution blocks to enhance the capability of local feature acquisition, and leveraged the residual mechanism with skip connections to guide the network to effectively capture features. A total of 393 frames of ultrasound backscattered signals collected from 131 children were included in the experiments. The hepatic steatosis index was used as the reference standard for diagnosing the steatosis grade, G0-G3. The ultrasound backscattered signals within the liver region of interests (ROIs) were normalized and augmented using a sliding gate method. The gated ROI signals were randomly divided into training, validation, and test sets with the ratio of 8:1:1. The area under the operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE) were used as the evaluation metrics. Experimental results showed that the MBR-Net yields AUCs for diagnosing pediatric hepatic steatosis grade ≥G1, ≥G2, and ≥G3 of 0.94 (ACC: 93.65%; SEN: 89.79%; SPE: 84.48%), 0.93 (ACC: 90.48%; SEN: 87.75%; SPE: 82.65%), and 0.93 (ACC: 87.76%; SEN: 84.84%; SPE: 86.55%), respectively, which were superior to the conventional one-branch CNNs without residual mechanisms. The proposed MBR-Net can be used as a new deep learning method for ultrasound backscattered signal analysis to characterize pediatric hepatic steatosis.

Parallelized ultrasound homodyned-K imaging based on a generalized artificial neural network estimator.

The homodyned-K (HK) distribution model is a generalized backscatter envelope statistical model for ultrasound tissue characterization, whose parameters are of physical meaning. To estimate the HK parameters is an inverse problem, and is quite complicated. Previously, we proposed an artificial neural network (ANN) estimator and an improved ANN (iANN) estimator for estimating the HK parameters, which are fast and flexible. However, a drawback of the conventional ANN and iANN estimators consists in that they use Monte Carlo simulations under known values of HK parameters to generate training samples, and thus the ANN and iANN models have to be re-trained when the size of the test sets (or of the envelope samples to be estimated) varies. In addition, conventional ultrasound HK imaging uses a sliding window technique, which is non-vectorized and does not support parallel computation, so HK image resolution is usually sacrificed to ensure a reasonable computation cost. To this end, we proposed a generalized ANN (gANN) estimator in this paper, which took the theoretical derivations of feature vectors for network training, and thus it is independent from the size of the test sets. Further, we proposed a parallelized HK imaging method that is based on the gANN estimator, which used a block-based parallel computation method, rather than the conventional sliding window technique. The gANN-based parallelized HK imaging method allowed a higher image resolution and a faster computation at the same time. Computer simulation experiments showed that the gANN estimator was generally comparable to the conventional ANN estimator in terms of HK parameter estimation performance. Clinical experiments of hepatic steatosis showed that the gANN-based parallelized HK imaging could be used to visually and quantitatively characterize hepatic steatosis, with similar performance to the conventional ANN-based HK imaging that used the sliding window technique, but the gANN-based parallelized HK imaging was over 3 times faster than the conventional ANN-based HK imaging. The parallelized computation method presented in this work can be easily extended to other quantitative ultrasound imaging applications.

A Study on a Parameter Estimator for the Homodyned K Distribution Based on Table Search for Ultrasound Tissue Characterization.

OBJECTIVE: The homodyned K (HK) distribution is considered to be the most suitable distribution in the context of tissue characterization; therefore, the search for a rapid and reliable parameter estimator for HK distribution is important. METHODS: We propose a novel parameter estimator based on a table search (TS) for HK parameter estimates. The TS estimator can inherit the strength of conventional estimators by integrating various features and taking advantage of the TS method in a rapid and easy operation. Performance of the proposed TS estimator was evaluated and compared with that of XU (the estimation method based on X and U statistics) and artificial neural network (ANN) estimators. DISCUSSION: The simulation results revealed that the TS estimator is superior to the XU and ANN estimators in terms of normalized standard deviations and relative root mean squared errors of parameter estimation, and is faster. Clinical experiments found that the area under the receiver operating curve for breast lesion classification using the parameters estimated by the TS estimator could reach 0.871. CONCLUSION: The proposed TS estimator is more accurate, reliable and faster than the state-of-the-art XU and ANN estimators and has great potential for ultrasound tissue characterization based on the HK distribution.

Evaluation of Hepatic Fibrosis Using Ultrasound Backscattered Radiofrequency Signals and One-Dimensional Convolutional Neural Networks.

The early detection of hepatic fibrosis is of critical importance. Ultrasound backscattered radiofrequency signals from the liver contain abundant information about its microstructure. We proposed a method for characterizing human hepatic fibrosis using one-dimensional convolutional neural networks (CNNs) based on ultrasound backscattered signals. The proposed CNN model was composed of four one-dimensional convolutional layers, four one-dimensional max-pooling layers, and four fully connected layers. Ultrasound radiofrequency signals collected from 230 participants (F0: 23; F1: 46; F2: 51; F3: 49; F4: 61) with a 3-MHz transducer were analyzed. Liver regions of interest (ROIs) that contained most of the liver ultrasound backscattered signals were manually delineated using B-mode images reconstructed from the backscattered signals. ROI signals were normalized and augmented by using a sliding window technique. After data augmentation, the radiofrequency signal segments were divided into training sets, validation sets and test sets at a ratio of 80%:10%:10%. In the test sets, the proposed algorithm produced an area under the receive operating characteristic curve of 0.933 (accuracy: 91.30%; sensitivity: 92.00%; specificity: 90.48%), 0.997 (accuracy: 94.29%; sensitivity: 94.74%; specificity: 93.75%), 0.818 (accuracy: 75.00%; sensitivity: 69.23%; specificity: 81.82%), and 0.934 (accuracy: 91.67%; sensitivity: 88.89%; specificity: 94.44%) for diagnosis liver fibrosis stage ≥F1, ≥F2, ≥F3, and ≥F4, respectively. Experimental results indicated that the proposed deep learning algorithm based on ultrasound backscattered signals yields a satisfying performance when diagnosing hepatic fibrosis stages. The proposed method may be used as a new quantitative ultrasound approach to characterizing hepatic fibrosis.

Identifying achilles tendon structure differences by ultrasound tissue characterization in asymptomatic individuals.

Ultrasound Tissue Characterization (UTC) is a modality that can be utilized to characterize tendon tissue structure using ultrasonographic imaging paired with a computer algorithm to distinguish echo-types. Several studies have demonstrated UTCs ability to distinguish Achilles tendon morphology changes, but no study has established normative data of the Achilles tendon in the general population. The aim of this study was to determine UTC echo-type distribution in the Achilles tendon in an asymptomatic population. UTC scans were completed and analyzed on 508 participants without Achilles tendinopathy. Dedicated UTC-algorithms were used to distinguish and calculate echo-type percentages and the fiber type distribution was compared. The overall sample echo-type percentages demonstrated greater levels of Type I and II echo-types, 65.73% and 32.00%, respectively, and lower levels of Type III and IV echo-types, 1.74% and 0.57%, respectively. In addition, females had lower levels of Echo-type I compared to men and greater levels of echo-type II (p < 0.001). We also found that African-Americans had significantly greater amounts of echo-type I and lesser amounts of echo-type II when compared to Caucasians (p < 0.05). The results of this study create a normative data set for future UTC studies to utilize as a baseline for the evaluation of Achilles tendons. In addition, it demonstrated tendon type differences between sexes and races that need to be accounted for in future studies.

Evaluation of Current Symptoms in Postoperative Achilles Tendons: A Multimodal Ultrasound Study.

(1) Background: It is unknown which imaging parameters are associated with clinical persistent symptoms in postoperative Achilles tendons. This study used B-Mode, Power Doppler (PD-US), Ultrasound Tissue Characterization (UTC) and Shear Wave Elastography (SWE) to investigate which imaging parameters are associated with persistent symptoms in postoperative Achilles tendon tissue. (2) Methods: Retrospective, cross-sectional, multimodal imaging study. Based on the VISA-A score, postoperative tendons were assigned to two groups: 1. asymptomatic (VISA-A ≥ 90, n = 18); 2. symptomatic (VISA-A < 90, n = 10). The following imaging parameters were analyzed: UTC (echo type I, II, III, IV), B-Mode (diameter, cross sectional area, calcification, fiber irregularity), PD-US (Öhberg score) and SWE (SWE 3 mm, SWE area) using a t-test and a Mann-Whitney U test. (3) Results: SWE and PD-US showed significantly reduced elasticity and increased neovascularization in symptomatic tendons (SWE 3 mm p = 0.031, SWE area p = 0.046, Öhberg score p < 0.001). The only significant correlation between imaging parameters and the VISA-A score was assessed for SWE 3 mm (r = 0.378; p = 0.047) and the Öhberg score (r = -0.737; p < 0.001). Conclusions: Symptomatic postoperative Achilles tendons showed increased neovascularization and lower SWE values than asymptomatic ones. Future studies should examine the diagnostic accuracy of PD-US and SWE in detecting current symptoms in postoperative Achilles tendons.

Multimodal Ultrasound Versus MRI for the Diagnosis and Monitoring of Achilles Tendinopathy: A Prospective Longitudinal Study.

BACKGROUND: The diagnosis and monitoring of Achilles tendinopathy with imaging are challenging. There is a lack of studies comparing the diagnostic accuracy of magnetic resonance imaging (MRI), brightness mode ultrasound (B-mode), and power Doppler ultrasound with recent technologies such as ultrasound tissue characterization (UTC) and shear wave elastography (SWE). PURPOSE: To assess whether SWE and UTC, which offer quantitative values, show a superior diagnostic accuracy and capacity to detect structural improvement in Achilles tendinopathy compared with MRI, B-mode, or power Doppler. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 2. METHODS: Patients with insertional (n = 28) and midportion (n = 38) Achilles tendinopathy were evaluated at baseline and 6-month follow-up using MRI, B-mode, power Doppler, SWE, and UTC. Asymptomatic controls (n = 37) were evaluated at T 0. Diagnostic accuracy was analyzed based on a quantitative receiver operating characteristic (ROC) analysis with quantitative cutoff values (anteroposterior diameter, Öhberg score, UTC echo type, Young modulus) and by semiquantitative Likert scale-based assessment of experienced physicians. RESULTS: For diagnosing insertional Achilles tendinopathy, semiquantitative MRI and power Doppler were most favorable (diagnostic accuracy, 95%), while the cross-sectional area of MRI revealed 89% accuracy in the ROC analyses (area under the curve [AUC], 0.911; P < .001). For diagnosing midportion Achilles tendinopathy, semiquantitative MRI and B-mode were most favorable (diagnostic accuracy, 87%), while UTC echo types 3 and 4 revealed 86% and 87% accuracy, respectively, in the ROC analyses (AUC, 0.911 and 0.941, respectively; P < .001). However, for quantitative and semiquantitative evaluation of diagnostic accuracy in both insertional and midportion Achilles tendinopathy, there was no significant difference in favor of one imaging modality over the others. Compared with baseline, only SWE showed a significant change at the 6-month follow-up (P = .003-.035), but there were only fair to poor monitoring accuracies of 71% (insertion) and 60% (midportion). However, compared with the other modalities, the monitoring accuracy of SWE was significantly higher (P = .002-.039). CONCLUSION: There was no statistically significant difference in favor of one imaging modality over the others, but MRI revealed the highest overall diagnostic accuracy for the diagnosis of both insertional and midportion Achilles tendinopathy.

Line- and Point-Focused Extracorporeal Shock Wave Therapy for Achilles Tendinopathy: A Placebo-Controlled RCT Study.

BACKGROUND: Extracorporeal shock wave therapy (ESWT) is a widely considered treatment option for Achilles tendinopathy. Line-focused ESWT is a novel technique treating a larger tendon area than point-focused ESWT. Monitoring capacities of clinical symptoms with ultrasound under ESWT treatment are unknown. HYPOTHESIS: Point- and line-focused ESWT have a superior outcome than placebo ESWT. ESWT leads to morphological tendon changes detectable with ultrasound. STUDY DESIGN: Single-blinded placebo-controlled randomized contolled trial. LEVEL OF EVIDENCE: Level 1. METHODS: The study was conducted in 3 cohorts, namely ESWT point (n = 21), ESWT line (n = 24), and ESWT placebo (n = 21). Victorian Institute of Sports Assessment-Achilles (VISA-A) score was measured before the intervention (T0), after 6 weeks (T1), and after 24 weeks (T2). All cohorts performed daily physiotherapy for 24 weeks and received 4 sessions of point-focused, line-focused, or placebo ESWT in the first 6 weeks. Ultrasound was performed with B-mode, power Doppler, shear wave elastography (SWE) at T0 and T2 and with ultrasound tissue characterization (UTC) at T0, T1, and T2. Data were analyzed with a mixed analysis of variance and t test. RESULTS: There was a significant VISA-A improvement over time for all groups (P < 0.001). ESWT point had the strongest VISA-A score improvement +23 (ESWT line: +18; ESWT placebo: +15), but there was no significant interaction between time and any of the groups: F(4, 116) = 1.393; P = 0.24. UTC, power Doppler, and B-mode could not show significant alterations over time. SWE revealed a significant increase of elastic properties for ESWT point in the insertion (t = -3.113, P = 0.03) and midportion (t = -2.627, P = 0.02) over time. CONCLUSION: There is a significant VISA-A score improvement for all study groups without a statistically significant benefit for ESWT point or ESWT line compared with ESWT placebo. Tendon adaptation could only be detected with SWE for ESWT point. CLINICAL RELEVANCE: The present study could not detect any statistically relevant effect of ESWT compared to placebo. SWE is able to demonstrate tendon adaptation.

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

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

Parameter estimation of the homodyned K distribution based on an artificial neural network for ultrasound tissue characterization.

The homodyned K (HK) distribution allows a general description of ultrasound backscatter envelope statistics with specific physical meanings. In this study, we proposed a new artificial neural network (ANN) based parameter estimation method of the HK distribution. The proposed ANN estimator took advantages of ANNs in learning and function approximation and inherited the strengths of conventional estimators through extracting five feature parameters from backscatter envelope signals as the input of the ANN: the signal-to-noise ratio (SNR), skewness, kurtosis, as well as X- and U-statistics. Computer simulations and clinical data of hepatic steatosis were used for validations of the proposed ANN estimator. The ANN estimator was compared with the RSK (the level-curve method that uses SNR, skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on X- and U-statistics) estimators. Computer simulation results showed that the relative bias was best for the XU estimator, whilst the normalized standard deviation was overall best for the ANN estimator. The ANN estimator was almost one order of magnitude faster than the RSK and XU estimators. The ANN estimator also yielded comparable diagnostic performance to state-of-the-art HK estimators in the assessment of hepatic steatosis. The proposed ANN estimator has great potential in ultrasound tissue characterization based on the HK distribution.

Ultrasound Backscatter Envelope Statistics Parametric Imaging for Liver Fibrosis Characterization: A Review.

Early detection and diagnosis of liver fibrosis is of critical importance. Currently the gold standard for diagnosing liver fibrosis is biopsy. However, liver biopsy is invasive and associated with sampling errors and can lead to complications such as bleeding. Therefore, developing noninvasive imaging techniques for assessing liver fibrosis is of clinical value. Ultrasound has become the first-line tool for the management of chronic liver diseases. However, the commonly used B-mode ultrasound is qualitative and can cause interobserver or intraobserver difference. Ultrasound backscatter envelope statistics parametric imaging is an important group of quantitative ultrasound techniques that have been applied to characterizing different kinds of tissue. However, a state-of-the-art review of ultrasound backscatter envelope statistics parametric imaging for liver fibrosis characterization has not been conducted. In this paper, we focused on the development of ultrasound backscatter envelope statistics parametric imaging techniques for assessing liver fibrosis from 1998 to September 2019. We classified these techniques into six categories: constant false alarm rate, fiber structure extraction technique, acoustic structure quantification, quantile-quantile probability plot, the multi-Rayleigh model, and the Nakagami model. We presented the theoretical background and algorithms for liver fibrosis assessment by ultrasound backscatter envelope statistics parametric imaging. Then, the specific applications of ultrasound backscatter envelope statistics parametric imaging techniques to liver fibrosis evaluation were reviewed and analyzed. Finally, the pros and cons of each technique were discussed, and the future development was suggested.

Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging.

Breast cancer is one of the most common cancers among women worldwide. Ultrasound imaging has been widely used in the detection and diagnosis of breast tumors. However, due to factors such as limited spatial resolution and speckle noise, classification of benign and malignant breast tumors using conventional B-mode ultrasound still remains a challenging task. H-scan is a new ultrasound technique that images the relative size of acoustic scatterers. However, the feasibility of H-scan ultrasound imaging in the classification of benign and malignant breast tumors has not been investigated. In this paper, we proposed a new method based on H-scan ultrasound imaging to classify benign and malignant breast tumors. Backscattered ultrasound radiofrequency signals of 100 breast tumors were used (48 benign and 52 malignant cases). H-scan ultrasound images were constructed with the radiofrequency signals by matched filtering using Gaussian-weighted Hermite polynomials. Experimental results showed that benign breast tumors had more red components, while malignant breast tumors had more blue components in H-scan ultrasound images. There were significant differences between the RGB channels of H-scan ultrasound images of benign and malignant breast tumors. We conclude H-scan ultrasound imaging can be used as a new method for classifying benign and malignant breast tumors.

Myocardial Fiber Mapping of Rat Hearts, Using Apparent Backscatter, with Histologic Validation.

Myocardial fiber architecture is a physiologically important regulator of ejection fraction, strain and pressure development. Apparent ultrasonic backscatter has been shown to be a useful method for recreating the myocardial fiber architecture in human-sized sheep hearts because of the dependence of its amplitude on the relative orientation of a myofiber to the angle of ultrasonic insonification. Thus, the anisotropy of the backscatter signal is linked to and provides information about the fiber orientation. In this study, we sought to determine whether apparent backscatter could be used to measure myofiber orientation in rodent hearts. Fixed adult-rat hearts were imaged intact, and both a transmural cylindrical core and transmural wedge of the left ventricular free wall were imaged. Cylindrical core samples confirmed that backscatter anisotropy could be measured in rat hearts. Ultrasound and histologic analysis of transmural myocardial wedge samples confirmed that the apparent backscatter could be reproducibly mapped to fiber orientation (angle of the fiber relative to the direction of insonification). These data provided a quantitative relationship between the apparent backscatter and fiber angle that was applied to whole-heart images. Myocardial fiber architecture was successfully measured in rat hearts. Quantifying myocardial fiber architecture, using apparent backscatter, provides a number of advantages, including its scalable use from rodents to man, its rapid low-cost acquisition and minimal contraindications. The method outlined in this study provides a method for investigators to begin detailed assessments of how the myocardial fiber architecture changes in preclinical disease models, which can be immediately translated into the clinic.