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Stroke is commonly caused by thromboembolic events originating from atherosclerotic plaques in the carotid vasculature. To improve stroke risk prediction by delineating vulnerable plaque features, our group has developed ARFI Variance of Acceleration log(VoA) imaging. We herein evaluate the ability of trained, blinded readers to interpret in vivo ARFI log(VoA) images of human carotid plaques, with validation by matched histology. Patients undergoing carotid endarterectomy were imaged using a Siemens S3000 and a 9L4 transducer. From 21 plaques, one was excluded due to specimen damage during surgery. Parametric 2D images of ARFI log(VoA) were rendered and evaluated by 3 neuroradiologists, 1 abdominal radiologist, 1 sonographer, and 1 pathologist, all blinded to the histological gold standard. Receiver operating characteristic (ROC) curve analysis was performed, and area under the curve (AUC) was taken as a metric of performance for detecting lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), collagen (COL), and calcium (CAL). Reader log(VoA) outcomes were compared to those achieved using ARFI peak displacement (PD) in a comparable prior study. Average AUC performance for plaque features were as follows: CAL, 0.77; COL, 0.76; LRNC, 0.79; IPH, 0.82. Grouping the stiff (COL and CAL) and soft (LRNC and IPH) features together increased average AUCs to 0.86 for stiff and 0.87 for soft. These log(VoA) AUC outcomes were higher than those achieved by blinded readers evaluating ARFI PD images. This study shows the relevance of ARFI log(VoA) imaging, as interpreted by trained, blinded readers, to delineating the structure and composition of carotid atherosclerotic plaque in humans, in vivo.

Rupture potential of atherosclerotic plaques in carotid arteries is conferred by both composition and structure of plaques. Previous studies have shown that from in vivo collected data, carotid plaque components such as collagen, calcium, necrotic core and intraplaque hemorrhage can be automatically detected by an ARFI imaging-derived machine learning classifier. Automatic classification considered normalized cross-correlation measurements of ARFI-induced displacement, signal-to-noise ratio and cross-correlation coefficients from an on-axis ARFI acquisition. We now extend our prior work by hypothesizing that using multiple ARFI data forms improves plaque feature detection and FC thickness measurement in human carotid plaques, relative to a single form of ARFI data. Carotid plaques were imaged in vivo prior to surgery in 20 patients undergoing carotid endarterectomy (CEA), and extracted plaque specimens were harvested after CEA for histological processing. ARFI data were acquired with cardiac gating to diastole with push (DP) and to systole without push (SNP) using fundamental low (FL), fundamental high (FH), and harmonic (H) tracking frequencies. Combinations of the resulting displacement profiles were 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, DP+FH+H achieved the highest average AUC of 0.926 (Sensitivity = 0.932, Specificity = 0.915) but required 2 acquisitions. The best data combination requiring only one acquisition (DP+FH) achieved an AUC of 0.917 (Sensitivity = 0.902, Specificity = 0.880). These results suggest that using multiple forms of frequency and gating of ARFI data as inputs to an automatic classifier improves discrimination of carotid plaque components, relevant for rupture vulnerability assessment.

Quantitative Viscoelastic Response (QVisR) ultrasound uses in silico on-axis VisR displacement profiles to estimate the elastic and viscous moduli of an interrogated material. This work studies the effect of varying the radio frequency (RF) data signal-to-noise ratio (SNR) on QVisR's estimates. White Gaussian noise was added to the RF data of simulated viscoelastic materials subject to a VisR beamsequence with SNRs from 0-50dB in steps of 10dB. Tracked displacements were used as features for a neural network model to estimate elastic and viscous moduli. Predicted elastic moduli RMSE was smaller than the simulated material elastic step size down to 20dB SNR and viscous moduli RMSE was smaller than the viscous step size down to 40dB SNR. These findings suggest QVisR can be used to estimate viscoelastic moduli in noisy environments that more closely model non-simulation data acquisitions.

The kidney is an anisotropic organ, with higher elasticity along versus across nephrons. The degree of mechanical anisotropy in the 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 the clinical feasibility of acoustic radiation force (ARF)-induced peak displacement (PD) measures for both exploiting and obviating mechanical anisotropy in the cortex of human kidney allografts, in vivo . Validation of the imaging methods is provided by preclinical studies in pig kidneys, in which ARF-induced PD values were significantly higher ( $p , Wilcoxon) when the transducer executing asymmetric ARF was oriented across versus along the nephrons. The ratio of these PD values obtained with the transducer oriented across versus along the nephrons strongly linearly correlated ( $R^{2} = 0.95$ ) to the ratio of shear moduli measured by shear wave elasticity imaging. On the contrary, when a symmetric ARF was implemented, no significant difference in PD was observed ( $p > 0.01$ ). Similar results were demonstrated in vivo in the kidney allografts of 14 patients. The symmetric ARF produced PD measures with no significant difference ( $p > 0.01$ ) between along versus across alignments, but the asymmetric ARF yielded PD ratios that remained constant over a six-month observation period post-transplantation, consistent with stable serum creatinine level and urine protein-to-creatinine ratio in the same patient population ( $p> 0.01$ ). The results of this pilot in vivo clinical study suggest the feasibility of 1) implementing symmetrical ARF to obviate mechanical anisotropy in the kidney cortex when anisotropy is a confounding factor and 2) implementing asymmetric ARF to exploit mechanical anisotropy when mechanical anisotropy is a potentially relevant biomarker.

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.

Acoustic Radiation Force Impulse (ARFI) imaging employs sound impulses to induce and track tissue motion that conveys mechanical property. In application to carotid atherosclerotic plaque, ARFI noninvasively delineates features that convey risk for ischemic stroke: intraplaque hemorrhage, lipid-rich necrotic core, thin or ruptured fibrous cap, diffuse collagen, and calcium deposits. This talk will feature recent advances to in vivo ARFI atherosclerosis imaging technology, including the use of machine learning for automated feature classification, which are validated histologically in patients undergoing carotid endarterectomy. New developments, including incorporating vector blood flow estimation for combined shear strain assessment, will be highlighted.

Viscoelastic Response (VisR) ultrasound is a noninvasive method for interrogating the viscoelastic properties of tissue by observing, in the region of excitation, tissue displacement in response to successive acoustic radiation force impulses. Recent VisR technology advancements now enable estimation of mechanical anisotropy and texture as well as, via machine learning approaches, quantitative evaluation of elastic and viscous moduli (as in Quantitative VisR (QVisR)). The diagnostic relevance of VisR outcome measures have been demonstrated for monitoring renal transplant status, differentiating malignant from benign breast masses, and delineating dystrophic muscle degeneration. For the latter two applications, method and pilot clinical results are reviewed herein. VisR-derived relative elasticity (RE) and relative viscosity (RV) mechanical anisotropy measures differentiated malignant from benign breast masses in women with sensitivities of 0.94 and specificities of 1.00, with accuracies of 0.96. In dystrophic muscle, QVisR-derived longitudinal shear elastic modulus in rectus femoris, vastus lateralus, sartorius, and gastrocnemius muscles statistically different between dystrophic and control for ages less than six years (Wilcoxon, p

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.

We present a quantitative extension of Viscoelastic Response (VisR) ultrasound that estimates shear elastic and viscous moduli from on-axis VisR displacement profiles in silico. Isotropic, homogeneous, linearly viscoelastic materials ranging from 1.57-33.33 kPa shear elasticity and 0.0033-2.34 Pa.s shear viscosity subject to a VisR beamsequence at 26 focal depths were simulated. Multi-target regression machine learning models were used to estimate shear elasticity and shear viscosity given the displacement profile, focal depth, and axial depth. The best performing models achieve a shear elasticity RMSE of 0.29 kPa and a shear viscosity RMSE of 0.13 Pa.s when predictions were made on the test set. These results suggest that machine learning methods can be used to quantitatively estimate viscoelasticity from VisR displacement profiles.

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.

Direct ultrasonic imaging of arterial and venous thrombi could aid in diagnosis and treatment planning by providing rapid and cost-effective measurements of thrombus volume and elastic modulus. Toward this end, it was demonstrated that open-air magnetomotive ultrasound (MMUS) provides specific contrast to superparamagnetic iron oxide-labeled model thrombi embedded in gelatin-based blood vessel-mimicking flow phantoms. MMUS was performed on model thrombi in the presence of pulsatile flow that mimics cardiac-induced motion found in real vasculature. The MMUS signal and contrast-to-noise ratio (CNR) were measured across a range of physiologically relevant thrombus volumes and elastic moduli. Model thrombus volumes as small as 0.5 ml were shown to be detectable (CNR > 1) over the entire range of elastic moduli tested (3.5–40 kPa). It was also found that MMUS signal and CNR are increased with increasing thrombus volume ( $r = 0.99$ ) and decreasing elastic modulus ( $r = -0.81$ ), while variations in pulsatile flow rate had little effect. These findings demonstrate that MMUS has promise as a direct in vivo thrombosis imaging modality for quantifying thrombus volume and stiffness.

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.

Degree of mechanical anisotropy in renal cortex can be assessed by evaluating the ratio of viscoelastic response (VisR) parameters achieved when the long axis of a spatially asymmetric ARF excitation PSF is aligned along versus across nephrons. In this work, intra-observer reproducibility and variability in VisR derived DoA assessment in renal cortex due to donor type, sex, race, and BMI is evaluated in healthy human kidney allografts, in vivo. Transcutaneous, in vivo VisR imaging was performed in 20 kidney allografts 2 months post-transplantation using a Siemens Acuson Antares™ imaging system and a VF7-3 linear array transducer. Ratios of VisR derived relative elasticity (RE), relative viscosity (RV), and peak displacement (PD) obtained with the ARF short-axis aligned along versus across nephrons were calculated. Patients were divided based on their sex (male: N=14 versus female: N=6), race (African American: N = 6 versus Caucasian: N=14), donor type (living: N=14 versus deceased: N =6), and BMI (BMI >30: N= 8 versus BMI 0.05) due to sex, race, donor types, or BMI. The median absolute percent difference in (PD, RE, RV) ratios were (23, 13, 23) due to sex, (5, 3, 3) due to race, (0.35, 14, 13) due to donor type, and 8.6, 6, 12) due to BMI. Ratios of PD, RE, and RV were not statistically different between 1st and 2nd imaging events with mean percent difference in (PD, RE, and RV) ratios of (-0.04, -0.11, and - 0.01). These findings suggest that VisR outcome measures are robust to potentially confounding demographic factors and reproducible by a trained practitioner.

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.

Tissue elasticity can be measured by applying an acoustic radiation force (ARF) excitation and tracking mechanical responses like deformation or shear wave propagation via displacement tracking. However, tissue displacements tracked by ultrasound is underestimated due to the shearing of scatterers under the tracking point-spread function. While such displacement underestimation is a source of error in conventional elasticity approaches, we herein present an alternative method that exploits displacement underestimation: double-profile intersection (DoPIo) elastography. We hypothesize that DoPIo can quantify material elasticity in silico.

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

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.

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.

Vulnerable atherosclerotic plaques have high risk for rupture, with rupture potential related to plaque composition and structure. We have previously shown that soft (intraplaque hemorrhage IPH, and lipid rich necrotic core LRNC) are differentiated from stiff (collagen COL, and calcium CAL) plaque elements in human carotid plaques by Acoustic Radiation Force Impulse (ARFI)-derived peak displacement (PD). However, PD had lower performance for differentiating between features with similar stiffness. Here we evaluate an alternative method to improve intraplaque feature delineation by using machine learning methods. From ARFI imaging data, SNR, cross-correlation coefficient, and displacement were used as inputs to random forests (RaF) and support vector machines (SVM) algorithms. The algorithms were trained to identify IPH, LRNC, COL and CAL by 5-fold cross-validation with ground truth identified from histology. From output likelihood matrices, CNR between plaque components were calculated and compared to the corresponding CNR achieved by ARFI PD and VoA. Results showed that both RaF and SVM achieved higher CNRs for distinguishing between features than ARFI outputs alone. These results suggest that, relative to PD, machine learning improves ARFI discrimination of carotid plaque components that are correlated to vulnerability for rupture.

In Golden Retriever Muscular Dystrophy (GRMD) dogs, a relevant animal model of human Duchenne muscular dystrophy (DMD), skeletal muscles progressively inflame, necrose, and undergo fibrous and fatty deposition. These degenerative changes alter the composition and structure of muscle, which affects the degree of directional variation, or anisotropy, in tissue mechanical properties. Further, such degenerative changes alter the spatial distribution of mechanical property across muscles. In this work we investigate the relevance of mechanical anisotropy and texture, estimated using Viscoelastic Response (VisR) ultrasound, to tracking progressive dystrophic muscle degeneration in GRMD dogs, in vivo. In a year-long study of 20 dogs, degree of shear elastic anisotropy (DoA), was significantly higher in the GRMD semitendinosus (ST) muscle compared to control ST (GRMD: 1.23 +- 0.25, Control 1.13 +- 0.27, 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.

In Duchenne muscular dystrophy (DMD), muscle fiber necrosis and subsequent progressive replacement of muscle by fibrous tissue and fat impacts the degree of anisotropy (DoA) in mechanical properties. Mechanical DoA can be assessed in skeletal muscle using Viscoelastic Response (VisR) ultrasound. We hypothesize that in vivo VisR DoA measures in the rectus femoris (RF) muscles of boys with DMD statistically differ from those in control boys. Further, we hypothesize that VisR DoA is correlated to RF functional output.

Degree of anisotropy (DoA) has been evaluated for clinical significance in several organs. In skeletal muscle, mechanical DoA has been shown to increase with passive extension, i.e. the shear modulus parallel to muscle fibers (μ l ) increases relative to that perpendicular (μ t ). Imaging such variations in DoA could facilitate diagnosing and monitoring muscle pathologies. We have previously demonstrated the feasibility of imaging DoA with VisR ultrasound, in silico. The purpose of this work is to experimentally demonstrate VisR DoA imaging ex vivo in pig and in vivo in human muscles. We hypothesize that 2D VisR anisotropy images represent mechanical anisotropy in muscle.

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.

Point shear wave elastography (pSWE) provides noninvasive measures of mechanical stiffness of biological tissue. Over the past decade, research has demonstrated that pSWE is effective at diagnosing a multitude of pathologies such as liver fibrosis and cancer. Life science researchers stand to benefit tremendously from access to pSWE but a number of challenges have limited its use in small animals. First, high frequency pSWE imaging suffers from transducer heating challenges and bandwidth requirements. Second, pSWE measurements are highly susceptible to variations in the environment and operator (e.g. precompression of tissue, transducer placement, etc.) which bias measurements and introduce error. Therefore, the objective of this work is to develop a robotically controlled, non-contact pSWE system capable of measuring liver stiffness in rodents.

Stroke is commonly caused by thromboembolic events originating from ruptured carotid plaque, with rupture potential related to plaque composition. We have previously shown that soft (intraplaque hemorrhage/necrotic core) and stiff (collagen/calcium) plaque components are differentiated with high sensitivity and specificity by peak displacement (PD) in Acoustic Radiation Force Impulse (ARFI) imaging. However, PD showed low performance for distinguishing between soft and between stiff features. We hypothesize that soft and stiff feature delineation will be improved using a new ARFI outcome metric — the variance of acceleration (VoA). We test our hypothesis using histological validation.

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.

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.

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.

Acoustic radiation force impulse (ARFI) Surveillance of Subcutaneous Hemorrhage (ASSH) has been previously demonstrated to differentiate bleeding phenotype and responses to therapy in dogs and humans, but to date, the method has lacked experimental validation. This work explores experimental validation of ASSH in a poroelastic tissue-mimic and in vivo in dogs. The experimental design exploits calibrated flow rates and infusion durations of evaporated milk in tofu or heparinized autologous blood in dogs. The validation approach enables controlled comparisons of ASSH-derived bleeding rate (BR) and time to hemostasis (TTH) metrics. In tissue-mimicking experiments, halving the calibrated flow rate yielded ASSH-derived BRs that decreased by 44% to 48%. Furthermore, for calibrated flow durations of 5.0 minutes and 7.0 minutes, average ASSH-derived TTH was 5.2 minutes and 7.0 minutes, respectively, with ASSH predicting the correct TTH in 78% of trials. In dogs undergoing calibrated autologous blood infusion, ASSH measured a 3-minute increase in TTH, corresponding to the same increase in the calibrated flow duration. For a measured 5% decrease in autologous infusion flow rate, ASSH detected a 7% decrease in BR. These tissue-mimicking and in vivo preclinical experimental validation studies suggest the ASSH BR and TTH measures reflect bleeding dynamics.

Acoustic radiation force impulse (ARFI) ultrasound is an elasticity imaging technique that has the potential to identify vulnerable atherosclerotic plaque characteristics. Previous studies have shown that regions of high ARFI-induced displacement correspond to lipid/necrotic areas in plaques, whereas regions of low displacement correspond with fibrotic/calcified areas. In this work, we continue our analysis of ARFI images captured from patients undergoing carotid endarterectomy. ARFI imaging of carotid plaque was performed prior to surgery, and extracted specimens were histologically processed and matched to the ultrasound imaging plane. ARFI images and histological slides were annotated independently for various features including necrotic core, calcification, fibrosis and fibrous cap, and wide hemorrhage. Results are presented for a number of advanced plaque types (Va, Vb, and VI), and ARFI-derived fibrous cap thickness measurements are compared quantitatively to histology. Results suggest ARFI is capable of measuring fibrous cap thickness with a mean positive bias of 0.09 ± 0.12 mm, and may be capable of identifying ruptured plaque.

Viscoelastic Response (VisR) imaging is an acoustic radiation force (ARF)-based ultrasonic technique for estimating the viscoelastic properties of tissue. It has been proposed as a method for monitoring degeneration in the skeletal muscles of boys with Duchenne muscular dystrophy (DMD). DMD causes progressive inflammation, necrosis, fibrosis and fatty deposition in muscle, all of which will alter the elasticity and viscosity of the tissue. The motivation of this work is to investigate VisR's potential as method for monitoring dystrophic muscle degeneration, in vivo, in boys with DMD. In an ongoing longitudinal clinical study, muscles in the lower limbs of boys affected with DMD and age-matched healthy control boys are imaged using VisR thrice yearly for four years. A case study of serial imaging results in the Medial Gastrocnemius (GM) muscle of one boy with DMD is herein presented. Beginning at age 6.2 years, parametric VisR images of τ, or the ratio of viscosity to elasticity, show a growing region of high τ (>1.2 ms) over the span of one year. This result is consistent with expected progressive inflammation and fatty deposition early in the GM's degenerative cycle. Over the course of the next four months, the area of high τ decreases, which is in agreement with the expected onset of muscle fibrosis. Then, at age 8.3 years, small and diffusely distributed high τ regions are observed in the muscle, consistent with expected distributed fatty depositions. These results suggest that VisR, a noninvasive ultrasound imaging method, may be clinically viable for monitoring local muscular compositional and structural changes associated with dystrophic degeneration, in vivo.

Coronary atherosclerotic disease is the major cause of mortality in the United States. Elasticity imaging techniques such as acoustic radiation force impulse (ARFI) imaging using intravascular ultrasound (IVUS) transducers can be used to characterize coronary plaque. Conventional IVUS transducers with frequencies of 20 MHz – 60 MHz are not optimized for high-voltage, long-duration pulses required for ARFI imaging. In this work, a dual-frequency IVUS transducer, consisting of a 6.5 MHz “pushing” element and a 26 MHz “tracking” element, was designed and fabricated for ARFI application. In ARFI testing with a 160 V, 1000-cycle burst excitation, a displacement of 12.3 µm was detected in a phantom with a Young's modulus of 10 kPa at an axial depth of 3.5 mm. The result of this study suggests great potential of this dual-frequency IVUS transducer for intravascular ARFI imaging.

Viscoelastic Response (VisR) ultrasound is a new Acoustic Radiation Force (ARF)-based imaging method that uses two successive ARF excitations, delivered to the same region of excitation, to approximate a creep response in tissue and thereby estimate viscoelastic property. The viscoelasticity of dystrophic muscle is altered over time by ongoing necrotic, fatty, and fibrous degenerative changes. Evaluating such changes by VisR in the Golden Retriever Muscular Dystrophy (GRMD) canine model, with comparison to matched MRI and histology, is the purpose of this work. In a cross-sectional study, in vivo VisR imaging was performed on the vastus lateralis (VL) and cranial sartorius (CS) muscles in 20 dogs (n=10 control and GRMD age-matched pairs) aged 3, 6, 12, 24, or 60 months. Following VisR, T2-weighted MRI imaging was performed, and run percentage (RP) was calculated to reflect heterogeneity. Finally, muscle tissue samples were acquired by open surgical biopsy, sectioned, and stained, and percent collagen and fat were calculated from digital microscopy. In the VL, SD of VisR τ was consistently larger in GRMD versus age-matched control dogs (p=0.001, Wilcoxon two-sample test). This VisR result was consistent with higher MRI RP measures and higher histology percent collagen. Similarly in the CS, SD of VisR τ was larger in GRMD than control (p=0.001), consistent with higher MRI RP and with histology percent collagen. These results suggest that VisR measures of τ SD reflect heterogeneity due to collagen deposition in dystrophic muscles.

This article introduces a new functional imaging paradigm that uses optical coherence tomography (OCT) to detect rehydrated, lyophilized platelets (RL platelets) that are in the preclinical trial stage and contain superparamagnetic iron oxides (SPIOs) approved by the U.S. Food and Drug Administration. Platelets are highly functional blood cells that detect and adhere to sites of vascular endothelial damage by forming primary hemostatic plugs. By applying magnetic gradient forces, induced nanoscale displacements (magnetomotion) of the SPIO-RL platelets are detected as optical phase shifts in OCT. In this article, we characterize the iron content and magnetic properties of SPIO-RL platelets, construct a model to predict their magnetomotion in a tissue medium, and demonstrate OCT imaging in tissue phantoms and ex vivo pig arteries. Tissue phantoms containing SPIO-RL platelets exhibited >3 dB contrast/noise ratio at ≥1.5 × 109 platelets/cm3. OCT imaging was performed on ex vivo porcine arteries after infusion of SPIO-RL platelets, and specific contrast was obtained on an artery that was surface-damaged (P < 10−6). This may enable new technologies for in vivo monitoring of the adherence of SPIO-RL platelets to sites of bleeding and vascular damage, which is broadly applicable for assessing trauma and cardiovascular diseases.

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.

In this second of a two part series, we present pilot clinical data demonstrating Acoustic Radiation Force Impulse (ARFI) ultrasound for monitoring the onset of subcutaneous hemostasis at femoral artery puncture sites (arteriotomies), in vivo. We conducted a randomized, reader-blinded investigation of 20 patient volunteers who underwent diagnostic percutaneous coronary catheterization. After sheath removal (6 French), patients were randomized to treatment with either standard of care manual compression alone or, to expedite hemostasis, manual compression augmented with a p-GlcNAc fiber-based hemostatic dressing (Marine Polymer Technologies, Danvers MA). Concurrent with manual compression, serial ARFI imaging began at the time of sheath removal and continued every minute for 15 min. Serial data sets were processed with custom software to (1) estimate the time of hemostasis onset, and (2) render hybrid ARFI/B-Mode images to highlight displacements considered to correspond to extravasted blood. Images were read by an observer blinded to the treatment groups. Average estimated times to hemostasis in patient volunteers treated with manual compression alone ( n = 10) and manual compression augmented by hemostatic dressing ( n = 9) were, respectively, 13.00 ± 1.56 and 9.44 ± 3.09 min, which are statistically significantly different ( p = 0.0065, Wilcoxon two-sample test). Example images are shown for three selected patient volunteers. These pilot data suggest that ARFI ultrasound is relevant to monitoring subcutaneous bleeding from femoral arteriotomies clinically and that time to hemostasis was significantly reduced by use of the hemostatic dressing.

Acoustic radiation force imaging methods distinguish tissue structure and composition by monitoring tissue responses to applied radiation force excitations. Although these responses are a complex, multidimensional function of the geometric and viscoelastic nature of tissue, simplified discrete biomechanical models offer meaningful insight to the physical phenomena that govern induced tissue motion. Applying Voigt and standard linear viscoelastic tissue models, we present a new radiation force technique - monitored steady-state excitation and recovery (MSSER) imaging - that tracks both steady-state displacement during prolonged force application and transient response following force cessation to estimate tissue mechanical properties such as elasticity and viscosity. In concert with shear wave elasticity imaging (SWEI) estimates for Young's modulus, MSSER methods are useful for estimating tissue mechanical properties independent of the applied force magnitude. We test our methods in gelatin phantoms and excised pig muscle, with confirmation through mechanical property measurement. Our results measured 10.6 kPa, 14.7 kPa, and 17.1 kPa (gelatin) and 122.4 kPa (pig muscle) with less than 10% error. This work demonstrates the feasibility of MSSER imaging and merits further efforts to incorporate relevant mechanical tissue models into the development of novel radiation force imaging techniques.

Cardiovascular disease (CVD) is the leading cause of death in the United States, with 70% of CVD mortalities the result of sequelae of atherosclerosis. An urgent need for enhanced delineation of vulnerable plaques has catalyzed the development of novel atherosclerosis imaging strategies that use X-ray computed tomography, magnetic resonance and ultrasound modalities. As suggested by the pathophysiology of plaque development and progression to vulnerability, insight to the focal material, i.e., mechanical, properties of arterial walls and plaques may enhance atherosclerosis characterization. We present acoustic radiation force impulse (ARFI) ultrasound in application to mechanically characterizing a raised focal atherosclerotic plaque in an iliac artery extracted from a relevant pig model. ARFI results are correlated to matched immunohistochemistry, indicating elastin and collagen composition. In regions of degraded elastin, slower recovery rates from peak ARFI-induced displacements were observed. In regions of collagen deposition, lower ARFI-induced displacements were achieved. This work demonstrates ARFI for characterizing the material nature of an atherosclerotic plaque.