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The clinical assessment of microvascular pathologies (in diabetes and in inflammatory skin diseases, for example) requires the visualization of superficial vascular anatomy. Photoacoustic tomography (PAT) scanners based on an all-optical Fabry–Perot ultrasound sensor can provide highly detailed 3D microvascular images, but minutes-long acquisition times have precluded their clinical use. Here we show that scan times can be reduced to a few seconds and even hundreds of milliseconds by parallelizing the optical architecture of the sensor readout, by using excitation lasers with high pulse-repetition frequencies and by exploiting compressed sensing. A PAT scanner with such fast acquisition minimizes motion-related artefacts and allows for the volumetric visualization of individual arterioles, venules, venous valves and millimetre-scale arteries and veins to depths approaching 15 mm, as well as for dynamic 3D images of time-varying tissue perfusion and other haemodynamic events. In exploratory case studies, we used the scanner to visualize and quantify microvascular changes associated with peripheral vascular disease, skin inflammation and rheumatoid arthritis. Fast all-optical PAT may prove useful in cardiovascular medicine, oncology, dermatology and rheumatology.

Photoacoustic tomography (PAT) is increasingly being used for high-resolution biological imaging at depth. Signal-to-noise ratios and resolution are the main factors that determine image quality. Various reconstruction algorithms have been proposed and applied to reduce noise and enhance resolution, but the efficacy of signal preprocessing methods which also affect image quality, are seldom discussed. We, therefore, compared common preprocessing techniques, namely bandpass filters, wavelet denoising, empirical mode decomposition, and singular value decomposition. Each was compared with and without accounting for sensor directivity. The denoising performance was evaluated with the contrast-to-noise ratio (CNR), and the resolution was calculated as the full width at half maximum (FWHM) in both the lateral and axial directions. In the phantom experiment, counting in directivity was found to significantly reduce noise, outperforming other methods. Irrespective of directivity, the best performing methods for denoising were bandpass, unfiltered, SVD, wavelet, and EMD, in that order. Only bandpass filtering consistently yielded improvements. Significant improvements in the lateral resolution were observed using directivity in two out of three acquisitions. This study investigated the advantages and disadvantages of different preprocessing methods and may help to determine better practices in PAT reconstruction.

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.

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.

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.

A computational and experimental study is conducted to examine how directivity associated with a finite aperture sensor affects photoacoustic tomography (PAT) image reconstruction. Acoustic signals for the simulation work were computed using a discrete particle approach from three numerical phantoms including a vasculature. The theoretical framework and a Monte Carlo approach for construction of a tissue configuration are discussed in detail. While simulating forward data, the directivity of the sensor was taken into account. The image reconstruction was accomplished using system matrix based methods like l₂ norm Tikhonov regularization, l₁ norm regularization and total variation (TV) minimization. Accordingly, two different system matrices were constructed- (i) assuming transducer as a point detector (PD) and (ii) retaining properties of a finite detector with directivity (FDWD). Image reconstruction was also performed utilizing experimentally measured PA signals. Both the computational and experimental results demonstrate that blur-free PAT imaging can be achieved with the FDWD method. Additionally, TV minimization provides marginally better image reconstruction compared to the other schemes.