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Although spherical gold (Au) nanoparticles have remarkable photothermal conversion efficiency and photostability, their weak absorption in the near-infrared (NIR) region and poor penetration into deep tissues have limited further applications to NIR light-mediated photoacoustic (PA) imaging and noninvasive photothermal cancer therapy. Here, we developed bimetallic hyaluronate-modified Au–platinum (HA-Au@Pt) nanoparticles for noninvasive cancer theranostics by NIR light-mediated PA imaging and photothermal therapy (PTT). The growth of Pt nanodots on the surface of spherical Au nanoparticles enhanced the absorbance in the NIR region and broadened the absorption bandwidth of HA-Au@Pt nanoparticles by the surface plasmon resonance (SPR) coupling effect. In addition, HA facilitated the transdermal delivery of HA-Au@Pt nanoparticles through the skin barrier and enabled clear tumor-targeted PA imaging. Compared to conventional PTT via injection, HA-Au@Pt nanoparticles were noninvasively delivered into deep tumor tissues and completely ablated the targeted tumor tissues by NIR light irradiation. Taken together, we could confirm the feasibility of HA-Au@Pt nanoparticles as a NIR light-mediated biophotonic agent for noninvasive skin cancer theranostics.

Significance. To effectively study preclinical animal models, medical imaging technology must be developed with a high enough resolution and sensitivity to perform anatomical, functional, and molecular assessments. Photoacoustic (PA) tomography provides high resolution and specificity, and fluorescence (FL) molecular tomography provides high sensitivity; the combination of these imaging modes will enable a wide range of research applications to be studied in small animals.

Aim. We introduce and characterize a dual-modality PA and FL imaging platform using in vivo and phantom experiments.

Approach. The imaging platform’s detection limits were characterized through phantom studies that determined the PA spatial resolution, PA sensitivity, optical spatial resolution, and FL sensitivity.

Results. The system characterization yielded a PA spatial resolution of 173 ± 17 μm in the transverse plane and 640 ± 120 μm in the longitudinal axis, a PA sensitivity detection limit not less than that of a sample with absorption coefficient μa = 0.258 cm − 1, an optical spatial resolution of 70 μm in the vertical axis and 112 μm in the horizontal axis, and a FL sensitivity detection limit not <0.9 μM concentration of IR-800. The scanned animals displayed in three-dimensional renders showed high-resolution anatomical detail of organs.

Conclusions. The combined PA and FL imaging system has been characterized and has demonstrated its ability to image mice in vivo, proving its suitability for biomedical imaging research applications.

Three-dimensional (3D) photoacoustic imaging (PAI) can provide rich information content and has gained increasingly more attention in various biomedical applications. However, current 3D PAI methods either involves pointwise scanning of the 3D volume using a single-element transducer, which can be time-consuming, or requires an array of transducers, which is known to be complex and expensive. By utilizing a 3D encoder and compressed sensing techniques, we develop a new imaging modality that is capable of single-shot 3D PAI using a single-element transducer. The proposed method is validated with phantom study, which demonstrates single-shot 3D imaging of different objects and 3D tracking of a moving object. After one-time calibration, while the system could perform single-shot 3D imaging for different objects, the calibration could remain effective over 7 days, which is highly beneficial for practical translation. Overall, the experimental results showcase the potential of this technique for both scientific research and clinical applications.

Abstract Photoacoustic computed tomography (PACT) has become a premier preclinical and clinical imaging modality. Although PACT\'s image quality can be dramatically improved with a large number of ultrasound (US) transducer elements and associated multiplexed data acquisition systems, the associated high system cost and/or slow temporal resolution are significant problems. Here, a deep learning-based approach is demonstrated that qualitatively and quantitively diminishes the limited-view artifacts that reduce image quality and improves the slow temporal resolution. This deep learning-enhanced multiparametric dynamic volumetric PACT approach, called DL-PACT, requires only a clustered subset of many US transducer elements on the conventional multiparametric PACT. Using DL-PACT, high-quality static structural and dynamic contrast-enhanced whole-body images as well as dynamic functional brain images of live animals and humans are successfully acquired, all in a relatively fast and cost-effective manner. It is believed that the strategy can significantly advance the use of PACT technology for preclinical and clinical applications such as neurology, cardiology, pharmacology, endocrinology, and oncology.

Photoacoustic tomography (PAT) is a non-invasive, non-ionizing hybrid imaging modality that holds great potential for various biomedical applications and the incorporation with deep learning (DL) methods has experienced notable advancements in recent times. In a typical 2D PAT setup, a single-element ultrasound detector (USD) is used to collect the PA signals by making a 360° full scan of the imaging region. The traditional backprojection (BP) algorithm has been widely used to reconstruct the PAT images from the acquired signals. Accurate determination of the scanning radius (SR) is required for proper image reconstruction. Even a slight deviation from its nominal value can lead to image distortion compromising the quality of the reconstruction. To address this challenge, two approaches have been developed and examined herein. The first framework includes a modified version of dense U-Net (DUNet) architecture. The second procedure involves a DL-based convolutional neural network (CNN) for image classification followed by a DUNet. The first protocol was trained with heterogeneous simulated images generated from three different phantoms to learn the relationship between the reconstructed and the corresponding ground truth (GT) images. In the case of the second scheme, the first stage was trained with the same heterogeneous dataset to classify the image type and the second stage was trained individually with the appropriate images. The performance of these architectures has been tested on both simulated and experimental images. The first method can sustain SR deviation up to approximately 6% for simulated images and 5% for experimental images and can accurately reproduce the GTs. The proposed DL-approach extends the limits further (approximately 7% and 8% for simulated and experimental images, respectively). Our results suggest that classification-based DL method does not need a precise assessment of SR for accurate PAT image formation.

In this paper, we exploited the fast-imaging technology for the deep structure of finger based on photoacoustic imaging, which adopted the self-designed 128-ring-array fast photoacoustic imaging system to acquire the latent inside information of finger. The home-made photoacoustic imaging system has the merits of fast imaging, high resolution and deep imaging depth. Specifically, our system could obtain a cross section scan of finger within 0.05 or 0.1s, achieve the resolution of approach 180 μm and image the latent inside information of finger as well as extend the imaging depth over 5 cm in chicken breast tissue at the laser density of 20 mJ/cm² (≤ANSI safety limit). In this work, we obtained the finger anatomical information of skin tissue, blood vessel tissue, and the information of tendon tissue and phalanx tissue which is relatively difficult to obtain by means of photoacoustic imaging. So, we will be able to restore an overall internal structure of a finger including its external shape its internal tendon structure and its internal phalanx structure or containing its blood vessel structure. And that more information from different angles can make its identification more accurate. It is prospective that the deep structure of finger we get by our fast photoacoustic imaging technology will help to provide more possibilities for finger identification and lead to more credible technology for human about relevant information collection and resolution.

Photoacoustic tomography is a contrast agent-free imaging technique capable of visualizing blood vessels and tumor-associated vascularization in breast tissue. While sophisticated breast imaging systems have been recently developed, there is yet much to be gained in imaging depth, image quality and tissue characterization capability before clinical translation is possible. In response, we have developed a hybrid photoacoustic and ultrasound-transmission tomographic system PAM3. The photoacoustic component has for the first time three-dimensional multi-wavelength imaging capability, and implements substantial technical advancements in critical hardware and software sub-systems. The ultrasound component enables for the first time, a three-dimensional sound speed map of the breast to be incorporated in photoacoustic reconstruction to correct for inhomogeneities, enabling accurate target recovery. The results demonstrate the deepest photoacoustic breast imaging to date namely 48 mm, with a more uniform field of view than hitherto, and an isotropic spatial resolution that rivals that of Magnetic Resonance Imaging. The in vivo performance achieved, and the diagnostic value of interrogating angiogenesis-driven optical contrast as well as tumor mass sound speed contrast, gives confidence in the system's clinical potential.

In this work, full-field detection of laser-induced ultrasound waves was performed with an off-axis LED-based Schlieren system. Sensing strobe light, pulsed laser dual light-sheet excitation, and CMOS sensor device were all synchronized to capture the pressure wave as it propagated through an elastic liquid surrounding the test sample. In addition, a reconstruction algorithm based on the Radon transform was applied to the digitally recorded field in order to obtain an image of the photoacoustic source. The proposed system is capable of retrieving the profile of cylindrical and hexagonal targets.

Abstract Although efficient light delivery is required for various biomedical applications, the high stiffness of traditional silica-based optical fibers limits their in vivo usage. In this study, highly deformable and stretchable soft optical fibers are prepared based on the mechanically tough hydrogels of a double network (DN) structure comprising covalently crosslinked acrylamide and ionically crosslinked alginate using a microfluidic device. Owing to the optimized chemical composition, the core/cladding structure, and the mechanical robustness of the prepared hydrogel optical fibers, highly efficient optical delivery is achieved even at highly deformed and elongated states. Furthermore, the microfluidic device further allowed the formation of dual-core, novel architectures for hydrogel optical fibers. With the aid of the dopamine moiety included in the cladding, the hydrogel optical fibers attached strongly to all surfaces tested. Light delivery is further confirmed by implantation in the biological tissues. The high light-guiding performance of the developed hydrogel optical fibers enables them to replace the conventional silica optical fibers used in UV/Vis, fluorescence, and photoacoustic spectroscopies. To demonstrate their in vivo fiber-optic application potential, they are placed inside mice, and the excitation and emission of the generated fluorescence signals are detected.

Photoacoustic imaging is an imaging technology which combines the advantages of high-resolution optical imaging and deep detection depth of acoustic imaging. Photoacoustic imaging combined with hysteroscopy may be a new diagnostic technique for endometrial cancer. However, the energy loss after pulsed laser passing through the hysteroscope is very large. Therefore, the energy of pulsed laser after hysteroscopy based on photoacoustic imaging is worth further discussion. A coupling Program of pulsed laser and hysteroscope based on the optical path of pulsed laser and hysteroscope was designed in this paper. The Program was optimized by ZEMAX simulation, and then the optimal effect of pulsed laser observation through hysteroscopy was verified by phantom experiment. The results show that the pulsed laser can obtain better photoacoustic signals after passing through our coupling module. This method is expected to be applied to the detection of endometrial diseases in clinic.