Multiplex Ultrasound Imaging of Perfluorocarbon Nanodroplets Enabled by Decomposition of Postvaporization Dynamics.

Despite the real-time, nonionizing, and cost-effective nature of ultrasound imaging, there is a dearth of methods to visualize two or more populations of contrast agents simultaneously─a technique known as multiplex imaging. Here, we present a new approach to multiplex ultrasound imaging using perfluorocarbon (PFC) nanodroplets. The nanodroplets, which undergo a liquid-to-gas phase transition in response to an acoustic trigger, act as activatable contrast agents. This work characterized the dynamic responses of two PFC nanodroplets with boiling points of 28 and 56 °C. These characteristic responses were then used to demonstrate that the relative concentrations of the two populations of PFC nanodroplets could be accurately measured in the same imaging volume within an average error of 1.1%. Overall, the findings indicate the potential of this approach for multiplex ultrasound imaging, allowing for the simultaneous visualization of multiple molecular targets simultaneously.

Fluorescent Phase-Changing Perfluorocarbon Nanodroplets as Activatable Near-Infrared Probes.

The sensitivity of fluorescence imaging is limited by the high optical scattering of tissue. One approach to improve sensitivity to small signals is to use a contrast agent with a signal that can be externally modulated. In this work, we present a new phase-changing perfluorocarbon nanodroplet contrast agent loaded with DiR dye. The nanodroplets undergo a liquid-to-gas phase transition when exposed to an externally applied laser pulse. This results in the unquenching of the encapsulated dye, thus increasing the fluorescent signal, a phenomenon that can be characterized by an ON/OFF ratio between the fluorescence of activated and nonactivated nanodroplets, respectively. We investigate and optimize the quenching/unquenching of DiR upon nanodroplets' vaporization in suspension, tissue-mimicking phantoms and a subcutaneous injection mouse model. We also demonstrate that the vaporized nanodroplets produce ultrasound contrast, enabling multimodal imaging. This work shows that these nanodroplets could be applied to imaging applications where high sensitivity is required.

Two-step training deep learning framework for computational imaging without physics priors.

Deep learning (DL) is a powerful tool in computational imaging for many applications. A common strategy is to use a preprocessor to reconstruct a preliminary image as the input to a neural network to achieve an optimized image. Usually, the preprocessor incorporates knowledge of the physics priors in the imaging model. One outstanding challenge, however, is errors that arise from imperfections in the assumed model. Model mismatches degrade the quality of the preliminary image and therefore affect the DL predictions. Another main challenge is that many imaging inverse problems are ill-posed and the networks are over-parameterized; DL networks have flexibility to extract features from the data that are not directly related to the imaging model. This can lead to suboptimal training and poorer image reconstruction results. To solve these challenges, a two-step training DL (TST-DL) framework is proposed for computational imaging without physics priors. First, a single fully-connected layer (FCL) is trained to directly learn the inverse model with the raw measurement data as the inputs and the images as the outputs. Then, this pre-trained FCL is fixed and concatenated with an un-trained deep convolutional network with a U-Net architecture for a second-step training to optimize the output image. This approach has the advantage that does not rely on an accurate representation of the imaging physics since the first-step training directly learns the inverse model. Furthermore, the TST-DL approach mitigates network over-parameterization by separately training the FCL and U-Net. We demonstrate this framework using a linear single-pixel camera imaging model. The results are quantitatively compared with those from other frameworks. The TST-DL approach is shown to perform comparable to approaches which incorporate perfect knowledge of the imaging model, to be robust to noise and model ill-posedness, and to be more robust to model mismatch than approaches which incorporate imperfect knowledge of the imaging model. Furthermore, TST-DL yields better results than end-to-end training while suffering from less overfitting. Overall, this TST-DL framework is a flexible approach for image reconstruction without physics priors, applicable to diverse computational imaging systems.

Compressed ultrafast tomographic imaging by passive spatiotemporal projections.

Existing streak-camera-based two-dimensional (2D) ultrafast imaging techniques are limited by long acquisition time, the trade-off between spatial and temporal resolutions, and a reduced field of view. They also require additional components, customization, or active illumination. Here we develop compressed ultrafast tomographic imaging (CUTI), which passively records 2D transient events with a standard streak camera. By grafting the concept of computed tomography to the spatiotemporal domain, the operations of temporal shearing and spatiotemporal integration in a streak camera's data acquisition can be equivalently expressed as the spatiotemporal projection of an (x,y,t) datacube from a certain angle. Aided by a new, to the best of our knowledge, compressed-sensing reconstruction algorithm, the 2D transient event can be accurately recovered in a few measurements. CUTI is exhibited as a new imaging mode universally adaptable to most streak cameras. Implemented in an image-converter streak camera, CUTI captures the sequential arrival of two spatially modulated ultrashort ultraviolet laser pulses at 0.5 trillion frames per second. Applied to a rotating-mirror streak camera, CUTI records an amination of fast-bouncing balls at 5,000 frames per second.

Super-Resolution Ultrasound Imaging in Vivo with Transient Laser-Activated Nanodroplets.

We have developed a method for super-resolution ultrasound imaging, which relies on a new class of blinking nanometer-size contrast agents: laser-activated nanodroplets (LANDs). The LANDs can be repeatedly optically triggered to undergo vaporization; the resulting spatially stationary, temporally transient microbubbles provide high ultrasound contrast for several to hundreds of milliseconds before recondensing to their native liquid nanodroplet state. By capturing high frame rate ultrasound images of blinking LANDs, we demonstrate the ability to detect individual recondensation events. Then we apply a newly developed super-resolution image processing algorithm to localize the LAND positions in vivo almost an order of magnitude better than conventional ultrasound imaging. These results pave the way for high resolution molecular imaging deep in tissue.

Label-free Detection of Lymph Node Metastases with US-guided Functional Photoacoustic Imaging.

PURPOSE: To determine the ability of ultrasonography (US)-guided spectroscopic photoacoustic (sPA) imaging to depict changes in blood oxygen saturation (SO2) in metastatic lymph nodes of a mouse model of oral cancer. MATERIALS AND METHODS: All studies were performed by following protocols approved by the institutional animal care and use committee at the University of Texas at Austin. Coregistered US and photoacoustic images were acquired spanning volumes containing a total of 31 lymph nodes in 17 female nu/nu mice. The mice were either healthy (three mice, five nodes) or bearing a primary tumor consisting of luciferase-labeled FaDu cells (14 mice, 26 nodes). Ten photoacoustic images acquired with optical wavelengths spanning from 680 to 860 nm were spectrally unmixed by using a linear least-squares method to obtain sPA images. After imaging, histologic analysis enabled confirmation of the presence of micrometastases. Generalized estimating equations were used to compare metastatic and normal lymph nodes, with a P value of .05 taken to indicate a significant difference. Sensitivity and specificity were determined with a receiver operator characteristic curve constructed from the background-subtracted SO2 values. RESULTS: Metastatic lymph nodes (n = 7) exhibited a significantly (P = .018) lower spatially averaged background-subtracted SO2 (mean, 5.4% ± 3.5 [standard error]) when compared with lymph nodes without metastases (mean, 13.7% ± 1.3; n = 24). This effect was observed throughout the entire volume of the nodes rather than being limited to the metastatic foci. The change in SO2, which was inversely related to the size of the metastasis, was detectable in metastases as small as 2.6 × 10(-3) mm(3). CONCLUSION: The results show that US-guided sPA imaging is capable of depicting changes in SO2 in lymph nodes that were correlated with metastatic invasion.

Optimization of in vivo spectroscopic photoacoustic imaging by smart optical wavelength selection.

Spectroscopic photoacoustic (sPA) imaging is an emerging biomedical imaging modality which can be used to simultaneously identify multiple optical absorbers in tissue. With current technology, the image acquisition time is limited primarily by the laser repetition rate, and sPA image acquisition can take seconds to minutes, depending on the system and imaging volume. We have developed an algorithm that can be used to eliminate extraneous wavelengths and decrease image acquisition time while maintaining image quality. Here, we show the effect the wavelength selection has on in vivo sPA imaging. As an example, dye draining to the lymph node of a mouse was imaged. We demonstrate that sPA image quality is more accurately preserved when wavelengths are chosen based on the spectral features of the absorbers compared to often-used selection of evenly spaced wavelengths. In fact, only three wavelengths are needed to accurately spectrally unmix the dye from oxygenated and deoxygenated hemoglobin.

Joint segmentation and image reconstruction with error prediction in photoacoustic imaging using deep learning.

Deep learning has been used to improve photoacoustic (PA) image reconstruction. One major challenge is that errors cannot be quantified to validate predictions when ground truth is unknown. Validation is key to quantitative applications, especially using limited-bandwidth ultrasonic linear detector arrays. Here, we propose a hybrid Bayesian convolutional neural network (Hybrid-BCNN) to jointly predict PA image and segmentation with error (uncertainty) predictions. Each output pixel represents a probability distribution where error can be quantified. The Hybrid-BCNN was trained with simulated PA data and applied to both simulations and experiments. Due to the sparsity of PA images, segmentation focuses Hybrid-BCNN on minimizing the loss function in regions with PA signals for better predictions. The results show that accurate PA segmentations and images are obtained, and error predictions are highly statistically correlated to actual errors. To leverage error predictions, confidence processing created PA images above a specific confidence level.

Silica-coated gold nanoplates as stable photoacoustic contrast agents for sentinel lymph node imaging.

A biopsy of the first lymph node to which a tumor drains-the sentinel lymph node (SLN)-is commonly performed to identify micrometastases. Image guidance of the SLN biopsy procedure has the potential to improve its accuracy and decrease its morbidity. We have developed a new stable contrast agent for photoacoustic image-guided SLN biopsy: silica-coated gold nanoplates (Si-AuNPs). The Si-AuNPs exhibit high photothermal stability when exposed to pulsed and continuous wave laser irradiation. This makes them well suited for in vivo photoacoustic imaging. Furthermore, Si-AuNPs are shown to have low cytotoxicity. We tested the Si-AuNPs for SLN mapping in a mouse model where they exhibited a strong, sustained photoacoustic signal. Real-time ultrasound and photoacoustic imaging revealed that the Si-AuNPs quickly drain to the SLN, gradually spreading throughout a large portion of the node.

Dual-drug loaded ultrasound-responsive nanodroplets for on-demand combination chemotherapy.

Phase-changing nanodroplets are nanometric sized constructs that can be vaporized via external stimuli, such as focused ultrasound, to generate gaseous bubbles that are visible in ultrasound. Their activation can also be leveraged to release their payload, creating a method for ultrasound-modulated localized drug delivery. Here, we develop a perfluoropentane core nanodroplet that can simultaneously load paclitaxel and doxorubicin, and release them in response to an acoustic trigger. A double emulsion method is used to incorporate the two drugs with different physio-chemical properties, which allows for a combinatorial chemotherapy regimen to be used. Their loading, release, and biological effects on a triple negative breast cancer mouse model are investigated. We show that activation enhances the drug-delivery effect and delays the tumor growth rate in vivo. Overall, the phase-changing nanodroplets are a useful platform to allow on-demand delivery of combinations of drugs.

Approximating the uncertainty of deep learning reconstruction predictions in single-pixel imaging.

Single-pixel imaging (SPI) has the advantages of high-speed acquisition over a broad wavelength range and system compactness. Deep learning (DL) is a powerful tool that can achieve higher image quality than conventional reconstruction approaches. Here, we propose a Bayesian convolutional neural network (BCNN) to approximate the uncertainty of the DL predictions in SPI. Each pixel in the predicted image represents a probability distribution rather than an image intensity value, indicating the uncertainty of the prediction. We show that the BCNN uncertainty predictions are correlated to the reconstruction errors. When the BCNN is trained and used in practical applications where the ground truths are unknown, the level of the predicted uncertainty can help to determine whether system, data, or network adjustments are needed. Overall, the proposed BCNN can provide a reliable tool to indicate the confidence levels of DL predictions as well as the quality of the model and dataset for many applications of SPI.

Focused ultrasound stimulation of an ex-vivo Aplysia abdominal ganglion preparation.

BACKGROUND: A growing body of research demonstrates that focused ultrasound stimulates activity in human and other mammalian nervous systems. However, there is no consensus on which sonication parameters are optimal. Furthermore, the mechanism of action behind ultrasound neurostimulation remains poorly understood. An invertebrate model greatly reduces biological complexity, permitting a systematic evaluation of sonication parameters suitable for ultrasound neurostimulation. NEW METHOD: Here, we describe the use of focused ultrasound stimulation with an ex-vivo abdominal ganglion preparation of the California sea hare, Aplysia californica, a long-standing model system in neurobiology. We developed a system for stimulating an isolated ganglion preparation while obtaining extracellular recordings from nerves. The focused ultrasound stimulation uses one of two single-element transducers, enabling stimulation at four distinct carrier frequencies (0.515 MHz, 1.l MHz, 1.61 MHz, 3.41 MHz). RESULTS: Using continuous wave ultrasound, we stimulated the ganglion at all four frequencies, and we present quantitative evaluation of elicited activation at four different sonication durations and three peak pressure levels, eliciting up to a 57-fold increase in spiking frequency. COMPARISON WITH ELECTRICAL STIMULATION: We demonstrated that ultrasound-induced activation is repeatable, and the response consistency is comparable to electrical stimulation. CONCLUSIONS: Due to the relative ease of long-term recordings for many hours, this ex-vivo ganglion preparation is suitable for investigating sonication parameters and the effects of focused ultrasound stimulation on neurons.

EGFR-Targeted Perfluorohexane Nanodroplets for Molecular Ultrasound Imaging.

Perfluorocarbon nanodroplets offer an alternative to gaseous microbubbles as contrast agents for ultrasound imaging. They can be acoustically activated to induce a liquid-to-gas phase transition and provide contrast in ultrasound images. In this study, we demonstrate a new strategy to synthesize antibody-conjugated perfluorohexane nanodroplet (PFHnD-Ab) ultrasound contrast agents that target cells overexpressing the epidermal growth factor receptor (EGFR). The perfluorohexane nanodroplets (PFHnD) containing a lipophilic DiD fluorescent dye were synthesized using a phospholipid shell. Antibodies were conjugated to the surface through a hydrazide-aldehyde reaction. Cellular binding was confirmed using fluorescence microscopy; the DiD fluorescence signal of the PFHnD-Ab was 5.63× and 6× greater than the fluorescence signal in the case of non-targeted PFHnDs and the EGFR blocking control, respectively. Cells were imaged in tissue-mimicking phantoms using a custom ultrasound imaging setup consisting of a high-intensity focused ultrasound transducer and linear array imaging transducer. Cells with conjugated PFHnD-Abs exhibited a significantly higher (p < 0.001) increase in ultrasound amplitude compared to cells with non-targeted PFHnDs and cells exposed to free antibody before the addition of PFHnD-Abs. The developed nanodroplets show potential to augment the use of ultrasound in molecular imaging cancer diagnostics.

Sparsity-Based Recovery of Three-Dimensional Photoacoustic Images from Compressed Single-Shot Optical Detection.

Photoacoustic (PA) imaging combines optical excitation with ultrasonic detection to achieve high-resolution imaging of biological samples. A high-energy pulsed laser is often used for imaging at multi-centimeter depths in tissue. These lasers typically have a low pulse repetition rate, so to acquire images in real-time, only one pulse of the laser can be used per image. This single pulse necessitates the use of many individual detectors and receive electronics to adequately record the resulting acoustic waves and form an image. Such requirements make many PA imaging systems both costly and complex. This investigation proposes and models a method of volumetric PA imaging using a state-of-the-art compressed sensing approach to achieve real-time acquisition of the initial pressure distribution (IPD) at a reduced level of cost and complexity. In particular, a single exposure of an optical image sensor is used to capture an entire Fabry-Pérot interferometric acoustic sensor. Time resolved encoding as achieved through spatial sweeping with a galvanometer. This optical system further makes use of a random binary mask to set a predetermined subset of pixels to zero, thus enabling recovery of the time-resolved signals. The Two-Step Iterative Shrinking and Thresholding algorithm is used to reconstruct the IPD, harnessing the sparsity naturally occurring in the IPD as well as the additional structure provided by the binary mask. We conduct experiments on simulated data and analyze the performance of our new approach.

Repeated Acoustic Vaporization of Perfluorohexane Nanodroplets for Contrast-Enhanced Ultrasound Imaging.

Superheated perfluorocarbon nanodroplets are emerging ultrasound imaging contrast agents that boast biocompatible components, unique phase-change dynamics, and therapeutic loading capabilities. Upon exposure to a sufficiently high-intensity pulse of acoustic energy, the nanodroplet's perfluorocarbon core undergoes a liquid-to-gas phase change and becomes an echogenic microbubble, providing ultrasound contrast. The controllable activation leads to high-contrast images, while the small size of the nanodroplets promotes longer circulation times and better in vivo stability. One drawback, however, is that the nanodroplets can only be vaporized a single time, limiting their versatility. Recently, we and others have addressed this issue by using a perfluorohexane core, which has a boiling point above body temperature. Thus after vaporization, the microbubbles recondense back into their stable nanodroplet form. Previous work with perfluorohexane nanodroplets relied on optical activation via pulsed laser absorption of an encapsulated dye. This strategy limits the imaging depth and temporal resolution of the method. In this study, we overcome these limitations by demonstrating acoustic droplet vaporization with 1.1-MHz high-intensity focused ultrasound (HIFU). A short-duration, high-amplitude pulse of focused ultrasound provides a sufficiently strong peak negative pressure to initiate vaporization. A custom imaging sequence was developed to enable the synchronization of a HIFU transducer and a linear array imaging transducer. We show a visualization of repeated acoustic activation of perfluorohexane nanodroplets in polyacrylamide tissue-mimicking phantoms. We further demonstrate the detection of hundreds of vaporization events from individual nanodroplets with activation thresholds well below the tissue cavitation limit. Overall, this approach has the potential to result in reliable and repeatable contrast-enhanced ultrasound imaging at clinically relevant depths.

Antibody-Conjugated Barium Titanate Nanoparticles for Cell-Specific Targeting.

Barium titanate nanoparticles (BTNPs) are gaining popularity in biomedical research because of their piezoelectricity, nonlinear optical properties, and high biocompatibility. However, the potential of BTNPs is limited by the ability to create stable nanoparticle dispersions in water and physiological media. In this work, we report a method of surface modification of BTNPs based on surface hydroxylation followed by covalent attachment of hydrophilic poly(ethylene glycol) (PEG) polymers. This polymer coating allows for additional modifications such as fluorescent labeling, surface charge tuning, or directional conjugation of IgG antibodies. We demonstrate the conjugation of anti-EGFR antibodies to the BTNP surface and show efficient molecular targeting of the nanoparticles to A431 cells. Overall, the reported modifications aim to expand the BTNP applications in molecular imaging, cancer therapy, or noninvasive neurostimulation.

Imaging of singlet oxygen feedback delayed fluorescence and lysosome permeabilization in tumor in vivo during photodynamic therapy with aluminum phthalocyanine.

Significance: Singlet oxygen is a key cytotoxic agent in photodynamic therapy (PDT). As such, its imaging is highly desirable, but existing direct imaging methods are still limited by the exceptionally low yield of the luminescence signal. Singlet oxygen feedback delayed fluorescence (SOFDF) of the photosensitizer is a higher yield alternative for indirect measurement of this signal.

Aim: The aim was to explore feasibility of SOFDF imaging in vivo in tumor-bearing mice during PDT and investigate how SOFDF images can be transformed into images of singlet oxygen. In addition, we study whether lysosome permeabilization can be visualized through fluorescence lifetime.

Approach: Mice were intravenously injected with 2.5 mg/kg of photosensitizer aluminum(III) phthalocyanine tetrasulfonate (AlPcS4) 20 h prior to experiments, having subcutaneous BxPC3 pancreas tumors. Time-resolved delayed fluorescence and prompt fluorescence (PF) were imaged using an intensified time-gated camera with 10-Hz pulsed laser excitation at 690 nm.

Results: Delayed emission from AlPcS4 was detected with lifetimes 7 to 11 µs, which was attributed to SOFDF and shown to be oxygen-dependent. Singlet oxygen images were approximated by the ratio of SOFDF/PF at each pixel. SOFDF images of a good quality could be captured within several seconds with a radiant exposure of ∼20 mJ / cm2. In addition, lifetime images of AlPcS4 PF in ns-time domain enabled us to visualize the event of lysosome permeabilization, as the lifetime increased from ∼4.7 to 5.2 ns.

Conclusions: Imaging of SOFDF in vivo in mouse tumor during PDT with AlPcS4 is feasible, and it is a promising method for singlet molecular oxygen monitoring. Moreover, the time-gated approach also enables visualization of the lysosome permeabilization that alters the PF lifetime.

Sparsity-based photoacoustic image reconstruction with a linear array transducer and direct measurement of the forward model.

Photoacoustic (PA) imaging is an emerging imaging technique for many clinical applications. One of the challenges posed by clinical translation is that imaging systems often rely on a finite-aperture transducer rather than a full tomography system. This results in imaging artifacts arising from an underdetermined reconstruction of the initial pressure distribution (IPD). Furthermore, clinical applications often require deep imaging, resulting in a low-signal-to-noise ratio for the acquired signal because of strong light attenuation in tissue. Conventional approaches to reconstruct the IPD, such as back projection and time-reversal, do not adequately suppress the artifacts and noise. We propose a sparsity-based optimization approach that improves the reconstruction of IPD in PA imaging with a linear array ultrasound transducer. In simulation studies, the forward model matrix was measured from k-Wave simulations, and the approach was applied to reconstruct simulated point objects and the Shepp-Logan phantom. The results were compared with the conventional back projection, time-reversal approach, frequency-domain reconstruction, and the iterative least-squares approaches. In experimental studies, the forward model of our imaging system is directly measured by scanning a graphite point source through the imaging field of view. Experimental images of graphite inclusions in tissue-mimicking phantoms are reconstructed and compared with the back projection and iterative least-squares approaches. Overall these results show that our proposed optimization approach can leverage the sparsity of the PA images to improve the reconstruction of the IPD and outperform the existing popular reconstruction approaches.

Impact of depth-dependent optical attenuation on wavelength selection for spectroscopic photoacoustic imaging.

An optical wavelength selection method based on the stability of the absorption cross-section matrix to improve spectroscopic photoacoustic (sPA) imaging was recently introduced. However, spatially-varying chromophore concentrations cause the wavelength- and depth-dependent variations of the optical fluence, which degrades the accuracy of quantitative sPA imaging. This study introduces a depth-optimized method that determines an optimal wavelength set minimizing an inverse of the multiplication of absorption cross-section matrix and fluence matrix to minimize the errors in concentration estimation. This method assumes that the optical fluence distribution is known or can be attained otherwise. We used a Monte Carlo simulation of light propagation in tissue with various depths and concentrations of deoxy-/oxy-hemoglobin. We quantitatively compared the developed and current approaches, indicating that the choice of wavelength is critical and our approach is effective especially when quantifying deeper imaging targets.

Spectroscopic Photoacoustic Imaging of Gold Nanorods.

Photoacoustic imaging is a rapidly developing tool capable of achieving high-resolution images with optical contrast at imaging depths up to a few centimeters. When combined with targeted nanoparticle contrast agents, sensitive detection of molecular signatures is possible. In this chapter, we discuss the achievements and future directions of nanoparticle-augmented photoacoustic imaging. We present a method to synthesize silica-coated gold nanorods, which are highly stable, signal amplifying photoacoustic contrast agents, and also describe spectroscopic image acquisition and processing steps to provide a specific map of nanoparticle distribution in vivo.