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Lewis hunting reaction refers to the alternating cold-induced vasoconstriction and dilation in extremities, whose underlying mechanism is complex. While numerous studies reported this intriguing phenomenon by measuring cutaneous temperature fluctuation under cold exposure, few of them tracked peripheral vascular responses in real-time, lacking a non-invasive and quantitative imaging tool. To better monitor hunting reaction and diagnose relevant diseases, we developed a hybrid photoacoustic ultrasound (PAUS) tomography system to monitor finger vessels’ dynamic response to cold, together with simultaneous temperature measurement. We also came out a standard workflow for image analysis with self-defined indices. In the small cohort observational study, vascular changes in the first cycle of hunting reaction were successfully captured by the image series and quantified. Time difference between vasodilation and temperature recovery was noticed and reported for the first time, thanks to the unique capability of the PAUS imaging system in real-time and continuous vascular monitoring. The developed imaging system and indices enabled more objective and quantitative monitoring of peripheral vascular activities, indicating its great potential in numerous clinical applications.
SignificanceEndocavity ultrasound (US) imaging is a frequently employed diagnostic technique in gynecology and urology for the assessment of male and female genital diseases that present challenges for conventional transabdominal imaging. The integration of photoacoustic (PA) imaging with clinical US imaging has displayed promising outcomes in clinical research. Nonetheless, its application has been constrained due to size limitations, restricting it to spatially confined locations such as vaginal or rectal canals.AimThis study presents the development of a video-rate (20 Hz) endocavity PA/harmonic US imaging (EPAUSI) system.ApproachThe approach incorporates a commercially available endocavity US probe with a miniaturized laser delivery unit, comprised of a single large-core fiber and a line beamshaping engineered diffuser. The system facilitates real-time image display and subsequent processing, including angular energy density correction and spectral unmixing, in offline mode.ResultsThe spatial resolutions of the concurrently acquired PA and harmonic US images were measured at 318 μm and 291 μm in the radial direction, respectively, and 1.22 deg and 1.50 deg in the angular direction, respectively. Furthermore, the system demonstrated its capability in multispectral PA imaging by successfully distinguishing two clinical dyes in a tissue-mimicking phantom. Its rapid temporal resolution enabled the capture of kinetic dye perfusion into an ex vivo porcine ovary through the depth of porcine uterine tissue. EPAUSI proved its clinical viability by detecting pulsating hemodynamics in the male rat’s prostate in vivo and accurately classifying human blood vessels into arteries and veins based on sO2 measurements.ConclusionsOur proposed EPAUSI system holds the potential to unveil previously overlooked indicators of vascular alterations in genital cancers or endometriosis, addressing pressing requirements in the fields of gynecology and urology.
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.
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.