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Rehabilitation from musculoskeletal injuries focuses on reestablishing and monitoring muscle activation patterns to accurately produce force. The aim of this study is to explore the use of a novel low-powered wearable distributed Simultaneous Musculoskeletal Assessment with Real-Time Ultrasound (SMART-US) device to predict force during an isometric squat task. Participants (N = 5) performed maximum isometric squats under two medical imaging techniques; clinical musculoskeletal motion mode (m-mode) ultrasound on the dominant vastus lateralis and SMART-US sensors placed on the rectus femoris, vastus lateralis, medial hamstring, and vastus medialis. Ultrasound features were extracted, and a linear ridge regression model was used to predict ground reaction force. The performance of ultrasound features to predict measured force was tested using either the Clinical M-mode, SMART-US sensors on the vastus lateralis (SMART-US: VL), rectus femoris (SMART-US: RF), medial hamstring (SMART-US: MH), and vastus medialis (SMART-US: VMO) or utilized all four SMART-US sensors (Distributed SMART-US). Model training showed that the Clinical M-mode and the Distributed SMART-US model were both significantly different from the SMART-US: VL, SMART-US: MH, SMART-US: RF, and SMART-US: VMO models (p < 0.05). Model validation showed that the Distributed SMART-US model had an R2 of 0.80 ± 0.04 and was significantly different from SMART-US: VL but not from the Clinical M-mode model. In conclusion, a novel wearable distributed SMART-US system can predict ground reaction force using machine learning, demonstrating the feasibility of wearable ultrasound imaging for ground reaction force estimation. [ABSTRACT FROM AUTHOR]

Fluorescence and photoacoustic imaging techniques offer valuable insights into cell- and tissue-level processes. However, these optical imaging modalities are limited by scattering and absorption in tissue, resulting in the low-depth penetration of imaging. Contrast-enhanced imaging in the near-infrared window improves imaging penetration by taking advantage of reduced autofluorescence and scattering effects. Current contrast agents for fluorescence and photoacoustic imaging face several limitations from photostability and targeting specificity, highlighting the need for a novel imaging probe development. This review covers a broad range of near-infrared fluorescent and photoacoustic contrast agents, including organic dyes, polymers, and metallic nanostructures, focusing on their optical properties and applications in cellular and animal imaging. Similarly, we explore encapsulation and functionalization technologies toward building targeted, nanoscale imaging probes. Bioimaging applications such as angiography, tumor imaging, and the tracking of specific cell types are discussed. This review sheds light on recent advancements in fluorescent and photoacoustic nanoprobes in the near-infrared window. It serves as a valuable resource for researchers working in fields of biomedical imaging and nanotechnology, facilitating the development of innovative nanoprobes for improved diagnostic approaches in preclinical healthcare. [ABSTRACT FROM AUTHOR]

In this study, we investigated the performance of four deep learning frameworks of U-Net, U-NeXt, DeepLabV3+, and ConResNet in multi-class pixel-based segmentation of the extraocular muscles (EOMs) from coronal MRI. Performances of the four models were evaluated and compared with the standard F-measure-based metrics of intersection over union (IoU) and Dice, where the U-Net achieved the highest overall IoU and Dice scores of 0.77 and 0.85, respectively. Centroid distance offset between identified and ground truth EOM centroids was measured where U-Net and DeepLabV3+ achieved low offsets (p > 0.05) of 0.33 mm and 0.35 mm, respectively. Our results also demonstrated that segmentation accuracy varies in spatially different image planes. This study systematically compared factors that impact the variability of segmentation and morphometric accuracy of the deep learning models when applied to segmenting EOMs from MRI. [ABSTRACT FROM AUTHOR]

Simulation tools for photoacoustic wave propagation have played a key role in advancing photoacoustic imaging by providing quantitative and qualitative insights into parameters affecting image quality. Classical methods for numerically solving the photoacoustic wave equation rely on a fine discretization of space and can become computationally expensive for large computational grids. In this work, we applied Fourier Neural Operator (FNO) networks as a fast data-driven deep learning method for solving the 2D photoacoustic wave equation in a homogeneous medium. Comparisons between the FNO network and pseudo-spectral time domain approach were made for the forward and adjoint simulations. Results demonstrate that the FNO network generated comparable simulations with small errors and was orders of magnitude faster than the pseudo-spectral time domain methods (~26× faster on a 64 × 64 computational grid and ~15× faster on a 128 × 128 computational grid). Moreover, the FNO network was generalizable to the unseen out-of-domain test set with a root-mean-square error of 9.5 × 10−3 in Shepp–Logan, 1.5 × 10−2 in synthetic vasculature, 1.1 × 10−2 in tumor and 1.9 × 10−2 in Mason-M phantoms on a 64 × 64 computational grid and a root mean squared of 6.9 ± 5.5 × 10−3 in the AWA2 dataset on a 128 × 128 computational grid. [ABSTRACT FROM AUTHOR]

The collapse of transient bubble clouds near a solid surface was investigated to test a scheme for mitigation of cavitation-induced damage. The target was a porous ceramic disk through which air could be forced. Transient cavitation bubbles were created using a shock-wave lithotripter focused on the surface of the disk. The dynamics of bubble clouds near the ceramic disks were studied for two boundary conditions: no back pressure resulting in surface free of bubbles and 10 psi (0. 7 atm) of back pressure, resulting in a surface with a sparse (30% of area) bubble layer. Images of the cavitation near the surface were obtained from a high-speed camera. Additionally, a passive cavitation detector (3.5 MHz focused acoustic transducer) was aligned with the surface. Both the images and the acoustic measurements indicated that bubble clouds near a ceramic face without a bubble layer collapsed onto the boundary, subsequently leading to surface erosion. When asparse bubble layer was introduced, bubble clouds collapsed away from the surface, thus mitigating cavitation damage. The erosion damage to the ceramic disks after 300 shock waves was quantified using micro-CT imaging. Pitting up to 1 mm deep was measured for the bubble-free surface, and the damage to the bubble surface was too small to be detected. [DOI: 10.1115/1.4001552] Keywords: cavitation, cavitation erosion, fluid structure interaction, water hammer

Traditional implanted drug delivery systems cannot easily change their release profile in real time to respond to physiological changes. Here we present a microfluidic aqueous two‐phase system to generate microcapsules that can release drugs on demand as triggered by focused ultrasound (FUS). The biphasic microcapsules are made of hydrogels with an outer phase of mixed molecular weight (MW) poly(ethylene glycol) diacrylate that mitigates premature payload release and an inner phase of high MW dextran with payload that breaks down in response to FUS. Compound release from microcapsules could be triggered as desired; 0.4 μg of payload was released across 16 on‐demand steps over days. We detected broadband acoustic signals amidst low heating, suggesting inertial cavitation as a key mechanism for payload release. Overall, FUS‐responsive microcapsules are a biocompatible and wirelessly triggerable structure for on‐demand drug delivery over days to weeks. [ABSTRACT FROM AUTHOR]

Electrical muscle stimulation (EMS) is widely used in rehabilitation and athletic training to generate involuntary muscle contractions. However, EMS leads to rapid muscle fatigue, limiting the force a muscle can produce during prolonged use. Currently available methods to monitor localized muscle fatigue and recovery are generally not compatible with EMS. The purpose of this study was to examine whether Doppler ultrasound imaging can assess changes in stimulated muscle twitches that are related to muscle fatigue from electrical stimulation. We stimulated five isometric muscle twitches in the medial and lateral gastrocnemius of 13 healthy subjects before and after a fatiguing EMS protocol. Tissue Doppler imaging of the medial gastrocnemius recorded muscle tissue velocities during each twitch. Features of the average muscle tissue velocity waveforms changed immediately after the fatiguing stimulation protocol (peak velocity: -38%, p = .022; time-to-zero velocity: þ8%, p = .050). As the fatigued muscle recovered, the features of the average tissue velocity waveforms showed a return towards their baseline values similar to that of the normalized ankle torque. We also found that features of the average tissue velocity waveform could significantly predict the ankle twitch torque for each participant (R² = 0.255-0.849, p < .001). Our results provide evidence that Doppler ultrasound imaging can detect changes in muscle tissue during isometric muscle twitch that are related to muscle fatigue, fatigue recovery, and the generated joint torque. Tissue Doppler imaging may be a feasible method to monitor localized muscle fatigue during EMS in a wearable device. [ABSTRACT FROM AUTHOR]

Photoacoustic imaging is an emerging imaging modality that is based upon the photoacoustic effect. In photoacoustic tomography (PAT), the induced acoustic pressure waves are measured by an array of detectors and used to reconstruct an image of the initial pressure distribution. A common challenge faced in PAT is that the measured acoustic waves can only be sparsely sampled. Reconstructing sparsely sampled data using standard methods results in severe artifacts that obscure information within the image. We propose a modified convolutional neural network (CNN) architecture termed fully dense UNet (FD-UNet) for removing artifacts from two-dimensional PAT images reconstructed from sparse data and compare the proposed CNN with the standard UNet in terms of reconstructed image quality. [ABSTRACT FROM AUTHOR]

Polymer-shelled micro-bubbles are employed as ultrasound contrast agents (UCAs) and vesicles for targeted drug delivery. UCA-based delivery of the therapeutic payload relies on ultrasound-induced shell rupture. The fragility of two polymer-shelled UCAs manufactured by Point Biomedical or Philips Research was investigated by characterizing their response to static overpressure. The nominal diameters of Point and Philips UCAs were 3 μm and 2 μm, respectively. The UCAs were subjected to static overpressure in a glycerol-filled test chamber with a microscope-reticule lid. UCAs were reconstituted in 0.1 mL of water and added over the glycerol surface in contact with the reticule. A video-microscope imaged UCAs as glycerol was injected (5 mL/h) to vary the pressure from 2 to 180 kPa over 1 h. Neither UCA population responded to overpressure until the rupture threshold was exceeded, which resulted in abrupt destruction. The rupture data for both UCAs indicated three subclasses that exhibited different rupture behavior, although their mean diameters were not statistically different. The rupture pressures provided a measure of UCA fragility; the Philips UCAs were more resilient than Point UCAs. Results were compared to theoretical models of spherical shells under compression. Observed variations in rupture pressures are attributed to shell imperfections. These results may provide means to optimize polymeric UCAs for drug delivery and elucidate associated mechanisms. [ABSTRACT FROM AUTHOR]

Detection of inertial and stable cavitation is important for guiding high-intensity focused ultrasound (HIFU). Acoustic transducers can passively detect broadband noise from inertial cavitation and the scattering of HIFU harmonics from stable cavitation bubbles. Conventional approaches to cavitation noise diagnostics typically involve computing the Fourier transform of the time-domain noise signal, applying a custom comb filter to isolate the frequency components of interest, followed by an inverse Fourier transform. We present an alternative technique based on singular value decomposition (SVD) that efficiently separates the broadband emissions and HIFU harmonics. Spatiotemporally resolved cavitation detection was achieved using a 128-element, 5-MHz linear-array ultrasound imaging system operating in the receive mode at 15 frames/s. A 1.1-MHz transducer delivered HIFU to tissue-mimicking phantoms and excised liver tissue for a duration of 5 s. Beamformed radio frequency signals corresponding to each scan line in a frame were assembled into a matrix, and SVD was performed. Spectra of the singular vectors obtained from a tissue-mimicking gel phantom were analyzed by computing the peak ratio (${R}$), defined as the ratio of the peak of its fifth-order polynomial fit and the maximum spectral peak. Singular vectors that produced an ${R} < 0.048$ were classified as those representing stable cavitation, i.e., predominantly containing harmonics of HIFU. The projection of data onto this singular base reproduced stable cavitation signals. Similarly, singular vectors that produced an ${R} >0.2$ were classified as those predominantly containing broadband noise associated with inertial cavitation. These singular vectors were used to isolate the inertial cavitation signal. The ${R}$ -value thresholds determined using gel data were then employed to analyze cavitation data obtained from bovine liver ex vivo. The SVD-based method faithfully reproduced the structural details in the spatiotemporal cavitation maps produced using the more cumbersome comb-filter approach with a maximum root-mean-squared error of 10%. [ABSTRACT FROM AUTHOR]

A frequency‐domain, non‐contact approach to photoacoustic microscopy (PAM) that employs amplitude‐modulated (0.1–1 MHz) laser for excitation (638‐nm pump) in conjunction with a 2‐wave mixing interferometer (532‐nm probe) for non‐contact detection of photoacoustic waves at the specimen surface is presented. A lock‐in amplifier is employed to detect the photoacoustic signal. Illustrative images of tissue‐mimicking phantoms, red‐blood cells and retinal vasculature are presented. Single‐frequency modulation of the pump beam directly provides an image that is equivalent to the 2‐dimensional projection of the image volume. Targets located superficially produce phase modulations in the surface‐reflected probe beam due to surface vibrations as well as direct intensity modulation in the backscattered probe light due to local changes in pressure and/or temperature. In comparison, the observed modulations in the probe beam due to targets located deeper in the specimen, for example, beyond the ballistic photon regime, predominantly consist of phase modulation. [ABSTRACT FROM AUTHOR]

The subharmonic threshold for ultrasound contrast agents has been defined as a 20–25 dB difference between the fundamental and subharmonic (2/1) spectral components of the backscatter signal. However, this Fourier-based criterion assumes a linear time-invariant signal. A more appropriate criterion for short cycle and frequency-modulated waveforms is proposed with an adaptive signal-processing approach based on the empirical mode decomposition (EMD) method. The signal is decomposed into an orthogonal basis known as intrinsic mode functions (IMFs) and a subharmonic threshold is defined with respect to the energy ratio of the subharmonic IMF component to that of the incident signal. The method is applied to backscatter data acquired from two polymer-shelled contrast agents, Philips (#38, mean diameter 2.0 \mu \textm ) and Point Biomedical (#12027, mean diameter 3.9 \mu \textm ). The acoustic backscatter signals are investigated for a single contrast agent subjected to monofrequency (20 MHz, 20 cycles) and chirp (15–25 MHz, 20 cycles) forcing for incident pressures ranging from 0.5 to 2.4 MPa. In comparison to the spectral peak difference (20 dB) criterion, the EMD method is more sensitive in determining subharmonic signals. [ABSTRACT FROM PUBLISHER]

This paper presents a combined ultrasound and photoacoustic (PA) imaging (PAI) system used to obtain high-quality, co-registered images of mouse-embryo anatomy and vasculature. High-frequency ultrasound (HFU, >20 MHz) is utilized to obtain high-resolution anatomical images of small animals while PAI provides high-contrast images of the vascular network. The imaging system is based on a 40 MHz, 5-element, 6 mm aperture annular-array transducer with a 800 μm diameter hole through its central element. The transducer was integrated in a cage-plate assembly allowing for a collimated laser beam to pass through the hole so that the optical and acoustic beams were collinear. The assembly was mounted on a two-axis, motorized stage to enable the simultaneous acquisition of co-registered HFU and PA volumetric data. Data were collected from all five elements in receive and a synthetic-focusing algorithm was applied in post-processing to beamform the data and increase the spatial resolution and depth-of-field (DOF) of the HFU and PA images. Phantom measurements showed that the system could achieve high-resolution images (down to 90 μm for HFU and 150 μm for PAI) and a large DOF of >8 mm. Volume renderings of a mouse embryo showed that the scanner allowed for visualizing morphologically precise anatomy of the entire embryo along with corresponding co-registered vasculature. Major head vessels, such as the superior sagittal sinus or rostral vein, were clearly identified as well as limb bud vasculature. [ABSTRACT FROM AUTHOR]

The Oak Ridge National Laboratory Spallation Neutron Source employs a high-energy pulsed proton beam incident on a mercury target to generate short bursts of neutrons. Absorption of the proton beam produces rapid heating of the mercury, resulting in the formation of acoustic shock waves and the nucleation of cavitation bubbles. The subsequent collapse of these cavitation bubbles promote erosion of the steel target walls. Preliminary measurements using two passive cavitation detectors (megahertz-frequency focused and unfocused piezoelectric transducers) installed in a mercury test target to monitor cavitation generated by proton beams with charges ranging from 0.041 to 4.1 μC will be reported on. Cavitation was initially detected for a beam charge of 0.082 μC by the presence of an acoustic emission approximately 250 μs after arrival of the incident proton beam. This emission was consistent with an inertial cavitation collapse of a bubble with an estimated maximum bubble radius of 0.19 mm, based on collapse time. The peak pressure in the mercury for the initiation of cavitation was predicted to be 0.6 MPa. For a beam charge of 0.41 μC and higher, the lifetimes of the bubbles exceeded the reverberation time of the chamber (∼300 μs), and distinct windows of cavitation activity were detected, a phenomenon that likely resulted from the interaction of the reverberation in the chamber and the cavitation bubbles. [ABSTRACT FROM AUTHOR]

A method for producing a prescribed acoustic pressure field from a piezoelectric array was investigated. The array consisted of 170 elements placed on the inner surface of a 15 cm radius spherical cap. Each element was independently driven by using individual pulsers each capable of generating 1.2 kV. Acoustic field customization was achieved by independently controlling the time when each element was excited. The set of time delays necessary to produce a particular acoustic field was determined by using an optimization scheme. The acoustic field at the focal plane was simulated by using the angular spectrum method, and the optimization searched for the time delays that minimized the least squared difference between the magnitudes of the simulated and desired pressure fields. The acoustic field was shaped in two different ways: the -6 dB focal width was increased to different desired widths and the ring-shaped pressure distributions of various prescribed diameters were produced. For both cases, the set of delays resulting from the respective optimization schemes were confirmed to yield the desired pressure distributions by using simulations and measurements. The simulations, however, predicted peak positive pressures roughly half those obtained from the measurements, which was attributed to the exclusion of nonlinearity in the simulations. [ABSTRACT FROM AUTHOR]

Measurements are presented of acoustic emissions from cavitation collapses on the surface of a synthetic kidney stone in response to shock waves (SWs) from an electrohydraulic lithotripter. A fiber optic probe hydrophone was used for pressure measurements, and passive cavitation detection was used to identify acoustic emissions from bubble collapse. At a lithotripter charging voltage of 20 kV, the focused SW incident on the stone surface resulted in a peak pressure of 43±6 MPa compared to 23±4 MPa in the free field. The focused SW incident upon the stone appeared to be enhanced due to the acoustic emissions from the forced cavitation collapse of the preexisting bubbles. The peak pressure of the acoustic emission from a bubble collapse was 34±15 MPa, that is, the same magnitude as the SWs incident on the stone. These data indicate that stresses induced by focused SWs and cavitation collapses are similar in magnitude thus likely play a similar role in stone fragmentation. [ABSTRACT FROM AUTHOR]