Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This paper aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane-wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high-frame-rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this paper, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation, and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-sectional profile with full-width at half-maximum of 57 μm could be imaged at approximately 2-cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ~200 μm). Cortical microvessels that are 76 μm apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

Our preliminary results suggest that Voigt elasticity and viscosity measured between 95 Hz and 380 Hz by using shear wave dispersion ultrasound vibrometry (SDUV) are correlated and that the use of ... PurposeTo investigate the value of viscosity measured with ultrasonographic (US) elastography in liver fibrosis staging and to determine whether the use of a viscoelastic model to estimate liver el...

Fast and accurate tissue elasticity imaging is essential in studying dynamic tissue mechanical properties. Various ultrasound shear elasticity imaging techniques have been developed in the last two decades. However, to reconstruct a full field-of-view 2-D shear elasticity map, multiple data acquisitions are typically required. In this paper, a novel shear elasticity imaging technique, comb-push ultrasound shear elastography (CUSE), is introduced in which only one rapid data acquisition (less than 35 ms) is needed to reconstruct a full field-of-view 2-D shear wave speed map (40 × 38 mm). Multiple unfocused ultrasound beams arranged in a comb pattern (comb-push) are used to generate shear waves. A directional filter is then applied upon the shear wave field to extract the left-to-right (LR) and right-to-left (RL) propagating shear waves. Local shear wave speed is recovered using a time-of-flight method based on both LR and RL waves. Finally, a 2-D shear wave speed map is reconstructed by combining the LR and RL speed maps. Smooth and accurate shear wave speed maps are reconstructed using the proposed CUSE method in two calibrated homogeneous phantoms with different moduli. Inclusion phantom experiments demonstrate that CUSE is capable of providing good contrast (contrast-to-noise ratio ≥25 dB) between the inclusion and background without artifacts and is insensitive to inclusion positions. Safety measurements demonstrate that all regulated parameters of the ultrasound output level used in CUSE sequence are well below the FDA limits for diagnostic ultrasound.

Non-invasive detection of microvascular alterations in deep tissues in vivo provides critical information for clinical diagnosis and evaluation of a broad-spectrum of pathologies. Recently, the emergence of super-resolution ultrasound localization microscopy (ULM) offers new possibilities for clinical imaging of microvasculature at capillary level. Currently, the clinical utility of ULM on clinical ultrasound scanners is hindered by the technical limitations, such as long data acquisition time, high microbubble (MB) concentration, and compromised tracking performance associated with low imaging frame-rate. Here we present a robust in-human ULM on a high frame-rate (HFR) clinical ultrasound scanner to achieve super-resolution microvessel imaging using a short acquisition time (<10 s). Ultrasound MB data were acquired from different human tissues, including a healthy liver and a diseased liver with acute-on-chronic liver failure, a kidney, a pancreatic tumor, and a breast mass using an HFR clinical scanner. By leveraging the HFR and advanced processing techniques including sub-pixel motion registration, MB signal separation, and Kalman filter-based tracking, MBs can be robustly localized and tracked for ULM under the circumstances of relatively high MB concentration associated with standard clinical MB administration and limited data acquisition time in humans. Subtle morphological and hemodynamic information in microvasculature were shown based on data acquired with single breath-hold and free-hand scanning. Compared with contrast-enhanced power Doppler generated based on the same MB dataset, ULM showed a 5.7-fold resolution improvement in a vessel based on a linear transducer, and provided a wide-range blood flow speed measurement that is Doppler angle-independent. Microvasculatures with complex hemodynamics can be well-differentiated at super-resolution in both normal and pathological tissues. This preliminary study implemented the ultrafast in-human ULM in various human tissues based on a clinical scanner that supports HFR imaging, indicating the potentials of the technique for various clinical applications. However, rigorous validation of the technique in imaging human microvasculature (especially for those tiny vessel structure), preferably with a gold standard, is still required.

Super-resolution ultrasound localization microscopy (ULM), based on localization and tracking of individual microbubbles (MBs), offers unprecedented microvascular imaging resolution at clinically relevant penetration depths. However, ULM is currently limited by the requirement of dilute MB concentrations to ensure spatially sparse MB events for accurate localization and tracking. The corresponding long imaging acquisition times (tens of seconds or several minutes) to accumulate sufficient isolated MB events for full reconstruction of microvasculature preclude the clinical translation of the technique. To break this fundamental tradeoff between acquisition time and MB concentration, in this paper we propose to separate spatially overlapping MB events into sub-populations, each with sparser MB concentration, based on spatiotemporal differences in the flow dynamics (flow speeds and directions). MB localization and tracking are performed for each sub-population separately, permitting more robust ULM imaging of high-concentration MB injections. The superiority of the proposed MB separation technique over conventional ULM processing is demonstrated in flow channel phantom data, and in the chorioallantoic membrane of chicken embryos with optical imaging as an in vivo reference standard. Substantial improvement of ULM is further demonstrated on a chicken embryo tumor xenograft model and a chicken brain, showing both morphological and functional microvasculature details at super-resolution within a short acquisition time (several seconds). The proposed technique allows more robust MB localization and tracking at relatively high MB concentrations, alleviating the need for dilute MB injections, and thereby shortening the acquisition time of ULM imaging and showing great potential for clinical translation.

Contrast microbubble (MB)-based super-resolution ultrasound microvessel imaging (SR-UMI) overcomes the compromise in conventional ultrasound imaging between spatial resolution and penetration depth and has been successfully applied to a wide range of clinical applications. However, clinical translation of SR-UMI remains challenging due to the limited number of MBs detected within a given accumulation time. Here, we propose a Kalman filter-based method for robust MB tracking and improved blood flow speed measurement with reduced numbers of MBs. An acceleration constraint and a direction constraint for MB movement were developed to control the quality of the estimated MB trajectory. An adaptive interpolation approach was developed to inpaint the missing microvessel signal based on the estimated local blood flow speed, facilitating more robust depiction of microvasculature with a limited amount of MBs. The proposed method was validated on an ex ovo chorioallantoic membrane and an in vivo rabbit kidney. Results demonstrated improved imaging performance on both microvessel density maps and blood flow speed maps. With the proposed method, the percentage of microvessel filling in a selected blood vessel at a given accumulation period was increased from 28.17% to 74.45%. A similar SR-UMI performance was achieved with MB numbers reduced by 85.96%, compared to that with the original MB number. The results indicate that the proposed method substantially improves the robustness of SR-UMI under a clinically relevant imaging scenario where SR-UMI is challenged by a limited MB accumulation time, reduced number of MBs, lowered imaging frame rate, and degraded signal-to-noise ratio.