Biomedical photoacoustic imaging

Probe fusion all-optic OCT-PAM dual-mode imaging system for biomedical imaging

We proposed a non-contact photoacoustic (PA) detection method using spectral domain optical coherence tomography (SDOCT). Two interference spectrums (A-lines) were acquired before and after the PA excitation with SDOCT. PA signal propagated within the sample causing the vibration. The vibration inner the sample introduced phase change between the acquired two A-lines. Thus, the PA signal can be detected by evaluating the difference in phase between the two A-lines. Based on the method, an OCT-PAM dual-mode imaging system was constructed. In the system, SDOCT served as the detection unit for PAM. Thus, the combination of the two imaging modalities was simplified. Another advantage of the system is that it realizes non-contact all-optic detection, which is attractive for biomedical imaging. Using the system, we imaged phantoms of carbon fibers, asparagus leaves and human hairs. Furthermore, the cortical vasculature of rat was imaged in vivo and the flow status was evaluated quantitatively.

Automatic Segmentation for Analysis of Murine Cardiac Ultrasound and Photoacoustic Image Data Using Deep Learning

OBJECTIVE

Although there are methods to identify regions of interest (ROIs) from echocardiographic images of myocardial tissue, they are often time-consuming and difficult to create when image quality is poor. Further, while myocardial strain from ultrasound (US) images can be estimated, US alone cannot obtain functional information, such as oxygen saturation (sO2). Photoacoustic (PA) imaging, however, can be used to quantify sO2 levels within tissue non-invasively.

METHODS

Here, we leverage deep learning methods to improve segmentation of the anterior wall of the left ventricle and apply both strain and oxygen saturation analysis via segmentation of murine US and PA images.

RESULTS

Data revealed that training on US/PA images using a U-Net deep neural network can be used to create reproducible ROIs of the anterior wall of the left ventricle in a murine image dataset. Accuracy and Dice score metrics were used to evaluate performance of the neural network on each image type. We report an accuracy of 97.3% and Dice score of 0.84 for ultrasound, 95.6% and 0.73 for photoacoustic, and 96.5% and 0.81 for combined ultrasound and photoacoustic images.

CONCLUSION

Rapid segmentation via such methods can assist in quantification of strain and oxygenation.

Accelerating photoacoustic microscopy by reconstructing undersampled images using diffusion models

Photoacoustic Microscopy (PAM) integrates optical and acoustic imaging, offering enhanced penetration depth for detecting optical-absorbing components in tissues. Nonetheless, challenges arise in scanning large areas with high spatial resolution. With speed limitations imposed by laser pulse repetition rates, the potential role of computational methods is highlighted in accelerating PAM imaging. We propose a novel and highly adaptable algorithm named DiffPam that utilizes diffusion models to speed up the photoacoustic imaging process. We leveraged a diffusion model trained exclusively on natural images, comparing its performance with an in-domain trained U-Net model using a dataset focused on PAM images of mice brain microvasculature. Our findings indicate that DiffPam performs similarly to a dedicated U-Net model without needing a large dataset. We demonstrate that scanning can be accelerated fivefold with limited information loss. We achieved a 24.70 % increase in peak signal-to-noise ratio and a 27.54 % increase in structural similarity index compared to the baseline bilinear interpolation method. The study also introduces the efficacy of shortened diffusion processes for reducing computing time without compromising accuracy. DiffPam stands out from existing methods as it does not require supervised training or detailed parameter optimization typically needed for other unsupervised methods. This study underscores the significance of DiffPam as a practical algorithm for reconstructing undersampled PAM images, particularly for researchers with limited artificial intelligence expertise and computational resources.

Optical tuning of copolymer-in-oil tissue-mimicking materials for multispectral photoacoustic imaging

Objective. The availability of tissue-mimicking materials (TMMs) for manufacturing high-quality phantoms is crucial for standardization, evaluating novel quantitative approaches, and clinically translating new imaging modalities, such as photoacoustic imaging (PAI). Recently, a gel comprising the copolymer styrene-ethylene/butylene-styrene (SEBS) in mineral oil has shown significant potential as TMM due to its optical and acoustic properties akin to soft tissue. We propose using artists' oil-based inks dissolved and diluted in balsam turpentine to tune the optical properties.Approach. A TMM was fabricated by mixing a SEBS copolymer and mineral oil, supplemented with additives to tune its optical absorption and scattering properties independently. A systematic investigation of the tuning accuracies and relationships between concentrations of oil-based pigments and optical absorption properties of the TMM across visible and near-infrared wavelengths using collimated transmission spectroscopy was conducted. The photoacoustic spectrum of various oil-based inks was studied to analyze the effect of increasing concentration and depth.Main results. Artists' oil-based inks dissolved in turpentine proved effective as additives to tune the optical absorption properties of mineral oil SEBS-gel with high accuracy. The TMMs demonstrated long-term stability and suitability for producing phantoms with desired optical absorption properties for PAI studies.Significance. The findings, including tuning of optical absorption and spectral shape, suggest that this TMM facilitates the development of more sophisticated phantoms of arbitrary shapes. This approach holds promise for advancing the development of PAI, including investigation of the spectral coloring effect. In addition, it can potentially aid in the development and clinical translation of ultrasound optical tomography.

Challenges and advances in two-dimensional photoacoustic computed tomography: a review

Significance

Photoacoustic computed tomography (PACT), a hybrid imaging modality combining optical excitation with acoustic detection, has rapidly emerged as a prominent biomedical imaging technique.

Aim

We review the challenges and advances of PACT, including (1) limited view, (2) anisotropy resolution, (3) spatial aliasing, (4) acoustic heterogeneity (speed of sound mismatch), and (5) fluence correction of spectral unmixing.

Approach

We performed a comprehensive literature review to summarize the key challenges in PACT toward practical applications and discuss various solutions.

Results

There is a wide range of contributions from both industry and academic spaces. Various approaches, including emerging deep learning methods, are proposed to improve the performance of PACT further.

Conclusions

We outline contemporary technologies aimed at tackling the challenges in PACT applications.

Multiwavelength laser diode based portable photoacoustic and ultrasound imaging system for point of care applications

Vascular diseases are a leading cause of death and disability worldwide. Despite having precursor conditions like peripheral arterial disease (PAD), they are often only diagnosed after the onset of stroke or heart attack. Low-cost, portable, noninvasive, point-of-care (POC), label-free assessment of deep vascular function benefits PAD diagnosis, especially in resource poor settings of the world. Doppler ultrasound-based blood flow measurements can diagnose PAD, albeit with limited sensitivity and specificity. To overcome this, here, we propose the first-of-its-kind dual-modality photoacoustic-and-ultrasound (PAUS) imaging system that integrates a multiwavelength pulsed laser diode (PLD) with a compact ultrasound data acquisition unit. The mesoscopic imaging depth of the portable PLD-PAUS system was validated using tissue phantoms, and its multispectral photoacoustic imaging capabilities were validated using an atherosclerosis-mimicking phantom. Furthermore, we demonstrated high-contrast volumetric in vivo photoacoustic imaging of rodent abdominal vasculature and quantified vessel reactivity due to hypercapnia stimulation. The multiparametric functional and molecular imaging capabilities of the PLD-PAUS system holds promise for POC applications.

High-frequency photoacoustic and ultrasound imaging for skin evaluation: Pilot study for the assessment of a chemical burn

Skin architecture and its underlying vascular structure could be used to assess the health status of skin. A non-invasive, high resolution and deep imaging modality able to visualize skin subcutaneous layers and vasculature structures could be useful for determining and characterizing skin disease and trauma. In this study, a multispectral high-frequency, linear array-based photoacoustic/ultrasound (PAUS) probe is developed and implemented for the imaging of rat skin in vivo. The study seeks to demonstrate the probe capabilities for visualizing the skin and its underlying structures, and for monitoring changes in skin structure and composition during a 5-day course of a chemical burn. We analayze composition of lipids, water, oxy-hemoglobin, and deoxy-hemoglobin (for determination of oxygen saturation) in the skin tissue. The study successfully demonstrated the high-frequency PAUS imaging probe was able to provide 3D images of the rat skin architecture, underlying vasculature structures, and oxygen saturation, water, lipids and total hemoglobin.

Virtual-point-based deconvolution for optical-resolution photoacoustic microscopy

Optical-resolution photoacoustic microscopy (OR-PAM) has been increasingly utilized for in vivo imaging of biological tissues, offering structural, functional, and molecular information. In OR-PAM, it is often necessary to make a trade-off between imaging depth, lateral resolution, field of view, and imaging speed. To improve the lateral resolution without sacrificing other performance metrics, we developed a virtual-point-based deconvolution algorithm for OR-PAM (VP-PAM). VP-PAM has achieved a resolution improvement ranging from 43% to 62.5% on a single-line target. In addition, it has outperformed Richardson-Lucy deconvolution with 15 iterations in both structural similarity index and peak signal-to-noise ratio on an OR-PAM image of mouse brain vasculature. When applied to an in vivo glass frog image obtained by a deep-penetrating OR-PAM system with compromised lateral resolution, VP-PAM yielded enhanced resolution and contrast with better-resolved microvessels.

Multiparametric Brain Hemodynamics Imaging Using a Combined Ultrafast Ultrasound and Photoacoustic System

Studying brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help gain new insights into the mechanisms of neuro- diseases and -disorders. Nonetheless, this task is challenging, primarily due to the complexity of neurovascular coupling, which encompasses interdependent hemodynamic parameters including cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral oxygen saturation (SO2). The current brain imaging technologies exhibit inherent limitations in resolution, sensitivity, and imaging depth, restricting their capacity to comprehensively capture the intricacies of cerebral functions. To address this, a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform is reported, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map individual dynamics of CBV, CBF, and SO2 as well as contrast agent enhanced brain imaging at high spatiotemporal resolutions. Following systematic characterization, the fUSPA system is applied to study brain-wide cerebrovascular reactivity (CVR) at single-vessel resolution via relative changes in CBV, CBF, and SO2 in response to hypercapnia stimulation. These results show that cortical veins and arteries exhibit differences in CVR in the stimulated state and consistent anti-correlation in CBV oscillations during the resting state, demonstrating the multiparametric fUSPA system's unique capabilities in investigating complex mechanisms of brain functions.

An Indocyanine Green-Based Nanoprobe for In Vivo Detection of Cellular Senescence

There is an urgent need to improve conventional cancer-treatments by preventing detrimental side effects, cancer recurrence and metastases. Recent studies have shown that presence of senescent cells in tissues treated with chemo- or radiotherapy can be used to predict the effectiveness of cancer treatment. However, although the accumulation of senescent cells is one of the hallmarks of cancer, surprisingly little progress has been made in development of strategies for their detection in vivo. To address a lack of detection tools, we developed a biocompatible, injectable organic nanoprobe (NanoJagg), which is selectively taken up by senescent cells and accumulates in the lysosomes. The NanoJagg probe is obtained by self-assembly of indocyanine green (ICG) dimers using a scalable manufacturing process and characterized by a unique spectral signature suitable for both photoacoustic tomography (PAT) and fluorescence imaging. In vitro, ex vivo and in vivo studies all indicate that NanoJaggs are a clinically translatable probe for detection of senescence and their PAT signal makes them suitable for longitudinal monitoring of the senescence burden in solid tumors after chemotherapy or radiotherapy.

Regulating interparticle proximity in plasmonic nanosphere aggregates to enhance photoacoustic response and photothermal stability

Designing plasmonic nanoparticles for biomedical photoacoustic (PA) imaging involves tailoring material properties at the nanometer scale. A key in developing plasmonic PA contrast nanoagents is to engineer their enhanced optical responses in the near-infrared wavelength range, as well as heat transfer properties and photostability. This study introduces anisotropic plasmonic nanosphere aggregates with close interparticle proximity as photostable and efficient contrast agent for PA imaging. Silver (Ag), among plasmonic metals, is particularly attractive due to its strongest optical response and highest heat conductivity. Our results demonstrate that close interparticle proximity in silver nanoaggregates (AgNAs), spatially confined within a polymer shell layer, leads to blackbody-like optical absorption, resulting in robust PA signals through efficient pulsed heat generation and transfer. Additionally, our AgNAs exhibit a high photodamage threshold highlighting their potential to outperform conventional plasmonic contrast agents for high-contrast PA imaging over multiple imaging sessions. Furthermore, we demonstrate the capability of the AgNAs for molecular PA cancer imaging in vivo by incorporating a tumor-targeting peptide moiety.

Multimodal Imaging-Guided Stem Cell Ocular Treatment

Stem cell therapies are gaining traction as promising treatments for a variety of degenerative conditions. Both clinical and preclinical studies of regenerative medicine are hampered by the lack of technologies that can evaluate the migration and behavior of stem cells post-transplantation. This study proposes an innovative method to longitudinally image in vivo human-induced pluripotent stem cells differentiated to retinal pigment epithelium (hiPSC-RPE) cells by multimodal photoacoustic microscopy, optical coherence tomography, and fluorescence imaging powered by ultraminiature chain-like gold nanoparticle cluster (GNC) nanosensors. The GNC exhibits an optical absorption peak in the near-infrared regime, and the 7-8 nm size in diameter after disassembly enables renal excretion and improved safety as well as biocompatibility. In a clinically relevant rabbit model, GNC-labeled hiPSC-RPE cells migrated to RPE degeneration areas and regenerated damaged tissues. The hiPSC-RPE cells' distribution and migration were noninvasively, longitudinally monitored for 6 months with exceptional sensitivity and spatial resolution. This advanced platform for cellular imaging has the potential to enhance regenerative cell-based therapies.

Quantitative evaluation of the impact of variation of optical parameters on the estimation of blood hematocrit and oxygen saturation for dual-wavelength photoacoustics

Photoacoustic (PA) spectroscopy is considered to be one of the most effective ways to measure the levels of hematocrit (H) and oxygenation saturation (S O 2) of blood, which are essential for diagnosing blood-related illnesses. This simulation study aims to investigate the impact of individual optical parameters, i.e., optical absorption coefficient (μ a), scattering coefficient (μ s), and anisotropy factor (g), on the accuracy of this technique in estimating the blood properties. We first performed the Monte Carlo simulations, using realistic optical parameters, to obtain the fluence maps for various samples. The wavelengths of the incident light were chosen to be 532, 700, 1000, and 1064 nm. Thereafter, the k-Wave simulations were executed, incorporating those fluence maps to generate the PA signals. The blood properties were obtained using the PA signals. We introduced variations in μ a, μ s, and g ranging from -10% to +10%, -10% to +10%, and -5% to +1%, respectively, at 700 and 1000 nm wavelengths. One parameter, at both wavelengths, was changed at a time, keeping others fixed. Subsequently, we examined how accurately the blood parameters could be determined at physiological hematocrit levels. A 10% variation in μ a induces a 10% change in H estimation but no change in S O 2 determination. Almost no change has been seen for μ s variation. However, a 5% (-5% to 0%) variation in the g factor resulted in approximately 160% and 115% changes in the PA signal amplitudes at 700 and 1000 nm, respectively, leading to ≈125% error in hematocrit estimation and ≈14% deviation in S O 2 assessment when nominal S O 2=70%. It is clear from this study that the scattering anisotropy factor is a very sensitive parameter and a small change in its value can result in large errors in the PA estimation of blood properties. In the future, in vitro experiments with pathological blood (inducing variation in the g parameter) will be performed, and accordingly, the accuracy of the PA technique in quantifying blood H and S O 2 will be evaluated.

Vascular regional analysis unveils differential responses to anti-angiogenic therapy in pancreatic xenografts through macroscopic photoacoustic imaging

Pancreatic cancer (PC) is a highly lethal malignancy and the third leading cause of cancer deaths in the U.S. Despite major innovations in imaging technologies, there are limited surrogate radiographic indicators to aid in therapy planning and monitoring. Amongst the various imaging techniques Ultrasound-guided photoacoustic imaging (US-PAI) is a promising modality based on endogenous blood (hemoglobin) and blood oxygen saturation (StO 2 ) contrast to monitor response to anti-angiogenic therapies. Adaptation of US-PAI to the clinical realm requires macroscopic configurations for adequate depth visualization, illuminating the need for surrogate radiographic markers, including the tumoral microvessel density (MVD). In this work, subcutaneous xenografts with PC cell lines AsPC-1 and MIA-PaCa-2 were used to investigate the effects of receptor tyrosine kinase inhibitor (sunitinib) treatment on MVD and StO 2 . Through histological correlation, we have shown that regions of high and low vascular density (HVD and LVD) can be identified through frequency domain filtering of macroscopic PA images which could not be garnered from purely global analysis. We utilized vascular regional analysis (VRA) of treatment-induced StO 2 and total hemoglobin (HbT) changes. VRA as a tool to monitor treatment response allowed us to identify potential timepoints of vascular remodeling, highlighting its ability to provide insights into the TME not only for sunitinib treatment but also other anti-angiogenic therapies.

The structure and application portfolio of intricately architected silver cluster-assembled materials

Silver Cluster-Assembled Materials (SCAMs) represent a new frontier of crystalline extended solids hallmarked by their customizable structures, commendable stabilities, and unique physical/chemical properties. Since their discovery in 2017, the diversity of organic linkers has endowed SCAMs with ingenious architectures and the application scenario has expanded beyond photoluminescence sensing to environmental sustainability and biomedical applications. It is critically important to chronicle these recent key advances and review the progress of SCAMs that can enable translating the material discoveries into real implementation. Herein, we provide a succinct overview of the trajectory of SCAM research, with crucial insights into atomic-level structural correlations with the phenomena at the nanoscale and discuss the gaps and opportunities that are still open in addition to charting a roadmap for future research directions.

A Dual-Mode Near-Infrared Optical and Photoacoustic Imaging Agent Based on a Low Energy Absorbing Ytterbium Complex

Near-infrared (NIR) luminescence and photoacoustic (PA) imaging have attracted increasing attention for the real-time monitoring of biological samples due to high sensitivity, resolution, and pronounced signal detection depth, respectively. For improved contrast, both techniques require imaging agents possessing high absorption in the red-NIR range. Herein, we took advantage of a ternary complex formed with the anionic ytterbium(III) tetrakis(2-thenoyltrifluoroacetonate) ([Yb(tta)4]-) and the cationic NIR-absorbing chromophore, 1,1'-diethyl-2,2'-dicarbocyanine (Cy+), to evaluate its potential to act as a dual-mode NIR luminescence and PA imaging agent. We demonstrated that, upon excitation with red-NIR light, Cy[Yb(tta)4] encapsulated into polystyrene nanoparticles is able to generate both NIR Yb3+ emission and a PA signal in an imaging experiment performed in a tissue-mimicking phantom.

Coupling Gold Nanospheres into Nanochain Constructs for High-Contrast, Longitudinal Photoacoustic Imaging

Structural parameters play a crucial role in determining the electromagnetic and thermal responses of gold nanoconstructs (GNCs) at near-infrared (NIR) wavelengths. Therefore, developing GNCs for reliable, high-contrast photoacoustic imaging has been focused on adjusting structural parameters to achieve robust NIR light absorption with photostability. In this study, we introduce an efficient photoacoustic imaging contrast agent: gold sphere chains (GSCs) consisting of plasmonically coupled gold nanospheres. The chain geometry results in enhanced photoacoustic signal generation originating from outstanding photothermal characteristics compared to traditional gold contrast agents, such as gold nanorods. Furthermore, the GSCs produce consistent photoacoustic signals at laser fluences within the limits set by the American National Standards Institute. The exceptional photoacoustic response of GSCs allows for high-contrast photoacoustic imaging over multiple imaging sessions. Finally, we demonstrate the utility of our GSCs for molecular photoacoustic cancer imaging, both in vitro and in vivo, through the integration of a tumor-targeting moiety.

Development of non-contact foreign body imaging base on photoacoustic signal intensity measurement

BACKGROUND

It is challenging to visually identify tiny and concealed foreign objects within the body due to their small size and subcutaneous location while they can cause infections.

METHODS

A non-contact photoacoustic system based on Rosencwaig-Gersho photoacoustic theory and dual modulator method is developed for detecting foreign objects in meat.

RESULT

The experiments conducted validate the successful development of this measurement technique with 10 μm spatial resolution and its corresponding mathematical model, demonstrating an 11% Mean Absolute Percentage Error (MAPE) in comparison to the experimental results. Dual modulator successfully regulates laser energy at MPE limit.

CONCLUSION

The utilization of non-contact photoacoustic signal intensity measurements enables the identification of foreign objects within the body. Further, the application of mathematical modelling can validate the measurement outcomes. These findings serve as a foundation for creating an affordable and straightforward foreign body detector.

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.

Artifact reduction in photoacoustic images by generating virtual dense array sensor from hemispheric sparse array sensor using deep learning

PURPOSE

Vascular distribution is important information for diagnosing diseases and supporting surgery. Photoacoustic imaging is a technology that can image blood vessels noninvasively and with high resolution. In photoacoustic imaging, a hemispherical array sensor is especially suitable for measuring blood vessels running in various directions. However, as a hemispherical array sensor, a sparse array sensor is often used due to technical and cost issues, which causes artifacts in photoacoustic images. Therefore, in this study, we reduce these artifacts using deep learning technology to generate signals of virtual dense array sensors.

METHODS

Generating 2D virtual array sensor signals using a 3D convolutional neural network (CNN) requires huge computational costs and is impractical. Therefore, we installed virtual sensors between the real sensors along the spiral pattern in three different directions and used a 2D CNN to generate signals of the virtual sensors in each direction. Then we reconstructed a photoacoustic image using the signals from both the real sensors and the virtual sensors.

RESULTS

We evaluated the proposed method using simulation data and human palm measurement data. We found that these artifacts were significantly reduced in the images reconstructed using the proposed method, while the artifacts were strong in the images obtained only from the real sensor signals.

CONCLUSION

Using the proposed method, we were able to significantly reduce artifacts, and as a result, it became possible to recognize deep blood vessels. In addition, the processing time of the proposed method was sufficiently applicable to clinical measurement.

Light on Alzheimer's disease: from basic insights to preclinical studies

Alzheimer's disease (AD), referring to a gradual deterioration in cognitive function, including memory loss and impaired thinking skills, has emerged as a substantial worldwide challenge with profound social and economic implications. As the prevalence of AD continues to rise and the population ages, there is an imperative demand for innovative imaging techniques to help improve our understanding of these complex conditions. Photoacoustic (PA) imaging forms a hybrid imaging modality by integrating the high-contrast of optical imaging and deep-penetration of ultrasound imaging. PA imaging enables the visualization and characterization of tissue structures and multifunctional information at high resolution and, has demonstrated promising preliminary results in the study and diagnosis of AD. This review endeavors to offer a thorough overview of the current applications and potential of PA imaging on AD diagnosis and treatment. Firstly, the structural, functional, molecular parameter changes associated with AD-related brain imaging captured by PA imaging will be summarized, shaping the diagnostic standpoint of this review. Then, the therapeutic methods aimed at AD is discussed further. Lastly, the potential solutions and clinical applications to expand the extent of PA imaging into deeper AD scenarios is proposed. While certain aspects might not be fully covered, this mini-review provides valuable insights into AD diagnosis and treatment through the utilization of innovative tissue photothermal effects. We hope that it will spark further exploration in this field, fostering improved and earlier theranostics for AD.

Hybrid ultrasound and photoacoustic contrast agent designs combining metal phthalocyanines and PBCA microbubbles

Photoacoustic (PA) imaging is an emerging diagnostic technology that combines the penetration depth of ultrasound (US) imaging and the contrast resolution of optical imaging. Although PA imaging can visualize several endogenous chromophores to obtain clinically-relevant information, multiple applications require the administration of external contrast agents. Metal phthalocyanines have strong PA properties and chemical stability, but their extreme hydrophobicity requires their encapsulation in delivery systems for biomedical applications. Hence, we developed hybrid US/PA contrast agents by encapsulating metal phthalocyanines in poly(butyl cyanoacrylate) microbubbles (PBCA MB), which display acoustic response and ability to efficiently load hydrophobic drugs. Six different metal chromophores were loaded in PBCA MB, showing greater encapsulation efficiency with higher chromophore hydrophobicity. Notably, while the US response of the MB was unaffected by the loading of the chromophores, the PA characteristics varied greatly. Among the different formulations, MB loaded with zinc and cobalt naphthalocyanines showed the strongest PA contrast, as a result of high encapsulation efficiencies and tunable optical properties. The strong US and PA contrast signals of the formulations were preserved in biological environment, as demonstrated by in vitro imaging in serum and whole blood, and ex vivo imaging in deceased mice. Taken together, these findings highlight the advantages of combining highly hydrophobic PA contrast agents and polymeric MB for the development of contrast agents for hybrid US/PA imaging, where different types of information (structural, functional, or potentially molecular) can be acquired by combining both imaging modalities.

Using imaging modalities to predict nanoparticle distribution and treatment efficacy in solid tumors: The growing role of ultrasound

Nanomedicine in oncology has not had the success in clinical impact that was anticipated in the early stages of the field's development. Ideally, nanomedicines selectively accumulate in tumor tissue and reduce systemic side effects compared to traditional chemotherapeutics. However, this has been more successful in preclinical animal models than in humans. The causes of this failure to translate may be related to the intra- and inter-patient heterogeneity of the tumor microenvironment. Predicting whether a patient will respond positively to treatment prior to its initiation, through evaluation of characteristics like nanoparticle extravasation and retention potential in the tumor, may be a way to improve nanomedicine success rate. While there are many potential strategies to accomplish this, prediction and patient stratification via noninvasive medical imaging may be the most efficient and specific strategy. There have been some preclinical and clinical advances in this area using MRI, CT, PET, and other modalities. An alternative approach that has not been studied as extensively is biomedical ultrasound, including techniques such as multiparametric contrast-enhanced ultrasound (mpCEUS), doppler, elastography, and super-resolution processing. Ultrasound is safe, inexpensive, noninvasive, and capable of imaging the entire tumor with high temporal and spatial resolution. In this work, we summarize the in vivo imaging tools that have been used to predict nanoparticle distribution and treatment efficacy in oncology. We emphasize ultrasound imaging and the recent developments in the field concerning CEUS. The successful implementation of an imaging strategy for prediction of nanoparticle accumulation in tumors could lead to increased clinical translation of nanomedicines, and subsequently, improved patient outcomes. This article is categorized under: Diagnostic Tools In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery Emerging Technologies.

Detecting Oxygenator Thrombosis in ECMO: A Review of Current Techniques and an Exploration of Future Directions

Extracorporeal membrane oxygenation (ECMO) is a life-support technique used to treat cardiac and pulmonary failure, including severe cases of COVID-19 (coronavirus disease 2019) involving acute respiratory distress syndrome. Blood clot formation in the circuit is one of the most common complications in ECMO, having potentially harmful and even fatal consequences. It is therefore essential to regularly monitor for clots within the circuit and take appropriate measures to prevent or treat them. A review of the various methods used by hospital units for detecting blood clots is presented. The benefits and limitations of each method are discussed, specifically concerning detecting blood clots in the oxygenator, as it is concluded that this is the most critical and challenging ECMO component to assess. We investigate the feasibility of solutions proposed in the surrounding literature and explore two areas that hold promise for future research: the analysis of small-scale pressure fluctuations in the circuit, and real-time imaging of the oxygenator. It is concluded that the current methods of detecting blood clots cannot reliably predict clot volume, and their inability to predict clot location puts patients at risk of thromboembolism. It is posited that a more in-depth analysis of pressure readings using machine learning could better provide this information, and that purpose-built imaging could allow for accurate, real-time clotting analysis in ECMO components.

Single-stage approach for estimating optical parameters in spectral quantitative photoacoustic tomography

In quantitative photoacoustic tomography, the optical parameters of a target, most importantly the concentrations of chromophores such as deoxygenated and oxygenated hemoglobin, are estimated from photoacoustic data measured on the boundary of the target. In this work, a numerical approximation of a forward model for spectral quantitative photoacoustic tomography is constructed by utilizing the diffusion approximation for light propagation, the acoustic wave equation for ultrasound propagation, and spectral models of optical absorption and scattering to describe the wavelength dependence of the optical parameters. The related inverse problem is approached in the framework of Bayesian inverse problems. Concentrations of four chromophores (deoxygenated and oxygenated hemoglobin, water, and lipid), two scattering parameters (reference scattering and scattering power), and the Grüneisen parameter are estimated in a single-stage from photoacoustic data. The methodology is evaluated using numerical simulations in different full-view and limited-view imaging settings. The results show that, utilizing spectral data and models, the spectral optical parameters and the Grüneisen parameter can be simultaneously estimated. Furthermore, the approach can also be utilized in limited-view imaging situations.

Beyond synthetic aperture focusing: deconvolution-based elevation resolution enhancement using simulated point spread function for linear array-based three-dimensional photoacoustic imaging

This paper introduces a deconvolution-based method to enhance the elevation resolution of a linear array-based three-dimensional (3D) photoacoustic (PA) imaging system. PA imaging combines the high contrast of optical imaging with the deep, multi-centimeter spatial resolution of ultrasound (US) imaging, providing structural and functional information about biological tissues. Linear array-based 3D PA imaging is easily accessible and applicable for ex vivo studies, small animal research, and clinical applications in humans. However, its elevation resolution is limited by the acoustic lens geometry, which establishes a single elevation focus. Previous work used synthetic aperture focusing (SAF) to enhance elevation resolution, but the resolution achievable by SAF is constrained by the size of the elevation focus. Here, we introduce the application of Richardson-Lucy deconvolution, grounded in simulated point-spread-functions, to surpass the elevation resolution attainable with SAF alone. We validated this approach using both simulation and experimental data, demonstrating that the full-width-at-half-maximum of point targets on the elevation plane was reduced compared to using SAF only, suggesting resolution improvement. This method shows promise for improving 3D image quality of existing linear array-based PA imaging systems, offering potential benefits for disease diagnosis and monitoring.

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.

Metabolic and molecular imaging in inflammatory arthritis

It is known that metabolic shifts and tissue remodelling precede the development of visible inflammation and structural organ damage in inflammatory rheumatic diseases such as the inflammatory arthritides. As such, visualising and measuring metabolic tissue activity could be useful to identify biomarkers of disease activity already in a very early phase. Recent advances in imaging have led to the development of so-called 'metabolic imaging' tools that can detect these changes in metabolism in an increasingly accurate manner and non-invasively.Nuclear imaging techniques such as 18F-D-glucose and fibroblast activation protein inhibitor-labelled positron emission tomography are increasingly used and have yielded impressing results in the visualisation (including whole-body staging) of inflammatory changes in both early and established arthritis. Furthermore, optical imaging-based bedside techniques such as multispectral optoacoustic tomography and fluorescence optical imaging are advancing our understanding of arthritis by identifying intra-articular metabolic changes that correlate with the onset of inflammation with high precision and without the need of ionising radiation.Metabolic imaging holds great potential for improving the management of patients with inflammatory arthritis by contributing to early disease interception and improving diagnostic accuracy, thereby paving the way for a more personalised approach to therapy strategies including preventive strategies. In this narrative review, we discuss state-of-the-art metabolic imaging methods used in the assessment of arthritis and inflammation, and we advocate for more extensive research endeavours to elucidate their full field of application in rheumatology.

Dynamic modeling of photoacoustic sensor data to classify human blood samples

The photoacoustic effect is an attractive tool for diagnosis in several biomedical applications. Analyzing photoacoustic signals, however, is challenging to provide qualitative results in an automated way. In this work, we introduce a dynamic modeling scheme of photoacoustic sensor data to classify blood samples according to their physiological status. Thirty-five whole human blood samples were studied with a state-space model estimated by a subspace method. Furthermore, the samples are classified using the model parameters and the linear discriminant analysis algorithm. The classification performance is compared with time- and frequency-domain features and an autoregressive-moving-average model. As a result, the proposed analysis can predict five blood classes: healthy women and men, microcytic and macrocytic anemia, and leukemia. Our findings indicate that the proposed method outperforms conventional signal processing techniques to analyze photoacoustic data for medical diagnosis. Hence, the method is a promising tool in point-of-care devices to detect hematological diseases in clinical scenarios.

An umbrella-inspired snap-on robotic 3D photoacoustic endoscopic probe for augmented intragastric sensing: Proof of concept study

In this paper, we present a novel on-demand modular robotic photoacoustic tomography (PAT) probe integrated into an endoscopic device, potentially for deep intragastric sensing. The proposed solution offers a plug-and-play approach through the use of meso-scale steerable endoscopy and a new 'snap-on' 3D robotic PAT probe that can reconfigure the geometry of the intracorporeal light delivery, inspired by an umbrella structure. Specifically, using the limited esophageal access, steerable endoscopy allows navigation and advancement of a distally mounted robotic add-on for PAT that is folded until it reaches the deep-seated gastric lesion. Once the tip is positioned near the lesion site in the gastric cavity, there is ample working space for the robotic probe to adjust its umbrella-like unfolded shape. This allows fine-tuning of the laser delivery orientation of the fiber bundles to achieve the lesion-specific light delivery scheme. This design allows volumetric imaging of the intragastric PAT with enhanced sensitivity. To evaluate the performance of the modular robotic PAT probe, we performed a simulation analysis of the light intensity and ultrasound field distribution. The simulation results show that the robotic probe is feasible for intracorporeal PAT imaging. In addition, we printed a 3D model of a human stomach containing a simulated gastric tumour. Both the phantom and ex vivo experimental results validate the feasibility of the proposed robotic PAT probe.

Dual-modality rigid endoscope for photoacoustic imaging and white light videoscopy

Significance

There has been significant interest in the development of miniature photoacoustic imaging probes for a variety of clinical uses, including the in situ assessment of tumors and minimally invasive surgical guidance. Most of the previously implemented probes are either side viewing or operate in the optical-resolution microscopy mode in which the imaging depth is limited to ∼ 1    mm . We describe a forward-viewing photoacoustic probe that operates in tomography mode and simultaneously provides white light video images.

Aim

We aim to develop a dual-modality endoscope capable of performing high-resolution PAT imaging and traditional white light videoscopy simultaneously in the forward-viewing configuration.

Approach

We used a Fabry-Pérot ultrasound sensor that operates in the 1500 to 1600 nm wavelength range and is transparent in the visible and near infrared region (580 to 1250 nm). The FP sensor was optically scanned using a miniature MEMs mirror located at the proximal end of the endoscope, resulting in a system that is sufficiently compact (10 mm outer diameter) and lightweight for practical endoscopic use.

Results

The imaging performance of the endoscope is evaluated, and dual-mode imaging capability is demonstrated using phantoms and abdominal organs of an ex vivo mouse including spleen, liver, and kidney.

Conclusions

The proposed endoscope design offers several advantages including the high acoustic sensitivity and wide detection bandwidth of the FP sensor, dual-mode imaging capability, compact footprint, and an all-optical distal end for improved safety. The dual-mode imaging capability also offers the advantage of correlating the tissue surface morphology with the underlying vascular anatomy. Potential applications include the guidance of laparoscopic surgery and other interventional procedures.

Real-time fetal monitoring using photoacoustic measurement of placental oxygen saturation in a rabbit hypoxia model

INTRODUCTION

Ensuring adequate fetal oxygenation is an essential aim of fetal monitoring. The purpose of this study was to establish a basic technique for real-time measurement of blood oxygen saturation of the placenta by photoacoustic (PA) technique as a new fetal monitoring method.

METHODS

The hypoxia model established in our previous study was applied to 7 pregnant rabbits. Three phases were induced: normal phase, hypoxia phase, and recovery phase. Three methods were simultaneously used for real-time fetal monitoring: fetal heat rate (FHR) monitoring, oxygen saturation (SO2) measurement by near-infrared spectroscopy (SNO2), and placenta SO2 measured by PA technique (SplO2). The maternal hypoxia was assessed by skin SO2 measured by PA technique (SsO2), and arterial blood SO2 by blood gas analysis (SaO2).

RESULTS

The average of SplO2 in normal phase was 52.6 ± 13.9 %. The averages of SNO2, SSO2, and SplO2 in the seven rabbits changed in parallel from the normal phase to hypoxia phase. In the recovery phase, the SplO2 rose in parallel with recovery of SaO2. There was lag in increase of the FHR compared to the change in the other values. In the detailed analysis of PA signals from the labyrinth and decidua, a unique change in oxygen saturation was seen in one case.

DISCUSSION

Results of this study showed that sensitivity of our novel PA technique in detecting tissue hypoxia was similar to near-infrared spectroscopy (NIRS). As an advantage, unlike NIRS, monitoring with PA technique was unaffected by ischemia and surface changes in oxygen saturation because of its higher spatial resolution. We conclude that PA technique provides more accurate information about fetal blood placenta than NIRS. Ultrasound imaging, combined with oxygen saturation monitoring by PA technique, would improve fetal monitoring and fetal diagnosis in the future.

Enhancing visualization and guidance in general surgery: a comprehensive and narrative review of the current cutting-edge technologies and future perspectives

BACKGROUND

In the last decade, there has been a great effort in developing new technologies to enhance surgical visualization and guidance. This comprehensive and narrative review aimed to provide a wide and extensive overview of the current state of the art on this topic and their near-future perspectives linked to the development of artificial intelligence (AI), by focusing on the most recent and relevant literature.

METHODS

A comprehensive and narrative review of the literature was performed by searching specific terms on PubMed/MEDLINE, Scopus, and Embase databases, assessing the current state of the art on this topic.

RESULTS

Fluorescence-guided surgery, contrast-enhanced ultrasound (CEUS), ultra-high frequency ultrasound (UHFUS), photoacoustic imaging (PAI), and augmented reality (AR) are boosting the field of image-guided techniques as the rapid development of AI in surgery is promising a more automated decision-making and surgical movements in the operating room.

CONCLUSION

Fluorescence-guided surgery, CEUS, UHFUS, PAI, and AR are becoming crucial to give surgeons a new level of information during the intervention, with the right timing and sequence, and represent the future of surgery. As many more controlled studies are needed to validate the employment of these technologies, the next generation of surgeons must become more familiar with the basics of AI to better incorporate new tools into the daily surgical practice of the future.

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.

Point spread function modeling for photoacoustic tomography - I: three-dimensional detection geometries

Photoacoustic computed tomography (PACT) has been under intensive investigation as a promising noninvasive biomedical imaging modality. Various acoustic detector arrays have been developed to achieve enhanced imaging performance. In this paper, we study the effect of the detection geometry on image quality through point spread function (PSF) modeling based on back-projection image reconstruction. Three commonly-used three-dimensional detection geometries, namely, spherical, cylindrical, and planar detector arrays, are investigated. The effect of detector bandwidth and aperture on PSF in these detection geometries is also studied. This work provides a performance evaluation tool for acoustic detector arrays used in PACT and can be helpful in the design and selection of detector arrays in practical imaging applications.

Recent Advances in the Development of Non-Invasive Imaging Probes for Cancer Immunotherapy

The last two decades have witnessed a major revolution in the field of tumor immunology including clinical progress using various immunotherapy strategies. These advances have highlighted the potential for approaches that harness the power of the immune system to fight against cancer. While cancer immunotherapies have shown significant clinical successes, patient responses vary widely due to the complex and heterogeneous nature of tumors and immune responses, calling for reliable biomarkers and therapeutic strategies to maximize the benefits of immunotherapy. Especially, stratifying responding individuals from non-responders during the early stages of treatment could help avoid long-term damage and tailor personalized treatments. In efforts to develop non-invasive means for accurately evaluating and predicting tumor response to immunotherapy, multiple affinity-based agents targeting immune cell markers and checkpoint molecules have been developed and advanced to clinical trials. In addition, researchers have recently turned their attention to substrate and activity-based imaging probes that can provide real-time, functional assessment of immune response to treatment. Here, we highlight some of those recently designed probes that image functional proteases as biomarkers of cancer immunotherapy with a focus on their chemical design and detection modalities and discuss challenges and opportunities for the development of imaging tools utilized in cancer immunotherapy.

Optical ultrasound sensors for photoacoustic imaging: a review

Significance

Photoacoustic (PA) imaging is an emerging biomedical imaging modality that can map optical absorption contrast in biological tissues by detecting ultrasound signal. Piezoelectric transducers are commonly used in PA imaging to detect the ultrasound signals. However, piezoelectric transducers suffer from low sensitivity when the dimensions are reduced and are easily influenced by electromagnetic interference. To avoid these limitations, various optical ultrasound sensors have been developed and shown their great potential in PA imaging.

Aim

Our study aims to summarize recent progress in optical ultrasound sensor technologies and their applications in PA imaging.

Approach

The commonly used optical ultrasound sensing techniques and their applications in PA systems are reviewed. The technical advances of different optical ultrasound sensors are summarized.

Results

Optical ultrasound sensors can provide wide bandwidth and improved sensitivity with miniatured size, which enables their applications in PA imaging.

Conclusions

The optical ultrasound sensors are promising transducers in PA imaging to provide higher-resolution images and can be used in new applications with their unique advantages.

Effects of skin tone on photoacoustic imaging and oximetry

Significance

Photoacoustic imaging (PAI) provides contrast based on the concentration of optical absorbers in tissue, enabling the assessment of functional physiological parameters such as blood oxygen saturation (sO 2 ). Recent evidence suggests that variation in melanin levels in the epidermis leads to measurement biases in optical technologies, which could potentially limit the application of these biomarkers in diverse populations.

Aim

To examine the effects of skin melanin pigmentation on PAI and oximetry.

Approach

We evaluated the effects of skin tone in PAI using a computational skin model, two-layer melanin-containing tissue-mimicking phantoms, and mice of a consistent genetic background with varying pigmentations. The computational skin model was validated by simulating the diffuse reflectance spectrum using the adding-doubling method, allowing us to assign our simulation parameters to approximate Fitzpatrick skin types. Monte Carlo simulations and acoustic simulations were run to obtain idealized photoacoustic images of our skin model. Photoacoustic images of the phantoms and mice were acquired using a commercial instrument. Reconstructed images were processed with linear spectral unmixing to estimate blood oxygenation. Linear unmixing results were compared with a learned unmixing approach based on gradient-boosted regression.

Results

Our computational skin model was consistent with representative literature for in vivo skin reflectance measurements. We observed consistent spectral coloring effects across all model systems, with an overestimation of sO 2 and more image artifacts observed with increasing melanin concentration. The learned unmixing approach reduced the measurement bias, but predictions made at lower blood sO 2 still suffered from a skin tone-dependent effect.

Conclusion

PAI demonstrates measurement bias, including an overestimation of blood sO 2 , in higher Fitzpatrick skin types. Future research should aim to characterize this effect in humans to ensure equitable application of the technology.

Molecular and cellular imaging of the eye

The application of molecular and cellular imaging in ophthalmology has numerous benefits. It can enable the early detection and diagnosis of ocular diseases, facilitating timely intervention and improved patient outcomes. Molecular imaging techniques can help identify disease biomarkers, monitor disease progression, and evaluate treatment responses. Furthermore, these techniques allow researchers to gain insights into the pathogenesis of ocular diseases and develop novel therapeutic strategies. Molecular and cellular imaging can also allow basic research to elucidate the normal physiological processes occurring within the eye, such as cell signaling, tissue remodeling, and immune responses. By providing detailed visualization at the molecular and cellular level, these imaging techniques contribute to a comprehensive understanding of ocular biology. Current clinically available imaging often relies on confocal microscopy, multi-photon microscopy, PET (positron emission tomography) or SPECT (single-photon emission computed tomography) techniques, optical coherence tomography (OCT), and fluorescence imaging. Preclinical research focuses on the identification of novel molecular targets for various diseases. The aim is to discover specific biomarkers or molecular pathways associated with diseases, allowing for targeted imaging and precise disease characterization. In parallel, efforts are being made to develop sophisticated and multifunctional contrast agents that can selectively bind to these identified molecular targets. These contrast agents can enhance the imaging signal and improve the sensitivity and specificity of molecular imaging by carrying various imaging labels, including radionuclides for PET or SPECT, fluorescent dyes for optical imaging, or nanoparticles for multimodal imaging. Furthermore, advancements in technology and instrumentation are being pursued to enable multimodality molecular imaging. Integrating different imaging modalities, such as PET/MRI (magnetic resonance imaging) or PET/CT (computed tomography), allows for the complementary strengths of each modality to be combined, providing comprehensive molecular and anatomical information in a single examination. Recently, photoacoustic microscopy (PAM) has been explored as a novel imaging technology for visualization of different retinal diseases. PAM is a non-invasive, non-ionizing radiation, and hybrid imaging modality that combines the optical excitation of contrast agents with ultrasound detection. It offers a unique approach to imaging by providing both anatomical and functional information. Its ability to utilize molecularly targeted contrast agents holds great promise for molecular imaging applications in ophthalmology. In this review, we will summarize the application of multimodality molecular imaging for tracking chorioretinal angiogenesis along with the migration of stem cells after subretinal transplantation in vivo.

Photoacoustic imaging for cutaneous melanoma assessment: a comprehensive review

Significance

Cutaneous melanoma (CM) has a high morbidity and mortality rate, but it can be cured if the primary lesion is detected and treated at an early stage. Imaging techniques such as photoacoustic (PA) imaging (PAI) have been studied and implemented to aid in the detection and diagnosis of CM.

Aim

Provide an overview of different PAI systems and applications for the study of CM, including the determination of tumor depth/thickness, cancer-related angiogenesis, metastases to lymph nodes, circulating tumor cells (CTCs), virtual histology, and studies using exogenous contrast agents.

Approach

A systematic review and classification of different PAI configurations was conducted based on their specific applications for melanoma detection. This review encompasses animal and preclinical studies, offering insights into the future potential of PAI in melanoma diagnosis in the clinic.

Results

PAI holds great clinical potential as a noninvasive technique for melanoma detection and disease management. PA microscopy has predominantly been used to image and study angiogenesis surrounding tumors and provide information on tumor characteristics. Additionally, PA tomography, with its increased penetration depth, has demonstrated its ability to assess melanoma thickness. Both modalities have shown promise in detecting metastases to lymph nodes and CTCs, and an all-optical implementation has been developed to perform virtual histology analyses. Animal and human studies have successfully shown the capability of PAI to detect, visualize, classify, and stage CM.

Conclusions

PAI is a promising technique for assessing the status of the skin without a surgical procedure. The capability of the modality to image microvasculature, visualize tumor boundaries, detect metastases in lymph nodes, perform fast and label-free histology, and identify CTCs could aid in the early diagnosis and classification of CM, including determination of metastatic status. In addition, it could be useful for monitoring treatment efficacy noninvasively.

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.

Quantitative photoacoustic tomography: modeling and inverse problems

Significance

Quantitative photoacoustic tomography (QPAT) exploits the photoacoustic effect with the aim of estimating images of clinically relevant quantities related to the tissue's optical absorption. The technique has two aspects: an acoustic part, where the initial acoustic pressure distribution is estimated from measured photoacoustic time-series, and an optical part, where the distributions of the optical parameters are estimated from the initial pressure.

Aim

Our study is focused on the optical part. In particular, computational modeling of light propagation (forward problem) and numerical solution methodologies of the image reconstruction (inverse problem) are discussed.

Approach

The commonly used mathematical models of how light and sound propagate in biological tissue are reviewed. A short overview of how the acoustic inverse problem is usually treated is given. The optical inverse problem and methods for its solution are reviewed. In addition, some limitations of real-life measurements and their effect on the inverse problems are discussed.

Results

An overview of QPAT with a focus on the optical part was given. Computational modeling and inverse problems of QPAT were addressed, and some key challenges were discussed. Furthermore, the developments for tackling these problems were reviewed. Although modeling of light transport is well-understood and there is a well-developed framework of inverse mathematics for approaching the inverse problem of QPAT, there are still challenges in taking these methodologies to practice.

Conclusions

Modeling and inverse problems of QPAT together were discussed. The scope was limited to the optical part, and the acoustic aspects were discussed only to the extent that they relate to the optical aspect.

Deep learning in vivo catheter tip locations for photoacoustic-guided cardiac interventions

Significance

Interventional cardiac procedures often require ionizing radiation to guide cardiac catheters to the heart. To reduce the associated risks of ionizing radiation, photoacoustic imaging can potentially be combined with robotic visual servoing, with initial demonstrations requiring segmentation of catheter tips. However, typical segmentation algorithms applied to conventional image formation methods are susceptible to problematic reflection artifacts, which compromise the required detectability and localization of the catheter tip.

Aim

We describe a convolutional neural network and the associated customizations required to successfully detect and localize in vivo photoacoustic signals from a catheter tip received by a phased array transducer, which is a common transducer for transthoracic cardiac imaging applications.

Approach

We trained a network with simulated photoacoustic channel data to identify point sources, which appropriately model photoacoustic signals from the tip of an optical fiber inserted in a cardiac catheter. The network was validated with an independent simulated dataset, then tested on data from the tips of cardiac catheters housing optical fibers and inserted into ex vivo and in vivo swine hearts.

Results

When validated with simulated data, the network achieved an F 1 score of 98.3% and Euclidean errors (mean ± one standard deviation) of 1.02 ± 0.84    mm for target depths of 20 to 100 mm. When tested on ex vivo and in vivo data, the network achieved F 1 scores as large as 100.0%. In addition, for target depths of 40 to 90 mm in the ex vivo and in vivo data, up to 86.7% of axial and 100.0% of lateral position errors were lower than the axial and lateral resolution, respectively, of the phased array transducer.

Conclusions

These results demonstrate the promise of the proposed method to identify photoacoustic sources in future interventional cardiology and cardiac electrophysiology applications.

Photoacoustic Imaging Endometriosis Lesions with Nanoparticulate Polydopamine as a Contrast Agent

Endometriosis (EM) is a prevalent and debilitating gynecological disorder primarily affecting women of reproductive age. The diagnosis of EM is historically hampered by delays, owing to the absence of reliable diagnostic and monitoring techniques. Herein, it is reported that photoacoustic imaging can be a noninvasive modality for deep-seated EM by employing a hyaluronic-acid-modified polydopamine (PDA@HA) nanoparticle as the contrast agent. The PDA@HA nanoparticles exhibit inherent absorption and photothermal effects when exposed to near-infrared light, proficiently converting thermal energy into sound waves. Leveraging the targeting properties of HA, distinct photoacoustic signals emanating from the periphery of orthotopic EM lesions are observed. These findings are corroborated through anatomical observations and in vivo experiments involving mice with green fluorescent protein-labeled EM lesions. Moreover, the changes in photoacoustic intensity over a 24 h period reflect the dynamic evolution of PDA@HA nanoparticle biodistribution. Through the utilization of a photoacoustic ultrasound modality, in vivo assessments of EM lesion volumes are conducted. This innovative approach not only facilitates real-time monitoring of the therapeutic kinetics of candidate drugs but also obviates the need for the sacrifice of experimental mice. As such, this study presents a promising avenue for enhancing the diagnosis and drug-screening processes of EM.

S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo

OBJECTIVE

Photoacoustic imaging has undergone rapid development in recent years. To simulate photoacoustic imaging on a computer, the most popular MATLAB toolbox currently used for the forward projection process is k-Wave. However, k-Wave suffers from significant computation time. Here we propose a straightforward simulation approach based on superposed Wave (s-Wave) to accelerate photoacoustic simulation.

METHODS

In this study, we consider the initial pressure distribution as a collection of individual pixels. By obtaining standard sensor data from a single pixel beforehand, we can easily manipulate the phase and amplitude of the sensor data for specific pixels using loop and multiplication operators. The effectiveness of this approach is validated through an optimization-based reconstruction algorithm.

RESULTS

The results reveal significantly reduced computation time compared with k-Wave. Particularly in a sparse 3-D configuration, s-Wave exhibits a speed improvement >2000 times compared with k-Wave. In terms of optimization-based image reconstruction, in vivo imaging results reveal that using the s-Wave method yields images highly similar to those obtained using k-Wave, while reducing the reconstruction time by approximately 50 times.

CONCLUSION

Proposed here is an accelerated optimization-based algorithm for photoacoustic image reconstruction, using the fast s-Wave forward projection simulation. Our method achieves substantial time savings, particularly in sparse system configurations. Future work will focus on further optimizing the algorithm and expanding its applicability to a broader range of photoacoustic imaging scenarios.

Fluorescence-Based Mono- and Multimodal Imaging for In Vivo Tracking of Mesenchymal Stem Cells

The advancement of stem cell therapy has offered transformative therapeutic outcomes for a wide array of diseases over the past decades. Consequently, stem cell tracking has become significant in revealing the mechanisms of action and ensuring safe and effective treatments. Fluorescence stands out as a promising choice for stem cell tracking due to its myriad advantages, including high resolution, real-time monitoring, and multi-fluorescence detection. Furthermore, combining fluorescence with other tracking modalities-such as bioluminescence imaging (BLI), positron emission tomography (PET), photoacoustic (PA), computed tomography (CT), and magnetic resonance (MR)-can address the limitations of single fluorescence detection. This review initially introduces stem cell tracking using fluorescence imaging, detailing various labeling strategies such as green fluorescence protein (GFP) tagging, fluorescence dye labeling, and nanoparticle uptake. Subsequently, we present several combinations of strategies for efficient and precise detection.

Multimodal photoacoustic microscopy, optical coherence tomography, and fluorescence imaging of USH2A knockout rabbits

Usher syndrome type 2A (USH2A) is a genetic disorder characterized by retinal degeneration and hearing loss. To better understand the pathogenesis and progression of this syndrome, animal models such as USH2A knockout (USH2AKO) rabbits have been developed. In this study, we employed multimodal imaging techniques, including photoacoustic microscopy (PAM), optical coherence tomography (OCT), fundus autofluorescence (FAF), fluorescein angiography (FA), and indocyanine green angiography (ICGA) imaging to evaluate the retinal changes in the USH2AKO rabbit model. Twelve New Zealand White rabbits including USH2AKO and wild type (WT) were used for the experiments. Multimodal imaging was implemented at different time points over a period of 12 months to visualize the progression of retinal changes in USH2AKO rabbits. The results demonstrate that ellipsoid zone (EZ) disruption and degeneration, key features of Usher syndrome, began at the age of 4 months old and persisted up to 12 months. The EZ degeneration areas were clearly observed on the FAF and OCT images. The FAF images revealed retinal pigment epithelium (RPE) degeneration, confirming the presence of the disease phenotype in the USH2AKO rabbits. In addition, PAM images provided high-resolution and high image contrast of the optic nerve and the retinal microvasculature, including retinal vessels, choroidal vessels, and capillaries in three-dimensions. The quantification of EZ fluorescent intensity using FAF and EZ thickness using OCT provided comprehensive quantitative data on the progression of degenerative changes over time. This multimodal imaging approach allowed for a comprehensive and non-invasive assessment of retinal structure, microvasculature, and degenerative changes in the USH2AKO rabbit model. The combination of PAM, OCT, and fluorescent imaging facilitated longitudinal monitoring of disease progression and provided valuable insights into the pathophysiology of USH2A syndrome. These findings contribute to the understanding of USH2A syndrome and may have implications for the development of diagnostic and therapeutic strategies for affected individuals. The multimodal imaging techniques employed in this study offer a promising platform for preclinical evaluation of potential treatments and may pave the way for future clinical applications in patients with Usher syndrome.

Nanotheranostics: Molecular Diagnostics and Nanotherapeutic Evaluation by Photoacoustic/Ultrasound Imaging in Small Animals

Nanotheranostics is a rapidly developing field that integrates nanotechnology, diagnostics, and therapy to provide novel methods for imaging and treating wide categories of diseases. Targeted nanotheranostics offers a platform for the precise delivery of theranostic agents, and their therapeutic outcomes are monitored in real-time. Presently, in vivo magnetic resonance imaging, fluorescence imaging, ultrasound imaging, and photoacoustic imaging (PAI), etc. are noninvasive imaging techniques that are preclinically available for the imaging and tracking of therapeutic outcomes in small animals. Additionally, preclinical imaging is essential for drug development, phenotyping, and understanding disease stage progression and its associated mechanisms. Small animal ultrasound imaging is a rapidly developing imaging technique for theranostics applications due to its merits of being nonionizing, real-time, portable, and able to penetrate deep tissues. Recently, different types of ultrasound contrast agents have been explored, such as microbubbles, echogenic exosomes, gas-vesicles, and nanoparticles-based contrast agents. Moreover, an optical image obtained through photoacoustic imaging is a noninvasive imaging technique that creates ultrasonic waves when pulsed laser light is used to expose an object and creates a picture of the tissue's distribution of light energy absorption on the object. Contrast agents for photoacoustic imaging may be endogenous (hemoglobin, melanin, and DNA/RNA) or exogenous (dyes and nanomaterials-based contrast agents). The integration of nanotheranostics with photoacoustic and ultrasound imaging allows simultaneous imaging and treatment of diseases in small animals, which provides essential information about the drug response and the disease progression. In this review, we have covered various endogenous and exogenous contrast agents for ultrasound and photoacoustic imaging. Additionally, we have discussed various drug delivery systems integrated with contrast agents for theranostic application. Further, we have briefly discussed the current challenges associated with ultrasound and photoacoustic imaging.