An ultrasensitive and broadband transparent ultrasound transducer for ultrasound and photoacoustic imaging in-vivo.

Transparent ultrasound transducers (TUTs) can seamlessly integrate optical and ultrasound components, but acoustic impedance mismatch prohibits existing TUTs from being practical substitutes for conventional opaque ultrasound transducers. Here, we propose a transparent adhesive based on a silicon dioxide-epoxy composite to fabricate matching and backing layers with acoustic impedances of 7.5 and 4-6 MRayl, respectively. By employing these layers, we develop an ultrasensitive, broadband TUT with 63% bandwidth at a single resonance frequency and high optical transparency ( > 80%), comparable to conventional opaque ultrasound transducers. Our TUT maximises both acoustic power and transfer efficiency with maximal spectrum flatness while minimising ringdowns. This enables high contrast and high-definition dual-modal ultrasound and photoacoustic imaging in live animals and humans. Both modalities reach an imaging depth of > 15 mm, with depth-to-resolution ratios exceeding 500 and 370, respectively. This development sets a new standard for TUTs, advancing the possibilities of sensor fusion.

Red blood cell trapping using single-beam acoustic tweezers in the Rayleigh regime.

Acoustic tweezers (ATs) are a promising technology that can trap and manipulate microparticles or cells with the focused ultrasound beam without physical contact. Unlike optical tweezers, ATs may be used for in vivo studies because they can manipulate cells through tissues. However, in previous non-invasive microparticle trapping studies, ATs could only trap spherical particles, such as beads. Here, we present a theoretical analysis of how the acoustic beam traps red blood cells (RBCs) with experimental demonstration. The proposed modeling shows that the trapping of a non-spherical, biconcave-shaped RBC could be successfully done by single-beam acoustic tweezers (SBATs). We demonstrate this by trapping RBCs using SBATs in the Rayleigh regime, where the cell size is smaller than the wavelength of the beam. Suggested SBAT is a promising tool for cell transportation and sorting.

Switchable preamplifier for dual modal photoacoustic and ultrasound imaging.

Photoacoustic (PA) imaging is a high-fidelity biomedical imaging technique based on the principle of molecular-specific optical absorption of biological tissue constitute. Because PA imaging shares the same basic principle as that of ultrasound (US) imaging, the use of PA/US dual-modal imaging can be achieved using a single system. However, because PA imaging is limited to a shallower depth than US imaging due to the optical extinction in biological tissue, the PA signal yields a lower signal-to-noise ratio (SNR) than US images. To selectively amplify the PA signal, we propose a switchable preamplifier for acoustic-resolution PA microscopy implemented on an application-specific integrated circuit. Using the preamplifier, we measured the increments in the SNR with both carbon lead and wire phantoms. Furthermore, in vivo whole-body PA/US imaging of a mouse with a preamplifier showed enhancement of SNR in deep tissues, unveiling deeply located organs and vascular networks. By selectively amplifying the PA signal range to a level similar to that of the US signal without contrast agent administration, our switchable amplifier strengthens the mutual complement between PA/US imaging. PA/US imaging is impending toward clinical translation, and we anticipate that this study will help mitigate the imbalance of image depth between the two imaging modalities.

Opto-ultrasound biosensor for wearable and mobile devices: realization with a transparent ultrasound transducer.

Mobile and wearable healthcare electronics are widely used for measuring bio-signals using various fusion sensors that employ photoplethysmograms, cameras, microphones, ultrasound (US) sensors, and accelerometers. However, the consumer demand for small form factors has significantly increased as the integration of multiple sensors is difficult in small mobile or wearable devices. This study proposes two novel opto-US sensors, namely (1) a wearable photoplethysmography (PPG)-US device and (2) a PPG sensor built-in mobile smartphone with a US sensor, seamlessly integrated using a transparent ultrasound transducer (TUT). The TUT exhibits a center frequency of 6 MHz with a 50% bandwidth and 82% optical transparency in visible and near-infrared regions. We developed an integrated wearable PPG-US device to demonstrate its feasibility and coupled the TUT sensor with a smartphone. We measured the heart rates optically and acoustically in human subjects and quantified the oxygen saturation optically by passing light through the TUT. The proposed proof-of-concept is a novel sensor fusion for mobile and wearable devices that require a small form factor and aim to improve digital healthcare. The results of this study can form the basis for innovative developments in sensor-based high-tech industrial applications, such as automobiles, robots, and drones, in addition to healthcare applications.

Deep learning alignment of bidirectional raster scanning in high speed photoacoustic microscopy.

Simultaneous point-by-point raster scanning of optical and acoustic beams has been widely adapted to high-speed photoacoustic microscopy (PAM) using a water-immersible microelectromechanical system or galvanometer scanner. However, when using high-speed water-immersible scanners, the two consecutively acquired bidirectional PAM images are misaligned with each other because of unstable performance, which causes a non-uniform time interval between scanning points. Therefore, only one unidirectionally acquired image is typically used; consequently, the imaging speed is reduced by half. Here, we demonstrate a scanning framework based on a deep neural network (DNN) to correct misaligned PAM images acquired via bidirectional raster scanning. The proposed method doubles the imaging speed compared to that of conventional methods by aligning nonlinear mismatched cross-sectional B-scan photoacoustic images during bidirectional raster scanning. Our DNN-assisted raster scanning framework can further potentially be applied to other raster scanning-based biomedical imaging tools, such as optical coherence tomography, ultrasound microscopy, and confocal microscopy.

Fully integrated photoacoustic microscopy and photoplethysmography of human in vivo.

Photoacoustic microscopy (PAM) is used to visualize blood vessels and to monitor their time-dependent changes. Photoplethysmography (PPG) measures hemodynamic time-series changes such as heart rate. However, PPG's limited visual access to the dynamic changes of blood vessels has prohibited further understanding of hemodynamics. Here, we propose a novel, fully integrated PAM and photoplethysmography (PAM-PPG) system to understand hemodynamic features in detail. Using the PAM-PPG system, we simultaneously acquire vascular images (by PAM) and changes in the blood volume (by PPG) from human fingers. Next, we determine the heart rate from changes in the PA signals, which match well with the PPG signals. These changes can be measured if the blood flow is not blocked. From the results, we believe that PAM-PPG could be a useful clinical tool in various clinical fields such as cardiology and endocrinology.

Deep learning acceleration of multiscale superresolution localization photoacoustic imaging.

A superresolution imaging approach that localizes very small targets, such as red blood cells or droplets of injected photoacoustic dye, has significantly improved spatial resolution in various biological and medical imaging modalities. However, this superior spatial resolution is achieved by sacrificing temporal resolution because many raw image frames, each containing the localization target, must be superimposed to form a sufficiently sampled high-density superresolution image. Here, we demonstrate a computational strategy based on deep neural networks (DNNs) to reconstruct high-density superresolution images from far fewer raw image frames. The localization strategy can be applied for both 3D label-free localization optical-resolution photoacoustic microscopy (OR-PAM) and 2D labeled localization photoacoustic computed tomography (PACT). For the former, the required number of raw volumetric frames is reduced from tens to fewer than ten. For the latter, the required number of raw 2D frames is reduced by 12 fold. Therefore, our proposed method has simultaneously improved temporal (via the DNN) and spatial (via the localization method) resolutions in both label-free microscopy and labeled tomography. Deep-learning powered localization PA imaging can potentially provide a practical tool in preclinical and clinical studies requiring fast temporal and fine spatial resolutions.

High-Attenuation Backing Layer for Miniaturized Ultrasound Imaging Transducer.

Current miniaturized ultrasound transducers suffer from insufficient attenuation from the backing layer due to their limited thickness. The thickness of the backing layer is one of the critical factors determining the device size and transducer performance for miniaturized transducers inserted and operated in a limited space. Glass bubbles, polyamide resin, and tungsten powder are combined to form a new highly attenuative backing material. It has high attenuation (>160 dB/cm at 5 MHz), which is five times greater than silver-based conductive epoxy commonly used for high-frequency ultrasound transducers, appropriate acoustic impedance (4.6 MRayl), and acceptable damping capability. An intravascular ultrasound (IVUS) transducer constructed with the 170 [Formula: see text] of the proposed backing layer demonstrated that the amplitude of the signal returned from the backing layer was 1.8 times smaller, with ring-down attenuated by 6 dB. Wire-phantom imaging revealed that the axial resolution was 30% better with the suggested backing than silver-based conductive epoxy backing. Because of its excellent attenuation capability even at a limited thickness, simple manufacturing process, and easy customization capability, the suggested highly attenuative backing layer may be used for miniaturized ultrasound transducers.

Automated estimation of cancer cell deformability with machine learning and acoustic trapping.

Cell deformability is a useful feature for diagnosing various diseases (e.g., the invasiveness of cancer cells). Existing methods commonly inflict pressure on cells and observe changes in cell areas, diameters, or thickness according to the degree of pressure. Then, the Young's moduli (i.e., a measure of deformability) of cells are estimated based on the assumption that the degrees of the changes are inversely proportional to Young's moduli. However, manual measurements of the physical changes in cells are labor-intensive, and the subjectivity of the operators can intervene during this step, thereby causing considerable uncertainty. Further, because the shapes of cells are nonuniform, we cannot ensure the assumption for linear correlations of physical changes in cells with their deformability. Therefore, this study aims at measuring non-linear elastic moduli of live cells (degrees of cell deformability) automatically by employing conventional neural networks (CNN) and multilayer perceptrons (MLP) while preserving (or enhancing) the accuracy of the manual methods. First, we obtain photomicrographs of cells on multiple pressure levels using single-beam acoustic tweezers, and then, we suggest an image preprocessing method for emphasizing changes in cell areas on the photomicrographs. The CNN model is trained to measure the ratios of the cell area change at each pressure level. Then, we apply the multilayer perceptron (MLP) to learn the correlations of the cell area change ratios according to the pressure levels with cell deformability. The accuracy of the CNN was evaluated using two types of breast cancer cells: MDA-MB-231 (invasive) and MCF-7 (noninvasive). The MLP was assessed using five different beads (Young's moduli from 0.214 to 9.235 kPa), which provides standardized reference data of the non-linear elastic moduli of live cells. Finally, we validated the practicality of the proposed system by examining whether the non-linear elastic moduli estimated by the proposed system can distinguish invasive breast cancer cells from noninvasive ones.

Bi-modal near-infrared fluorescence and ultrasound imaging via a transparent ultrasound transducer for sentinel lymph node localization: publisher's note.

This publisher's note contains a correction to Opt. Lett.47, 393 (2022)10.1364/OL.446041.

Bi-modal near-infrared fluorescence and ultrasound imaging via a transparent ultrasound transducer for sentinel lymph node localization.

Sentinel lymph node biopsy with an indocyanine green-based near-infrared fluorescence imaging system avoids the shortcomings of using a radioisotope or a combination of a blue dye and a radioactive tracer. To improve surgical precision, recent research has provided a depth profile of the sentinel lymph node by fusing fluorescence and ultrasound imaging. Here, we present a combined near-infrared fluorescence and ultrasound imaging system based on a transparent ultrasound transducer. The transparent ultrasound transducer enables seamless coaxial alignment of the fluorescence and ultrasound beam paths, allowing bi-modal observation of a single region of interest. Further, we demonstrate that the sentinel lymph node of mice injected with indocyanine green can be successfully localized and dissected based on information from the bi-modal imaging system.

Collapse pressure measurement of single hollow glass microsphere using single-beam acoustic tweezer.

Microbubbles are widely used in medical ultrasound imaging and drug delivery. Many studies have attempted to quantify the collapse pressure of microbubbles using methods that vary depending on the type and population of bubbles and the frequency band of the ultrasound. However, accurate measurement of collapse pressure is difficult as a result of non-acoustic pressure factors generated by physical and chemical reactions such as dissolution, cavitation, and interaction between bubbles. In this study, we developed a method for accurately measuring collapse pressure using only ultrasound pulse acoustic pressure. Under the proposed method, the collapse pressure of a single hollow glass microsphere (HGM) is measured using a high-frequency (20-40 MHz) single-beam acoustic tweezer (SBAT), thereby eliminating the influence of additional factors. Based on these measurements, the collapse pressure is derived as a function of the HGM size using the microspheres' true density. We also developed a method for estimating high-frequency acoustic pressure, whose measurement using current hydrophone equipment is complicated by limitations in the size of the active aperture. By recording the transmit voltage at the moment of collapse and referencing it against the corresponding pressure, it is possible to estimate the acoustic pressure at the given transmit condition. These results of this study suggest a method for quantifying high-frequency acoustic pressure, provide a potential reference for the characterization of bubble collapse pressure, and demonstrate the potential use of acoustic tweezers as a tool for measuring the elastic properties of particles/cells.

Detection of micro inclusions in steel sheets using high-frequency ultrasound speckle analysis.

With the increasing need for steel sheet quality assurance, the detection of micro-scaled inclusions in steel sheets has become critical. Many techniques have been explored to detect inclusions, e.g., visual inspection, radiography, magnetic testing, and ultrasound. Among these methods, ultrasound (US) is the most commonly used non-destructive testing (NDT) method due to its ease of use and deep penetration depth. However, ultrasound currently cannot be used for detecting the micro-scaled inclusions due to low spatial resolution, e.g., less than 30 µm, which are the key important factors causing the cracks in the high-quality steel sheets. Here, we demonstrate a high-resolution US imaging (USI) using high-frequency US transducers to image micro inclusions in steel sheets. Our system utilizes through-transmission USI and identifies ultrasound scattering produced by the inclusions. We first ultrasonically imaged the artificial flaws induced by the laser on the steel sheet surface for validating the system. We then imaged the real inclusions in the steel sheets formed during manufacturing processes and analyzed them to derive quantitative parameters related to the number of micro-scaled inclusions. Our results confirm that inclusions less than 30 µm can be identified using our high-resolution USI modality and has the potential to be used as an effective tool for quality assurance of the steel sheets.

A photoacoustic finder fully integrated with a solid-state dye laser and transparent ultrasound transducer.

The standard-of-care for evaluating lymph node status in breast cancers and melanoma metastasis is sentinel lymph node (SLN) assessment performed with a handheld gamma probe and radioisotopes. However, this method inevitably exposes patients and physicians to radiation, and the special facilities required limit its accessibility. Here, we demonstrate a non-ionizing, cost-effective, handheld photoacoustic finder (PAF) fully integrated with a solid-state dye laser and transparent ultrasound transducer (TUT). The solid-state dye laser handpiece is coaxially aligned with the spherically focused TUT. The integrated finder readily detected photoacoustic signals from a tube filled with methylene blue (MB) beneath a 22 mm thick layer of chicken tissue. In live animals, we also photoacoustically detected both SLNs injected with MB and subcutaneously injected melanomas. We believe that our radiation-free and inexpensive PAF can play a vital role in SLN assessment.

Quadruple ultrasound, photoacoustic, optical coherence, and fluorescence fusion imaging with a transparent ultrasound transducer.

Ultrasound and optical imagers are used widely in a variety of biological and medical applications. In particular, multimodal implementations combining light and sound have been actively investigated to improve imaging quality. However, the integration of optical sensors with opaque ultrasound transducers suffers from low signal-to-noise ratios, high complexity, and bulky form factors, significantly limiting its applications. Here, we demonstrate a quadruple fusion imaging system using a spherically focused transparent ultrasound transducer that enables seamless integration of ultrasound imaging with photoacoustic imaging, optical coherence tomography, and fluorescence imaging. As a first application, we comprehensively monitored multiparametric responses to chemical and suture injuries in rats' eyes in vivo, such as corneal neovascularization, structural changes, cataracts, and inflammation. As a second application, we successfully performed multimodal imaging of tumors in vivo, visualizing melanomas without using labels and visualizing 4T1 mammary carcinomas using PEGylated gold nanorods. We strongly believe that the seamlessly integrated multimodal system can be used not only in ophthalmology and oncology but also in other healthcare applications with broad impact and interest.

Synthetic Aperture Imaging Using High-Frequency Convex Array for Ophthalmic Ultrasound Applications.

High-frequency ultrasound (HFUS) imaging has emerged as an essential tool for pre-clinical studies and clinical applications such as ophthalmic and dermatologic imaging. HFUS imaging systems based on array transducers capable of dynamic receive focusing have considerably improved the image quality in terms of spatial resolution and signal-to-noise ratio (SNR) compared to those by the single-element transducer-based one. However, the array system still suffers from low spatial resolution and SNR in out-of-focus regions, resulting in a blurred image and a limited penetration depth. In this paper, we present synthetic aperture imaging with a virtual source (SA-VS) for an ophthalmic application using a high-frequency convex array transducer. The performances of the SA-VS were evaluated with phantom and ex vivo experiments in comparison with the conventional dynamic receive focusing method. Pre-beamformed radio-frequency (RF) data from phantoms and excised bovine eye were acquired using a custom-built 64-channel imaging system. In the phantom experiments, the SA-VS method showed improved lateral resolution (>10%) and sidelobe level (>4.4 dB) compared to those by the conventional method. The SNR was also improved, resulting in an increased penetration depth: 16 mm and 23 mm for the conventional and SA-VS methods, respectively. Ex vivo images with the SA-VS showed improved image quality at the entire depth and visualized structures that were obscured by noise in conventional imaging.

Thermal Ablation and High-Resolution Imaging Using a Back-to-Back (BTB) Dual-Mode Ultrasonic Transducer: In Vivo Results.

We present a back-to-back (BTB) structured, dual-mode ultrasonic device that incorporates a single-element 5.3 MHz transducer for high-intensity focused ultrasound (HIFU) treatment and a single-element 20.0 MHz transducer for high-resolution ultrasound imaging. Ultrasound image-guided surgical systems have been developed for lesion monitoring to ensure that ultrasonic treatment is correctly administered at the right locations. In this study, we developed a dual-element transducer composed of two elements that share the same housing but work independently with a BTB structure, enabling a mode change between therapy and imaging via 180-degree mechanical rotation. The optic fibers were embedded in the HIFU focal region of ex vivo chicken breasts and the temperature change was measured. Images were obtained in vivo mice before and after treatment and compared to identify the treated region. We successfully acquired B-mode and C-scan images that display the hyperechoic region indicating coagulation necrosis in the HIFU-treated volume up to a depth of 10 mm. The compact BTB dual-mode ultrasonic transducer may be used for subcutaneous thermal ablation and monitoring, minimally invasive surgery, and other clinical applications, all with ultrasound only.

Classification of Breast Cancer Cells Using the Integration of High-Frequency Single-Beam Acoustic Tweezers and Convolutional Neural Networks.

Single-beam acoustic tweezers (SBAT) is a widely used trapping technique to manipulate microscopic particles or cells. Recently, the characterization of a single cancer cell using high-frequency (>30 MHz) SBAT has been reported to determine its invasiveness and metastatic potential. Investigation of cell elasticity and invasiveness is based on the deformability of cells under SBAT's radiation forces, and in general, more physically deformed cells exhibit higher levels of invasiveness and therefore higher metastatic potential. However, previous imaging analysis to determine substantial differences in cell deformation, where the SBAT is turned ON or OFF, relies on the subjective observation that may vary and requires follow-up evaluations from experts. In this study, we propose an automatic and reliable cancer cell classification method based on SBAT and a convolutional neural network (CNN), which provides objective and accurate quantitative measurement results. We used a custom-designed 50 MHz SBAT transducer to obtain a series of images of deformed human breast cancer cells. CNN-based classification methods with data augmentation applied to collected images determined and validated the metastatic potential of cancer cells. As a result, with the selected optimizers, precision, and recall of the model were found to be greater than 0.95, which highly validates the classification performance of our integrated method. CNN-guided cancer cell deformation analysis using SBAT may be a promising alternative to current histological image analysis, and this pretrained model will significantly reduce the evaluation time for a larger population of cells.

Versatile Single-Element Ultrasound Imaging Platform using a Water-Proofed MEMS Scanner for Animals and Humans.

Single-element transducer based ultrasound (US) imaging offers a compact and affordable solution for high-frequency preclinical and clinical imaging because of its low cost, low complexity, and high spatial resolution compared to array-based US imaging. To achieve B-mode imaging, conventional approaches adapt mechanical linear or sector scanning methods. However, due to its low scanning speed, mechanical linear scanning cannot achieve acceptable temporal resolution for real-time imaging, and the sector scanning method requires specialized low-load transducers that are small and lightweight. Here, we present a novel single-element US imaging system based on an acoustic mirror scanning method. Instead of physically moving the US transducer, the acoustic path is quickly steered by a water-proofed microelectromechanical (MEMS) scanner, achieving real-time imaging. Taking advantage of the low-cost and compact MEMS scanner, we implemented both a tabletop system for in vivo small animal imaging and a handheld system for in vivo human imaging. Notably, in combination with mechanical raster scanning, we could acquire the volumetric US images in live animals. This versatile US imaging system can be potentially used for various preclinical and clinical applications, including echocardiography, ophthalmic imaging, and ultrasound-guided catheterization.

Investigation of cell mechanics using single-beam acoustic tweezers as a versatile tool for the diagnosis and treatment of highly invasive breast cancer cell lines: an in vitro study.

Advancements in diagnostic systems for metastatic cancer over the last few decades have played a significant role in providing patients with effective treatment by evaluating the characteristics of cancer cells. Despite the progress made in cancer prognosis, we still rely on the visual analysis of tissues or cells from histopathologists, where the subjectivity of traditional manual interpretation persists. This paper presents the development of a dual diagnosis and treatment tool using an in vitro acoustic tweezers platform with a 50 MHz ultrasonic transducer for label-free trapping and bursting of human breast cancer cells. For cancer cell detection and classification, the mechanical properties of a single cancer cell were quantified by single-beam acoustic tweezers (SBAT), a noncontact assessment tool using a focused acoustic beam. Cell-mimicking phantoms and agarose hydrogel spheres (AHSs) served to standardize the biomechanical characteristics of the cells. Based on the analytical comparison of deformability levels between the cells and the AHSs, the mechanical properties of the cells could be indirectly measured by interpolating the Young's moduli of the AHSs. As a result, the calculated Young's moduli, i.e., 1.527 kPa for MDA-MB-231 (highly invasive breast cancer cells), 2.650 kPa for MCF-7 (weakly invasive breast cancer cells), and 2.772 kPa for SKBR-3 (weakly invasive breast cancer cells), indicate that highly invasive cancer cells exhibited a lower Young's moduli than weakly invasive cells, which indicates a higher deformability of highly invasive cancer cells, leading to a higher metastasis rate. Single-cell treatment may also be carried out by bursting a highly invasive cell with high-intensity, focused ultrasound.