On the Feasibility of Quantifying Fibrous Cap Thickness With Acoustic Radiation Force Impulse (ARFI) Ultrasound

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

ARFI Imaging for Noninvasive Material Characterization of Atherosclerosis Part II: Toward In Vivo Characterization

Seventy percent of cardiovascular disease (CVD) deaths are attributed to atherosclerosis. Despite their clinical significance, nonstenotic atherosclerotic plaques are not effectively detected by conventional atherosclerosis imaging methods. Moreover, conventional imaging methods are insufficient for describing plaque composition, which is relevant to cardiovascular risk assessment. Atherosclerosis imaging technologies capable of improving plaque detection and stratifying cardiovascular risk are needed. Acoustic Radiation Force Impulse (ARFI) ultrasound, a novel imaging method for noninvasively differentiating the mechanical properties of tissue, is demonstrated for in vivo detection of nonstenotic plaques and plaque material assessment in this pilot investigation. In vivo ARFI imaging was performed on four iliac arteries: 1) of a normocholesterolemic pig with no atherosclerosis as a control, 2) of a familial hypercholesterolemic pig with diffuse atherosclerosis, 3) of a normocholesterolemic pig fed a high-fat diet with early atherosclerotic plaques and 4) of a familial hypercholesterolemic pig with diffuse atherosclerosis and a small, minimally-occlusive plaque. ARFI results were compared to spatially matched immunohistochemistry, showing correlations between elastin and collagen content and ARFI-derived peak displacement and recovery time parameters. Faster recoveries from ARFI-induced peak displacements and smaller peak displacements were observed in areas of higher elastin and collagen content. Importantly, spatial correlations between tissue content and ARFI results were consistent and observable in both large and highly evolved as well as small plaques. ARFI imaging successfully distinguished nonstenotic plaques, while conventional B-Mode ultrasound did not. This work validates the potential relevance of ARFI imaging as a noninvasive imaging technology for in vivo detection and material assessment of atherosclerotic plaques

Viscoelastic response (VisR) imaging for assessment of viscoelasticity in voigt materials

Viscoelastic response (VisR) imaging is presented as a new acoustic radiation force (ARF)-based elastographic imaging method. Exploiting the Voigt model, VisR imaging estimates displacement in only the ARF region of excitation from one or two successive ARF impulses to estimate τσ, the relaxation time for constant stress. Double-push VisR τσ estimates were not statistically significantly different (p < 0.02) from those of shearwave dispersion ultrasound vibrometry (SDUV) or monitored steady-state excitation recovery (MSSER) ultrasound in six homogeneous viscoelastic tissue mimicking phantoms with elastic moduli ranging from 3.92 to 15.34 kPa and coefficients of viscosity ranging from 0.87 to 14.06 Pa·s. In two-dimensional imaging, double-push VisR τσ images discriminated a viscous spherical inclusion in a structured phantom with higher CNR over a larger axial range than single-push VisR or conventional acoustic radiation force impulse (ARFI) ultrasound. Finally, 2-D in vivo double-push VisR images in normal canine semitendinosus muscle were compared with spatially matched histochemistry to corroborate lower double-push VisR τσ values in highly collagenated connective tissue than in muscle, suggesting double-push VisR’s in vivo relevance to diagnostic imaging, particularly in muscle. The key advantages and disadvantages to VisR, including lack of compensation for inertial terms, are discussed

On the Quantitative Potential of Viscoelastic Response (VisR) Ultrasound Using the One-Dimensional Mass-Spring-Damper Model

Viscoelastic Response (VisR) ultrasound is an acoustic radiation force (ARF)-based imaging method that fits induced displacements to a one-dimensional (1D) mass-spring-damper (MSD) model to estimate the ratio of viscous to elastic moduli, τ, in viscoelastic materials. Error in VisR τ estimation arises from inertia and acoustic displacement underestimation. These error sources are herein evaluated using finite element method (FEM) simulations, error correction methods are developed, and corrected VisR τ estimates are compared to true simulated τ values to assess VisR’s relevance to quantifying viscoelasticity. In regards to inertia, adding a mass term in series with the Voigt model, to achieve the MSD model, accounts for inertia due to tissue mass when ideal point force excitations are used. However, when volumetric ARF excitations are applied, the induced complex system inertia is not described by the single-degree-of-freedom MSD model, causing VisR to overestimate τ. Regarding acoustic displacement underestimation, associated deformation of ARF-induced displacement profiles further distorts VisR τ estimates. However, median error in VisR τ is reduced to approximately −10% using empirically derived error correction functions applied to simulated viscoelastic materials with viscous and elastic properties representative of tissue. The feasibility of corrected VisR imaging is then demonstrated in vivo in the rectus femoris muscle of an adult with no known neuromuscular disorders. These results suggest VisR’s potential relevance to quantifying viscoelastic properties clinically

Design, Fabrication, and Characterization of a Bifrequency Colinear Array

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 dB fractional bandwidth of ~70 %, limiting the imaging resolution or depth of field. In this paper, a bi-frequency co-linear array with resonant frequencies of 8 MHz 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 bi-frequency co-linear array was designed and fabricated, followed by element characterization and real-time sectorial scan (S-scan) phantom imaging using a Verasonics system. The bi-frequency co-linear 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, (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 bi-frequency co-linear arrays are potential aids for wideband fundamental imaging and harmonic/sub-harmonic imaging

Experimental Validation of Displacement Underestimation in ARFI Ultrasound

Acoustic radiation force impulse (ARFI) imaging is an elastography technique that uses ultrasonic pulses to both displace and track tissue motion. Previous modeling studies have shown that ARFI displacements are susceptible to underestimation due to lateral and elevational shearing that occurs within the tracking resolution cell. In this study, optical tracking was utilized to experimentally measure the displacement underestimation achieved by acoustic tracking using a clinical ultrasound system. Three optically translucent phantoms of varying stiffness were created, embedded with sub-wavelength diameter microspheres, and ARFI excitation pulses with F/1.5 or F/3 lateral focal configurations were transmitted from a standard linear array to induce phantom motion. Displacements were tracked using confocal optical and acoustic methods. As predicted by earlier FEM studies, significant acoustic displacement underestimation was observed for both excitation focal configurations; the maximum underestimation error was 35% of the optically measured displacement for the F/1.5 excitation pulse in the softest phantom. Using higher F/#, less tightly focused beams in the lateral dimension improved accuracy of displacements by approximately 10 percentage points. This work experimentally demonstrates limitations of ARFI implemented on a clinical scanner using a standard linear array and sets up a framework for future displacement tracking validation studies

Experimental Validation of ARFI Surveillance of Subcutaneous Hemorrhage (ASSH) Using Calibrated Infusions in a Tissue-Mimicking Model and Dogs

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

A review of current methods for assessing hemostasis in vivo and introduction to a potential alternative approach

A validated method for assessing hemostasis in vivo is critical for testing the hemostatic efficacy of therapeutic agents in preclinical animal models and in patients with inherited bleeding disorders, such as von Willebrand disease (VWD) and hemophilia A, or with acquired bleeding disorders such as those resulting from medications or disease processes. In this review, we discuss current methods for assessing hemostasis in vivo and the associated challenges. We also present ARFI-Monitored Hemostatic Challenge; a new, potentially alternate method for in vivo hemostasis monitoring that is in development by our group

Robust Principal Component Analysis and Clustering Methods for Automated Classification of Tissue Response to ARFI Excitation

We introduce a new method for automatic classification of Acoustic Radiation Force Impulse (ARFI) displacement profiles using what have been termed ‘robust’ methods for principal component analysis (PCA) and clustering. Unlike classical approaches, the robust methods are less sensitive to high variance outlier profiles and require no a priori information regarding expected tissue response to ARFI excitation. We first validate our methods using synthetic data with additive noise and/or outlier curves. Second, the robust techniques are applied to classifying ARFI displacement profiles acquired in an atherosclerotic familial hypercholesterolemic (FH) pig iliac artery in vivo. The in vivo classification results are compared to parametric ARFI images showing peak induced displacement and time to 67% recovery and to spatially correlated immunohistochemistry. Our results support that robust techniques outperform conventional PCA and clustering approaches to classification when ARFI data is inclusive of low to relatively high noise levels (up to 5dB average SNR to amplitude) but no outliers: for example, 99.53% correct for robust techniques versus 97.75% correct for the classical approach. The robust techniques also perform better than conventional approaches when ARFI data is inclusive of moderately high noise levels (10dB average SNR to amplitude) in addition to a high concentration of outlier displacement profiles (10% outlier content): for example, 99.87% correct for robust techniques versus 33.33% correct for the classical approach. This work suggests that automatic identification of tissue structures exhibiting similar displacement responses to ARFI excitation is possible, even in the context of outlier profiles. Moreover, this work represents an important first step toward automatic correlation of ARFI data to spatially matched immunohistochemistry