Brief Report: Subclinical Carotid Artery Atherosclerosis Is Associated With Increased Expression of Peripheral Blood IL-32 Isoforms Among Women Living With HIV

BACKGROUND

Persistent inflammation in HIV infection is associated with elevated cardiovascular disease (CVD) risk, even with viral suppression. Identification of novel surrogate biomarkers can enhance CVD risk stratification and suggest novel therapies. We investigated the potential of interleukin 32 (IL-32), a proinflammatory multi-isoform cytokine, as a biomarker for subclinical carotid artery atherosclerosis in virologically suppressed women living with HIV (WLWH).

METHODS AND RESULTS

Nested within the Women's Interagency HIV Study, we conducted a cross-sectional comparison of IL-32 between 399 WLWH and 100 women without HIV, followed by a case-control study of 72 WLWH (36 carotid artery plaque cases vs. 36 age-matched controls without plaque). Plasma IL-32 protein was measured by ELISA, and mRNA of IL-32 isoforms (IL-32α, β, γ, D, ε, and θ) was quantified by reverse transcription polymerase chain reaction from peripheral blood mononuclear cells. Plasma IL-32 protein levels were higher in WLWH compared with women without HIV (P = 0.02). Among WLWH, although plasma IL-32 levels did not differ significantly between plaque cases and controls, expression of IL-32 isoforms α, β, and ε mRNA was significantly higher in peripheral blood mononuclear cells from cases (P = 0.01, P = 0.005, and P = 0.018, respectively). Upregulation of IL-32β and IL-32ε among WLWH with carotid artery plaque persisted after adjustment for age, race/ethnicity, smoking, systolic blood pressure, body mass index, and history of hepatitis C virus (P = 0.04 and P = 0.045); the adjusted association for IL-32α was marginally significant (P = 0.07).

CONCLUSIONS

IL-32 isoforms should be studied further as potential CVD biomarkers. This is of particular interest in WLWH by virtue of altered IL-32 levels in this population.

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

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

Multiparametric in vivo ultrasound shear wave viscoelastography on farm-raised fatty duck livers: human radiology imaging applied to food sciences

Nine mulard ducks that were being raised for foie gras (steatosis) production went through in vivo shear wave (SW) elastography imaging of their liver during the force-feeding period to investigate changes in liver tissue characteristics. A total of 4 imaging sessions at an interval of 3 to 4 d were conducted at the farm on each animal. Three ducks were sacrificed at the second, third, and fourth imaging sessions for histopathology analysis of all animals at these time points. Six SW elastography parameters were evaluated: SW speed, SW attenuation, SW dispersion, Young's modulus, viscosity, and shear modulus. Shear waves of different frequencies propagate with different phase velocities. Thus, SW speed and other dependent parameters such as Young's modulus, viscosity, and shear modulus were computed at 2 frequencies: 75 and 202 Hz. Each parameter depicted a statistically significant trend along the force-feeding process (P-values between 0.001 and 0.0001). The fat fraction of the liver increased over the 12-day period of feeding. All parameters increased monotonically over time at 75 Hz, whereas modal relations were seen at 202 Hz. Shear wave dispersion measured between 75 and 202 Hz depicted a plateau from day 5. Based on this validation, proposed imaging methods are aimed to be used in the future on naturally fed ducks and geese.

Parameterized Strain Estimation for Vascular Ultrasound Elastography With Sparse Representation

Ultrasound vascular strain imaging has shown its potential to interrogate the motion of the vessel wall induced by the cardiac pulsation for predicting plaque instability. In this study, a sparse model strain estimator (SMSE) is proposed to reconstruct a dense strain field at a high resolution, with no spatial derivatives, and a high computation efficiency. This sparse model utilizes the highly-compacted property of discrete cosine transform (DCT) coefficients, thereby allowing to parameterize displacement and strain fields with truncated DCT coefficients. The derivation of affine strain components (axial and lateral strains and shears) was reformulated into solving truncated DCT coefficients and then reconstructed with them. Moreover, an analytical solution was derived to reduce estimation time. With simulations, the SMSE reduced estimation errors by up to 50% compared with the state-of-the-art window-based Lagrangian speckle model estimator (LSME). The SMSE was also proven to be more robust than the LSME against global and local noise. For in vitro and in vivo tests, residual strains assessing cumulated errors with the SMSE were 2 to 3 times lower than with the LSME. Regarding computation efficiency, the processing time of the SMSE was reduced by 4 to 25 times compared with the LSME, according to simulations, in vitro and in vivo results. Finally, phantom studies demonstrated the enhanced spatial resolution of the proposed SMSE algorithm against LSME.

Automatic Frame Selection using CNN in Ultrasound Elastography

Ultrasound elastography is used to estimate the mechanical properties of the tissue by monitoring its response to an internal or external force. Different levels of deformation are obtained from different tissue types depending on their mechanical properties, where stiffer tissues deform less. Given two radio frequency (RF) frames collected before and after some deformation, we estimate displacement and strain images by comparing the RF frames. The quality of the strain image is dependent on the type of motion that occurs during deformation. In-plane axial motion results in high-quality strain images, whereas out-of-plane motion results in low-quality strain images. In this paper, we introduce a new method using a convolutional neural network (CNN) to determine the suitability of a pair of RF frames for elastography in only 5.4 ms. Our method could also be used to automatically choose the best pair of RF frames, yielding a high-quality strain image. The CNN was trained on 3,818 pairs of RF frames, while testing was done on 986 new unseen pairs, achieving an accuracy of more than 91%. The RF frames were collected from both phantom and in vivo data.

Pilot clinical study of quantitative ultrasound spectroscopy measurements of erythrocyte aggregation within superficial veins

BACKGROUND:

An enhanced inflammatory response is a trigger to the production of blood macromolecules involved in abnormally high levels of erythrocyte aggregation.

OBJECTIVE:

This study aimed at demonstrating for the first time the clinical feasibility of a non-invasive ultrasound-based erythrocyte aggregation quantitative measurement method for potential application in critical care medicine.

METHODS:

Erythrocyte aggregation was evaluated using modeling of the backscatter coefficient with the Structure Factor Size and Attenuation Estimator (SFSAE). SFSAE spectral parameters W (packing factor) and D (mean aggregate diameter) were measured within the antebrachial vein of the forearm and tibial vein of the leg in 50 healthy participants at natural flow and reduced flow controlled by a pressurized bracelet. Blood samples were also collected to measure erythrocyte aggregation ex vivo with an erythroaggregometer (parameter S₁₀).

RESULTS:

W and Din vivo measurements were positively correlated with the ex vivoS₁₀ index for both measurement sites and shear rates (correlations between 0.35–0.81, p < 0.05). Measurement at low shear rate was found to increase the sensitivity and reliability of this non-invasive measurement method.

CONCLUSIONS:

We behold that the SFSAE method presents systemic measures of the erythrocyte aggregation level, since results on upper and lower limbs were highly correlated.

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

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

A77 FURTHER CARACTERIZATION OF THE 67 KDA LAMININ RECEPTOR (67LR) IN COLORECTAL CANCER CELLS

Background

The 67 kDa laminin receptor (67LR) was the first non-integrin cell surface receptor for laminin isolated on laminin affinity columns from cancer cells in the 1980’s. Initially, 67LR is found as a cytoplasmic precursor of a 37 kDa protein, named 37LR, associated with the small ribosomal subunit. In human cells, 37LR allows the formation of the polyribosome complex and plays a key role in the initiation of translation. The mechanism by which the ribosomal protein becomes the 67LR membrane receptor is still unclear. It is presumed that the process involves post-translational modifications combined with homo or hetero-dimerization with non-associated ribosomal proteins. It has been shown that 37/67LR regulates adhesion and proliferation of normal human intestinal epithelial cells. Interestingly, overexpression of 37/67LR is correlated with aggressiveness and a poor prognosis in a wide variety of cancers.

Aims

The aim of this study was to confirm the overexpression of 37/67LR at the membrane of colorectal cancer cells and to identify its homo or heterodimerization partners.

Methods

To detect the expression of 37/67LR in colorectal cancer we performed an indirect immunofluorescence on tissues from normal and diseased colons. To confirm the presence of 67LR at the membrane of Caco-2 cells we used a cellular fractionation extraction protocol combined with ultracentrifugation and detergent treatment to separate ribosome-containing fractions from the membranes and isolate the membrane associated 67LR. Mass spectrometry analysis to study the molecular identity of 67LR was performed on immunoreactive bands corresponding to 37LR and 67LR.

Results

Immunolocalization of 37/67LR revealed an overexpression in colorectal cancer tissues. Following analysis by western blotting, immunoreactive 67LR protein was found in the soluble fraction after ultracentrifugation at 210,000 x g while 37LR was detected in the insoluble counterpart which was solubilized after treatment with detergent, suggesting that 37LR is associated with the membrane. Mass spectrometry analysis of these fractions indicated that 37LR was not identified in the immunoreactive bands of 67LR in the soluble fraction but identified the 67 kDa elastin binding protein, another 67 kDa cell surface laminin receptor.

Conclusions

These results indicate that 37LR is overexpressed in colorectal adenocarcinoma cells. Further characterization of the receptor by cell fractionation and mass spectrometry indicated that the 67 kDa immunoreactive form is not related to 37LR. Supported by CIHR.

Funding Agencies

CIHR

Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions

The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for classification of solid breast lesions at ultrasonography by means of random forests. One hundred and three women with 103 suspicious solid breast lesions (BI-RADS categories 4-5) were enrolled. Before biopsy, additional SWE images and a cine sequence of ultrasound images were obtained. The contours of lesions were delineated, and parametric maps of the homodyned-K distribution were computed on three regions: intra-tumoral, supra-tumoral and infra-tumoral zones. Maximum elasticity and total attenuation coefficient were also extracted. Random forests yielded receiver operating characteristic (ROC) curves for various combinations of features. Adding BI-RADS category improved the classification performance of other features. The best result was an area under the ROC curve of 0.97, with 75.9% specificity at 98% sensitivity.

Anthropomorphic and biomechanical mockup for abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is an asymptomatic condition due to the dilation of abdominal aorta along with progressive wall degeneration, where rupture of AAA is life-threatening. Failures of AAA endovascular repair (EVAR) reflect our inadequate knowledge about the complex interaction between the aortic wall and medical devices. In this regard, we are presenting a hydrogel-based anthropomorphic mockup (AMM) to better understand the biomechanical constraints during EVAR. By adjusting the cryogenic treatments, we tailored the hydrogel to mimic the mechanical behavior of human AAA wall, thrombus and abdominal fat. A specific molding sequence and a pressurizing system were designed to reproduce the geometrical and diseased characteristics of AAA. A mechanically, anatomically and pathologically realistic AMM for AAA was developed for the first time, EVAR experiments were then performed with and without the surrounding fat. Substantial displacements of the aortic centerlines and vessel expansion were observed in the case without surrounding fat, revealing an essential framework created by the surrounding fat to account for the interactions with medical devices. In conclusion, the importance to consider surrounding tissue for the global deformation of AAA during EVAR was highlighted. Furthermore, potential use of this AMM for medical training was also suggested.

MRI cine-tagging of cardiac-induced motion for noninvasive staging of liver fibrosis

BACKGROUND

MR elastography is a noninvasive technique that provides high diagnostic accuracy for the staging of liver fibrosis; however, it requires external hardware and mainly assesses the right lobe.

PURPOSE

To evaluate the diagnostic performance of MRI cine-tagging for staging fibrosis in the left liver lobe, using biopsy as the reference standard.

STUDY TYPE

Institutional Review Board (IRB)-approved two-center prospective study.

POPULATION

Seventy-six patients with chronic liver disease who underwent an MRI cine-tagging examination and a liver biopsy within a 6-week interval.

FIELD STRENGTH/SEQUENCE

2D-GRE multislice sequence at 3.0T with spatial modulation of the magnetization preparation sequence and peripheral pulse-wave triggering on two coronal slices chosen underneath the heart apex to capture maximal deformation with consecutive breath-holds adapted to patient cardiac frequency.

ASSESSMENT

A region of interest was selected in the liver close to the heart apex. Maximal strain was evaluated with the harmonic phase (HARP) technique.

STATISTICAL TESTS

Spearman's correlation, Kruskal-Wallis test, Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were performed.

RESULTS

Liver strain measured on tagged images decreased with higher histological fibrosis stage (ρ = -0.68, P < 0.0001). Strain values were significantly different between all fibrosis stages (P < 0.0001), and between groups of fibrosis stages ≤F3 vs. F4 (P < 0.05). Areas under the ROC curves were 0.95 (95% confidence interval: 0.89-1.00) to distinguish fibrosis stages F0 vs. F4, 0.81 (0.70-0.92) for stages F0 vs. ≥F1, 0.84 (0.76-0.93) for stages ≤F1 vs. ≥F2, 0.86 (0.78-0.94) for stages ≤F2 vs. ≥F3, and 0.87 (0.77-0.96) for stages ≤F3 vs. F4.

DATA CONCLUSION

MRI cine-tagging is a promising technique for measuring liver strain without additional elastography hardware. It could be used to assess the left liver lobe as a complement to current techniques assessing the right lobe.

LEVEL OF EVIDENCE

1 Technical Efficacy: 3 J. Magn. Reson. Imaging 2020;51:1570-1580.

Diagnostic Accuracy of Echo Envelope Statistical Modeling Compared to B-Mode and Power Doppler Ultrasound Imaging in Patients With Clinically Diagnosed Lateral Epicondylosis of the Elbow

OBJECTIVES

To compare the accuracy of homodyned K quantitative ultrasound (QUS) with that of B-mode and Doppler ultrasound imaging for discriminating between lateral epicondylosis (LE) and asymptomatic elbows.

METHODS

This prospective study received Institutional Review Board approval, and participants provided written informed consent. Between February 2015 and March 2017, 30 LE elbows in 27 patients and 24 asymptomatic elbows in 13 volunteers underwent B-mode, Doppler, and radiofrequency ultrasound imaging of the common extensor tendon (CET) and radial collateral ligament (RCL). Two readers classified the elbows independently on the basis of a review of B-mode and Doppler images. The global and local estimates of QUS parameters (μ _n , 1/α, and k) were computed in the CET and CET-RCL regions, respectively, and the area of each region was calculated. A random-forest classifier identified the most discriminating 3-parameter combination: CET global estimate of 1/α, CET-RCL area, and local estimate of k.

RESULTS

The patients with LE had a mean age of 50 years (range, 31-66 years), and the volunteers had a mean age of 50 years (range, 37-57 years). The area under the receiver operating characteristic curve, sensitivity, and specificity of reader 1, reader 2, and the QUS-based model were 0.80 (95% confidence interval [CI], 0.66-0.95), 0.72 (95% CI, 0.56-0.89), and 0.88 (95% CI, 0.72-1.04); 0.79 (95% CI, 0.66-0.93), 0.65 (95% CI, 0.47-0.82), and 0.84 (95% CI, 0.67-1.01); and 0.82 (95% CI, 0.80-0.85), 0.73, and 0.79, respectively.

CONCLUSIONS

An automated, computer-based QUS technique diagnosed LE with accuracy of 0.82. This technique could provide quantitative biomarkers for the characterization of LE disease.

Automatic Respiratory Gating Hepatic DCEUS-based Dual-phase Multi-parametric Functional Perfusion Imaging using a Derivative Principal Component Analysis

Purpose: Angiogenesis in liver cancers can be characterized by hepatic functional perfusion imaging (FPI) on the basis of dynamic contrast-enhanced ultrasound (DCEUS). However, accuracy is limited by breathing motion which results in out-of-plane image artifacts. Current hepatic FPI studies do not correct for these artifacts and lack the evaluation of correction accuracy. Thus, a hepatic DCEUS-based dual-phase multi-parametric FPI (DM-FPI) scheme using a derivative principal component analysis (PCA) respiratory gating is proposed to overcome these limitations.

Materials and Methods: By considering severe 3D out-of-plane respiratory motions, the proposed scheme's accuracy was verified with in vitro DCEUS experiments in a flow model mimicking a hepatic vein. The feasibility was further demonstrated by considering in vivo DCEUS measurements in normal rabbit livers, and hepatic cavernous hemangioma and hepatocellular carcinoma in patients. After respiratory kinetics was extracted through PCA of DCEUS sequences under free-breathing condition, dual-phase respiratory gating microbubble kinetics was identified by using a derivative PCA zero-crossing dual-phase detection, respectively. Six dual-phase hemodynamic parameters were estimated from the dual-phase microbubble kinetics and DM-FPI was then reconstructed via color-coding to quantify 2.5D angiogenic hemodynamic distribution for live tumors.

Results: Compared with no respiratory gating, the mean square error of respiratory gating DM-FPI decreased by 1893.9 ± 965.4 (p < 0.05), and mean noise coefficients decreased by 17.5 ± 7.1 (p < 0.05), whereas correlation coefficients improved by 0.4 ± 0.2 (p < 0.01). DM-FPI observably removed severe respiratory motion artifacts on PFI and markedly enhanced the accuracy and robustness both in vitro and in vivo.

Conclusions: DM-FPI precisely characterized and distinguished the heterogeneous angiogenic hemodynamics about perfusion volume, blood flow and flow rate within two anatomical sections in the normal liver, and in benign and malignant hepatic tumors. DCEUS-based DM-FPI scheme might be a useful tool to help clinicians diagnose and provide suitable therapies for liver tumors.

Numerical and experimental investigation of impacts of nonlinear scattering encapsulated microbubbles on Nakagami distribution

PURPOSE

The Nakagami statistical model and Nakagami shape parameter m have been widely used in linear tissue characterization and preliminarily characterized the envelope distributions of nonlinear encapsulated microbubbles (EMBs). However, the Nakagami distribution of nonlinear scattering EMBs lacked a systematical investigation. Thus, this study aimed to investigate the Nakagami distribution of EMBs and illustrate the impact of EMBs' nonlinearity on the Nakagami model.

METHOD

A group of simulated EMB phantoms and in vitro EMB dilutions with an increasing concentration distribution under various EMB nonlinearities, as regulated by acoustic parameters, were characterized by using the window-modulated compounding Greenwood-Durand estimator.

RESULTS

Raw envelope histograms of simulated and in vitro EMBs were well matched with the Nakagami distribution with a high correlation coefficient of 0.965 ± 0.021 (P < 0.005). The mean values and gradients of m parameters of simulated and in vitro EMBs were smaller than those of linear scatterers due to the stronger nonlinearity. These m values exhibited a quasi-linear improvement with the increase in second harmonic nonlinear-to-linear component ratio regulated by pulse lengths and excitation frequencies at low- and high-concentration conditions.

CONCLUSIONS

The Nakagami distribution was suitable for the EMBs characterization but the corresponding m parameter was affected by the EMBs' nonlinearity. These validations provided support and nonlinear impact assessment for the EMBs' characterization using the Nakagami statistical model in the future.

Prospective comparison of transient, point shear wave, and magnetic resonance elastography for staging liver fibrosis

OBJECTIVES

To perform head-to-head comparisons of the feasibility and diagnostic performance of transient elastography (TE), point shear-wave elastography (pSWE), and magnetic resonance elastography (MRE).

METHODS

This prospective, cross-sectional, dual-center imaging study included 100 patients with known or suspected chronic liver disease caused by hepatitis B or C virus, nonalcoholic fatty liver disease, or autoimmune hepatitis identified between 2014 and 2018. Liver stiffness measured with the three elastographic techniques was obtained within 6 weeks of a liver biopsy. Confounding effects of inflammation and steatosis on association between fibrosis and liver stiffness were assessed. Obuchowski scores and AUCs for staging fibrosis were evaluated and the latter were compared using the DeLong method.

RESULTS

TE, pSWE, and MRE were technically feasible and reliable in 92%, 79%, and 91% subjects, respectively. At univariate analysis, liver stiffness measured by all techniques increased with fibrosis stages and inflammation and decreased with steatosis. For classification of dichotomized fibrosis stages, the AUCs were significantly higher for distinguishing stages F0 vs. ≥ F1 with MRE than with TE (0.88 vs. 0.71; p < 0.05) or pSWE (0.88 vs. 0.73; p < 0.05), and for distinguishing stages ≤ F1 vs. ≥ F2 with MRE than with TE (0.85 vs. 0.75; p < 0.05). TE, pSWE, and MRE Obuchowski scores for staging fibrosis stages were respectively 0.89 (95% CI 0.85-0.93), 0.90 (95% CI 0.85-0.94), and 0.94 (95% CI 0.91-0.96).

CONCLUSION

MRE provided a higher diagnostic performance than TE and pSWE for staging early stages of liver fibrosis.

TRIAL REGISTRATION

NCT02044523 KEY POINTS: • The technical failure rate was similar between MRE and US-based elastography techniques. • Liver stiffness measured by MRE and US-based elastography techniques increased with fibrosis stages and inflammation and decreased with steatosis. • MRE provided a diagnostic accuracy higher than US-based elastography techniques for staging of early stages of histology-determined liver fibrosis.

Reconstruction of Viscosity Maps in Ultrasound Shear Wave Elastography

Change in viscoelastic properties of biological tissues may often be symptomatic of a dysfunction that can be correlated to tissue pathology. Shear wave elastography is an imaging method mainly used to assess stiffness but with the potential to measure viscoelasticity of biological tissues. This can enable tissue characterization; and thus, can be used as a marker to improve diagnosis of pathological lesions. In this study, a frequency-shift method based framework is presented for the reconstruction of viscosity by analyzing the spectral properties of acoustic radiation force-induced shear waves. The aim of the study was to investigate the feasibility of viscosity reconstruction maps in homogeneous as well as heterogeneous samples. Experiments were performed in four in vitro phantoms, two ex vivo porcine liver samples, two ex vivo fatty duck liver samples, and one in vivo fatty goose liver. Successful viscosity maps were reconstructed in homogeneous and heterogeneous phantoms with embedded mechanical inclusions having different geometries. Quantitative values of viscosity obtained for two porcine liver tissues, two fatty duck liver samples, and one goose fatty liver were (mean ± SD) 0.61 ± 0.21, 0.52 ± 0.35; 1.28 ± 0.54, 1.36 ± 0.73, and 1.67 ± 0.70 Pa.s, respectively.

Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms

Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide complementary quantitative tissue information, characterization of carotid artery plaques may gain from their combination. Sixty-six patients with symptomatic ( n = 26 ) and asymptomatic ( n = 40 ) carotid atherosclerotic plaques were included in the study. Of these, 31 underwent magnetic resonance imaging (MRI) to characterize plaque vulnerability and quantify plaque components. US radio-frequency data sequence acquisitions were performed on all patients and were used to compute noninvasive vascular US elastography and other QUS features. Additional QUS features were computed from three types of images: homodyned-K (HK) parametric maps, Nakagami parametric maps, and log-compressed B-mode images. The following six classification tasks were performed: detection of 1) a small area of lipid; 2) a large area of lipid; 3) a large area of calcification; 4) the presence of a ruptured fibrous cap; 5) differentiation of MRI-based classification of nonvulnerable carotid plaques from neovascularized or vulnerable ones; and 6) confirmation of symptomatic versus asymptomatic patients. Feature selection was first applied to reduce the number of QUS parameters to a maximum of three per classification task. A random forest machine learning algorithm was then used to perform classifications. Areas under receiver-operating curves (AUCs) were computed with a bootstrap method. For all tasks, statistically significant higher AUCs were achieved with features based on elastography, HK parametric maps, and B-mode gray levels, when compared to elastography alone or other QUS alone ( ). For detection of a large area of lipid, the combination yielding the highest AUC (0.90, 95% CI 0.80-0.92, ) was based on elastography, HK, and B-mode gray-level features. To detect a large area of calcification, the highest AUC (0.95, 95% CI 0.94-0.96, ) was based on HK and B-mode gray level features. For other tasks, AUCs varied between 0.79 and 0.97. None of the best combinations contained Nakagami features. This study shows the added value of combining different features computed from a single US acquisition with machine learning to characterize carotid artery plaques.

Coupling Myocardium and Vortex Dynamics in Diverging-Wave Echocardiography

Echocardiography is widely used to provide critical left ventricular indices describing myocardial motion and blood inflow velocity. Tissue motion and blood flow are strongly connected and interdependent in the ventricle. During cardiac relaxation, rapid filling leads to the formation of a vortical blood flow pattern. In this paper, we introduce a high-frame-rate method to track vortex dynamics alongside myocardium motion, in a single heartbeat. Cardiac triplex imaging (B-mode + tissue Doppler + color Doppler) was obtained by insonating the left ventricle with diverging waves. We used coherent compounding with integrated motion compensation to obtain high-quality B-mode images. Tissue Doppler was retrieved and the septal and lateral velocities of the mitral annulus were deduced. A rate of ~80 triplex images/s was obtained. Vortex dynamics was analyzed by Doppler vortography. Blood vortex signature maps were used to track the vortex and compute core vorticities. The sequence was implemented in a Verasonics scanner with a 2.5-MHz phased array and tested in vivo in 12 healthy volunteers. Two main peaks appeared on the vorticity curves. These peaks were synchronized with the mitral inflow velocities with a small delay. We observed a relationship between the tissue and vortex waveforms, though also with a delay, which denoted the lag between the wall and the flow motion. Clinical diastolic indices combining basal and mitral inflow velocities (E/A ratio and E/ e' ratio) were determined and compared with those measured using a conventional ultrasound scanner; a good correlation was obtained ( r² = 0.96 ). High-frame-rate Doppler echocardiography enabled us to retrieve time-resolved dynamics of the myocardium and vortex flow within the same cardiac cycle. Coupling wall-flow analysis could be of clinical relevance for early diagnosis of filling impairment.

Intraluminal Ultrasonic Palpation Imaging Technique Revisited for Anisotropic Characterization of Healthy and Atherosclerotic Coronary Arteries: A Feasibility Study

Accurate mechanical characterization of coronary atherosclerotic lesions remains essential for the in vivo detection of vulnerable plaques. Using intravascular ultrasound strain measurements and based on the mechanical response of a circular and concentric vascular model, E. I. Céspedes, C. L. de Korte and A. F. van der Steen developed an elasticity-palpography technique in 2000 to estimate the apparent stress-strain modulus palpogram of the thick subendoluminal arterial wall layer. More recently, this approach was improved by our group to consider the real anatomic shape of the vulnerable plaque. Even though these two studies highlighted original and promising approaches for improving the detection of vulnerable plaques, they did not overcome a main limitation related to the anisotropic mechanical behavior of the vascular tissue. The present study was therefore designed to extend these previous approaches by considering the orthotropic mechanical properties of the arterial wall and lesion constituents. Based on the continuum mechanics theory prescribing the strain field, an elastic anisotropy index was defined. This new anisotropic elasticity-palpography technique was successfully applied to characterize ten coronary plaque and one healthy vessel geometries of patients imaged in vivo with intravascular ultrasound. The results revealed that the anisotropy index-palpograms were estimated with a good accuracy (with a mean relative error of 26.8 ± 48.8%) compared with ground true solutions.

Two-dimensional affine model-based estimators for principal strain vascular ultrasound elastography with compound plane wave and transverse oscillation beamforming

Polar strain (radial and circumferential) estimations can suffer from artifacts because the center of a nonsymmetrical carotid atherosclerotic artery, defining the coordinate system in cross-sectional view, can be misregistered. Principal strains are able to remove coordinate dependency to visualize vascular strain components (i.e., axial and lateral strains and shears). This paper presents two affine model-based estimators, the affine phase-based estimator (APBE) developed in the framework of transverse oscillation (TO) beamforming, and the Lagrangian speckle model estimator (LSME). These estimators solve simultaneously the translation (axial and lateral displacements) and deformation (axial and lateral strains and shears) components that were then used to compute principal strains. To improve performance, the implemented APBE was also tested by introducing a time-ensemble estimation approach. Both APBE and LSME were tested with and without the plane strain incompressibility assumption. These algorithms were evaluated on coherent plane wave compounded (CPWC) images considering TO. LSME without TO but implemented with the time-ensemble and incompressibility constraint (Porée et al., 2015) served as benchmark comparisons. The APBE provided better principal strain estimations with the time-ensemble and incompressibility constraint, for both simulations and in vitro experiments. With a few exceptions, TO did not improve principal strain estimates for the LSME. With simulations, the smallest errors compared with ground true measures were obtained with the LSME considering time-ensemble and the incompressibility constraint. This latter estimator also provided the highest elastogram signal-to-noise ratios (SNRs) for in vitro experiments on a homogeneous vascular phantom without any inclusion, for applied strains varying from 0.07% to 4.5%. It also allowed the highest contrast-to-noise ratios (CNRs) for a heterogeneous vascular phantom with a soft inclusion, at applied strains from 0.07% to 3.6%. In summary, the LSME outperformed the implemented APBE, and the incompressibility constraint improved performances of both estimators.