Deep learning acceleration of multiscale superresolution localization photoacoustic imaging

3D Multiparametric Photoacoustic Computed Tomography of Primary and Metastatic Tumors in Living Mice

Photoacoustic computed tomography (PACT), an emerging imaging modality in preclinical cancer research, can provide multiparametric 3D information about structures, physiological functions, and pharmacokinetics. Here, we demonstrate the use of high-definition 3D multiparametric PACT imaging of both primary and metastatic tumors in living mice to noninvasively monitor angiogenesis, carcinogenesis, hypoxia, and pharmacokinetics. The high-definition PACT system with a 1024-element hemispherical ultrasound transducer array provides an isotropic spatial resolution of 380 μm, an effective volumetric field-of-view of 12.8 mm × 12.8 mm × 12.8 mm without scanning, and an acquisition time of <30 s for a whole mouse body. Initially, we monitor the structural progression of the tumor microenvironment (e.g., angiogenesis and vessel tortuosity) after tumor cell inoculation. Then, we analyze the change in oxygen saturation of the tumor during carcinogenesis, verifying induced hypoxia in the tumor's core region. Finally, the whole-body pharmacokinetics are photoacoustically imaged after intravenous injection of micelle-loaded IR780 dye, and the in vivo PACT results are validated in vivo and ex vivo by fluorescence imaging. By employing the premium PACT system and applying multiparametric analyses to subcutaneous primary tumors and metastatic liver tumors, we demonstrate that this PACT system can provide multiparametric analyses for comprehensive cancer research.

DOVE: Doodled vessel enhancement for photoacoustic angiography super resolution

Deep-learning-based super-resolution photoacoustic angiography (PAA) has emerged as a valuable tool for enhancing the resolution of blood vessel images and aiding in disease diagnosis. However, due to the scarcity of training samples, PAA super-resolution models do not generalize well, especially in the challenging in-vivo imaging of organs with deep tissue penetration. Furthermore, prolonged exposure to high laser intensity during the image acquisition process can lead to tissue damage and secondary infections. To address these challenges, we propose an approach doodled vessel enhancement (DOVE) that utilizes hand-drawn doodles to train a PAA super-resolution model. With a training dataset consisting of only 32 real PAA images, we construct a diffusion model that interprets hand-drawn doodles as low-resolution images. DOVE enables us to generate a large number of realistic PAA images, achieving a 49.375% fool rate, even among experts in photoacoustic imaging. Subsequently, we employ these generated images to train a self-similarity-based model for super-resolution. During cross-domain tests, our method, trained solely on generated images, achieves a structural similarity value of 0.8591, surpassing the scores of all other models trained with real high-resolution images. DOVE successfully overcomes the limitation of insufficient training samples and unlocks the clinic application potential of super-resolution-based biomedical imaging.

On the Importance of Low-Frequency Signals in Functional and Molecular Photoacoustic Computed Tomography

In photoacoustic computed tomography (PACT) with short-pulsed laser excitation, wideband acoustic signals are generated in biological tissues with frequencies related to the effective shapes and sizes of the optically absorbing targets. Low-frequency photoacoustic signal components correspond to slowly varying spatial features and are often omitted during imaging due to the limited detection bandwidth of the ultrasound transducer, or during image reconstruction as undesired background that degrades image contrast. Here we demonstrate that low-frequency photoacoustic signals, in fact, contain functional and molecular information, and can be used to enhance structural visibility, improve quantitative accuracy, and reduce spare-sampling artifacts. We provide an in-depth theoretical analysis of low-frequency signals in PACT, and experimentally evaluate their impact on several representative PACT applications, such as mapping temperature in photothermal treatment, measuring blood oxygenation in a hypoxia challenge, and detecting photoswitchable molecular probes in deep organs. Our results strongly suggest that low-frequency signals are important for functional and molecular PACT.

MyoV: a deep learning-based tool for the automated quantification of muscle fibers

Accurate approaches for quantifying muscle fibers are essential in biomedical research and meat production. In this study, we address the limitations of existing approaches for hematoxylin and eosin-stained muscle fibers by manually and semiautomatically labeling over 660 000 muscle fibers to create a large dataset. Subsequently, an automated image segmentation and quantification tool named MyoV is designed using mask regions with convolutional neural networks and a residual network and feature pyramid network as the backbone network. This design enables the tool to allow muscle fiber processing with different sizes and ages. MyoV, which achieves impressive detection rates of 0.93-0.96 and precision levels of 0.91-0.97, exhibits a superior performance in quantification, surpassing both manual methods and commonly employed algorithms and software, particularly for whole slide images (WSIs). Moreover, MyoV is proven as a powerful and suitable tool for various species with different muscle development, including mice, which are a crucial model for muscle disease diagnosis, and agricultural animals, which are a significant meat source for humans. Finally, we integrate this tool into visualization software with functions, such as segmentation, area determination and automatic labeling, allowing seamless processing for over 400 000 muscle fibers within a WSI, eliminating the model adjustment and providing researchers with an easy-to-use visual interface to browse functional options and realize muscle fiber quantification from WSIs.

Unveiling precision: a data-driven approach to enhance photoacoustic imaging with sparse data

This study presents the Fourier Decay Perception Generative Adversarial Network (FDP-GAN), an innovative approach dedicated to alleviating limitations in photoacoustic imaging stemming from restricted sensor availability and biological tissue heterogeneity. By integrating diverse photoacoustic data, FDP-GAN notably enhances image fidelity and reduces artifacts, particularly in scenarios of low sampling. Its demonstrated effectiveness highlights its potential for substantial contributions to clinical applications, marking a significant stride in addressing pertinent challenges within the realm of photoacoustic acquisition techniques.

Sounding out the dynamics: a concise review of high-speed photoacoustic microscopy

Significance

Photoacoustic microscopy (PAM) offers advantages in high-resolution and high-contrast imaging of biomedical chromophores. The speed of imaging is critical for leveraging these benefits in both preclinical and clinical settings. Ongoing technological innovations have substantially boosted PAM's imaging speed, enabling real-time monitoring of dynamic biological processes.

Aim

This concise review synthesizes historical context and current advancements in high-speed PAM, with an emphasis on developments enabled by ultrafast lasers, scanning mechanisms, and advanced imaging processing methods.

Approach

We examine cutting-edge innovations across multiple facets of PAM, including light sources, scanning and detection systems, and computational techniques and explore their representative applications in biomedical research.

Results

This work delineates the challenges that persist in achieving optimal high-speed PAM performance and forecasts its prospective impact on biomedical imaging.

Conclusions

Recognizing the current limitations, breaking through the drawbacks, and adopting the optimal combination of each technology will lead to the realization of ultimate high-speed PAM for both fundamental research and clinical translation.

Video-rate endocavity photoacoustic/harmonic ultrasound imaging with miniaturized light delivery

Significance

Endocavity 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.

Aim

This study presents the development of a video-rate (20 Hz) endocavity PA/harmonic US imaging (EPAUSI) system.

Approach

The 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.

Results

The spatial resolutions of the concurrently acquired PA and harmonic US images were measured at 318    μ m and 291    μ m 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 sO 2 measurements.

Conclusions

Our 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 imaging plus X: a review

Significance

Photoacoustic (PA) imaging (PAI) represents an emerging modality within the realm of biomedical imaging technology. It seamlessly blends the wealth of optical contrast with the remarkable depth of penetration offered by ultrasound. These distinctive features of PAI hold tremendous potential for various applications, including early cancer detection, functional imaging, hybrid imaging, monitoring ablation therapy, and providing guidance during surgical procedures. The synergy between PAI and other cutting-edge technologies not only enhances its capabilities but also propels it toward broader clinical applicability.

Aim

The integration of PAI with advanced technology for PA signal detection, signal processing, image reconstruction, hybrid imaging, and clinical applications has significantly bolstered the capabilities of PAI. This review endeavor contributes to a deeper comprehension of how the synergy between PAI and other advanced technologies can lead to improved applications.

Approach

An examination of the evolving research frontiers in PAI, integrated with other advanced technologies, reveals six key categories named "PAI plus X." These categories encompass a range of topics, including but not limited to PAI plus treatment, PAI plus circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities.

Results

After conducting a comprehensive review of the existing literature and research on PAI integrated with other technologies, various proposals have emerged to advance the development of PAI plus X. These proposals aim to enhance system hardware, improve imaging quality, and address clinical challenges effectively.

Conclusions

The progression of innovative and sophisticated approaches within each category of PAI plus X is positioned to drive significant advancements in both the development of PAI technology and its clinical applications. Furthermore, PAI not only has the potential to integrate with the above-mentioned technologies but also to broaden its applications even further.

Transcytosis-Inducing Multifunctional Albumin Nanomedicines with Deep Penetration Ability for Image-Guided Solid Tumor Treatment

Transcytosis is an active transcellular transportation pathway that has garnered interest for overcoming the limited deep penetration of nanomedicines in solid tumors. In this study, a charge-convertible nanomedicine that facilitates deep penetration into solid tumors via transcytosis is designed. It is an albumin-based calcium phosphate nanomedicine loaded with IR820 (mAlb-820@CaP) for high-resolution photoacoustic imaging and enhanced photothermal therapy. Biomineralization on the surface stabilizes the albumin-IR820 complex during circulation and provides calcium ions (Ca2+ ) for tissue penetration on degradation in an acidic environment. pH-triggered transcytosis of the nanomedicine enabled by caveolae-mediated endocytosis and calcium ion-induced exocytosis in 2D cellular, 3D spheroid, and in vivo tumor models is demonstrated. Notably, the extravasation and penetration ability of the nanomedicine is observed in vivo using a high-resolution photoacoustic system, and nanomedicine shows the most potent photothermal antitumor effect in vivo. Overall, the strategy provides a versatile theragnosis platform for both noninvasive photoacoustic imaging and high therapeutic efficiency resulting from deep penetration of nanomedicine.

Contrast Agent-Free 3D Renal Ultrafast Doppler Imaging Reveals Vascular Dysfunction in Acute and Diabetic Kidney Diseases

To combat the irreversible decline in renal function associated with kidney disease, it is essential to establish non-invasive biomarkers for assessing renal microcirculation. However, the limited resolution and/or vascular sensitivity of existing diagnostic imaging techniques hinders the visualization of complex cortical vessels. Here, a 3D renal ultrafast Doppler (UFD) imaging system that uses a high ultrasound frequency (18 MHz) and ultrahigh frame rate (1 KHz per slice) to scan the entire volume of a rat's kidney in vivo is demonstrated. The system, which can visualize the full 3D renal vascular branching pyramid at a resolution of 167 µm without any contrast agent, is used to chronically and noninvasively monitor kidneys with acute kidney injury (AKI, 3 days) and diabetic kidney disease (DKD, 8 weeks). Multiparametric UFD analyses (e.g., vessel volume occupancy (VVO), fractional moving blood volume (FMBV), vessel number density (VND), and vessel tortuosity (VT)) describe rapid vascular rarefaction from AKI and long-term vascular degeneration from DKD, while the renal pathogeneses are validated by in vitro blood serum testing and stained histopathology. This work demonstrates the potential of 3D renal UFD to offer valuable insights into assessing kidney perfusion levels for future research in diabetes and kidney transplantation.

Compressed single-shot 3D photoacoustic imaging with a single-element transducer

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.

Contrast-Free Super-Resolution Power Doppler (CS-PD) Based on Deep Neural Networks

Super-resolution ultrasound microvessel imaging based on ultrasound localization microscopy (ULM) is an emerging imaging modality that is capable of resolving micrometer-scaled vessels deep into tissue. In practice, ULM is limited by the need for contrast injection, long data acquisition, and computationally expensive postprocessing times. In this study, we present a contrast-free super-resolution power Doppler (CS-PD) technique that uses deep networks to achieve super-resolution with short data acquisition. The training dataset is comprised of spatiotemporal ultrafast ultrasound signals acquired from in vivo mouse brains, while the testing dataset includes in vivo mouse brain, chicken embryo chorioallantoic membrane (CAM), and healthy human subjects. The in vivo mouse imaging studies demonstrate that CS-PD could achieve an approximate twofold improvement in spatial resolution when compared with conventional power Doppler. In addition, the microvascular images generated by CS-PD showed good agreement with the corresponding ULM images as indicated by a structural similarity index of 0.7837 and a peak signal-to-noise ratio (PSNR) of 25.52. Moreover, CS-PD was able to preserve the temporal profile of the blood flow (e.g., pulsatility) that is similar to conventional power Doppler. Finally, the generalizability of CS-PD was demonstrated on testing data of different tissues using different imaging settings. The fast inference time of the proposed deep neural network also allows CS-PD to be implemented for real-time imaging. These features of CS-PD offer a practical, fast, and robust microvascular imaging solution for many preclinical and clinical applications of Doppler ultrasound.

Ultrafast photoacoustic cavitation pumped by picosecond laser for high-efficient and long-term shockwave theranostics

Photoacoustic (PA) theranostics is a new emerging field that uniquely combines diagnosis and treatment in one modality. However, its current status is compromised by the indispensable dependence on nonreversible phase-change nanoprobes that provides one-time-only action. Here, we demonstrate a picosecond-laser-pumped ultrafast PA cavitation technique for highly efficient shockwave theranostics, guaranteeing sustained PA cavitation by using non-phase-change nanoprobes. Theoretical simulations validate that, when compressing the excitation laser pulse width to hundred-picosecond, the thermal confinement effects of a conventional nanoprobe will induce transient heating of the extremely thin surrounding liquid layer of the nanoprobes beyond its cavitation point in a localized area at nanoscale, resulting in intense cavitation and PA shockwaves by the environment rather than the nanoprobes. Both cellular and mouse model experiments have demonstrated the highly effective anti-tumor effects. This method provides a sustainable, reproducible, and highly effective strategy for PA theranostics, prefiguring great potential for the clinical applications.

Enhanced resolution and sensitivity acoustic-resolution photoacoustic microscopy with semi/unsupervised GANs

Acoustic-resolution photoacoustic microscopy (AR-PAM) enables visualization of biological tissues at depths of several millimeters with superior optical absorption contrast. However, the lateral resolution and sensitivity of AR-PAM are generally lower than those of optical-resolution PAM (OR-PAM) owing to the intrinsic physical acoustic focusing mechanism. Here, we demonstrate a computational strategy with two generative adversarial networks (GANs) to perform semi/unsupervised reconstruction with high resolution and sensitivity in AR-PAM by maintaining its imaging capability at enhanced depths. The b-scan PAM images were prepared as paired (for semi-supervised conditional GAN) and unpaired (for unsupervised CycleGAN) groups for label-free reconstructed AR-PAM b-scan image generation and training. The semi/unsupervised GANs successfully improved resolution and sensitivity in a phantom and in vivo mouse ear test with ground truth. We also confirmed that GANs could enhance resolution and sensitivity of deep tissues without the ground truth.

On the importance of low-frequency signals in functional and molecular photoacoustic computed tomography

In photoacoustic computed tomography (PACT) with short-pulsed laser excitation, wideband acoustic signals are generated in biological tissues with frequencies related to the effective shapes and sizes of the optically absorbing targets. Low-frequency photoacoustic signal components correspond to slowly varying spatial features and are often omitted during imaging due to the limited detection bandwidth of the ultrasound transducer, or during image reconstruction as undesired background that degrades image contrast. Here we demonstrate that low-frequency photoacoustic signals, in fact, contain functional and molecular information, and can be used to enhance structural visibility, improve quantitative accuracy, and reduce spare-sampling artifacts. We provide an in-depth theoretical analysis of low-frequency signals in PACT, and experimentally evaluate their impact on several representative PACT applications, such as mapping temperature in photothermal treatment, measuring blood oxygenation in a hypoxia challenge, and detecting photoswitchable molecular probes in deep organs. Our results strongly suggest that low-frequency signals are important for functional and molecular PACT.

Dual-wavelength UV-visible metalens for multispectral photoacoustic microscopy: A simulation study

Photoacoustic microscopy is advancing with research on utilizing ultraviolet and visible light. Dual-wavelength approaches are sought for observing DNA/RNA- and vascular-related disorders. However, the availability of high numerical aperture lenses covering both ultraviolet and visible wavelengths is severely limited due to challenges such as chromatic aberration in the optics. Herein, we present a groundbreaking proposal as a pioneering simulation study for incorporating multilayer metalenses into ultraviolet-visible photoacoustic microscopy. The proposed metalens has a thickness of 1.4 µm and high numerical aperture of 0.8. By arranging cylindrical hafnium oxide nanopillars, we design an achromatic transmissive lens for 266 and 532 nm wavelengths. The metalens achieves a diffraction-limited focal spot, surpassing commercially available objective lenses. Through three-dimensional photoacoustic simulation, we demonstrate high-resolution imaging with superior endogenous contrast of targets with ultraviolet and visible optical absorption bands. This metalens will open new possibilities for downsized multispectral photoacoustic microscopy in clinical and preclinical applications.

In vivo quantitative photoacoustic monitoring of corticosteroid-induced vasoconstriction

SIGNIFICANCE

Corticosteroids-commonly prescribed medications for skin diseases-inhibit the secretion of vasodilators, such as prostaglandin, thereby exerting anti-inflammatory action by constricting capillaries in the dermis. The effectiveness of corticosteroids is determined by the degree of vasoconstriction followed by skin whitening, namely, the blanching effect. However, the current method of observing the blanching effect indirectly evaluates the effects of corticosteroids.

AIM

In this study, we employed optical-resolution photoacoustic (PA) microscopy (OR-PAM) to directly visualize the blood vessels and quantitatively evaluate vasoconstriction.

APPROACH

Using OR-PAM, the vascular density in mice skin was monitored for 60 min after performing each experimental procedure for four groups, and the vasoconstriction was quantified. Volumetric PA data were segmented into the papillary dermis, reticular dermis, and hypodermis based on the vascular characteristics obtained through OR-PAM. The vasoconstrictive effect of each skin layer was quantified according to the dermatological treatment method.

RESULTS

In the case of corticosteroid topical application, vasoconstriction was observed in the papillary ( 56.4 ± 10.9 % ) and reticular ( 45.1 ± 4.71 % ) dermis. For corticosteroid subcutaneous injection, constriction was observed solely in the reticular ( 49.5 ± 9.35 % ) dermis. In contrast, no vasoconstrictions were observed with nonsteroidal topical application.

CONCLUSIONS

Our results indicate that OR-PAM can quantitatively monitor the vasoconstriction induced by corticosteroids, thereby validating OR-PAMs potential as a practical evaluation tool for predicting the effectiveness of corticosteroids in dermatology.

Automated Laser-Fiber Coupling Module for Optical-Resolution Photoacoustic Microscopy

Photoacoustic imaging has emerged as a promising biomedical imaging technique that enables visualization of the optical absorption characteristics of biological tissues in vivo. Among the different photoacoustic imaging system configurations, optical-resolution photoacoustic microscopy stands out by providing high spatial resolution using a tightly focused laser beam, which is typically transmitted through optical fibers. Achieving high-quality images depends significantly on optical fluence, which is directly proportional to the signal-to-noise ratio. Hence, optimizing the laser-fiber coupling is critical. Conventional coupling systems require manual adjustment of the optical path to direct the laser beam into the fiber, which is a repetitive and time-consuming process. In this study, we propose an automated laser-fiber coupling module that optimizes laser delivery and minimizes the need for manual intervention. By incorporating a motor-mounted mirror holder and proportional derivative control, we successfully achieved efficient and robust laser delivery. The performance of the proposed system was evaluated using a leaf-skeleton phantom in vitro and a human finger in vivo, resulting in high-quality photoacoustic images. This innovation has the potential to significantly enhance the quality and efficiency of optical-resolution photoacoustic microscopy.

Artificial Intelligence Assisted Multi-modal Photoacoustic-Ultrasound Imaging for Studying Renal Tissue Function and Hemodynamics

Combined functional-anatomic imaging modalities, which integrate the benefits of visualizing gross anatomy along with the functional or metabolic information of tissue has revolutionized the world of medical imaging. However, such existing imaging modalities are very costly. An alternative option could be a hybrid modality combining contrast-enhanced ultrasound, doppler and photoacoustic imaging. In the current study, we propose an artificial intelligence assisted multi-modal imaging platform where we have used U-net model for segmenting the anatomical features from the ultrasound images obtained from an animal model study. The neural network has performed accurately for three different cases, each with a high dice score. The model was co-validated with doppler images. Further, blood perfusion and tissue oxygenation information from the predicted anatomical structures were also studied. The present findings confirm the feasibility of using this multimodal imaging modality facilitated by artificial intelligence for better understanding of the hemodynamics of the kidney.Clinical Relevance-A multi-modal imaging technique has been proposed which would provide anatomical and functional information to the clinicians for early detection and tracking of the disease prognosis. Unlike existing imaging modalities like PET-CT (Positron Emission Tomography- Computed Tomography), the proposed modality is much more costeffective and radiation free (non-ionizing nature).

Functional photoacoustic imaging: from nano- and micro- to macro-scale

Functional photoacoustic imaging is a promising biological imaging technique that offers such unique benefits as scalable resolution and imaging depth, as well as the ability to provide functional information. At nanoscale, photoacoustic imaging has provided super-resolution images of the surface light absorption characteristics of materials and of single organelles in cells. At the microscopic and macroscopic scales. photoacoustic imaging techniques have precisely measured and quantified various physiological parameters, such as oxygen saturation, vessel morphology, blood flow, and the metabolic rate of oxygen, in both human and animal subjects. This comprehensive review provides an overview of functional photoacoustic imaging across multiple scales, from nano to macro, and highlights recent advances in technology developments and applications. Finally, the review surveys the future prospects of functional photoacoustic imaging in the biomedical field.

Artificial Intelligence-Aided Optical Imaging for Cancer Theranostics

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accuracy and high efficiency in medical decision-making for individualized cancer medicine. In particular, optical imaging methods are able to visualize both the structural and functional information of tumors tissues with high contrast, low cost, and noninvasive property. However, no systematic work has been performed to inspect the recent advances on AI-aided optical imaging for cancer theranostics. In this review, we demonstrated how AI can guide optical imaging methods to improve the accuracy on tumor detection, automated analysis and prediction of its histopathological section, its monitoring during treatment, and its prognosis by using computer vision, deep learning and natural language processing. By contrast, the optical imaging techniques involved mainly consisted of various tomography and microscopy imaging methods such as optical endoscopy imaging, optical coherence tomography, photoacoustic imaging, diffuse optical tomography, optical microscopy imaging, Raman imaging, and fluorescent imaging. Meanwhile, existing problems, possible challenges and future prospects for AI-aided optical imaging protocol for cancer theranostics were also discussed. It is expected that the present work can open a new avenue for precision oncology by using AI and optical imaging tools.

Panoramic volumetric clinical handheld photoacoustic and ultrasound imaging

Photoacoustic (PA) imaging has gained much attention, providing structural and functional information in combination with clinical ultrasound (US) imaging systems. 2D PA and US imaging is easily implemented, but its heavy dependence on operator skills makes 3D imaging preferable. In this study, we propose a panoramic volumetric clinical PA and US imaging system equipping a handheld imaging scanner weighing 600 g and measuring 70 × 62 × 110 mm³. Multiple PA/US scans were performed to cover a large field-of-view (FOV), and the acquired PA/US volumes were mosaic-stitched after manually correcting the positions and rotations in a total of 6 degrees of freedom. PA and US maximum amplitude projection images were visualized online, while spectral unmixed data was quantified offline. The performance of the system was tested via tissue-mimicking phantom experiments. The system's potential was confirmed in vivo by panoramically imaging vascular networks in human arms and necks, with FOVs of 331 × 38 and 129 × 120 mm², respectively. Further, we quantified hemoglobin oxygen saturation levels in the radial artery, brachial artery, carotid artery, and jugular vein. We hope that this system can be applied for various clinical fields such as cardiovascular imaging, dermatology, vascular surgery, internal medicine, and oncology.

Azimuth mapping of fibrous tissue in linear dichroism-sensitive photoacoustic microscopy

Photoacoustic imaging (PAI) has emerged as a molecular-selective imaging technology based on optical absorption contrast. Dichroism-sensitive photoacoustic (DS-PA) imaging has been reported, where the absorption coefficient has a vector characteristic, featuring dimensions of contrast in polarization and wavelength. Herein, we present a DS-PA microscopy (DS-PAM) system that implements optical anisotropy contrast and molecular selectivity. Moreover, we propose mathematical solutions to fully derive dichroic properties. A wavelength for the PAI of collagenous tissue was used, and the proposed algorithms were validated using linear dichroic materials. We successfully mapped dichroic information in fibrous tissue imaging based on the degree of anisotropy and axis orientation, and also deduced mechanical assessment from the tissue arrangement. The proposed DS-PAM system and algorithms have great potential in various diagnostic fields using polarimetry, such as musculoskeletal and cardiovascular systems.

Review on ultrasound-guided photoacoustic imaging for complementary analyses of biological systems in vivo

Photoacoustic imaging has been developed as a new biomedical molecular imaging modality. Due to its similarity to conventional ultrasound imaging in terms of signal detection and image generation, dual-modal photoacoustic and ultrasound imaging has been applied to visualize physiological and morphological information in biological systems in vivo. By complementing each other, dual-modal photoacoustic and ultrasound imaging showed synergistic advances in photoacoustic imaging with the guidance of ultrasound images. In this review, we introduce our recent progresses in dual-modal photoacoustic and ultrasound imaging systems at various scales of study, from preclinical small animals to clinical humans. A summary of the works reveals various strategies for combining the structural information of ultrasound images with the molecular information of photoacoustic images.

Photoacoustic imaging with limited sampling: a review of machine learning approaches

Photoacoustic imaging combines high optical absorption contrast and deep acoustic penetration, and can reveal structural, molecular, and functional information about biological tissue non-invasively. Due to practical restrictions, photoacoustic imaging systems often face various challenges, such as complex system configuration, long imaging time, and/or less-than-ideal image quality, which collectively hinder their clinical application. Machine learning has been applied to improve photoacoustic imaging and mitigate the otherwise strict requirements in system setup and data acquisition. In contrast to the previous reviews of learned methods in photoacoustic computed tomography (PACT), this review focuses on the application of machine learning approaches to address the limited spatial sampling problems in photoacoustic imaging, specifically the limited view and undersampling issues. We summarize the relevant PACT works based on their training data, workflow, and model architecture. Notably, we also introduce the recent limited sampling works on the other major implementation of photoacoustic imaging, i.e., photoacoustic microscopy (PAM). With machine learning-based processing, photoacoustic imaging can achieve improved image quality with modest spatial sampling, presenting great potential for low-cost and user-friendly clinical applications.

In vivo photoacoustic monitoring of vasoconstriction induced by acute hyperglycemia

Postprandial hyperglycemia, blood glucose spikes, induces endothelial dysfunction, increasing cardiovascular risks. Endothelial dysfunction leads to vasoconstriction, and observation of this phenomenon is important for understanding acute hyperglycemia. However, high-resolution imaging of microvessels during acute hyperglycemia has not been fully developed. Here, we demonstrate that photoacoustic microscopy can noninvasively monitor morphological changes in blood vessels of live animals' extremities when blood glucose rises rapidly. As blood glucose level rose from 100 to 400 mg/dL following intraperitoneal glucose injection, heart/breath rate, and body temperature remained constant, but arterioles constricted by approximately -5.7 ± 1.1% within 20 min, and gradually recovered for another 40 min. In contrast, venular diameters remained within about 0.6 ± 1.5% during arteriolar constriction. Our results experimentally and statistically demonstrate that acute hyperglycemia produces transitory vasoconstriction in arterioles, with an opposite trend of change in blood glucose. These findings could help understanding vascular glucose homeostasis and the relationship between diabetes and cardiovascular diseases.

Bimetallic Hyaluronate-Modified Au@Pt Nanoparticles for Noninvasive Photoacoustic Imaging and Photothermal Therapy of Skin Cancer

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.

Recent Advances in Photoacoustic Agents for Theranostic Applications

Photoacoustic agents are widely used in various theranostic applications. By evaluating the biodistribution obtained from photoacoustic images, the effectiveness of theranostic agents in terms of their delivery efficiency and treatment responses can be analyzed. Through this study, we evaluate and summarize the recent advances in photoacoustic-guided phototherapy, particularly in photothermal and photodynamic therapy. This overview can guide the future directions for theranostic development. Because of the recent applications of photoacoustic imaging in clinical trials, theranostic agents with photoacoustic monitoring have the potential to be translated into the clinical world.

Recent Advances in Contrast-Enhanced Photoacoustic Imaging: Overcoming the Physical and Practical Challenges

For decades now, photoacoustic imaging (PAI) has been investigated to realize its potential as a niche biomedical imaging modality. Despite its highly desirable optical contrast and ultrasonic spatiotemporal resolution, PAI is challenged by such physical limitations as a low signal-to-noise ratio (SNR), diminished image contrast due to strong optical attenuation, and a lower-bound on spatial resolution in deep tissue. In addition, contrast-enhanced PAI has faced practical limitations such as insufficient cell-specific targeting due to low delivery efficiency and difficulties in developing clinically translatable agents. Identifying these limitations is essential to the continuing expansion of the field, and substantial advances in developing contrast-enhancing agents, complemented by high-performance image acquisition systems, have synergistically dealt with the challenges of conventional PAI. This review covers the past four years of research on pushing the physical and practical challenges of PAI in terms of SNR/contrast, spatial resolution, targeted delivery, and clinical application. Promising strategies for dealing with each challenge are reviewed in detail, and future research directions for next generation contrast-enhanced PAI are discussed.

Wide-field three-dimensional photoacoustic/ultrasound scanner using a two-dimensional matrix transducer array

Two-dimensional matrix transducer arrays are the most appropriate imaging probes for acquiring dual-modal 3D photoacoustic (PA)/ultrasound (US) images. However, they have small footprints which limit the field-of-view (FOV) to less than 10 mm × 10 mm and degrade the spatial resolution. In this study, we demonstrate a dual-modal PA and US imaging system (using a 2D matrix transducer array and a motorized 2D scanning system) to enlarge the FOV of volumetric images. Multiple PA volumes were merged to form a wide-field image of approximately 45 mm × 45 mm. In vivo imaging was demonstrated using rat sentinel lymph nodes (SLNs) and bladders stained with methylene blue. We believe that this volumetric PA/US imaging technique with a 2D matrix transducer array can be a useful tool for narrow-field real-time monitoring and wide-field imaging of various preclinical and clinical studies.

Simultaneous Functional Magnetic Resonance and Optoacoustic Imaging of Brain-Wide Sensory Responses in Mice

Functional magnetic resonance imaging (fMRI) has massively contributed to the understanding of mammalian brain function. However, the origin and interpretation of the blood oxygen level-dependent (BOLD) signals retrieved by fMRI remain highly disputed. This article reports on the development of a fully hybridized system enabling concurrent functional magnetic resonance optoacoustic tomography (MROT) measurements of stimulus-evoked brain-wide sensory responses in mice. The highly complementary angiographic and soft tissue contrasts of both modalities along with simultaneous multi-parametric readings of stimulus-evoked hemodynamic responses are leveraged in order to establish unequivocal links between the various counteracting physiological and metabolic processes in the brain. The results indicate that the BOLD signals are highly correlated, both spatially and temporally, with the total hemoglobin readings resolved with volumetric multi-spectral optoacoustic tomography. Furthermore, the differential oxygenated and deoxygenated hemoglobin optoacoustic readings exhibit superior sensitivity as compared to the BOLD signals when detecting stimulus-evoked hemodynamic responses. The fully hybridized MROT approach greatly expands the neuroimaging toolset to comprehensively study neurovascular and neurometabolic coupling mechanisms and related diseases.

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.

Motion Compensation for 3D Multispectral Handheld Photoacoustic Imaging

Three-dimensional (3D) handheld photoacoustic (PA) and ultrasound (US) imaging performed using mechanical scanning are more useful than conventional 2D PA/US imaging for obtaining local volumetric information and reducing operator dependence. In particular, 3D multispectral PA imaging can capture vital functional information, such as hemoglobin concentrations and hemoglobin oxygen saturation (sO₂), of epidermal, hemorrhagic, ischemic, and cancerous diseases. However, the accuracy of PA morphology and physiological parameters is hampered by motion artifacts during image acquisition. The aim of this paper is to apply appropriate correction to remove the effect of such motion artifacts. We propose a new motion compensation method that corrects PA images in both axial and lateral directions based on structural US information. 3D PA/US imaging experiments are performed on a tissue-mimicking phantom and a human wrist to verify the effects of the proposed motion compensation mechanism and the consequent spectral unmixing results. The structural motions and sO₂ values are confirmed to be successfully corrected by comparing the motion-compensated images with the original images. The proposed method is expected to be useful in various clinical PA imaging applications (e.g., breast cancer, thyroid cancer, and carotid artery disease) that are susceptible to motion contamination during multispectral PA image analysis.

Deep Learning Enhances Multiparametric Dynamic Volumetric Photoacoustic Computed Tomography In Vivo (DL-PACT)

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.

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.

Whole-Body Photoacoustic Imaging Techniques for Preclinical Small Animal Studies

Photoacoustic imaging is a hybrid imaging technique that has received considerable attention in biomedical studies. In contrast to pure optical imaging techniques, photoacoustic imaging enables the visualization of optical absorption properties at deeper imaging depths. In preclinical small animal studies, photoacoustic imaging is widely used to visualize biodistribution at the molecular level. Monitoring the whole-body distribution of chromophores in small animals is a key method used in preclinical research, including drug-delivery monitoring, treatment assessment, contrast-enhanced tumor imaging, and gastrointestinal tracking. In this review, photoacoustic systems for the whole-body imaging of small animals are explored and summarized. The configurations of the systems vary with the scanning methods and geometries of the ultrasound transducers. The future direction of research is also discussed with regard to achieving a deeper imaging depth and faster imaging speed, which are the main factors that an imaging system should realize to broaden its application in biomedical studies.