Displacement Tracking Techniques in Ultrasound Elastography: From Cross-Correlation to Deep Learning.

Ultrasound elastography is a non-invasive medical imaging technique that maps viscoelastic properties to characterize tissues and diseases. Elastography can be divided into two classes in a broad sense: strain elastography (SE), which relies on Hooke's law to delineate strain as a surrogate for elasticity, and shear-wave elastography (SWE), which tracks the propagation of shear waves in tissues to estimate the elasticity. As tracking the displacement field in the temporal or spatial domain is an inevitable step of both SE and SWE, the success is contingent on the displacement estimation accuracy. Recent reviews mostly focused on clinical applications of elastography, disregarding advances in displacement tracking algorithms. Herein, we comprehensively review the recently proposed displacement estimation algorithms applied to both SE and SWE. In addition to cross-correlation, block-matching (i.e., window-based), model-based, energy-based, and deep learning-based tracking techniques, we review large and lateral displacement tracking, adaptive beamforming, data enhancement, and noise-suppression algorithms facilitating better displacement estimation. We also discuss the simulation models for displacement tracking validation, clinical translation and validation of displacement tracking methods, performance evaluation metrics, and publicly available codes and data for displacement tracking in elastography. Finally, we provide experiential opinions on different tracking algorithms, list the limitations of the current state of elastographic tracking, and comment on possible future research.

Assessing the treatment response of lateral elbow tendinopathy using time-dependent ultrasonography, Doppler imaging, and elastography.

OBJECTIVE: To investigate the structural alterations, neovascularity, and elasticity of tendons and the relationship between elasticity and the Patient Rated Tennis Elbow Evaluation score after undergoing US-guided fenestration or surgery in patients with chronic lateral elbow tendinopathy. METHODS: Participants from the per-protocol population of a randomized trial conducted between October 2016 and June 2020 were included. The surgery and fenestration groups included 24 (mean age, 50 ± 7 years [standard deviation], 10 men) and 29 (47 ± 8 years, 18 men) participants, respectively. Ultrasound exams were performed at baseline, 6 months, and 12 months. Statistical analyses included linear mixed effects and generalized equation estimation models. RESULTS: Fenestration had no significant impact on tendon thickness (p = 0.46). Conversely, surgery significantly increased tendon thickness at 6 months (p < 0.0001) and remained elevated at 12 months (p = 0.04). Tendon echostructure exhibited a group effect (p = 0.03), indicating a higher proportion of pathological scores in the surgery group post-intervention compared to the fenestration group. Both groups showed a similar reduction in neovascularity from 6 to 12 months postintervention (p = 0.006). Shear-wave velocity increased in the fenestration group at 6 months (p = 0.04), while the surgery group experienced a nonsignificant decrease at 6 months, with some improvement at 12 months (p = 0.08). Changes in shear-wave velocity did not correlate with clinical outcome. CONCLUSIONS: Fenestration and surgery reduced tendon neovascularity over time. Unlike surgery, fenestration did not impact tendon size while improving tendon echostructure and elasticity. CRITICAL RELEVANCE STATEMENT: Fenestration and surgery equally alleviated symptoms and decreased tendon neovascularity in lateral elbow tendinopathy; however, fenestration did not alter tendon thickness and improved echostructure and shear-wave velocity, suggesting shear-wave velocity's potential for quantitatively monitoring tendon elasticity during healing. KEY POINTS: Reliable markers for monitoring healing response and informing treatment protocols in elbow tendinopathy are lacking. Fenestration and surgery reduced tendon neovascularity, while fenestration improved tendon echostructure and shear-wave velocity. Shear-wave velocity may provide quantitative measures to monitor tendon elasticity in response to treatment.

Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches.

Quantitative ultrasound (QUS) analyzes the ultrasound (US) backscattered data to find the properties of scatterers that correlate with the tissue microstructure. Statistics of the envelope of the backscattered radio frequency (RF) data can be utilized to estimate several QUS parameters. Different distributions have been proposed to model envelope data. The homodyned K-distribution (HK-distribution) is one of the most comprehensive distributions that can model US backscattered envelope data under diverse scattering conditions (varying scatterer number density and coherent scattering). The scatterer clustering parameter ( α ) and the ratio of the coherent to diffuse scattering power ( k ) are the parameters of this distribution that have been used extensively for tissue characterization in diagnostic US. The estimation of these two parameters (which we refer to as HK parameters) is done using optimization algorithms in which statistical features such as the envelope point-wise signal-to-noise ratio (SNR), skewness, kurtosis, and the log-based moments have been utilized as input to such algorithms. The optimization methods minimize the difference between features and their theoretical value from the HK model. We propose that the true value of these statistical features is a hyperplane that covers a small portion of the feature space. In this article, we follow two approaches to reduce the effect of sample features' error. We propose a model projection neural network based on denoising autoencoders to project the noisy features into this space based on this assumption. We also investigate if the noise distribution can be learned by the deep estimators. We compare the proposed methods with conventional methods using simulations, an experimental phantom, and data from an in vivo animal model of hepatic steatosis. The network weight and a demo code are available online at ht.tp://code.sonography.ai.

Effect of rt-PA on Shear Wave Mechanical Assessment and Quantitative Ultrasound Properties of Blood Clot Kinetics In Vitro.

OBJECTIVE: The consequences associated with blood clots are numerous and are responsible for many deaths worldwide. The assessment of treatment efficacy is necessary for patient follow-up and to detect treatment-resistant patients. The aim of this study was to characterize the effect of treatment on blood clots in vitro using quantitative ultrasound parameters. METHODS: Blood from 10 pigs was collected to form three clots per pig in gelatin phantoms. Clots were subjected to 1) no treatment, 2) rt-PA (recombinant tissue plasminogen activator) treatment after 20 minutes of clotting, and 3) rt-PA treatment after 60 minutes of clotting. Clots were weighted before and after the experiment to assess the treatment effect by the mass loss. The clot kinetics was studied over 100 minutes using elastography (Young's modulus, shear wave dispersion, and shear wave attenuation). Homodyne K-distribution (HKD) parameters derived from speckle statistics were also studied during clot formation and dissolving (diffuse-to-total signal power ratio and intensity parameters). RESULTS: Treated clots loosed significantly more mass than non-treated ones (P < .005). A significant increase in Young's modulus was observed over time (P < .001), and significant reductions were seen for treated clots at 20 or 60 minutes compared with untreated ones (P < .001). The shear wave dispersion differed for treated clots at 60 minutes versus no treatments (P < .001). The shear wave attenuation decreased over time (P < .001), and was different for clots treated at 20 minutes versus no treatments (P < .031). The HKD intensity parameter varied over time (P < .032), and was lower for clots treated at 20 and 60 minutes than those untreated (P < .001 and P < .02). CONCLUSION: The effect of rt-PA treatment could be confirmed by a decrease in Young's modulus and HKD intensity parameter. The shear wave dispersion and shear wave attenuation were sensitive to late and early treatments, respectively. The Young's modulus, shear wave attenuation, and HKD intensity parameter varied over time despite treatment.

Resonance, Velocity, Dispersion, and Attenuation of Ultrasound-Induced Shear Wave Propagation in Blood Clot In Vitro Models.

OBJECTIVE: Improve the characterization of mechanical properties of blood clots. Parameters derived from shear wave (SW) velocity and SW amplitude spectra were determined for gel phantoms and in vitro blood clots. METHODS: Homogeneous phantoms and phantoms with gel or blood clot inclusions of different diameters and mechanical properties were analyzed. SW amplitude spectra were used to observe resonant peaks. Parameters derived from those resonant peaks were related to mimicked blood clot properties. Three regions of interest were tested to analyze where resonances occurred the most. For blood experiments, 20 samples from different pigs were analyzed over time during a 110-minute coagulation period using the Young modulus, SW frequency dispersion, and SW attenuation. RESULTS: The mechanical resonance was manifested by an increase in the number of SW spectral peaks as the inclusion diameter was reduced (P < .001). In blood clot inclusions, the Young modulus increased over time during coagulation (P < .001). Descriptive spectral parameters (frequency peak, bandwidth, and distance between resonant peaks) were linearly correlated with clot elasticity values (P < .001) with R2 = .77 for the frequency peak, .60 for the bandwidth, and .48 for the distance between peaks. The SW dispersion and SW attenuation reflecting the viscous behavior of blood clots decreased over time (P < .001), mainly in the early stage of coagulation (first minutes). CONCLUSION: The confined soft inclusion configuration favored SW mechanical resonances potentially challenging the computation of spectral-based parameters, such as the SW attenuation. The impact of resonances can be reduced by properly selecting the region of interest for data analysis.

Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis.

Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepatic steatosis in NAFLD at US, with biopsy as the reference standard. Materials and Methods This retrospective study included patients with NAFLD and control patients without hepatic steatosis who underwent abdominal US and contemporaneous liver biopsy from September 2010 to October 2019. Six readers visually graded steatosis on US images twice, 2 weeks apart. Reader agreement was assessed with use of κ statistics. Three deep learning techniques applied to B-mode US images were used to classify dichotomized steatosis grades. Classification performance of human radiologists and the deep learning model for dichotomized steatosis grades (S0, S1, S2, and S3) was assessed with area under the receiver operating characteristic curve (AUC) on a separate test set. Results The study included 199 patients (mean age, 53 years ± 13 [SD]; 101 men). On the test set (n = 52), radiologists had fair interreader agreement (0.34 [95% CI: 0.31, 0.37]) for classifying steatosis grades S0 versus S1 or higher, while AUCs were between 0.49 and 0.84 for radiologists and 0.85 (95% CI: 0.83, 0.87) for the deep learning model. For S0 or S1 versus S2 or S3, radiologists had fair interreader agreement (0.30 [95% CI: 0.27, 0.33]), while AUCs were between 0.57 and 0.76 for radiologists and 0.73 (95% CI: 0.71, 0.75) for the deep learning model. For S2 or lower versus S3, radiologists had fair interreader agreement (0.37 [95% CI: 0.33, 0.40]), while AUCs were between 0.52 and 0.81 for radiologists and 0.67 (95% CI: 0.64, 0.69) for the deep learning model. Conclusion Deep learning approaches applied to B-mode US images provided comparable performance with human readers for detection and grading of hepatic steatosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tuthill in this issue.

Ultrasound Shear Wave Attenuation Imaging for Grading Liver Steatosis in Volunteers and Patients With Non-alcoholic Fatty Liver Disease: A Pilot Study.

OBJECTIVE: The aims of the work described here were to assess shear wave attenuation (SWA) in volunteers and patients with non-alcoholic fatty liver disease (NAFLD) and compare its diagnostic performance with that of shear wave dispersion (SWD), magnetic resonance imaging (MRI) proton density fat fraction (PDFF) and biopsy. METHODS: Forty-nine participants (13 volunteers and 36 NAFLD patients) were enrolled. Ultrasound and MRI examinations were performed in all participants. Biopsy was also performed in patients. SWA was used to assess histopathology grades as potential confounders. The areas under curves (AUCs) of SWA, SWD and MRI-PDFF were assessed in different steatosis grades by biopsy. Youden's thresholds of SWA were obtained for steatosis grading while using biopsy or MRI-PDFF as the reference standard. RESULTS: Spearman's correlations of SWA with histopathology (steatosis, inflammation, ballooning and fibrosis) were 0.89, 0.73, 0.62 and 0.31, respectively. Multiple linear regressions of SWA confirmed the correlation with steatosis grades (adjusted R2 = 0.77, p < 0.001). The AUCs of MRI-PDFF, SWA and SWD were respectively 0.97, 0.99 and 0.94 for S0 versus ≥S1 (p > 0.05); 0.94, 0.98 and 0.78 for ≤S1 versus ≥S2 (both MRI-PDFF and SWA were higher than SWD, p < 0.05); and 0.90, 0.93 and 0.68 for ≤S2 versus S3 (both SWA and MRI-PDFF were higher than SWD, p < 0.05). SWA's Youden thresholds (Np/m/Hz) (sensitivity, specificity) for S0 versus ≥S1, ≤S1 versus ≥S2 and ≤S2 versus S3 were 1.05 (1.00, 0.92), 1.37 (0.96, 0.96) and 1.51 (0.83, 0.87), respectively. These values were 1.16 (1.00, 0.81), 1.49 (0.91, 0.82) and 1.67 (0.87, 0.92) when considering MRI-PDFF as the reference standard. CONCLUSION: In this pilot study, SWA increased with increasing steatosis grades, and its diagnostic performance was higher than that of SWD but equivalent to that of MRI-PDFF.

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.

US Quantification of Liver Fat: Past, Present, and Future.

Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardiovascular events and higher long-term medical costs, and may lead to liver-related morbidity and mortality. There is an urgent need for accurate, reproducible, accessible, and noninvasive techniques appropriate for detecting and quantifying liver fat in the general population and for monitoring treatment response in at-risk patients. CT may play a potential role in opportunistic screening, and MRI proton-density fat fraction provides high accuracy for liver fat quantification; however, these imaging modalities may not be suited for widespread screening and surveillance, given the high global prevalence. US, a safe and widely available modality, is well positioned as a screening and surveillance tool. Although well-established qualitative signs of liver fat perform well in moderate and severe steatosis, these signs are less reliable for grading mild steatosis and are likely unreliable for detecting subtle changes over time. New and emerging quantitative biomarkers of liver fat, such as those based on standardized measurements of attenuation, backscatter, and speed of sound, hold promise. Evolving techniques such as multiparametric modeling, radiofrequency envelope analysis, and artificial intelligence-based tools are also on the horizon. The authors discuss the societal impact of fatty liver disease, summarize the current state of liver fat quantification with CT and MRI, and describe past, currently available, and potential future US-based techniques for evaluating liver fat. For each US-based technique, they describe the concept, measurement method, advantages, and limitations. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Imaging the subcellular viscoelastic properties of mouse oocytes.

In recent years, cellular biomechanical properties have been investigated as an alternative to morphological assessments for oocyte selection in reproductive science. Despite the high relevance of cell viscoelasticity characterization, the reconstruction of spatially distributed viscoelastic parameter images in such materials remains a major challenge. Here, a framework for mapping viscoelasticity at the subcellular scale is proposed and applied to live mouse oocytes. The strategy relies on the principles of optical microelastography for imaging in combination with the overlapping subzone nonlinear inversion technique for complex-valued shear modulus reconstruction. The three-dimensional nature of the viscoelasticity equations was accommodated by applying an oocyte geometry-based 3D mechanical motion model to the measured wave field. Five domains-nucleolus, nucleus, cytoplasm, perivitelline space, and zona pellucida-could be visually differentiated in both oocyte storage and loss modulus maps, and statistically significant differences were observed between most of these domains in either property reconstruction. The method proposed herein presents excellent potential for biomechanical-based monitoring of oocyte health and complex transformations across lifespan. It also shows appreciable latitude for generalization to cells of arbitrary shape using conventional microscopy equipment.

Differential Impact of IL-32 Isoforms on the Functions of Coronary Artery Endothelial Cells: A Potential Link with Arterial Stiffness and Atherosclerosis.

Chronic inflammation is associated with higher risk of cardiovascular disease (CVD) in people living with HIV (PLWH). We have previously shown that interleukin-32 (IL-32), a multi-isoform proinflammatory cytokine, is chronically upregulated in PLWH and is linked with CVD. However, the mechanistic roles of the different IL-32 isoforms in CVD are yet to be identified. In this study, we aimed to investigate the potential impact of IL-32 isoforms on coronary artery endothelial cells (CAEC), whose dysfunction represents a major factor for atherosclerosis. Our results demonstrated that the predominantly expressed IL-32 isoforms (IL-32ß and IL-32γ) have a selective impact on the production of the proinflammatory cytokine IL-6 by CAEC. Furthermore, these two isoforms induced endothelial cell dysfunction by upregulating the expression of the adhesion molecules ICAM-I and VCAM-I and the chemoattractants CCL-2, CXCL-8 and CXCL-1. IL-32-mediated expression of these chemokines was sufficient to drive monocyte transmigration in vitro. Finally, we demonstrate that IL-32 expression in both PLWH and controls correlates with the carotid artery stiffness, measured by the cumulated lateral translation. These results suggest a role for IL-32-mediated endothelial cell dysfunction in dysregulation of the blood vessel wall and that IL-32 may represent a therapeutic target to prevent CVD in PLWH.

Non-Invasive Vascular Elastography as a One-Step Imaging Technique to Evaluate Early Vascular Changes in Children Compared to B-Mode-Based Intima-Media Thickness Technique : A Validation Study Using Inter- and Intra-Rater Reliability.

Background: Childhood obesity is linked to higher adult mortality and morbidity from atherosclerosis. It is primordial to detect at-risk children earlier-on to prevent disease progression. Carotid intima-media thickness (IMT) is a subclinical radiological marker for early atherosclerosis. B-mode ultrasound is a known technique to assess IMT, but no gold standard technique exists in children. Non-invasive vascular elastography (NIVE) using speckle statistics is an innovative alternative to evaluate IMT and adds by providing translation, strain and shear strain measurements. Validation studies for both techniques lack in children. Purpose: Validate the reproducibility of the 2 techniques in Canadian children. Methods: We conducted a prospective study where anthropometry, blood pressure, IMT and elastography were measured. Six operators obtained 2 measurements for both carotid arteries using both techniques, for a total of 720 measurements. Inter- and intra-class correlation coefficients (ICC) were calculated for each measurement technique and elastography parameters. Results: 30 participants (13.0 ± 1.26 years, 17 girls) were recruited. Twelve were overweight. No significant difference was found in mean IMT between weight groups for either technique (P = .15 and P = .60). We found excellent inter- (ICC = .98 [95% Confidence Interval (CI): .97; .99]) and intra- (ICC = .90-.93) operator reliability for the B-mode technique, and good inter (ICC = .70 [95% CI: .47; .85]) and intra- (ICC = .71-.91) operator reliability for the NIVE-based technique. Poor reliability was found between techniques (ICC = .30 [95% CI: -.31; .65). For elastography parameters, translation was the most reliable (ICC = .94-.95). Conclusion: IMT measurement is reproducible in children but not between techniques. NIVE gives the advantage of evaluating elastography.

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

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

Ultrafast Myocardial Principal Strain Ultrasound Elastography During Stress Tests: In Vitro Validation and In Vivo Feasibility.

Objective myocardial contractility assessment during stress tests aims to improve the diagnosis of myocardial ischemia. Tissue Doppler imaging (TDI) or optical flow (OF) speckle tracking echocardiography (STE) has been used to quantify myocardial contractility at rest. However, this is more challenging during stress tests due to image decorrelation at high heart rates. Moreover, stress tests imply a high frame rate which leads to a limited lateral field of view. Therefore, a large lateral field-of-view robust ultrafast myocardial regularized OF-TDI principal strain estimator has been developed for high-frame-rate echocardiography of coherently compounded transmitted diverging waves. The feasibility and accuracy of the proposed estimator were validated in vitro (using sonomicrometry as the gold standard) and in vivo stress experiments. Compared with OF strain imaging, the proposed estimator improved the accuracy of principal major and minor strains during stress tests, with an average contrast-to-noise ratio improvement of 4.4 ± 2.7 dB ( p -value < 0.01). Moreover, there was a significant correlation and a very close agreement between the proposed estimator and sonomicrometry for tested heart rates between 60 and 180 beats per minute (bpm). The averages ± standard deviations (STD) of R2 and biases ± STD between them were 0.96 ± 0.04 ( p -value < 0.01) and 0.01 ± 0.03% in the axial direction, respectively; and 0.94 ± 0.02 ( p -value < 0.01) and 0.04 ± 0.06% in the lateral direction, respectively. These results suggest that the proposed estimator could be useful clinically to provide an accurate and quantitative 2-D large lateral field-of-view myocardial strain assessment at high heart rates during stress echocardiography.

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

Nonalcoholic fatty liver disease (NAFLD) is believed to affect one-third of American adults. Noninvasive methods that enable detection and monitoring of NAFLD have the potential for great public health benefits. Because of its low cost, portability, and noninvasiveness, US is an attractive alternative to both biopsy and MRI in the assessment of liver steatosis. NAFLD is qualitatively associated with enhanced B-mode US echogenicity, but visual measures of B-mode echogenicity are negatively affected by interobserver variability. Alternatively, quantitative backscatter parameters, including the hepatorenal index and backscatter coefficient, are being investigated with the goal of improving US-based characterization of NAFLD. The American Institute of Ultrasound in Medicine and Radiological Society of North America Quantitative Imaging Biomarkers Alliance are working to standardize US acquisition protocols and data analysis methods to improve the diagnostic performance of the backscatter coefficient in liver fat assessment. This review article explains the science and clinical evidence underlying backscatter for liver fat assessment. Recommendations for data collection are discussed, with the aim of minimizing potential confounding effects associated with technical and biologic variables.

Regional pleural strain measurements during mechanical ventilation using ultrasound elastography: A randomized, crossover, proof of concept physiologic study.

Background: Mechanical ventilation is a common therapy in operating rooms and intensive care units. When ill-adapted, it can lead to ventilator-induced lung injury (VILI), which is associated with poor outcomes. Excessive regional pulmonary strain is thought to be a major mechanism responsible for VILI. Scarce bedside methods exist to measure regional pulmonary strain. We propose a novel way to measure regional pleural strain using ultrasound elastography. The objective of this study was to assess the feasibility and reliability of pleural strain measurement by ultrasound elastography and to determine if elastography parameters would correlate with varying tidal volumes. Methods: A single-blind randomized crossover proof of concept study was conducted July to October 2017 at a tertiary care referral center. Ten patients requiring general anesthesia for elective surgery were recruited. After induction, patients received tidal volumes of 6, 8, 10, and 12 mL.kg-1 in random order, while pleural ultrasound cineloops were acquired at 4 standardized locations. Ultrasound radiofrequency speckle tracking allowed computing various pleural translation, strain and shear components. We screened 6 elastography parameters (lateral translation, lateral absolute translation, lateral strain, lateral absolute strain, lateral absolute shear and Von Mises Strain) to identify those with the best dose-response with tidal volumes using linear mixed effect models. Goodness-of-fit was assessed by the coefficient of determination. Intraobserver, interobserver and test-retest reliability were calculated using intraclass correlation coefficients. Results: Analysis was possible in 90.7% of ultrasound cineloops. Lateral absolute shear, lateral absolute strain and Von Mises strain varied significantly with tidal volume and offered the best dose-responses and data modeling fits. Point estimates for intraobserver reliability measures were excellent for all 3 parameters (0.94, 0.94, and 0.93, respectively). Point estimates for interobserver (0.84, 0.83, and 0.77, respectively) and test-retest (0.85, 0.82, and 0.76, respectively) reliability measures were good. Conclusion: Strain imaging is feasible and reproducible. Future studies will have to investigate the clinical relevance of this novel imaging modality. Clinical trial registration: www.Clinicaltrials.gov, identifier NCT03092557.

Deep learning in ultrasound elastography imaging: A review.

It is known that changes in the mechanical properties of tissues are associated with the onset and progression of certain diseases. Ultrasound elastography is a technique to characterize tissue stiffness using ultrasound imaging either by measuring tissue strain using quasi-static elastography or natural organ pulsation elastography, or by tracing a propagated shear wave induced by a source or a natural vibration using dynamic elastography. In recent years, deep learning has begun to emerge in ultrasound elastography research. In this review, several common deep learning frameworks in the computer vision community, such as multilayered perceptron, convolutional neural network, and recurrent neural network, are described. Then, recent advances in ultrasound elastography using such deep learning techniques are revisited in terms of algorithm development and clinical diagnosis. Finally, the current challenges and future developments of deep learning in ultrasound elastography are prospected.

Associative Prediction of Carotid Artery Plaques Based on Ultrasound Strain Imaging and Cardiovascular Risk Factors in People Living With HIV and Age-Matched Control Subjects of the CHACS Cohort.

BACKGROUND: There is a need for a specific atherosclerotic risk assessment for people living with HIV (PLWH). SETTING: A machine learning classification model was applied to PLWH and control subjects with low-to-intermediate cardiovascular risks to identify associative predictors of diagnosed carotid artery plaques. Associations with plaques were made using strain elastography in normal sections of the common carotid artery and traditional cardiovascular risk factors. METHODS: One hundred two PLWH and 84 control subjects were recruited from the prospective Canadian HIV and Aging Cohort Study (57 ± 8 years; 159 men). Plaque presence was based on clinical ultrasound scans of left and right common carotid arteries and internal carotid arteries. A classification task for identifying subjects with plaque was defined using random forest (RF) and logistic regression models. Areas under the receiver operating characteristic curves (AUC-ROCs) were applied to select 5 among 50 combinations of 4 or less features yielding the highest AUC-ROCs. RESULTS: To retrospectively classify individuals with and without plaques, the 5 most discriminant combinations of features had AUC-ROCs between 0.76 and 0.79. AUC-ROCs from RF were statistically significantly higher than those obtained with logistic regressions ( P = 0.0001). The most discriminant features of RF classifications in PLWH were age, smoking status, maximum axial strain and pulse pressure (equal weights), and sex and antiretroviral therapy exposure (equal weights). When considering the whole population, the HIV status was identified as a cofactor associated with carotid artery plaques. CONCLUSIONS: Strain elastography adds to traditional cardiovascular risk factors for identifying individuals with carotid artery plaques.

Treatment of chronic lateral epicondylosis: a randomized trial comparing the efficacy of ultrasound-guided tendon dry needling and open-release surgery.

OBJECTIVE: Evaluate the efficacy of ultrasound-guided dry needling and open-release surgery in reducing pain and improving function in workers with lateral epicondylosis refractory to at least 6 months of nonsurgical management. METHODS: We randomly assigned participants in a 1:1 ratio to receive dry needling or surgery. The primary outcome was the Patient Rated Tennis Elbow Evaluation (PRTEE) score at 6 months. Secondary outcome measures examined the impact of these techniques on professional activity, grip strength, and Global Rating of Change and Satisfaction scales. Statistical analyses included mixed-effects models and Fisher's exact tests. RESULTS: From October 2016 through June 2019, we enrolled 64 participants. Two participants were excluded, and data from 62 participants (48 ± 8 years, 33 men) with a mean duration of symptoms of 23 ± 21 months were analyzed. Baseline characteristics were similar in both groups. In the intention-to-treat analysis, no treatment-by-time interaction was observed (F(4,201) = 0.72; p = .58). The least-squares mean difference from baseline in PRTEE scores at 6 months was 33.4 (CI 25.2 - 41.5) in the surgery group and 26.9 (CI 19.4 - 34.4) in the dry needling group (p = .25). The proportion of successful treatment was 83% (CI 63 - 95%) and 81% (CI 63 - 93%) in the surgery and dry needling groups, respectively (p = 1.00). Changes in secondary outcomes were in the same direction as those of the primary outcome. No adverse event occurred. CONCLUSIONS: Ultrasound-guided dry needling resulted in comparable improvement in outcome scores on scales of pain, physical function, and global assessment of change and satisfaction than open-release surgery. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02710682 KEY POINTS: • In patients with chronic lateral epicondylosis, ultrasound-guided tendon dry needling provides comparable therapeutic efficacy to open-release surgery. • Ultrasound-guided tendon dry needling allows for an earlier return to work and may be less costly than open-release surgery. • Care management guidelines should recommend treatment by ultrasound-guided tendon dry needling before open-release surgery.

The Revisited Frequency-Shift Method for Shear Wave Attenuation Computation and Imaging.

Ultrasound (US) shear wave (SW) elastography has been widely studied and implemented on clinical systems to assess the elasticity of living organs. Imaging of SW attenuation reflecting viscous properties of tissues has received less attention. A revisited frequency shift (R-FS) method is proposed to improve the robustness of SW attenuation imaging. Performances are compared with the FS method that we originally proposed and with the two-point frequency shift (2P-FS) and attenuation measuring US SW elastography (AMUSE) methods. In the proposed R-FS method, the shape parameter of the gamma distribution fitting SW spectra is assumed to vary with distance, in contrast to FS. Second, an adaptive random sample consensus (A-RANSAC) line fitting method is used to prevent outlier attenuation values in the presence of noise. Validation was made on ten simulated phantoms with two viscosities (0.5 and 2 Pa [Formula: see text]) and different noise levels (15 to -5 dB), two experimental homogeneous gel phantoms, and six in vivo liver acquisitions on awake ducks (including three normal and three fatty duck livers). According to the conducted experiments, R-FS revealed mean reductions in coefficients of variation (CV) of 62.6% on simulations, 62.5% with phantoms, and 62.3% in vivo compared with FS. Corresponding reductions compared with 2P-FS were 45.4%, 77.1%, and 62.0%, respectively. Reductions in normalized root-mean-square errors for simulations were 63.9% and 48.7% with respect to FS and 2P-FS, respectively.