Another decade of photoacoustic imaging

In vivo quantitative characterization of nano adjuvant transport in the tracheal layer by photoacoustic imaging

Adjuvants are indispensable ingredients in vaccine formulations. Evaluating the in vivo transport processes of adjuvants, particularly for inhalation formulations, presents substantial challenges. In this study, a nanosized adjuvant aluminum hydroxide (AlOOH) was synthesized and labeled with indocyanine green (ICG) and bovine serum albumin (BSA) to achieve strong optical absorption ability and high biocompatibility. The adjuvant nanomaterials (BSA@ICG@AlOOH, BIA) were delivered as an aerosol into the airways of mice, its distribution was monitored using photoacoustic imaging (PAI) in vivo. PAI results illustrated the gradual cross-layer transmission process of BIA in the tracheal layer, traversing approximately 250 µm from the inner layer of the trachea to the outer layer. The results were consistent with pathology. While the intensity of the BIA reduced by approximately 46.8% throughout the transport process. The ability of PAI for quantitatively characterized the dynamic transport process of adjuvant within the tracheal layer may be widely used in new vaccine development.

Compressed Sensing for Biomedical Photoacoustic Imaging: A Review

Photoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging. Abnormal biological tissues (such as tumors and inflammation) generate different levels of thermal expansion after absorbing optical energy, producing distinct acoustic signals from normal tissues. This technique can detect small tissue lesions in biological tissues and has demonstrated significant potential for applications in tumor research, melanoma detection, and cardiovascular disease diagnosis. During the process of collecting photoacoustic signals in a PAI system, various factors can influence the signals, such as absorption, scattering, and attenuation in biological tissues. A single ultrasound transducer cannot provide sufficient information to reconstruct high-precision photoacoustic images. To obtain more accurate and clear image reconstruction results, PAI systems typically use a large number of ultrasound transducers to collect multi-channel signals from different angles and positions, thereby acquiring more information about the photoacoustic signals. Therefore, to reconstruct high-quality photoacoustic images, PAI systems require a significant number of measurement signals, which can result in substantial hardware and time costs. Compressed sensing is an algorithm that breaks through the Nyquist sampling theorem and can reconstruct the original signal with a small number of measurement signals. PAI based on compressed sensing has made breakthroughs over the past decade, enabling the reconstruction of low artifacts and high-quality images with a small number of photoacoustic measurement signals, improving time efficiency, and reducing hardware costs. This article provides a detailed introduction to PAI based on compressed sensing, such as the physical transmission model-based compressed sensing method, two-stage reconstruction-based compressed sensing method, and single-pixel camera-based compressed sensing method. Challenges and future perspectives of compressed sensing-based PAI are also discussed.

Development and validation of nomograms using photoacoustic imaging and 2D ultrasound to predict breast nodule benignity and malignancy

BACKGROUND

The application of photoacoustic imaging (PAI), utilizing laser-induced ultrasound, shows potential in assessing blood oxygenation in breast nodules. However, its effectiveness in distinguishing between malignant and benign nodules remains insufficiently explored.

PURPOSE

This study aims to develop nomogram models for predicting the benign or malignant nature of breast nodules using PAI.

METHOD

A prospective cohort study enrolled 369 breast nodules, subjecting them to PAI and ultrasound examination. The training and testing cohorts were randomly divided into two cohorts in a ratio of 3:1. Based on the source of the variables, three models were developed, Model 1: photoacoustic-BIRADS+BMI + blood oxygenation, Model 2: BIRADS+Shape+Intranodal blood (Doppler) + BMI, Model 3: photoacoustic-BIRADS+BIRADS+ Shape+Intranodal blood (Doppler) + BMI + blood oxygenation. Risk factors were identified through logistic regression, resulting in the creation of three predictive models. These models were evaluated using calibration curves, subject receiver operating characteristic (ROC), and decision curve analysis.

RESULTS

The area under the ROC curve for the training cohort was 0.91 (95% confidence interval, 95% CI: 0.88-0.95), 0.92 (95% CI: 0.89-0.95), and 0.97 (95% CI: 0.96-0.99) for Models 1-3, and the ROC curve for the testing cohort was 0.95 (95% CI: 0.91-0.98), 0.89 (95% CI: 0.83-0.96), and 0.97 (95% CI: 0.95-0.99) for Models 1-3.

CONCLUSIONS

The calibration curves demonstrate that the model's predictions agree with the actual values. Decision curve analysis suggests a good clinical application.

Photoacoustic Imaging as a Novel Non-invasive Biomarker to Assess Intestinal Tissue Oxygenation and Motility in Neonatal Rats

BACKGROUND

Within the premature infant intestine, oxygenation and motility play key physiological roles in healthy development and disease such as necrotizing enterocolitis. To date, there are limited techniques to reliably assess these physiological functions that are also clinically feasible for critically ill infants. To address this clinical need, we hypothesized that photoacoustic imaging (PAI) can provide non-invasive assessment of intestinal tissue oxygenation and motility to characterize intestinal physiology and health.

METHODS

Ultrasound and photoacoustic images were acquired in 2-day and 4-day old neonatal rats. For PAI assessment of intestinal tissue oxygenation, an inspired gas challenge was performed using hypoxic, normoxic, and hyperoxic inspired oxygen (FiO2). For intestinal motility, oral administration of ICG contrast agent was used to compare control animals to an experimental model of loperamide-induced intestinal motility inhibition.

RESULTS

PAI demonstrated progressive increases in oxygen saturation (sO2) as FiO2 increased, while the pattern of oxygen localization remained relatively consistent in both 2-day and 4-day old neonatal rats. Analysis of intraluminal ICG contrast enhanced PAI images yielded a map of the motility index in control and loperamide treated rats. From PAI analysis, loperamide significantly inhibited intestinal motility, with a 32.6% decrease in intestinal motility index scores in 4-day old rats.

CONCLUSION

These data establish the feasibility and application of PAI to non-invasively and quantitatively measure intestinal tissue oxygenation and motility. This proof-of-concept study is an important first step in developing and optimizing photoacoustic imaging to provide valuable insight into intestinal health and disease to improve the care of premature infants.

Reconstructing microvascular network skeletons from 3D images: What is the ground truth?

Structural changes to microvascular networks are increasingly highlighted as markers of pathogenesis in a wide range of disease, e.g. Alzheimer's disease, vascular dementia and tumour growth. This has motivated the development of dedicated 3D imaging techniques, alongside the creation of computational modelling frameworks capable of using 3D reconstructed networks to simulate functional behaviours such as blood flow or transport processes. Extraction of 3D networks from imaging data broadly consists of two image processing steps: segmentation followed by skeletonisation. Much research effort has been devoted to segmentation field, and there are standard and widely-applied methodologies for creating and assessing gold standards or ground truths produced by manual annotation or automated algorithms. The Skeletonisation field, however, lacks widely applied, simple to compute metrics for the validation or optimisation of the numerous algorithms that exist to extract skeletons from binary images. This is particularly problematic as 3D imaging datasets increase in size and visual inspection becomes an insufficient validation approach. In this work, we first demonstrate the extent of the problem by applying 4 widely-used skeletonisation algorithms to 3 different imaging datasets. In doing so we show significant variability between reconstructed skeletons of the same segmented imaging dataset. Moreover, we show that such a structural variability propagates to simulated metrics such as blood flow. To mitigate this variability we introduce a new, fast and easy to compute super metric that compares the volume, connectivity, medialness, bifurcation point identification and homology of the reconstructed skeletons to the original segmented data. We then show that such a metric can be used to select the best performing skeletonisation algorithm for a given dataset, as well as to optimise its parameters. Finally, we demonstrate that the super metric can also be used to quickly identify how a particular skeletonisation algorithm could be improved, becoming a powerful tool in understanding the complex implication of small structural changes in a network.

Recent advances in DNA-based probes for photoacoustic imaging

Photoacoustic imaging(PAI) is a widely developing imaging modality that has seen tremendous evolvement in the last decade. PAI has gained the upper hand in the imaging field as it takes advantage of optical absorption and ultrasound detection that imparts higher resolution, rich contrast and elevated penetration depth. Unlike other imaging techniques, PAI does not use ionising radiation and is a better, cost-effective and healthier alternative to other imaging techniques. It offers greater specificity than conventional ultrasound imaging with the ability to detect haemoglobin, lipids, water and other light-absorbing chromophores. These properties of PAI have led to its extended applications in the biomedical field in the treatment of diseases such as cancer. This paper reviews how DNA probes have been used in PAI, the various techniques by which it has been modified, and their role in the process. We also focus on different nanocomposites containing DNA having PAI and photothermal therapy(PTT) properties for detection, diagnosis and therapy, its constituents and the role of DNA in it.

Low-Cost Scalable PCB-Based 2-D Transducer Arrays for Volumetric Photoacoustic Imaging

Photoacoustic (PA) imaging provides deep tissue molecular imaging of chromophores with optical absorption contrast and ultrasonic resolution. Present PA imaging techniques are predominantly limited to one 2D plane per acquisition. 2D ultrasound transducers, required for real-time 3D PA imaging, are high-cost, complex to fabricate and have limited scalability in design. We present novel PCB-based 2D matrix ultrasound transducer arrays that are capable of being bulk manufactured at low-cost without using laborious ultrasound fabrication tools. The 2D ultrasound array specifications are easily scalable with respect to widely available PCB design and fabrication tools at low cost. To demonstrate scalability, we fabricated low (11 MHz) frequency 8x8 matrix array and high (40 MHz) frequency 4x4 matrix array by directly bonding an undiced polyvinylidene fluoride (PVDF) piezoelectric material of desired thickness to the custom designed PCB substrate. Characterization results demonstrate wideband PA receive sensitivity for both low (87%) and high (188%) frequency arrays. Volumetric PA imaging results of light absorbing targets inside optical scattering medium demonstrate improved spatial resolution and field of view with increase in aperture size.

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.

Intravital photoacoustic brain stimulation with high-precision

Significance

Neural regulation at high precision vitally contributes to propelling fundamental understanding in the field of neuroscience and providing innovative clinical treatment options. Recently, photoacoustic brain stimulation has emerged as a cutting-edge method for precise neuromodulation and shows great potential for clinical application.

Aim

The goal of this perspective is to outline the advancements in photoacoustic brain stimulation in recent years. And, we also provide an outlook delineating several prospective paths through which this burgeoning approach may be substantively refined for augmented capability and wider implementations.

Approach

First, the mechanisms of photoacoustic generation as well as the potential mechanisms of photoacoustic brain stimulation are provided and discussed. Then, the state-of-the-art achievements corresponding to this technology are reviewed. Finally, future directions for photoacoustic technology in neuromodulation are provided.

Results

Intensive research endeavors have prompted substantial advancements in photoacoustic brain stimulation, illuminating the unique advantages of this modality for noninvasive and high-precision neuromodulation via a nongenetic way. It is envisaged that further technology optimization and randomized prospective clinical trials will enable a wide acceptance of photoacoustic brain stimulation in clinical practice.

Conclusions

The innovative practice of photoacoustic technology serves as a multifaceted neuromodulation approach, possessing noninvasive, high-accuracy, and nongenetic characteristics. It has a great potential that could considerably enhance not only the fundamental underpinnings of neuroscience research but also its practical implementations in a clinical setting.

Ultrasound-guided needle tracking with deep learning: A novel approach with photoacoustic ground truth

Accurate needle guidance is crucial for safe and effective clinical diagnosis and treatment procedures. Conventional ultrasound (US)-guided needle insertion often encounters challenges in consistency and precisely visualizing the needle, necessitating the development of reliable methods to track the needle. As a powerful tool in image processing, deep learning has shown promise for enhancing needle visibility in US images, although its dependence on manual annotation or simulated data as ground truth can lead to potential bias or difficulties in generalizing to real US images. Photoacoustic (PA) imaging has demonstrated its capability for high-contrast needle visualization. In this study, we explore the potential of PA imaging as a reliable ground truth for deep learning network training without the need for expert annotation. Our network (UIU-Net), trained on ex vivo tissue image datasets, has shown remarkable precision in localizing needles within US images. The evaluation of needle segmentation performance extends across previously unseen ex vivo data and in vivo human data (collected from an open-source data repository). Specifically, for human data, the Modified Hausdorff Distance (MHD) value stands at approximately 3.73, and the targeting error value is around 2.03, indicating the strong similarity and small needle orientation deviation between the predicted needle and actual needle location. A key advantage of our method is its applicability beyond US images captured from specific imaging systems, extending to images from other US imaging systems.

Multikernel positional embedding convolutional neural network for photoacoustic reconstruction with sparse data

Photoacoustic imaging (PAI) is an emerging noninvasive imaging modality that merges the high contrast of optical imaging with the high resolution of ultrasonic imaging. Low-quality photoacoustic reconstruction with sparse data due to sparse spatial sampling and limited view detection is a major obstacle to the popularization of PAI for medical applications. Deep learning has been considered as the best solution to this problem in the past decade. In this paper, we propose what we believe to be a novel architecture, named DPM-UNet, which consists of the U-Net backbone with additional position embedding block and two multi-kernel-size convolution blocks, a dilated dense block and dilated multi-kernel-size convolution block. Our method was experimentally validated with both simulated data and in vivo data, achieving a SSIM of 0.9824 and a PSNR of 33.2744 dB. Furthermore, the reconstructed images of our proposed method were compared with those obtained by other advanced methods. The results have shown that our proposed DPM-UNet has a great advantage in PAI over other methods with respect to the imaging effect and memory consumption.

Imagining the future of optical microscopy: everything, everywhere, all at once

The optical microscope has revolutionized biology since at least the 17th Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once - from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.

A PD-L1 targeting nanotheranostic for effective photoacoustic imaging guided photothermal-immunotherapy of tumor

Tumor immunotherapy has been partly effective for specific cancers. However, problems such as low immune response, limited antitumor effectiveness, and high antibody costs still persist. Synergistic therapeutic approaches, such as immune checkpoint inhibition in conjunction with photothermal therapy and photoacoustic imaging, are expected to provide approaches for more precise and efficient immunotherapy of tumors. Furthermore, developing alternatives for antibodies, such as PD-L1 aptamers and nanocarriers, would reduce the cost of tumor immunotherapy. Herein, we develop a PD-L1-targeting nanotheranostic to block immune checkpoints for synergistic photothermal-immunotherapy against tumors, along with effective photoacoustic (PA) imaging. The nanotheranostic is synthesized by the modification of gold nanorods (GNRs) with the PD-L1 aptamer (APDL1), which can sensitively and specifically recognize PD-L1 on the tumor cell surface, and mediate nanoparticle accumulation and strong PA signals in tumors. The aptamer is released from GNR through a competition of glutathione (GSH) and is then functionalized as a PD-L1 blockade. In collaboration with the concurrent photothermal therapy, antitumor immunity is significantly augmented by enhancing the filtration of matured dendritic cells and suppressing regulatory T cells, followed by the activation of cytotoxic T cells and inhibition of T cell exhaustion. Such a nanotheranostic modality effectively suppresses tumor growth in mice, representing an appealing platform for both biological imaging and photoimmunotherapy of tumors.

Monodisperse Sub-100 nm Au Nanoshells for Low-Fluence Deep-Tissue Photoacoustic Imaging

Nanoparticles with high absorption cross sections will advance therapeutic and bioimaging nanomedicine technologies. While Au nanoshells have shown great promise in nanomedicine, state-of-the-art synthesis methods result in scattering-dominant particles, mitigating their efficacy in absorption-based techniques that leverage the photothermal effect, such as photoacoustic (PA) imaging. We introduce a highly reproducible synthesis route to monodisperse sub-100 nm Au nanoshells with an absorption-dominant optical response. Au nanoshells with 48 nm SiO2 cores and 7 nm Au shells show a 14-fold increase in their volumetric absorption coefficient compared to commercial Au nanoshells with dimensions commonly used in nanomedicine. PA imaging with Au nanoshell contrast agents showed a 50% improvement in imaging depth for sub-100 nm Au nanoshells compared with the smallest commercially available nanoshells in a turbid phantom. Furthermore, the high PA signal at low fluences, enabled by sub-100 nm nanoshells, will aid the deployment of low-cost, low-fluence light-emitting diodes for PA imaging.

Spiral volumetric optoacoustic tomography for imaging whole-body biodynamics in small animals

Fast tracking of biological dynamics across multiple murine organs using the currently commercially available whole-body preclinical imaging systems is hindered by their limited contrast, sensitivity and spatial or temporal resolution. Spiral volumetric optoacoustic tomography (SVOT) provides optical contrast, with an unprecedented level of spatial and temporal resolution, by rapidly scanning a mouse using spherical arrays, thus overcoming the current limitations in whole-body imaging. The method enables the visualization of deep-seated structures in living mammalian tissues in the near-infrared spectral window, while further providing unrivalled image quality and rich spectroscopic optical contrast. Here, we describe the detailed procedures for SVOT imaging of mice and provide specific details on how to implement a SVOT system, including component selection, system arrangement and alignment, as well as the image processing methods. The step-by-step guide for the rapid panoramic (360°) head-to-tail whole-body imaging of a mouse includes the rapid visualization of contrast agent perfusion and biodistribution. The isotropic spatial resolution possible with SVOT can reach 90 µm in 3D, while alternative steps enable whole-body scans in less than 2 s, unattainable with other preclinical imaging modalities. The method further allows the real-time (100 frames per second) imaging of biodynamics at the whole-organ level. The multiscale imaging capacity provided by SVOT can be used for visualizing rapid biodynamics, monitoring responses to treatments and stimuli, tracking perfusion, and quantifying total body accumulation and clearance dynamics of molecular agents and drugs. Depending on the imaging procedure, the protocol requires 1-2 h to complete by users trained in animal handling and biomedical imaging.

Photoacoustic Imaging as a Novel Non-Invasive Biomarker to Assess Intestinal Tissue Oxygenation and Motility in Neonatal Rats

Background

Within the premature infant intestine, oxygenation and motility play key physiological roles in healthy development and disease such as necrotizing enterocolitis. To date, there are limited techniques to reliably assess these physiological functions that are also clinically feasible for critically ill infants. To address this clinical need, we hypothesized that photoacoustic imaging (PAI) can provide non-invasive assessment of intestinal tissue oxygenation and motility to characterize intestinal physiology and health.

Methods

Ultrasound and photoacoustic images were acquired in 2-day and 4-day old neonatal rats. For PAI assessment of intestinal tissue oxygenation, an inspired gas challenge was performed using hypoxic, normoxic, and hyperoxic inspired oxygen (FiO2). For intestinal motility, oral administration of ICG contrast agent was used to compare control animals to an experimental model of loperamide-induced intestinal motility inhibition.

Results

PAI demonstrated progressive increases in oxygen saturation (sO2) as FiO2 increased, while the pattern of oxygen localization remained relatively consistent in both 2-day and 4-day old neonatal rats. Analysis of intraluminal ICG contrast enhanced PAI images yielded a map of the motility index in control and loperamide treated rats. From PAI analysis, loperamide significantly inhibited intestinal motility, with a 32.6% decrease in intestinal motility index scores in 4-day old rats.

Conclusion

These data establish the feasibility and application of PAI to non-invasively and quantitatively measure intestinal tissue oxygenation and motility. This proof-of-concept study is an important first step in developing and optimizing photoacoustic imaging to provide valuable insight into intestinal health and disease to improve the care of premature infants.

Highlights

Intestinal tissue oxygenation and intestinal motility are important biomarkers of intestinal physiology in health and disease of premature infants.This proof-of-concept preclinical rat study is the first to report application of photoacoustic imaging for the neonatal intestine.Photoacoustic imaging is demonstrated as a promising non-invasive diagnostic imaging method for quantifying intestinal tissue oxygenation and intestinal motility in premature infants.

Graphical abstract

Enzyme-Triggered Transforming of Assembly Peptide-Modified Magnetic Resonance-Tuned Probe for Highly Sensitive Imaging of Bacterial Infection In Vivo

Confirming bacterial infection at an early stage and distinguishing between sterile inflammation and bacterial infection is still highly needed for efficient treatment. Here, in situ highly sensitive magnetic resonance imaging (MRI) bacterial infection in vivo based on a peptide-modified magnetic resonance tuning (MRET) probe (MPD-1) that responds to matrix metallopeptidase 2 (MMP-2) highly expressed in bacteria-infected microenvironments is achieved. MPD-1 is an assembly of magnetic nanoparticle (MNP) bearing with gadolinium ion (Gd3+ ) modified MMP-2-cleavable self-assembled peptide (P1 ) and bacteria-targeting peptide (P), and it shows T2 -weighted signal due to the assemble of MNP and MRET ON phenomenon between MNP assembly and Gd3+ . Once MPD-1 accumulates at the bacterially infected site, P1 included in MPD-1 is cleaved explicitly by MMP-2, which triggers the T2 contrast agent of MPD-1 to disassemble into the monomer of MNP, leading the recovery of T1 -weighted signal. Simultaneously, Gd3+ detaches from MNP, further enhancing the T1 -weighted signal due to MRET OFF. The sensitive MRI of Staphylococcus aureus (low to 104 CFU) at the myositis site and accurate differentiation between sterile inflammation and bacterial infection based on the proposed MPD-1 probe suggests that this novel probe would be a promising candidate for efficiently detecting bacterial infection in vivo.

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.

Head-to-tail imaging of mice with spiral volumetric optoacoustic tomography

Optoacoustic tomography has been established as a powerful modality for preclinical imaging. However, efficient whole-body imaging coverage has not been achieved owing to the arduous requirement for continuous acoustic coupling around the animal. In this work, we introduce panoramic (360⁰) head-to-tail 3D imaging of mice with spiral volumetric optoacoustic tomography (SVOT). The system combines multi-beam illumination and a dedicated head holder enabling uninterrupted acoustic coupling for whole-body scans. Image fidelity is optimized with self-gated respiratory motion rejection and dual speed-of-sound reconstruction algorithms to attain spatial resolution down to 90 µm. The developed system is thus highly suitable for visualizing rapid biodynamics across scales, such as hemodynamic changes in individual organs, responses to treatments and stimuli, perfusion, total body accumulation, or clearance of molecular agents and drugs with unmatched contrast, spatial and temporal resolution.

Adaptive enhancement of acoustic resolution photoacoustic microscopy imaging via deep CNN prior

Acoustic resolution photoacoustic microscopy (AR-PAM) is a promising medical imaging modality that can be employed for deep bio-tissue imaging. However, its relatively low imaging resolution has greatly hindered its wide applications. Previous model-based or learning-based PAM enhancement algorithms either require design of complex handcrafted prior to achieve good performance or lack the interpretability and flexibility that can adapt to different degradation models. However, the degradation model of AR-PAM imaging is subject to both imaging depth and center frequency of ultrasound transducer, which varies in different imaging conditions and cannot be handled by a single neural network model. To address this limitation, an algorithm integrating both learning-based and model-based method is proposed here so that a single framework can deal with various distortion functions adaptively. The vasculature image statistics is implicitly learned by a deep convolutional neural network, which served as plug and play (PnP) prior. The trained network can be directly plugged into the model-based optimization framework for iterative AR-PAM image enhancement, which fitted for different degradation mechanisms. Based on physical model, the point spread function (PSF) kernels for various AR-PAM imaging situations are derived and used for the enhancement of simulation and in vivo AR-PAM images, which collectively proved the effectiveness of proposed method. Quantitatively, the PSNR and SSIM values have all achieve best performance with the proposed algorithm in all three simulation scenarios; The SNR and CNR values have also significantly raised from 6.34 and 5.79 to 35.37 and 29.66 respectively in an in vivo testing result with the proposed algorithm.

Signal restoration algorithm for photoacoustic imaging systems

In a photoacoustic (PA) imaging system, the detectors are bandwidth-limited. Therefore, they capture PA signals with some unwanted ripples. This limitation degrades the resolution/contrast and induces sidelobes and artifacts in the reconstructed images along the axial direction. To compensate for the limited bandwidth effect, we present a PA signal restoration algorithm, where a mask is designed to extract the signals at the absorber positions and remove the unwanted ripples. This restoration improves the axial resolution and contrast in the reconstructed image. The restored PA signals can be considered as the input of the conventional reconstruction algorithms (e.g., Delay-and-sum (DAS) and Delay-multiply-and-sum (DMAS)). To compare the performance of the proposed method, DAS and DMAS reconstruction algorithms were performed with both the initial and restored PA signals on numerical and experimental studies (numerical targets, tungsten wires, and human forearm). The results show that, compared with the initial PA signals, the restored PA signals can improve the axial resolution and contrast by 45% and 16.1 dB, respectively, and suppress background artifacts by 80%.

Ultrasound nanotheranostics: Toward precision medicine

Ultrasound (US) is a mechanical wave that can penetrate biological tissues and trigger complex bioeffects. The mechanisms of US in different diagnosis and treatment are different, and the functional application of commercial US is also expanding. In particular, recent developments in nanotechnology have led to a wider use of US in precision medicine. In this review, we focus on US in combination with versatile micro and nanoparticles (NPs)/nanovesicles for tumor theranostics. We first introduce US-assisted drug delivery as a stimulus-responsive approach that spatiotemporally regulates the deposit of nanomedicines in target tissues. Multiple functionalized NPs and their US-regulated drug-release curves are analyzed in detail. Moreover, as a typical representative of US therapy, sonodynamic antitumor strategy is attracting researchers' attention. The collaborative efficiency and mechanisms of US and various nano-sensitizers such as nano-porphyrins and organic/inorganic nanosized sensitizers are outlined in this paper. A series of physicochemical processes during ultrasonic cavitation and NPs activation are also discussed. Finally, the new applications of US and diagnostic NPs in tumor-monitoring and image-guided combined therapy are summarized. Diagnostic NPs contain substances with imaging properties that enhance US contrast and photoacoustic imaging. The development of such high-resolution, low-background US-based imaging methods has contributed to modern precision medicine. It is expected that the integration of non-invasive US and nanotechnology will lead to significant breakthroughs in future clinical applications.

Feasibility of photoacoustic-guided ultrasound treatment for port wine stains

BACKGROUND AND OBJECTIVES

Port wine birthmark, also known as port wine stain (PWS) is a skin discoloration characterized by red/purple patches caused by vascular malformation. PWS is typically treated by using lasers to destroy abnormal blood vessels. The laser heating facilitates selective photothermolysis of the vessels and attenuates quickly in the tissue due to high optical scattering. Therefore, residual abnormal capillaries deep in the tissue survive and often lead to the resurgence of PWS. Ultrasound (US) has also been proposed to treat PWS, however, it is nonselective with respect to the vasculature but penetrates deeper into the tissue. We aim to study the feasibility of a hybrid PWS treatment modality combining the advantages of both modalities.

MATERIALS AND METHODS

In this manuscript, we propose a photoacoustic (PA) guided US focusing methodology for PWS treatment which combines the optical contrast-based selectivity with US penetration to focus the US energy onto the vasculature. The PA signals collected by the transducers, when time-reversed, amplified, and transmitted, converge onto the PWS, thus minimally affecting the neighboring tissue. We performed two- and three-dimensional simulations that mimic realistic transducers and medium properties in this proof of concept study.

RESULTS

The time-reversed PA signals when transmitted from the transducers converged onto the vasculature, as expected, thus reducing the heating of the neighboring tissue. We observed that while the US focus is indeed affected due to experimental factors such as limited-view, large detector separation and finite detection bandwidth, and so forth, the US did focus completely or partially onto the vasculature demonstrating the feasibility of the proposed methodology.

CONCLUSION

The results demonstrate the potential of the proposed methodology for PWS treatment. This treatment method can destroy the deeper capillaries while minimally heating the neighboring tissue, thus reducing the chances of the resurgence of PWS and as well as cosmetic scarring.

Deep and Domain Transfer Learning Aided Photoacoustic Microscopy: Acoustic Resolution to Optical Resolution

Acoustic resolution photoacoustic micros- copy (AR-PAM) can achieve deeper imaging depth in biological tissue, with the sacrifice of imaging resolution compared with optical resolution photoacoustic microscopy (OR-PAM). Here we aim to enhance the AR-PAM image quality towards OR-PAM image, which specifically includes the enhancement of imaging resolution, restoration of micro-vasculatures, and reduction of artifacts. To address this issue, a network (MultiResU-Net) is first trained as generative model with simulated AR-OR image pairs, which are synthesized with physical transducer model. Moderate enhancement results can already be obtained when applying this model to in vivo AR imaging data. Nevertheless, the perceptual quality is unsatisfactory due to domain shift. Further, domain transfer learning technique under generative adversarial network (GAN) framework is proposed to drive the enhanced image's manifold towards that of real OR image. In this way, perceptually convincing AR to OR enhancement result is obtained, which can also be supported by quantitative analysis. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values are significantly increased from 14.74 dB to 19.01 dB and from 0.1974 to 0.2937, respectively, validating the improvement of reconstruction correctness and overall perceptual quality. The proposed algorithm has also been validated across different imaging depths with experiments conducted in both shallow and deep tissue. The above AR to OR domain transfer learning with GAN (AODTL-GAN) framework has enabled the enhancement target with limited amount of matched in vivo AR-OR imaging data.

Photoacoustic Imaging Probes for Theranostic Applications

Photoacoustic imaging (PAI), an emerging biomedical imaging technology, capitalizes on a wide range of endogenous chromophores and exogenous contrast agents to offer detailed information related to the functional and molecular content of diseased biological tissues. Compared with traditional imaging technologies, PAI offers outstanding advantages, such as a higher spatial resolution, deeper penetrability in biological tissues, and improved imaging contrast. Based on nanomaterials and small molecular organic dyes, a huge number of contrast agents have recently been developed as PAI probes for disease diagnosis and treatment. Herein, we report the recent advances in the development of nanomaterials and organic dye-based PAI probes. The current challenges in the field and future research directions for the designing and fabrication of PAI probes are proposed.

Clinical photoacoustic/ultrasound dual-modal imaging: Current status and future trends

Photoacoustic tomography (PAT) is an emerging biomedical imaging modality that combines optical and ultrasonic imaging, providing overlapping fields of view. This hybrid approach allows for a natural integration of PAT and ultrasound (US) imaging in a single platform. Due to the similarities in signal acquisition and processing, the combination of PAT and US imaging creates a new hybrid imaging for novel clinical applications. Over the recent years, particular attention is paid to the development of PAT/US dual-modal systems highlighting mutual benefits in clinical cases, with an aim of substantially improving the specificity and sensitivity for diagnosis of diseases. The demonstrated feasibility and accuracy in these efforts open an avenue of translating PAT/US imaging to practical clinical applications. In this review, the current PAT/US dual-modal imaging systems are discussed in detail, and their promising clinical applications are presented and compared systematically. Finally, this review describes the potential impacts of these combined systems in the coming future.

Recent progress on bioimaging strategies based on Janus nanoparticles

Janus nanoparticles refer to a kind of asymmetric-structured nanoparticles composed of two or more distinct sides with differences in chemical nature and/or polarity on each side and thus can integrate two or more properties in one single particle. Due to their unique structure and surface properties, Janus nanoparticles have shown broad application potentials in optics, nuclear magnetic resonance, multi-mode imaging, and other fields. Unlike traditional contrast agents used in biological imaging, Janus nanoparticles are asymmetrically and directionally oriented to ensure stable partitioning of individual nanoparticles while integrating more functions. Much advancement have been carried out in the past few years, with some studies partially covering bioimaging applications. However, to our best knowledge, there are still no review papers specifically dedicated to the bioimaging applications with Janus nanoparticles. Bearing this in mind and taking the current challenges in this field into consideration, herein, we discuss representative approaches orchestrated for bioimaging applications, with the focus on the improvement of imaging quality brought by Janus nanoparticles and the development of multifunctional nanoplatforms in biological imaging fields, such as theranostics and therapies. Finally, based on the research experience of our group in this field, prospects for future research trends are put forward to provide new ideas for designing new Janus nanoparticles for clinical bioimaging.

Lighting up Micro-/Nanorobots with Fluorescence

Micro-/nanorobots (MNRs) can be autonomously propelled on demand in complex biological environments and thus may bring revolutionary changes to biomedicines. Fluorescence has been widely used in real-time imaging, chemo-/biosensing, and photo-(chemo-) therapy. The integration of MNRs with fluorescence generates fluorescent MNRs with unique advantages of optical trackability, on-the-fly environmental sensitivity, and targeting chemo-/photon-induced cytotoxicity. This review provides an up-to-date overview of fluorescent MNRs. After the highlighted elucidation about MNRs of various propulsion mechanisms and the introductory information on fluorescence with emphasis on the fluorescent mechanisms and materials, we systematically illustrate the design and preparation strategies to integrate MNRs with fluorescent substances and their biomedical applications in imaging-guided drug delivery, intelligent on-the-fly sensing and photo-(chemo-) therapy. In the end, we summarize the main challenges and provide an outlook on the future directions of fluorescent MNRs. This work is expected to attract and inspire researchers from different communities to advance the creation and practical application of fluorescent MNRs on a broad horizon.

Acoustic-resolution-based spectroscopic photoacoustic endoscopy towards molecular imaging in deep tissues

Due to many technical difficulties, the study of molecular photoacoustic endoscopic (PAE) imaging in deep tissues is limited. In this work, we have set up a multimodal acoustic-resolution-based PAE (AR-PAE) system to image the rabbit rectum and preliminarily explored the potential of molecular PAE for deep-seated targets in proof-of-concept. We developed an improved back-projection (IBP) algorithm for focused detection over the centimeter-scale imaging depth. We also developed a deep-learning-based algorithm to remove the electrical noise from the step motor to prevent data averaging for reduced scanning time. We injected a dose of indocyanine green (ICG) near the rabbit rectum and compared 2D and 3D photoacoustic/ultrasound (PA/US) images at different wavelengths. We proposed incorporating a small camera to guide the slow PA/US endoscopic scan. Results show that this system has achieved a lateral resolution of about 0.77/0.65 mm for PA/US images with a signal-to-noise ratio (SNR) of 25/38 dB at an imaging depth of 1.4 cm. We found that the rectum wall and the ICG can be well distinguished spectroscopically. Results also show that the PA images at 532 nm have higher signal intensity and reflection artifacts from pelvic tendons and bones than those at longer wavelengths such as 800 nm. The proposed methods and the intuitive findings in this work may guide and promote the development of high-penetration molecular PAE.

Multi-angle data acquisition to compensate transducer finite size in photoacoustic tomography

In photoacoustic tomography (PAT) systems, the tangential resolution decreases due to the finite size of the transducer as the off-center distance increases. To address this problem, we propose a multi-angle detection approach in which the transducer used for data acquisition rotates around its center (with specific angles) as well as around the scanning center. The angles are calculated based on the central frequency and diameter of the transducer and the radius of the region-of-interest (ROI). Simulations with point-like absorbers (for point-spread-function evaluation) and a vasculature phantom (for quality assessment), and experiments with ten 0.5 mm-diameter pencil leads and a leaf skeleton phantom are used for evaluation of the proposed approach. The results show that a location-independent tangential resolution is achieved with 150 spatial sampling and central rotations with angles of ±8°/±16°. With further developments, the proposed detection strategy can replace the conventional detection (rotating a transducer around ROI) in PAT.

Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis

SIGNIFICANCE

Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods.

AIM

We aim to provide a systematic overview of the field of hemoglobin imaging and sensing.

APPROACH

We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy.

RESULTS

We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application.

CONCLUSIONS

We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.

Volumetric tri-modal imaging with combined photoacoustic, ultrasound, and shear wave elastography

Photoacoustic imaging is a hybrid imaging approach that combines the advantages of optical and ultrasonic imaging in one modality. However, for comprehensive tissue characterization, optical contrast alone is not always sufficient. In this study, we combined photoacoustic imaging with high-resolution ultrasound and shear wave elastography. The multi-modal system can calculate optical absorption, acoustic reflection, and stiffness volumetrically. We constructed a multi-modal phantom with contrast for each imaging modality to test the system's performance. Experimental results indicate that the system successfully visualizes the embedded structures. We envision that the system will lead to more comprehensive tissue characterization for cancer screening and diagnosis.

Looking deep inside tissue with photoacoustic molecular probes: a review

Significance

Deep tissue noninvasive high-resolution imaging with light is challenging due to the high degree of light absorption and scattering in biological tissue. Photoacoustic imaging (PAI) can overcome some of the challenges of pure optical or ultrasound imaging to provide high-resolution deep tissue imaging. However, label-free PAI signals from light absorbing chromophores within the tissue are nonspecific. The use of exogeneous contrast agents (probes) not only enhances the imaging contrast (and imaging depth) but also increases the specificity of PAI by binding only to targeted molecules and often providing signals distinct from the background.

Aim

We aim to review the current development and future progression of photoacoustic molecular probes/contrast agents.

Approach

First, PAI and the need for using contrast agents are briefly introduced. Then, the recent development of contrast agents in terms of materials used to construct them is discussed. Then, various probes are discussed based on targeting mechanisms, in vivo molecular imaging applications, multimodal uses, and use in theranostic applications.

Results

Material combinations are being used to develop highly specific contrast agents. In addition to passive accumulation, probes utilizing activation mechanisms show promise for greater controllability. Several probes also enable concurrent multimodal use with fluorescence, ultrasound, Raman, magnetic resonance imaging, and computed tomography. Finally, targeted probes are also shown to aid localized and molecularly specific photo-induced therapy.

Conclusions

The development of contrast agents provides a promising prospect for increased contrast, higher imaging depth, and molecularly specific information. Of note are agents that allow for controlled activation, explore other optical windows, and enable multimodal use to overcome some of the shortcomings of label-free PAI.

High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning

SIGNIFICANCE

In circular scanning photoacoustic tomography (PAT), it takes several minutes to generate an image of acceptable quality, especially with a single-element ultrasound transducer (UST). The imaging speed can be enhanced by faster scanning (with high repetition rate light sources) and using multiple-USTs. However, artifacts arising from the sparse signal acquisition and low signal-to-noise ratio at higher scanning speeds limit the imaging speed. Thus, there is a need to improve the imaging speed of the PAT systems without hampering the quality of the PAT image.

AIM

To improve the frame rate (or imaging speed) of the PAT system by using deep learning (DL).

APPROACH

For improving the frame rate (or imaging speed) of the PAT system, we propose a novel U-Net-based DL framework to reconstruct PAT images from fast scanning data.

RESULTS

The efficiency of the network was evaluated on both single- and multiple-UST-based PAT systems. Both phantom and in vivo imaging demonstrate that the network can improve the imaging frame rate by approximately sixfold in single-UST-based PAT systems and by approximately twofold in multi-UST-based PAT systems.

CONCLUSIONS

We proposed an innovative method to improve the frame rate (or imaging speed) by using DL and with this method, the fastest frame rate of ∼ 3    Hz imaging is achieved without hampering the quality of the reconstructed image.

Synchronization of RF Data in Ultrasound Open Platforms (UOPs) for High-Accuracy and High-Resolution Photoacoustic Tomography Using the "Scissors" Programming Method

Synchronization is important for photoacoustic (PA) tomography, but some fixed delays between the data acquisition (DAQ) and the light pulse are a common problem degrading imaging quality. Here, we present a simple yet versatile method named "Scissors" to help synchronize ultrasound open platforms (UOPs) for PA imaging. Scissors is a programed function that can cut or add a fixed delay to radio frequency (RF) data and, thus, synchronize it before reconstruction. Scissors applies the programmable metric of UOPs and has several advantages. It is compatible with many setups regardless of the synchronization methods, light sources, transducers, and delays. The synchronization is adjustable in steps reciprocal to the UOPs' sampling rate (20-ns step with a 50-MHz sampling rate). Scissors works in real-time PA imaging, and no extra hardware is needed. We programed Scissors in Vantage UOP (Verasonics, Inc., Kirkland, WA, USA) and then imaged two 30- [Formula: see text] nichrome wires with a 20.2-MHz central frequency transducer. The PA image was severely distorted by an 828-ns delay; over 90% delay was caused by our Q -switch laser. The axial and lateral resolutions are 112 and [Formula: see text], respectively, after using Scissors. We imaged a human finger in vivo, and the imaging quality is tremendously improved after solving the 828-ns delay by using Scissors.

Photoacoustic imaging of posterior periodontal pocket using a commercial hockey-stick transducer

SIGNIFICANCE

Photoacoustic imaging has shown advantages over the periodontal probing method in measuring the periodontal probing depth, but the large size of conventional photoacoustic transducers prevents imaging of the more posterior teeth.

AIM

Our aim is to develop a photoacoustic imaging system to image the more posterior periodontal pocket.

APPROACH

We report a clinical "hockey-stick"-style transducer integrated with fibers for periodontal photoacoustic imaging. Cuttlefish ink labeled the periodontal pocket as the photoacoustic contrast agent.

RESULTS

We characterized the imaging system and then measured the pocket depth of 35 swine teeth. Three raters evaluated the performance of the hockey-stick transducer. The measurements between the Williams probing (gold standard) and the photoacoustic methods were blinded but highly correlated. We showed a bias of ∼0.3  mm for the imaging-based technique versus Williams probing. The minimum inter-reliability was over 0.60 for three different raters of varying experience, suggesting that this approach to measure the periodontal pocket is reproducible. Finally, we imaged three pre-molars of a human subject. We could access more upper and posterior teeth than conventional linear transducers.

CONCLUSIONS

The unique angle shape of the hockey-stick transducer allows it to image more posterior teeth than regular linear transducers. This study demonstrated the ability of a hockey-stick transducer to measure the periodontal pocket via photoacoustic imaging.

The emerging role of photoacoustic imaging in clinical oncology

Clinical oncology can benefit substantially from imaging technologies that reveal physiological characteristics with multiscale observations. Complementing conventional imaging modalities, photoacoustic imaging (PAI) offers rapid imaging (for example, cross-sectional imaging in real time or whole-breast scanning in 10-15 s), scalably high levels of spatial resolution, safe operation and adaptable configurations. Most importantly, this novel imaging modality provides informative optical contrast that reveals details on anatomical, functional, molecular and histological features. In this Review, we describe the current state of development of PAI and the emerging roles of this technology in cancer screening, diagnosis and therapy. We comment on the performance of cutting-edge photoacoustic platforms, and discuss their clinical applications and utility in various clinical studies. Notably, the clinical translation of PAI is accelerating in the areas of macroscopic and mesoscopic imaging for patients with breast or skin cancers, as well as in microscopic imaging for histopathology. We also highlight the potential of future developments in technological capabilities and their clinical implications, which we anticipate will lead to PAI becoming a desirable and widely used imaging modality in oncological research and practice.

Tissue-mimicking phantoms for performance evaluation of photoacoustic microscopy systems

Phantom-based performance test methods are critically needed to support development and clinical translation of emerging photoacoustic microscopy (PAM) devices. While phantoms have been recently developed for macroscopic photoacoustic imaging systems, there is an unmet need for well-characterized tissue-mimicking materials (TMMs) and phantoms suitable for evaluating PAM systems. Our objective was to develop and characterize a suitable dermis-mimicking TMM based on polyacrylamide hydrogels and demonstrate its utility for constructing image quality phantoms. TMM formulations were optically characterized over 400-1100 nm using integrating sphere spectrophotometry and acoustically characterized using a pulse through-transmission method over 8-24 MHz with highly confident extrapolation throughout the usable band of the PAM system. This TMM was used to construct a spatial resolution phantom containing gold nanoparticle point targets and a penetration depth phantom containing slanted tungsten filaments and blood-filled tubes. These phantoms were used to characterize performance of a custom-built PAM system. The TMM was found to be broadly tunable and specific formulations were identified to mimic human dermis at an optical wavelength of 570 nm and acoustic frequencies of 10-50 MHz. Imaging results showed that tungsten filaments yielded 1.1-4.2 times greater apparent maximum imaging depth than blood-filled tubes, which may overestimate real-world performance for vascular imaging applications. Nanoparticles were detectable only to depths of 120-200 µm, which may be due to the relatively weaker absorption of single nanoparticles vs. larger targets containing high concentration of hemoglobin. The developed TMMs and phantoms are useful tools to support PAM device characterization and optimization, streamline regulatory decision-making, and accelerate clinical translation.

Video-Rate Dual-Modal Wide-Beam Harmonic Ultrasound and Photoacoustic Computed Tomography

Dual-modal ultrasound (US) and photoacoustic (PA) imaging has tremendous advantages in biomedical applications, such as pharmacokinetics, cancer screening, and imaging-guided therapy. Compared with ring-shaped arrays, a linear piezoelectric transducer array applies to more anatomical sites and has been widely used in US/PA imaging. However, the linear array may limit the imaging quality due to narrow bandwidth, partial detection view, or sparse spatial sampling. To meet clinic demand of high-quality US/PA imaging with the linear transducer, we develop dual-modal wide-beam harmonic ultrasound (WBHUS) and photoacoustic computed tomography at video rate. The harmonic US imaging employs pulse phase inversion to reduce clutters and improve spatial resolution. Wide-beam US transmission can shorten the scanning times by 267% and enables a 20-Hz imaging rate, which can minimize motion artifacts in in vivo imaging. The harmonic US imaging does not only provide accurate anatomical references for locating PA features but also reduces artifacts in PA images. The improved image quality allows us to acquire high-resolution anatomical structures in deep tissue without labeling. The fast-imaging speed enables visualizing interventional procedures and monitoring the pulsations of the thoracic aorta and radial artery in real-time. The video-rate dual-modal harmonic US and single-shot PA computed tomography use a clinical-grade linear-array transducer and thus can be readily implemented in clinical US imaging.

Accuracy of peak-power compensation in fiber-guided and free-space acoustic-resolution photoacoustic microscopy

Acoustic resolution photoacoustic microscopy (AR-PAM) has gained much attention in the past two decades due to its high contrast, scalable resolution, and relatively higher imaging depth. Multimode optical fibers (MMF) are extensively used to transfer light to AR-PAM imaging scan-head from the laser source. Typically, peak-power-compensation (PPC) is used to reduce the effect of pulse-to-pulse peak-power variation in generated photoacoustic (PA) signals. In MMF, the output intensity profile fluctuates due to the coherent nature of light and mode exchange caused by variations in the bending of the fibers during scanning. Therefore, using a photodiode (PD) to capture a portion of the total power of pulses as a measure of illuminated light on the sample may not be appropriate for accurate PPC. In this study, we have investigated the accuracy of PPC in fiber-guided and free-space AR-PAM systems. Experiments were conducted in the transparent and highly scattering medium. Based on obtained results for the MMF-based system, to apply PPC to the generated PA signals, tightly focused light confocal with the acoustic focus in a transparent medium must be used. In the clear medium and highly focused illumination, enhancement of about 45% was obtained in the homogeneity of an optically homogeneous sample image. In addition, it is shown that, as an alternative, free-space propagation of the laser pulses results in more accurate PPC in both transparent and highly scattering mediums. In free-space light transmission, enhancement of 25-75% was obtained in the homogeneity of the optically homogeneous sample image.

Predicting optoacoustic spectral behaviour of human erythrocytes, stomatocytes and echinocytes using a modified Green's function method

Optoacoustic (OA) spectral properties of various sources mimicking normal and pathological red blood cells (RBCs) have been studied. The shapes of normal RBC and cells suffering from stomatocytosis (denoted by ST) were generated using mathematical models. However, the shape corresponding to the cells affected by echinocytosis (referred to as ET) was constructed by uniformly distributing half prolate spheroids on a central spherical object. The OA field emitted by an acoustically inhomogeneous source was calculated for a wide acoustic frequency bandwidth (1-1500 MHz with an increment 5 MHz) by solving the time-independent wave equation employing a modified Green's function approach. The OA spectra averaged over 200 orientations for normal RBC and STs demonstrate similar features (one minimum occurring nearly at 906 MHz). The same graphs for ETs are remarkably different from that of normal RBC and exhibit better match with that of a spherical RBC (first minimum appearing at around 425 MHz). The spectral features of ETs above 425 MHz may enable us to differentiate diseased cells (echinocytosis) from normal RBCs.

Hybrid Carbon Dot Assembly as a Reactive Oxygen Species Nanogenerator for Ultrasound-Assisted Tumor Ablation

The efficacy of reactive oxygen species (ROS)-based therapy is substantially constrained by the limited ROS generation, stern activation conditions, and lack of a straightforward reaction paradigm. Carbon dots (CDs) have been highly sought after for therapeutic applications for their biocompatibility and intrinsic fluorescence imaging capabilities, making them suitable for ROS generation. Herein, we synthesized a CD-based ultrasmall hybrid nanostructure possessing active sites of Mo, Cu, and IR-780 dye. After cooperative self-assembly with 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-poly(ethylene glycol), the obtained assembly (CMIR-CDa) exhibits near-infrared fluorescence imaging and photoacoustic tomography. Interestingly, CMIR-CDa can generate singlet oxygen (1O2), hydroxyl radical (·OH), and superoxide radical anion (O2 • -) upon ultrasound stimulus owing to its sonosensitizing and enzyme-mimicking properties, showing an enhanced efficacy for tumor ablation in vivo. The collective in vitro and in vivo results indicate that CMIR-CDa has a high potency as an ROS nanogenerator under US irradiation, even at a low concentration. The present study offers an approach for engineering hybrid CDs in a bioinspired way for intratumoral ROS augmentation in response to deep tissue penetrable external stimuli.

SVD-based filtering to detect intraplaque hemorrhage using single wavelength photoacoustic imaging

SIGNIFICANCE

Intraplaque hemorrhage (IPH) is an important indicator of plaque vulnerability. Early detection could aid the prevention of stroke.

AIM

We aim to detect IPH with single wavelength PA imaging in vivo and to improve image quality.

APPROACH

We developed a singular value decomposition (SVD)-based filter to detect the nonstationary and stationary components in ultrasound data. A PA mask was created to detect stationary (IPH) sources. The method was tested ex vivo using phantoms and in vivo in patients.

RESULTS

The flow and IPH channels were successfully separated in the phantom data. We can also detect the PA signals from IPH and reject signals from the carotid lumen in vivo. Generalized contrast-to-noise ratio improved in both ex vivo and in vivo in US imaging.

CONCLUSIONS

SVD-based filtering can successfully detect IPH using a single laser wavelength, opening up opportunities for more economical and cost-effective laser sources.

Recent Technical Progression in Photoacoustic Imaging—Towards Using Contrast Agents and Multimodal Techniques

For combining optical and ultrasonic imaging methodologies, photoacoustic imaging (PAI) is the most important and successful hybrid technique, which has greatly contributed to biomedical research and applications. Its theoretical background is based on the photoacoustic effect, whereby a modulated or pulsed light is emitted into tissue, which selectively absorbs the optical energy of the light at optical wavelengths. This energy produces a fast thermal expansion in the illuminated tissue, generating pressure waves (or photoacoustic waves) that can be detected by ultrasonic transducers. Research has shown that optical absorption spectroscopy offers high optical sensitivity and contrast for ingredient determination, for example, while ultrasound has demonstrated good spatial resolution in biomedical imaging. Photoacoustic imaging combines these advantages, i.e., high contrast through optical absorption and high spatial resolution due to the low scattering of ultrasound in tissue. In this review, we focus on advances made in PAI in the last five years and present categories and key devices used in PAI techniques. In particular, we highlight the continuously increasing imaging depth achieved by PAI, particularly when using exogenous reagents. Finally, we discuss the potential of combining PAI with other imaging techniques.

Deep-learning-based multi-transducer photoacoustic tomography imaging without radius calibration

Pulsed laser diodes are used in photoacoustic tomography (PAT) as excitation sources because of their low cost, compact size, and high pulse repetition rate. In combination with multiple single-element ultrasound transducers (SUTs) the imaging speed of PAT can be improved. However, during PAT image reconstruction, the exact radius of each SUT is required for accurate reconstruction. Here we developed a novel deep learning approach to alleviate the need for radius calibration. We used a convolutional neural network (fully dense U-Net) aided with a convolutional long short-term memory block to reconstruct the PAT images. Our analysis on the test set demonstrates that the proposed network eliminates the need for radius calibration and improves the peak signal-to-noise ratio by ∼73% without compromising the image quality. In vivo imaging was used to verify the performance of the network.

Sounding out the hidden data: A concise review of deep learning in photoacoustic imaging

The rapidly evolving field of photoacoustic tomography utilizes endogenous chromophores to extract both functional and structural information from deep within tissues. It is this power to perform precise quantitative measurements in vivo-with endogenous or exogenous contrast-that makes photoacoustic tomography highly promising for clinical translation in functional brain imaging, early cancer detection, real-time surgical guidance, and the visualization of dynamic drug responses. Considering photoacoustic tomography has benefited from numerous engineering innovations, it is of no surprise that many of photoacoustic tomography's current cutting-edge developments incorporate advances from the equally novel field of artificial intelligence. More specifically, alongside the growth and prevalence of graphical processing unit capabilities within recent years has emerged an offshoot of artificial intelligence known as deep learning. Rooted in the solid foundation of signal processing, deep learning typically utilizes a method of optimization known as gradient descent to minimize a loss function and update model parameters. There are already a number of innovative efforts in photoacoustic tomography utilizing deep learning techniques for a variety of purposes, including resolution enhancement, reconstruction artifact removal, undersampling correction, and improved quantification. Most of these efforts have proven to be highly promising in addressing long-standing technical obstacles where traditional solutions either completely fail or make only incremental progress. This concise review focuses on the history of applied artificial intelligence in photoacoustic tomography, presents recent advances at this multifaceted intersection of fields, and outlines the most exciting advances that will likely propagate into promising future innovations.