Shear wave elastography is emerging as a clinically valuable diagnostic tool to differentiate between benign and malignant breast masses. Elastography techniques assume that soft tissue can be modelled as a purely elastic medium. However, this assumption is often violated as soft tissue exhibits viscoelastic properties. In order to explore the role of viscoelastic parameters in suspicious breast masses, a study was conducted on a group of patients using shear wave dispersion ultrasound vibrometry in the frequency range of 50–400 Hz. A total of 43 female patients with suspicious breast masses were recruited before their scheduled biopsy. Of those, 15 patients did not meet the data selection criteria. Voigt model based shear elasticity showed a significantly (p = 7.88x10^-6) higher median value for the 13 malignant masses (16.76±13.10 kPa) compared to 15 benign masses (1.40±1.12 kPa). Voigt model based shear viscosity was significantly different (p = 4.13x10^-5) between malignant (8.22±3.36 Pa-s) and benign masses (2.83±1.47 Pa-s). Moreover, the estimated time constant from the Voigt model, which is dependent on both shear elasticity and viscosity, differed significantly (p = 6.13x10^-5) between malignant (0.68±0.33 ms) and benign masses (3.05±1.95 ms). Results suggest that besides elasticity, viscosity based parameters like shear viscosity and time constant can also be used to differentiate between malignant and benign breast masses.

The paper presents the design and validation of body-conformal active ultrasound patches with integrated imaging and modulation modalities for image-guided neural therapy. A mechanically-flexible linear 64-element array of piezoelectric transducers with a resonance frequency of 5 MHz was designed for nerve localization. A second 8-element array using larger elements was integrated on the wearable probe for low intensity focused ultrasound neuromodulation at a resonance frequency of 1.3 MHz. Full-wave simulations were used to model the flexible arrays and estimate their generated pressure profiles. A focal depth of 10-20 mm was assumed for beamforming and focusing to support modulation of the vagus, tibial, and other nerves. A strain sensor integrated on the probe provides patient-specific feedback information on array curvature for real-time optimization of focusing and image processing. Each patch also includes high voltage (HV) multiplexers, transmit/receive switches, and pre-amplifiers that simplify connectivity and also improve the signal-to-noise ratio (SNR) of the received echo signals by ∼5 dB. Experimental results from a flexible prototype show a sensitivity of 80 kPa/V with ∼3 MHz bandwidth for the modulation and 20 kPa/V with ∼6 MHz bandwidth for the imaging array. An algorithm for accurate and automatic localization of targeted nerves based on using nearby blood vessels (e.g., the carotid artery) as image markers is also presented.

Objective: Recent advances in ultrasound Doppler imaging have made it possible to visualize small vessels with diameters near the imaging resolution limits using spatiotemporal singular value thresholding of long ensembles of ultrasound data. However, vessel images derived based on this method present severe intensity variations and additional background noise that limits visibility and subsequent processing such as centerline extraction and morphological analysis. The goal of this paper is to devise a method to enhance vessel-background separation directly on the power Doppler images by exploiting blood echo-noise independence. Method: We present a two-step algorithm to mitigate these adverse effects when using singular value thresholding for obtaining gross vasculature images. Our method comprises a morphological-based filtering for removing global and local background signals and a multiscale Hessian-based vessel enhancement filtering to further improve the vascular structures. We applied our method for in vivo imaging of the microvasculature of kidney in one healthy subject, liver in five healthy subjects, thyroid nodules in five patients, and breast tumors in five patients. Results: Singular value thresholding, top-hat filtering, and Hessian-based vessel enhancement filtering each provided an average peak-to-side level gain of 1.11, 18.55, and 2.26 dB, respectively, resulting in an overall gain of 21.92 dB when compared to the conventional power Doppler imaging using infinite impulse response filtering. Conclusion: Singular value thresholding combined with morphological and Hessian-based vessel enhancement filtering provides a powerful tool for visualization of the deep-seated small vessels using long ultrasound echo ensembles without requiring any type of contrast enhancing agents. Significance: This method provides a fast and cost-effective modality for in vivo assessment of the microvasculature suitable for both clinical and preclinical applications.

Lesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses. With written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19–85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young’s modulus. In correlation to pathology results, statistical analyses were performed. Pathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21). CUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness.

The objective of this study is to assess correlation between bladder wall mechanical properties obtained by ultrasound bladder vibrometry (UBV) and urodynamic study (UDS) measurements in a group of patients undergoing clinical UDS procedure. Concurrent UBV and UDS were performed on 70 patients with neurogenic bladders (56 male and 14 female). Bladder wall mechanical properties measured by UBV at different filling volumes were correlated with recorded detrusor pressure (Pdet) values. Mean, median and standard deviation of correlation values were calculated and the significance of these observations was tested. Bladder wall mechanical properties obtained by UBV as group velocity squared and elasticity showed high correlations with Pdet measured at different volumes (median correlation 0.73, CI: 0.64–0.80 and 0.72, CI: 0.56–0.82 respectively). The correlation of group velocity squared and elasticity with Pdet were both significantly higher than 0.5. The results of this study suggest that UBV can closely monitor changes in bladder wall mechanical properties at different volumes in a group of patients undergoing UDS. The high correlation between UBV parameters and detrusor pressure measurements suggests that UBV can be utilized as a reliable and cost-effective tool for assessment of the bladder wall mechanical changes in a noninvasive fashion.

Real-time ultrasound thermography has been recently demonstrated on commercially available diagnostic imaging probes. In vitro experimental results demonstrate high sensitivity to small, localized temperature changes induced by subtherapeutic focused ultrasound. Most of the published results, however, are based on a thermally induced echo strain model that assumes infinitesimal change in temperature between imaging frames. Under this assumption, the echo strain is computed using a low-pass axial differentiator, which is implemented by a finite-impulse response digital filter. In this paper, we introduce a new model for temperature estimation, which employs a recursive axial filter that acts as a spatial differentiator-integrator of echo shifts. The filter is derived from first principles and it accounts for a nonuniform temperature baseline, when computing the spatial temperature change between two frames. This is a major difference from the previously proposed infinitesimal echo strain filter (δ-ESF) approach. We show that the new approach can be implemented by a first-order infinite-impulse response digital filter with depth-dependent spatial frequency response. Experimental results in vitro demonstrate the advantages over the δ-ESF approach in terms of suppressing the spatial variations in the estimated temperature without resorting to ad hoc low-pass filtering of echo strains. The performance of the new recursive echo strain filter (RESF) is also illustrated using echo data obtained during subtherapeutic localized heating in the hind limb of Copenhagen rat in vivo. In addition to the RESF, we have used an adaptive spatial filter to remove motion and deformation artifacts during real-time data collection. The adaptive filtering algorithm is described and comparisons with uncompensated estimated spatio-temporal temperature profiles are given. The results demonstrate the feasibility of in vivo ultrasound thermography with high sensitivity and specificity.