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Degree of anisotropy (DoA) of mechanical properties has been assessed as the ratio of Acoustic Radiation Force Impulse (ARFI) induced peak displacements (PDs) achieved using spatially asymmetric point spread functions (PSFs) that are rotated 90° to each other. Such PSF rotation has been achieved by manually rotating a linear array transducer, but manual rotation is cumbersome and prone to misalignment errors and higher variability in measurements. The purpose of this work is to evaluate the feasibility of electronic PSF rotation using a three-row transducer, which will reduce variability in DoA assessment. A Siemens 9L4, with 3×192 elements, was simulated in Field II to generate spatially asymmetric ARFI PSFs that were electronically rotated 63° from each other. Then, using the finite element method (FEM), peak displacements (PD) due to the ARFI excitation PSFs in 42 elastic, incompressible, transversely isotropic (TI) materials with shear moduli ratios of 1.0 to 6.0 were modeled. Finally, the ratio of PDs achieved using the two rotated PSFs was evaluated to assess elastic DoA. DoA increased with increasing shear moduli ratios and distinguished materials with 17% or greater difference in shear moduli ratios (Wilcoxon, p < 0.05). Experimentally, the ratio of PDs achieved using ARFI PSF rotated 63° from each other distinguished the biceps femoris muscle from two pigs, which had median shear moduli ratios of 4.25 and 3.15 as assessed by Shear Wave Elasticity Imaging (SWEI). These results suggest that ARFI-based DoA assessment can be achieved without manual transducer rotation using a three-row transducer capable of electronically rotating PSFs by 63°. It is expected that electronic PSF rotation will facilitate data acquisitions and improve the reproducibility of elastic anisotropy assessments.

While in vivo acoustic radiation force impulse (ARFI)-induced peak displacement (PD) has been demonstrated to have high sensitivity and specificity for differentiating soft from stiff plaque components in patients with carotid plaque, the parameter exhibits poorer performance for distinguishing between plaque features with similar stiffness. To improve discrimination of carotid plaque features relative to PD, we hypothesize that signal correlation and signal-to-noise ratio (SNR) can be combined, outright or via displacement variance. Plaque feature detection by displacement variance, evaluated as the decadic logarithm of the variance of acceleration and termed “log(VoA),” was compared to that achieved by exploiting SNR, cross correlation coefficient, and ARFI-induced PD outcome metrics. Parametric images were rendered for 25 patients undergoing carotid endarterectomy, with spatially matched histology confirming plaque composition and structure. On average, across all plaques, log(VoA) was the only outcome metric with values that statistically differed between regions of lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), collagen (COL), and calcium (CAL). Further, log(VoA) achieved the highest contrast-to-noise ratio (CNR) for discriminating between LRNC and IPH, COL and CAL, and grouped soft (LRNC and IPH) and stiff (COL and CAL) plaque components. More specifically, relative to the previously demonstrated ARFI PD parameter, log(VoA) achieved 73% higher CNR between LRNC and IPH and 59% higher CNR between COL and CAL. These results suggest that log(VoA) enhances the differentiation of LRNC, IPH, COL, and CAL in human carotid plaques, in vivo , which is clinically relevant to improving stroke risk prediction and medical management.

Our group has previously found that in silico, mechanical anisotropy may be interrogated by exciting transversely isotropic materials with geometrically asymmetric acoustic radiation force excitations and then monitoring the associated induced displacements in the region of excitation. We now translate acoustic radiation force-based anisotropy assessment to human muscle in vivo and investigate its clinical relevance to monitoring muscle degeneration in Duchenne muscular dystrophy (DMD). Clinical anisotropy assessments were performed using Viscoelastic Response ultrasound, with a degree of anisotropy reflected by the ratios of Viscoelastic Response relative elasticity (RE) or relative viscosity (RV) measured with the asymmetric radiation force oriented parallel versus perpendicular to muscle fiber alignment. In vivo results from rectus femoris and gastrocnemius muscles of boys aged ∼7.9–10.4 y indicate that RE and RV anisotropy ratios in rectus femoris muscles of boys with DMD were significantly higher than those of healthy control boys (RE: DMD = 1.51 ± 0.87, control = 0.99 ± 0.69, p = 0.04, Wilcoxon rank sum test; RV: DMD = 1.04 ± 0.71, control = 0.74 ± 0.22, p = 0.02). In the gastrocnemius muscle, only the RV anisotropy ratio was significantly higher in dystrophic than control patients (DMD = 1.23 ± 0.35, control = 0.88 ± 0.31, p = 0.04). In the dystrophic rectus femoris muscle, the RE anisotropy ratio was inversely correlated (slope = –0.03/lbf, r = –0.43, p = 0.07, Pearson correlation) with quantitative muscle testing functional output measures but was not correlated with quantitative muscle testing in the dystrophic gastrocnemius. These results suggest that Viscoelastic Response RE and RV measures reflect differences in mechanical anisotropy associated with functional impairment with dystrophic degeneration that are relevant to monitoring DMD clinically.

Many biological tissues, including muscle or kidney, are mechanically anisotropic, and the degree of anisotropy (DoA) in mechanical properties is diagnostically relevant. DoA can be assessed either using the ratio of shear wave velocities (SWVs) or acoustic radio forced impulse (ARFI)-induced peak displacements (PD) measured longitudinal over transverse orientations. Whether using SWV or PD as a basis, DoA expressed as the ratio of values requires 90° transducer rotation when a linear array is employed. This large rotation angle is prone to misalignment errors. One solution is the use of a fully sampled matrix array for electronic rotation of point spread function (PSF). However, the challenges of matrix array are its high fabrication cost and complicated fabrication procedures. The cheaper and simpler alternative of matrix array is the use of a row–column array. A $3\times64$ elements 1.5-D array with a row–column excitation mode is proposed to assess DoA in mechanical properties using the PD ratio. Different numbers of elements in elevational and lateral directions were selected to have orthogonal ARFI excitation beams without rotating the transducer. A custom-designed flex circuit was used to fabricate the array with a simpler electrode connection than a fully sampled matrix array. The performance of the array was evaluated in Field II simulation and experiment. The output pressure was 0.57-MPa output under a 40- ${V}_{\text {pp}}$ excitation with a −6-dB point spread dimension of $14\times4$ mm2 in orthogonal directions. The PD was measured to be $1.4~\mu \text{m}$ in an isotropic elastic phantom with Young’s modulus of 5.4 kPa. These results suggest that the array is capable of assessing DoA using PD ratio without physical rotation of the transducer. The array has the potential to reduce the misalignment errors for DoA assessment.

Many tissues, such as muscle, kidney, and breast, are mechanically anisotropic. Appropriately exploited, mechanical anisotropy can be a clinically relevant target for noninvasive imaging. An imaging method's potential for interrogating mechanical anisotropy can be experimentally evaluated using tissue-mimicking materials, also known as phantoms. The objective of this work is to demonstrate the feasibility of constructing mechanically anisotropic phantoms using 3D-printed polylactic acid (PLA) fibers embedded in gelatin hydrogel or polyvinyl alcohol (PVA) cryogel. Four identical fiber sets were printed; two were embedded in gelatin and two in PVA. Acoustic Radiation Force Impulse (ARFI) imaging was performed on the constructed phantoms, with data acquisitions at 0°, 30°, 60°, and 90° concentric orientations, where 0° and 90° corresponded to the long-axis of the spatially asymmetric ARF excitation being aligned across and along the fibers, respectively. Degree of anisotropy (DoA) was calculated as the ratio of peak displacements achieved at 90° versus 0° orientations. While both gelatin and PVA embedded fibers demonstrated elastic anisotropy, DoA values were 32% higher in gelatin. These pilot experimental results demonstrate that phantoms constructed of 3D-printed PLA fibers embedded in gelatin or PVA exhibit mechanical anisotropy as assessed by ARFI ultrasound.

While SWEI methods require shear wave propagation to be sampled across a measurement kernel, the recently-introduced double-profile intersection (DoPIo) ultrasound can estimate shear moduli locally and on-axis by exploiting ARF-induced displacement underestimation caused by scatterer shearing under a tracking PSF. We herein perform a systematic comparison of DoPIo to MTL/STL-SWEI to identify the benefits and limitations of using multiple tracking F-numbers. We further compare DoPIo performance achieved using conventional normalized cross-correlation (NCC) to that using a blind source separation (BSS) estimator by assessing its impact of mechanical feature resolution and measurements via automatic segmentation. DoPIo shear modulus estimates in a simulated elastic phantom using BSS resulted in a contrast transfer efficiency comparable to STL-SWEI (0.81 for a 12.0 kPa feature within an 8.0 kPa background using BSS-DoPIo, compared to 0.77 for NCC, 0.76 for MTL-SWEI, and 0.81 for STL-SWEI). We also demonstrate DoPIo measurements in a calibrated phantomm using a clinical ultrasound scanner system. In doing so, we present DoPIo as a method to ultrasonically measure the shear modulus of tissue that may be performed on-axis independently of ARF amplitudes.

Double-profile intersection (DoPIo) ultrasound is a new acoustic radiation force (ARF) imaging technique that exploits scatterer shearing under two different tracking point spread functions to estimate shear elastic moduli. Previous versions of DoPIo used an empirically derived model to relate the time where two displacement profiles, each measuring displacement in identical positions using different aperture sizes. We herein propose an alternative, machine learning-based approach that obviates the need for an empirically-derived model by replacing it with a support vector machine that uses paired displacement profiles in their entirety. In this work, we describe the implementation of such a model, validate its ability in shear modulus for simulated materials, and deploy it to image a calibrated phantom.

Delineating carotid plaque components that confer rupture risk is vital to stoke prevention. We have previously shown that combining temporal profiles of Acoustic Radiation Force Impulse (ARFI)-induced displacement, cross-correlation coefficient, and signal-to-noise ratio (SNR) as the input feature set to a machine learning classifier enabled the classifier to differentiate intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), collagen (COL), and calcium (CAL) plaque components, with accurate fibrous cap thickness measurement. We hypothesize that machine learning-based classification of carotid plaque structure and composition will be improved by including more information in the input feature set. This study analyzed six carotid plaques imaged in vivo in patients undergoing carotid endarterectomy CEA). Data were acquired with ECG gating to diastole and to systole, with and without ARF excitation. From these data, temporal profiles of displacement, crosscorrelation coefficient (CC), and signal-to-noise ratio (SNR) were generated and used as inputs to a support vector machine classifier. The classifier was trained and tested using spatially matched histology. Over all examined plaques, combining acquisitions at systole and diastole, with and without ARFI push, achieved CNRs that were statistically higher than any one or combination of two inputs. These results suggest that the performance of a machine learning classifier for automatic plaque feature delineation can be improved by optimizing the feature set, with clinical relevance to in vivo human carotid plaque feature delineation herein demonstrated.

Differentiating malignant from benign breast lesions remains a challenge that may be met by a new imaging biomarker: lesion-to-background mechanical anisotropy assessed by VisR ultrasound. VisR is an ultrasound imaging method that uses 2 consecutive acoustic radiation force excitations, separated in time and delivered to the same region of excitation, to directionally interrogate peak displacement (PD), relative elasticity (RE), and relative viscosity (RV). From these directional measurements, mechanical degree of anisotropy is measured. In a pilot clinical study involving 29 women with BIRADS-4 or −5 breast masses, VisR PD, RE, and RV were measured in lesions and in surrounding tissue at 0°, 30°, 60°, and 90° concentric orientations. From these measurements, lesion DoA (LDoA), surrounding tissue DoA (SDoA), and log(LDoA/SDoA) were assessed per parameter and compared between biopsy-confirmed malignant versus benign masses. Across all patients, PD-, RE-, and RV-based LDoA or SDoA alone did not achieve statistical difference between malignant and benign masses (Wilcoxon, $\mathrm{p} > 0.05$ ). However, PD-, RE-, and RV-based log(LDoA/SDoA) statistically differentiated malignant from benign masses (Wilcoxon, $\mathrm{p} ), with AUC values of 0.96 for PD-based, and 0.94 for RE- and RV-based outcomes. These results demonstrate the relevance of lesion-to-background mechanical anisotropy assessed by VisR ultrasound for differentiating malignant from benign breast masses in women, in vivo.

Stroke is often caused by carotid plaque rupture, with rupture potential indicated by plaque structure and composition. Delineating carotid plaque components that confer rupture risk is vital to stoke prevention. We have previously shown that ARFI Log Variance of Acceleration, log(VoA), discriminates intraplaque hemorrhage (IPH) from lipid-rich necrotic core (LRNC) and collagen (COL) from calcium (CAL) in vivo in humans, while ARFI peak displacement does not. We hypothesize that log(VoA) performance will be further improved by harmonic tracking of ARF-induced displacement. In a pilot clinical study of six carotid plaques imaged in vivo in patients undergoing carotid endarterectomy (CEA), plaque component contrast-to-noise ratio (CNR) achieved by harmonic log(VoA) was compared to that achieved by tracking at fundamental low (4.0 MHz, FL) and high (8.89 MHz, FH) frequencies with validation by spatially-matched histology derived from the extracted plaque specimens. Over all examined plaques, harmonic and both fundamental low and high log(VoA) distributions statistically differentiated plaque components (Wilcoxon, $\mathrm{p} , panel iv). Harmonic log(VoA) achieved the highest CNR between COL and LRNC, which is relevant to fibrous cap delineation, but FH tracking yielded the highest CNR between LRNC and IPH and between COL and CAL. These results suggest that combined harmonic and FH tracking could improve ARFI log(VoA) characterization of carotid plaque components that are correlated to rupture.

ARFI Variance of Acceleration (VoA) has been previously used in clinical applications to delineate atherosclerotic plaque morphology and detect subcutaneous hemorrhage. In silico models also demonstrated that behavior of the parameter is influenced by error in the displacement estimates, which are accentuated by decreasing SNR or correlation. This study experimentally demonstrates that in non-elastic materials, decreasing correlation, induced by a greater magnitude ARFI push, increases VoA when the material SNR is above 40–45 dB. This signal correlation dependent change is realizable with focused and PW tracking, potentially expanding the clinical utility of high framerate VoA analysis.

Viscoelastic response (VisR) ultrasound characterizes the viscoelastic properties of tissue by fitting acoustic radiation force (ARF)-induced displacements in the region of ARF excitation to a 1-D mass-spring-damper (MSD) model. Elasticity and viscosity are calculated separately but relative to the applied ARF amplitude. We refer to these parameters as “relative elasticity (RE)” and “relative viscosity (RV).” We herein test the hypothesis that RE and RV linearly correlate to true elasticity and viscosity in tissue. VisR imaging was simulated in 144 homogeneous viscoelastic materials with varying elasticities and viscosities. Derived RE linearly correlated with material elasticity and varied by an average of 2.52% when the material viscosity changed from 0.1 to 1.3 Pa $\cdot $ s. Derived RV linearly correlated with material viscosity but varied by an average of 102.5% when material elasticity changed from 3.33 to 20 kPa. The effect of elasticity on RV measurement was compensated using the slope of the linear relationship between RV and natural frequency ( $\omega _{text{n}}$ ). After compensation, RV $^{\text {EC}}$ (elasticity compensated RV) linearly correlated with material viscosity and varied by less than 1.00% on average when the modeled shear elastic modulus changed from 3.3 to 20 kPa. In addition to elasticity compensation, variation in ARF amplitude over depth was compensated, yielding REDC and ${\text {RV}}_{\text {DC}}^{\text {EC}}$ . REDC and ${\text {RV}}_{\text {DC}}^{\text {EC}} $ successfully contrasted elastic and viscous inclusions, respectively, in three simulated phantoms. Experimentally, in the homogeneous oil-in-gelatin phantoms and excised livers, REDC linearly correlated with shear wave dispersion ultrasound vibrometry (SDUV) derived shear elastic modulus, and ${\text {RV}}_{\text {DC}}^{\text {EC}}$ linearly correlated with SDUV-derived shear viscosity. In excised livers containing viscoelastic oil-in-gelatin inclusions, the inclusions were successfully contrasted from the liver background by both REDC and ${\text {RV}}_{\text {DC}}^{\text {EC}}$ . These results suggest that RE and RV are relevant for qualitatively assessing the elastic and viscous properties of tissue.

Chronic kidney disease is most desirably and cost-effectively treated by renal transplantation, but graft survival is a major challenge. Although irreversible graft damage can be averted by timely treatment, intervention is delayed when early graft dysfunction goes undetected by standard clinical metrics. A more sensitive and specific parameter for delineating graft health could be the viscoelastic properties of the renal parenchyma, which are interrogated non-invasively by Viscoelastic Response (VisR) ultrasound, a new acoustic radiation force (ARF)-based imaging method. Assessing the performance of VisR imaging in delineating histologically confirmed renal transplant pathologies in vivo is the purpose of the study described here. VisR imaging was performed in patients with (n = 19) and without (n = 25) clinical indication for renal allograft biopsy. The median values of VisR outcome metrics (τ, relative elasticity [RE] and relative viscosity [RV]) were calculated in five regions of interest that were manually delineated in the parenchyma (outer, center and inner) and in the pelvis (outer and inner). The ratios of a given VisR metric for all possible region-of-interest combinations were calculated, and the corresponding ratios were statistically compared between biopsied patients subdivided by diagnostic categories versus non-biopsied, control allografts using the two-sample Wilcoxon test (p 0.05). Although τ ratios non-specifically differentiated allografts with vascular disease, tubular/interstitial scarring, chronic allograft nephropathy and glomerulonephritis from non-biopsied control allografts, RE distinguished only allografts with vascular disease and tubular/interstitial scarring, and RV distinguished only vascular disease. These results suggest that allografts with scarring and vascular disease can be identified using non-invasive VisR RE and RV metrics.

Low blood SNR makes detecting small vessels, measuring slow flow rates, and assessing blood perfusion without contrast administration challenging. A potential approach is to use Variance of Acceleration (VoA) imaging, which has been demonstrated previously in humans in vivo for monitoring subcutaneous bleeding and delineating intraplaque hemorrhage. We hypothesize that, without the addition of contrast agents, VoA can detect slow flow in small vessels for perfusion assessment. Experiments were performed on an ATS 700-D 527 calibrated flow phantom (vessel diameter of 1 mm, flow rates of 0-53 cm/s) and in the surgically exteriorized right kidneys of 3 pigs (2M/1F, mean body weight of 74.4 ± 9.3 kg) at baseline and after inducing ischemia. In the phantom, logVoA increased in the vessel with increasing flow rate, and it remained constant in the background. LogVoA values were higher in the background with versus without the ARF excitation. Similarly, logVoA values were higher in the vessel, particularly for flow rates < 12 cm/s, with versus without ARF excitation. Vessel CNR by logVoA was higher with versus without ARF excitation for flow rates < 12 cm/s, and CNR by logVoA was greater than CNR by power Doppler for all flow rates. Additionally, logVoA was statistically significantly greater at baseline than ischemia in all three in vivo pig kidneys. Finally, logVoA delineates a 1.25 mm-diameter vessel in a pig renal cortex in vivo, while power Doppler does not. These results suggest that logVoA could support contrast-free detection of slow blood flow in small vessels and in vivo perfusion assessment.

A significant risk factor in ischemic strokes is carotid atherosclerotic plaque that is susceptible to rupture, with rupture potential conveyed by plaque composition and structure. Prior work has shown that Variance of Acceleration (VOA), derived from Acoustic Radiation Force Impulse (ARFI) imaging, is capable of delineating plaque components. However, the method relies on focused ARF excitations at each lateral location, limiting framerate. To increase framerate, it is hypothesized that VoA imaging may be implemented using fast plane wave imaging techniques. In this work, VoA’s ability to discriminate materials based on signal decorrelation and SNR is compared for conventional focused wave versus plane wave tracking methods. Relative to focused wave tracking, plane wave tracking yields comparable discrimination. This study suggests that a plane wave implementation of ARFI VoA analysis could be feasible for increased frame rate in atherosclerosis imaging.

Mechanical property changes associated with inflammation, necrosis, fibrosis, and fatty deposition in dystrophic muscle may be quantitatively evaluated by Quantitative Viscoelastic Response (QVisR) ultrasound. QVisR uses a machine learning (ML) framework that takes as input tissue displacement in response to two consecutive and co-located acoustic radiation force (ARF) excitations and yields as output estimates of shear elastic and shear viscous moduli. QVisR imaging was performed in the vastus lateralis (VL) muscles of 11 boys with Duchenne muscular dystrophy (DMD) aged 5 to 12 years and of 8 age-matched boys with no known neuromuscular disorders, who served as controls. QVisR measures of elastic moduli differed between DMD and control VL in boys aged less than six years and six-to-seven years. Similarly, QVisR measures of viscous moduli differed between DMD and control VL in boys aged six-to-seven years. These results demonstrate that QVisR measures of elastic and viscous moduli differentiate dystrophic from control muscle. The findings suggest that QVisR may be relevant to monitoring dystrophic muscle degeneration and response to intervention, particularly in early stages when interventions are most likely to be impactful.

Chronic kidney disease is associated with progressive inflammation and fibrosis, which is conventionally assessed by invasive biopsy. A noninvasive alternative to biopsy may be interrogating elastic and viscous anisotropy. This work evaluates the feasibility of using in vivo Viscoelastic Response (VisR) ultrasound for detecting changes in the elastic and viscous degree of anisotropy (DoA) associated with fibrosis after chronic ischemia-reperfusion injury (IRI) in pig kidney. Histology was used to validate VisR DoA measurements, which were compared to those derived using Shear Wave Elasticity Imaging (SWEI) and Shearwave Dispersion Ultrasound Vibrometry (SDUV). In the injured and contralateral (control) kidneys of 8 pigs, VisR, SWEI, and SDUV-derived elastic DoA, evaluated as the ratio of longitudinal over transverse shear elasticity, was significantly (p

Breast cancer screening is beneficial when it averts progression of disease to metastasis, but adverse effects to patients and unnecessary medical expense may result downstream from false positives. Achieving early breast cancer detection with high sensitivity and specificity remains a challenge that may be met by using acoustic radiation force to assess the mechanical properties of tissue. The objective of this study is to evaluate in vivo the diagnostic relevance of Viscoelastic Response (VisR)-derived metrics for mechanical anisotropy. We compare our in vivo human results against biopsy findings. This study analyzed 9 breast lesions (4 malignant, 5 benign) imaged in vivo in women with BIRADS-4 or -5 ratings after standard screening. VisR relative elasticity (RE), relative viscosity (RV), and peak displacement (PD) were measured for each transducer orientation, and fit to a sinusoid by least-squares minimization, extrapolating to 360°. The fits were phase-aligned, and the point-wise differences in each parameter between lesion and background were integrated over angle. Finally, the ratio of the maximum to the minimum parameter value was calculated to reflect the degree of anisotropy (DoA). DoAs by PD, RE, and RV were statistically significantly greater in background than in lesion for all malignant cases but statistically significantly smaller in background than in lesion for all benign cases (Wilcoxon, p < 0.05). Additionally, differences between lesion and background integrated over angle by RE, RV and PD were statistically significantly different (Wilcoxon, p < 0.05) for malignant and benign lesions across all examined patients. These results suggest that VisR-derived mechanical anisotropy assessment could be diagnostically relevant for discriminating malignant from benign breast lesions.

Quantitative Viscoelastic Response (QVisR) ultrasound is a new machine learning-based elasticity imaging method in which elastic and viscous moduli are estimated from tissue deformation in response to two consecutive acoustic radiation force (ARF) excitations. The estimated moduli are rendered into two-dimensional parametric images of elastic and viscous modulus. From QVisR images, the spatial distribution of elastic and viscous properties may be evaluated using established computational texture analysis tools. In this study, computational texture analysis by the omnidirectional gray-level run-length matrix (GLRLM) was applied to QVisR images. The images were obtained in the vastus lateralis (VL) muscles of 11 boys with Duchenne muscular dystrophy, aged 5-12 years, and 8 age-matched boys with no known neuromuscular disorders, who served as controls. GLRLM-derived elastic entropy in QVisR images was statistically higher (Wilcoxin, p

Mechanical property assessment by elastographic ultrasound methods, including those that exploit acoustic radiation force (ARF), relies on accurate estimation of tissue displacement. Several displacement estimators have been developed, but their relevance to tracking ARF-induced displacements smaller than one micrometer is limited by estimation variance. To minimize displacement estimation variance, a new blind source separation (BSS)-based approach that exploits the spatial distribution of displacements is presented. This new approach applies principal component analysis (PCA) in three-dimensional (3D) kernels to derive dominant eigenvectors, from which displacements are estimated. We call this new approach the ‘3DK-BSS’ estimator. The 3DK-BSS estimator is evaluated in terms of contrast-to-noise ratio (CNR) achieved in ARFI peak displacement (PD) images of a stiff (80 kPa) and a soft (8 kPa) spherical inclusion in a commercial phantom with a 25 kPA background. The CNR values achieved by 3DK-BSS were compared to those produced by normalized cross-correlation (NCC), Bayesian regularization, and BSS implemented using a two-dimensional (2D) kernel at ARF power levels of 5 to 45% of the full system power. For all power levels, and for both stiff and soft inclusions, 3DK-BSS inclusion CNR was higher than any other examined displacement estimator. For example, 3DK-BSS stiff inclusion CNR was 16.3, 11.8, and 4.2 times higher than the CNRs achieved by NCC, Bayesian regularization, and 2D BSS, respectively at 5% power level. CNR improvement by 3DK-BSS was largest at the lowest (5%) ARF power level, where displacement in the stiff phantom was measured by 3DK-BSS as 250 nm. These results suggest that, by accurately measuring sub-micrometer displacements, the 3DK-BSS displacement estimator could enable deeper ARF-based mechanical property assessments, finer mechanical resolution in stiff tissues, and/or lower ARF power requirements to expand the diagnostic relevance of ARF-based mechanical property assessments.

Atherosclerotic plaque rupture potential is conferred by plaque composition and structure. We have previously shown in humans in vivo that carotid plaque components can be automatically delineated by a support vector machine (SVM) classifier considering normalized crosscorrelation (NCC)-derived measures of ARFI-induced displacement. We now extend our prior work by hypothesizing that classification is improved by using displacements derived using blind source separation (BSS). In 20 carotid plaques imaged in vivo in patients undergoing carotid endarterectomy (CEA) were imaged prior to extraction, and specimens were harvested after CEA for histological processing. ARFI displacement profiles were calculated from each of the first five principal components of the RF data and used as inputs to the SVM classifier. The classifier was evaluated by 5-fold cross-validation, with the histological samples acting as gold standards. From the output SVM likelihood matrices, ROC curves were calculated for separating collagen from calcium and lipid-rich necrotic core from intraplaque hemorrhage. For all examined plaques, inputting displacement profiles derived from the first four eigenvectors to the SVM classifier increased sensitivity and specificity over using NCCderived displacement profiles. These results suggest that using BSS-derived displacement profiles as inputs to the SVM classifier improves discrimination of carotid plaque components that are correlated to vulnerability for rupture.

Ultrasound imaging with high resolution and large penetration depth has been increasingly adopted in medical diagnosis, surgery guidance, and treatment assessment. Conventional ultrasound works at a particular frequency, with a $- 6\text{-dB}$ fractional bandwidth of ${\sim}\text{70}\% $ , limiting the imaging resolution or depth of field. In this paper, a bifrequency colinear array with resonant frequencies of 8 and 20 MHz was investigated to meet the requirements of resolution and penetration depth for a broad range of ultrasound imaging applications. Specifically, a 32-element bifrequency colinear array was designed and fabricated, followed by element characterization and real-time sectorial scan (S-scan) phantom imaging using a Verasonics system. The bifrequency colinear array was tested in four different modes by switching between low and high frequencies on transmit and receive. The four modes included the following: 1) transmit low, receive low; 2) transmit low, receive high; 3) transmit high, receive low; and 4) transmit high, receive high. After testing, the axial and lateral resolutions of all modes were calculated and compared. The results of this study suggest that bifrequency colinear arrays are potential aids for wideband fundamental imaging and harmonic/subharmonic imaging.

Chronic kidney disease is associated with progressive inflammation, which is conventionally assessed by invasive biopsy. A noninvasive alternative is to interrogate the mechanical property alterations that occur with inflammation. This work evaluates the feasibility of using in vivo Viscoelastic Response (VisR) ultrasound for detecting differences in mechanical degree of anisotropy (DoA) associated with inflammation after ischemia-reperfusion injury (IRI) in pig kidney. VisR measurements were validated by histology, Shear Wave Elasticity Imaging (SWEI), and Shearwave Dispersion Ultrasound Vibrometry (SDUV) derived DoA. In 6 pigs, data were acquired in vivo in the kidney following IRI and in the contralateral kidney, which did not undergo IRI and served as a control. VisR (relative elasticity (RE), relative viscosity (RV), and peak displacement (PD)), SWEI (shear elastic modulus $(\mu))$ , and SDUV (shear elastic $(\mu_{1})$ and viscous $(\mu_{2})$ moduli) outcomes were evaluated alone and as ratios to reflect DoA (longitudinal over transverse). VisR PD and RE, SWEI $\mu$ , and SDUV $\mu_{1}$ demonstrated significantly increased DoA (p $\mu$ in cortex). Notably, while elastic DoA increased in both medulla and cortex, the underlying causes differed (cortex: diminished transverse modulus v. medulla: elevated longitudinal modulus). VisR RV indicated decreased viscous DoA in the medulla after IRI. Spatially matched histology indicated mild inflammation in the injured, but not the control, kidneys. These results suggest that VisR noninvasively detects changes in DoA associated with inflammation induced by IRI in a pig model. VisR may be diagnostically relevant to delineating inflammation in human kidney.

In transversely isotropic (TI) materials, mechanical properties differ along versus across the axis of symmetry (AoS). The degree of these directional differences has been interrogated as the ratio of ARFI peak displacements (PD) acquired when the long axis of the ARFI excitation point spread function (PSF) was aligned along versus across the AoS. When performed using a conventional linear array transducer, such measurements require a 90° transducer rotation, which can be cumbersome and prone to misalignment errors. Rather than 90°, we hypothesize that smaller rotation angles via electronic steering can be used to assess mechanical anisotropy. This hypothesis was tested in silico using finite-element method (FEM) models and Field II simulation. ARFI Imaging was simulated in thirty-four TI elastic materials using a 3×192 (elevational x lateral) elements multi-D array transducer with elevational elements width >> wavelength of ultrasound. The longitudinal versus transverse shear moduli ratios and Young's moduli ratios were varied from 1.0 to 5.0 and from 1.0 to 4.0, respectively. Via electronic steering, ARFI excitation PSF was rotated at 0°and 59°and was asymmetric at focal depth with long over short axis lengths of 2.7. PD ratio (PD 0 /PD 59 ) increased with increasing shear moduli ratio and did not statistically vary with Young's moduli ratio (p>0.05, Wilcoxon ranksum). PD ratio distinguished simulated materials with greater than 25% difference in shear moduli ratio (p < 0.05). These results suggest that elastic anisotropy may be interrogated by PD ratios acquired via electronically rotating PSF instead of manually rotating transducer, which could facilitate data acquisitions and improve the reproducibility of elastic anisotropy assessment.

In this work, we present preliminary characterization results from a 32 x 32 row-column (RC) addressed 2D capacitive micromachined ultrasonic transducer (CMUT) array. The device was fabricated using anodic bonding on a borosilicate glass substrate, which eliminates the substrate - bottom electrode coupling previously observed in traditional CMUT RC arrays fabricated on silicon substrates. The characterization results were compared for the top and bottom electrodes and include impedance measurements, pulseecho impulse responses, and 2D scans of the pressure field using a calibrated hydrophone. The results showed that the array elements behave similarly when ground and hot electrodes were switched between the top and bottom electrodes for all of the measured parameters including device capacitance, center frequency, and pulse-echo response amplitude. The pressure scans verified the highly customizable nature of RC arrays by showing multiple active element configurations. A sample cross-sectional image of a metal target was also demonstrated.

In magnetomotive ultrasound (MMUS) imaging, an oscillating external magnetic field displaces tissue loaded with super-paramagnetic iron oxide (SPIO) particles. The induced motion is on the nanometer scale, which makes its detection and its isolation from background motion challenging. Previously, a frequency and phase locking (FPL) algorithm was used to suppress background motion by subtracting magnetic field off (B-off) from on (B-on) data. Shortcomings to this approach include long tracking ensembles and the requirement for B-off data. In this article, a novel blind source separation based FPL (BSS-FPL) algorithm is presented for detecting motion using a shorter ensemble length than FPL and without B-off data. MMUS imaging of 2 phantoms containing an SPIO-laden cubical inclusion and 1 control phantom was performed using an open-air MMUS system. When background subtraction was used, contrast, and contrast to noise ratio (CNR) were respectively 1.20 ± 0.20 and 1.56 ± 0.34 times higher in BSS-FPL as compared to FPL-derived images for ensemble lengths < 3.5s. However, contrast and CNR were similar for BSS-FPL and FPL for ensemble lengths ≥ 3.5s. When only B-on data was used, contrast and CNR were 1.94 ± 0.21 and 1.56 ± 0.28 times higher respectively in BSS-FPL as compared to FPL-derived images for all ensemble lengths. Percent error in the estimated width and height was 39.30 ± 19.98 % and 110.37 ± 6.5 % for FPL and was 7.30 ± 7.6 % and 16.21 ± 10.29 % for BSS-FPL algorithm. This study is an important step toward translating MMUS imaging to in vivo application, where long tracking ensembles would increase acquisition time and B-off data may be misaligned with B-on due to physiological motion.

Ultrasound imaging is uniquely relevant in the modern era of clinical medicine. While the fundamental platform remains low-cost and portable, meeting demands for cost-efficient diagnostic and therapeutic options in the context of constrained medical resources, technology development races forward to achieve applications that were not possible just years ago. A vital first step to translating these cutting-edge ultrasound methods to clinical implementation is performing pilot studies in humans, in vivo. Initial human studies are critical because they demonstrate the feasibility of new methodologies in the context of complex tissue environments with unknown parameters and when penetration requirements and complicated noise sources interfere with signal detection. Furthermore, developing methods for validating outcome measures in the complex and unknown in vivo human setting is difficult. Finally, the logistics associated with obtaining regulatory approval for conducting human studies, the time required to recruit subjects, and the associated expenses compound the technical challenges.

Sub-micrometer, periodic motion detection using blind source separation (BSS) via principal component analysis (PCA) is presented in the context of magnetomotive ultrasound (MMUS) imaging and Shearwave Dispersion Ultrasound Vibrometry (SDUV). In MMUS, an oscillating external magnetic field displaces tissue loaded with superparamagnetic iron oxide (SPIO) particles, whereas in SDUV, periodic tissue motion is induced using acoustic radiation force (ARF) to measure visco-elastic properties. BSS motion detection performance in MMUS imaging and SDUV was compared against frequency-phase locked (FPL) and normalized cross-correlation (NCC) motion detectors, respectively, in silico and in experimental phantoms. Parametric MMUS phantom images constructed using the BSS method had nearly twice the SNR of the corresponding images constructed using FPL method when a 0.043 mm or smaller kernel size was used. In FEM models of SDUV, the error in the BSS-estimated viscoelastic properties of simulated materials was < 10%, whereas the error was > 20% using NCC when the simulated SNR was 15 dB. In a calibrated elasticity phantom, the amplitude of the motion was ≤ 0.5 μm for a scanner power level ≤ 20%. The median percent error in BSS-derived shear modulus of the phantom was −6.8%, −1.55%, −17.11% for power level of 20%, 15%, and 10%, respectively. The corresponding NCC-derived errors were 29.90%, 127.1%, and 244.70%. These results suggest the relevance of using BSS for the detection of sub-micrometer, periodic motion in MMUS and SDUV imaging, particularly when SNR is less than 15 dB and/or induced displacements are less than 0.5 μm.

VisR ultrasound characterizes the viscoelastic properties of tissue by fitting acoustic radiation force (ARF)-induced displacements in the region of ARF excitation to a 1D mass-spring-damper (MSD) model. Viscosity and elasticity are found separately from each other but relative to the applied ARF amplitude. We refer to these parameters as ‘relative elasticity (RE)’ and ‘relative viscosity (RV)’. We hypothesize that RE and RV linearly correlate to true elasticity and viscosity in tissue.

In transversely isotropic (TI) materials, mechanical properties differ along versus across the axis of symmetry (AoS). The degree of these directional differences has been interrogated by ultrasound-based measures of shear wave velocity (SWV) and ARFI peak displacements (PD) acquired along versus across the AoS. When performed using a conventional linear array transducer, such measurements require a 90o transducer rotation, which can be cumbersome and prone to misalignment errors. Rather than 90o, we hypothesize that smaller rotation angles can be used to assess mechanical anisotropy. This hypothesis was tested in silico using finite-element method (FEM) models and Field II. ARFI and Shear Wave Elasticity Imaging (SWEI) were simulated in five TI elastic materials with longitudinal versus transverse shear elastic modulus ratios (SRs) of 1.22 to 5.44. The simulated rotation angles were 15o, 30o, and 90o. The ratio of PD was measured with the long-axis of the ARF PSF aligned along the AoS versus long-axis rotated by 90o, 30o, or 15o from the AoS. The ratio of SWV was measured along the AoS versus 90o, 30o, or 15o rotation from the AoS. For a 90o rotation angle, both SWV and PD ratios were statistically different (2-sample t-test, p

Previous work has shown that the degree of anisotropy in tissue can be assessed using Acoustic Radiation Force Impulse (ARFI) imaging performed with a geometrically asymmetric excitation. In this work, we investigate the clinical relevance of mechanical anisotropy in Duchenne muscular dystrophy (DMD). Anisotropy assessment was performed using relative elasticity (RE) and relative viscosity (RV) parameters measured by Viscoelastic Response (VisR) ultrasound. These parameters were evaluated as the ratio of their respective values obtained with two orthogonal transducer orientations, i.e. parallel and perpendicular to the muscle fiber direction, to represent the transverse over the longitudinal RE or RV. In a pilot clinical feasibility study performed in six, 7.9–10.4 year-old boys with (DMD) and five age-matched boys with no known neuromuscular disorders, VisR anisotropy imaging was performed in vivo in the rectus femoris (RF) serially for a total of 22 time points in DMD and 12 time points in control boys. Both the RE and RV anisotropy ratios in the RF muscles of boys with DMD were significantly higher (Wilcoxon, p

While skeletal muscle is often assumed to be structurally transversely isotropic (TI), its mechanical anisotropy is not well characterized in vivo. VisR ultrasound, a technique that provides information about the viscoelastic mechanical response of tissue, can be used for such in vivo characterization. Specifically, VisR-derived Relative Elasticity (RE) provides directionally dependent information about the shear modulus of materials. We hypothesize that VisR RE can be used in healthy older adults and in stroke patients to 1) assess the degree of anisotropy (DoA) of the biceps brachii (BB) and 2) characterize the effect of passive loading on the BB. VisR imaging was performed in the BB long head of 2 healthy controls and 1 stroke patient. The subjects' arms were imaged in full extension and approximately 90° flexion at rest. Data were acquired in the transverse and longitudinal imaging planes at the medial location of the BB. The ratio of RE obtained in the transverse to the longitudinal muscle views was found to reflect the DoA in shear modulus, where DoA = 1 indicates perfect isotropy. In control subjects, RE values for flexion and extension in the transverse imaging plane (previously shown to reflect the longitudinal shear modulus, μL) were higher than the RE values in the longitudinal imaging plane (which, primarily reflects the transverse shear modulus, μT). Additionally, both the longitudinal and transverse shear moduli increased in extension vs. flexion. Both the magnitude and direction of anisotropy appeared to change in the stroke patient compared to the healthy controls. This work indicates VisR can be used to assess DoA in skeletal muscle of older adults and examine effects of passive loading on mechanical properties, in vivo, which may be clinically relevant to studying impairment post stroke.

Tissue mechanical anisotropy has been shown to be diagnostically relevant in numerous clinical applications. Anisotropy can be assessed using acoustic radiation force-based techniques, including Acoustic Radiation Force Impulse (ARFI) and Viscoelastic Response (VisR) ultrasound. In this work, ARFI peak displacement (PD), as well as VisR relative elasticity (RE) and relative viscosity (RV), were implemented to image mechanical anisotropy in ex vivo porcine posas major muscle. Two psoas major samples were imaged in this work. The first sample was imaged whole. The second sample was sectioned into a 1 cm-diameter cylinder (with cylinder height oriented along the muscle fibers) and embedded into an isotropic gelatin phantom for imaging. ARFI and VisR were performed on both muscle samples using a linear array transducer mounted to a translation and rotation stage. By rotating the transducer 90o as it stepped across a 2D imaging field of view, PD, RE, and RV were measured along and across muscle fibers. Then, the ratios of PD, RE, and RV measurements made along versus across the muscle fibers were calculated, and these ratios were parametrically rendered in to 2D images representing degree of anisotropy. In the whole psoas major, PD anisotropy ratio was 1.08 +− 0.11, the RE anisotropy ratio was 0.94 +− 0.09 and the RV ratio was 0.94 +− 0.08. These PD and RE anisotropy ratios suggest that the longitudinal shear elastic modulus was greater than the transverse shear elastic modulus, which agrees with previous studies on muscle anisotropy. The RV results suggest that the longitudinal viscous modulus was greater than the transverse viscous modulus. Similar PD, RE, and RV anisotropy ratios were measured in the embedded psoas major section, and contrast ratios were 0.21, 0.14, and 0.30 for PD, RE and RV 2D anisotropy images, respectively. CNR for PD, RE, and RV anisotropy images were 3.26, 2.09 and 2.41, respectively. These results demonstrate that ARFI and VisR anisotropy imaging are relevant for delineating the spatial distribution of anisotropic features in tissue.

The kidney is an anisotropic organ, with higher elasticity along versus across nephrons. The degree of elastic anisotropy in kidney may be diagnostically relevant if properly exploited; however, if improperly controlled, anisotropy may confound stiffness measurements. The purpose of this study is to demonstrate a novel method for selectively exploiting or obviating elastic anisotropy in kidney using Acoustic Radiation Force Impulse (ARFI)-induced peak displacement (PD). The kidneys of three pigs were imaged in vivo at baseline, with venous ligation, and with arterial ligation, and then kidneys were extracted and imaged ex vivo. Imaging was performed with ARF excitation impulses having F/1.5 or F/5.0 focal configurations, and data were acquired with the transducer oriented along and across nephrons alignment in the renal cortex. In addition to ARFI PD, shear wave velocity was measured along and across nephrons to estimate longitudinal and transverse shear elastic moduli. Elastic anisotropy was then assessed as the ratio of PD across versus along nephrons, and as the ratio of shear moduli along versus across nephrons. PD ratio using the F/1.5 ARF linearly correlated with shear moduli ratio (R2 = 0.95). However, PD ratio using the F/5.0 ARF was approximately 1.0 and had weak correlation to shear moduli ratio (R2= 0.56). Further, the average difference in PD measured along versus across nephrons was 2.91 μm for the F/1.5 ARF but was 0.2 μm for the F/5.0 ARF. These results suggest that the F/1.5 ARF excitation exploited elastic anisotropy in the renal cortex, while the F/5.0 ARF excitation obviated it.

VisR ultrasound characterizes the viscoelastic properties of tissue by fitting acoustic radiation force (ARF)-induced displacements in the region of ARF excitation to a 1D mass-spring-damper (MSD) model. By so doing, viscosity and elasticity are found separately from each other but relative to the applied ARF amplitude. We refer to these parameters as ‘relative elasticity (RE)’ and ‘relative viscosity (RV)’. We herein test the hypothesis that RE and RV linearly correlate to true elasticity and viscosity, in silico. VisR imaging was simulated in 144 homogeneous, isotropic, viscoelastic materials with varying elasticity and viscosity using finite element model (FEM) and Field II simulation. RE linearly correlated with shear elasticity of the modeled materials, with R2 = 1.0. For a given elasticity, RE values varied by 2.5% on average when the shear viscosity was changed from 0.1 to 1.3 Pa.s. Similarly, RV linearly correlated with shear viscosity (R2 ≥ 0.99); however, for a given viscosity, RV values varied by 112.7% on average when shear elasticity changed from 3.33 to 20 kPa. This high degree of variation in RV was due to complex 3D system inertia, with greater inertial effects in stiffer materials. This confounding impact of elasticity on RV was compensated by using the natural frequency parameter, ω. After so compensating, corrected RV varied by < 1.0% on average for a given viscosity when the shear elasticity changed from 3.3 to 20 kPa. These results suggest the potential of VisR ultrasound for independently evaluating elastic and viscous properties in tissue.

Stroke is commonly caused by thromboembolic events originating from a ruptured carotid plaque. Histological studies have shown that plaque rupture potential is related to plaque composition rather than degree of stenosis. The use of Acoustic Radiation Force Impulse (ARFI) ultrasound imaging has enabled assessment of carotid plaque composition and structure. In particular, a previous study has shown that ARFI-derived peak displacement (PD) can differentiate between soft (intraplaque hemorrhage/necrotic core) and stiff (collagen/calcium) plaque components with high sensitivity and specificity. However, PD showed low performance for distinguishing between soft and between stiff features. This study evaluates an alternative ARFI-derived parameter, variance of acceleration (VoA), for intraplaque feature delineation. This study analyzed 20 carotid plaques imaged in vivo in patients undergoing carotid endarterectomy (CEA). After imaging, CEA specimens were harvested for histological validation. VoA was statistically significantly different (Wilcoxon, p < 0.01) between all examined plaque features, including between intraplaque hemorrhage and necrotic core and between collagen and calcium. Results suggest that VoA analysis improves ARFI discrimination between soft and between stiff carotid plaque components that are related to vulnerability for rupture.

In transversely isotropic (TI) materials, mechanical properties (Young’s modulus, shear modulus, and Poisson’s ratio) are different along versus across the axis of symmetry (AoS). In this paper, the feasibility of interrogating such directional mechanical property differences using acoustic radiation force impulse (ARFI) imaging is investigated. We herein test the hypotheses that: 1) ARFI-induced peak displacements (PDs) vary with TI material orientations when an asymmetrical ARFI excitation point spread function (PSF) is used, but not when a symmetrical ARFI PSF is employed and 2) the ratio of PDs induced with the long axis of an asymmetrical ARFI PSF oriented along versus across the material’s AoS is related to the degree of anisotropy of the material. These hypotheses were tested in silico using finite-element method (FEM) models and Field II. ARFI excitations had F/1.5, 3, 4, or 5 focal configurations, with the F/1.5 and F/5 cases having the most asymmetrical and symmetrical PSFs at the focal depth, respectively. These excitations were implemented for ARFI imaging in 52 different simulated TI materials with varying degrees of anisotropy, and the ratio of ARFI-induced PDs was calculated. The change in the ratio of PDs with respect to the anisotropy of the materials was highest for the F/1.5, indicating that PD was most strongly impacted by the material orientation when the ARFI excitation was the most asymmetrical. On the contrary, the ratio of PDs did not depend on the anisotropy of the material for the F/5 ARFI excitation, suggesting that PD did not depend on material orientation when the ARFI excitation was symmetrical. Finally, the ratio of PDs achieved using asymmetrical ARFI PSF reflected the degree of anisotropy in TI materials. These results support that symmetrical ARFI focal configurations are desirable when the orientation of the ARFI excitation to the AoS is not specifically known and measurement standardization is important, such as for longitudinal or cross-sectional studies of anisotropic organs. However, asymmetrical focal configurations are useful for exploiting anisotropy, which may be diagnostically relevant. Feasibility for future experimental implementation is demonstrated by simulating ultrasonic displacement tracking and by varying the ARF duration.

In the original publication of this paper [1] , equation (3) contained sign errors for the amplitude of the third and fourth Heaviside functions. The corrected equation is shown in the following: \begin{align*}&\hspace {-1.8pc}\frac {d^{2}}{dt^{2}}u( t )+\omega ^{2}\tau \frac {d}{dt}u( t )+\omega ^{2}u( t ) \\=&S\omega ^{2}( H( t )-H( t-t_{\mathrm {ARF}} ) \\&\quad \qquad +\,H( t-{t_{\mathrm {ARF}}-t}_{s} )-H( t-{2t}_{\mathrm {ARF}}-t_{s} ) ).\tag{3}\end{align*}

Duchenne muscular dystrophy (DMD) is a genetic disorder that causes progressive muscle degeneration involving necrosis and inflammation, with subsequent replacement of muscle fibers by fibrosis and fatty tissue. These compositional changes underlie mechanical property alterations in affected muscles, which may be assessed using Viscoelastic Response (VisR) ultrasound. We hypothesize that VisR will delineate differences in the viscoelastic properties of lower limb skeletal muscles in boys with versus without DMD. VisR imaging was performed in the vastus intermedius (VI), rectus femoris (RF), sartorius (SM) and gastrocnemius (GM) muscles of seven boys (4 DMD, 3 control) aged 7.9 – 10.4 years. Parametric images of relative elasticity (RE) and relative viscosity (RV) were rendered. From the parametric images, percent muscle area with relatively high RE or RV value was calculated and compared (Wilcoxon rank-sum) between DMD and control on a per-muscle basis. In the VI, RF and SM, percent muscle with relatively high RV was larger (VI: 17.7% v. 13.1% RF: 98.9% v. 93.7%, SM: 43.2% v. 40.6% p < 0.05) in DMD than control muscles. In the VI, percent muscle with relatively high RE was larger (32.8% v. 29.5%, p < 0.05) in DMD muscles. No significant differences were observed in the GM between DMD and control. VisR results were consistent with temporally-matched functional testing using a hand-held dynamometer, which showed 40.5% to 70.0% lower force output in DMD RF, VL and SM - and only 21.8% lower force output in DMD GM - relative to the corresponding control muscles. These results suggest that VisR imaging is relevant to delineating viscoelastic property alterations that are associated with dystrophic muscle degeneration in boys with DMD, in vivo.

VisR ultrasound is an acoustic radiation force (ARF)-based imaging method that fits induced displacements to a 1D mass-spring-damper (MSD) model to estimate the ratio of viscous to elastic moduli, τ, in viscoelastic materials. A source of error in VisR τ estimation is complex and interrelated 3D system inertia. We hypothesize that error due to system inertia may be reduced by minimizing the volumetric extent of the employed ARF excitations, i.e. by reducing elevational and lateral F/#s using a matrix array transducer. This hypothesis was tested in silico using finite element method (FEM) models and Field II simulating homogeneous viscoelastic materials and viscoelastic materials with inclusions. In homogeneous viscoelastic materials, decreasing the elevational F/# from 5.0 to 0.75 yielded 62.5%, 96.7%, and 223.69% decreases in the median percent error in VisR τ estimates in materials with Young's modulus of 10, 50, and 100 kPa, respectively. In viscoelastic materials with inclusions, the elevational F/0.75 focal configuration better delineated inclusion borders in comparison to F/5.0, and measured contrast was closer to the true contrast. The CNRs achieved using elevational F/0.75 was 1.25 – 5.0 times higher than those from F/5.0. These results show that as the volumetric extent of ARF excitations decreases by reducing the elevational F/#, VisR τ estimates more closely approximate the true material τ. These results suggest that error in quantitative VisR τ estimates would be reduced by using a transducer capable of elevational focusing.

Stroke is commonly caused by thromboembolic events originating from vulnerable atherosclerotic plaque in the carotid vasculature. The purpose of this study was to evaluate the ability of acoustic radiation force impulse (ARFI) imaging, a noninvasive elastography imaging technique, to assess the composition of carotid artery plaques using histologic examination as the gold standard. Twenty-five patients undergoing carotid endarterectomy (CEA) were enrolled and imaged with ARFI. After surgery, extracted specimens were histologically processed and matched to the ultrasound imaging plane. Parametric 2D ARFI images of peak displacement (PD) were evaluated by three radiologists blinded to the histology result. Receiver operating characteristic (ROC) curve analysis was performed, and area under the ROC curve (AUC) was taken as a metric of performance for detecting plaque features such as necrotic core (NC), intraplaque hemorrhage (IPH), collagen (COL), and calcium (CAL). Additionally, linear regression was performed on fibrous cap (FC) thickness measurements. Areas of plaque with NC and IPH were observed to have substantially increased ARFI PD (2× to 4×) compared to areas of plaque with COL or CAL. Median AUC for detecting soft plaque features (NC/IPH) was 0.887 (range: 0.867 – 0.924) and stiff plaque features (COL/CAL) was 0.859 (range: 0.771 – 0.929). FC thickness measured by two of the three radiologists matched closely with histology (reader 1: R2 = 0.64; reader 2: R2 = 0.89). This study suggests that ARFI is capable of distinguishing soft from stiff compositional elements of atherosclerotic plaques and may be relevant to improving plaque risk assessment.

Acute cerebrovascular accidents are associated with the rupture of vulnerable atherosclerotic plaques in the carotid arteries. Fibrous cap thickness has been shown to be an important predictor of plaque rupture, but has been challenging to measure accurately with clinical noninvasive imaging modalities. The goals of this investigation were first, to evaluate the feasibility of using transcutaneous acoustic radiation force impulse (ARFI) ultrasound to quantify fibrous cap thickness and second, to optimize both imaging and motion tracking parameters to support such measurements. Fibrous caps with varying thickness (0.1 – 1.0 mm) were simulated using a simple layered geometry, and their mechanical response to an impulse of radiation force was solved using finite element method (FEM) modeling. Ultrasound tracking of FEM displacements was performed in Field II utilizing three center frequencies (6, 9, and 12 MHz) and eight motion tracking kernel lengths (0.5λ – 4λ). Additionally, fibrous cap thickness in two carotid plaques imaged in vivo was measured with ARFI and compared to matched histology. The results of this study demonstrate that 1) tracking pulse frequencies around 12 MHz are necessary to resolve caps around 0.2 mm, 2) large motion-tracking kernel sizes introduce bias into thickness measurements and overestimate the true cap thickness, and 3) color saturation settings on ARFI peak displacement images can impact thickness measurement accuracy substantially.

Objective Stroke is commonly caused by thromboembolic events originating from ruptured carotid plaque with vulnerable composition. This study assessed the performance of acoustic radiation force impulse (ARFI) imaging, a noninvasive ultrasound elasticity imaging method, for delineating the composition of human carotid plaque in vivo with histologic validation. Methods Carotid ARFI images were captured before surgery in 25 patients undergoing clinically indicated carotid endarterectomy. The surgical specimens were histologically processed with sectioning matched to the ultrasound imaging plane. Three radiologists, blinded to histology, evaluated parametric images of ARFI-induced peak displacement to identify plaque features such as necrotic core (NC), intraplaque hemorrhage (IPH), collagen (COL), calcium (CAL), and fibrous cap (FC) thickness. Reader performance was measured against the histologic standard using receiver operating characteristic curve analysis, linear regression, Spearman correlation (ρ), and Bland-Altman analysis. Results ARFI peak displacement was two-to-four-times larger in regions of NC and IPH relative to regions of COL or CAL. Readers detected soft plaque features (NC/IPH) with a median area under the curve of 0.887 (range, 0.867-0.924) and stiff plaque features (COL/CAL) with median area under the curve of 0.859 (range, 0.771-0.929). FC thickness measurements of two of the three readers correlated with histology (reader 1: R 2 = 0.64, ρ = 0.81; reader 2: R 2 = 0.89, ρ = 0.75). Conclusions This study suggests that ARFI is capable of distinguishing soft from stiff atherosclerotic plaque components and delineating FC thickness.

A method for adaptive clutter rejection via blind source separation (BSS) using principal and independent component analyses is presented in application to blood velocity measurement in the carotid artery. In particular, the filtering method's efficacy for eliminating clutter and preserving lateral blood flow signal components is presented. The performance of IIR filters is compromised by shorth data ensembles (10 to 20 temporal samples) as implemented for color-flow and high frame-rate imaging due to initialization requirements. Further, the ultrasonic imaging system's transfer function maps axial wall and lateral blood motion to overlapping spectra. As such, frequency domain-based approaches to wall filtering are ineffective for distinguishing wall from blood motion signals. Rather than operating in the frequency domain, BSS performs clutter rejection by decomposing the input data ensemble into N constitutive source signals in time, where N is the ensemble length. Source signal energy coupled with respective signal depth and time course profiles reveal which source signals correspond to blood, noise and clutter components. Clutter components may then be removed without disruption of lateral blood flow information needed for two-dimensional blood velocity measurement. A simplistic data simulation is employed to offer an intuitive understanding of BSS methods for signal separation. The adaptive BSS filter is further demonstrated using a Field II simulation of blood flow through the carotid artery including tissue motion. BSS clutter filter performance is compared to the performance of FIR, IIR and polynomial regression clutter filters. Finally, the filter is employed for clinical application using a Siemens Elegra scanner, carotid artery data with lateral blood flow collected from healthy volunteers, and Speckle Tracking; velocity magnitude and angle profiles are shown. Once again, the BSS clutter filter is contrasted to FIR, IIR and polynomial regression clutter filters using clinical examples. Velocities computed with Speckle Tracking after BSS wall filtering are highest in the center of the artery and diminish to low velocities near the vessel walls, with velocity magnitudes consistent with physiological expectations. These results demonstrate that the BSS adaptive filter sufficiently suppresses wall motion signal for clinical lateral blood velocity measurement using data ensembles suitable for color-flow and high frame-rate imaging.