Optoacoustic imaging and tomography: reconstruction approaches and outstanding challenges in image performance and quantification

Limited-view photoacoustic imaging reconstruction via high-quality self-supervised neural representation

In practical applications within the human body, it is often challenging to fully encompass the target tissue or organ, necessitating the use of limited-view arrays, which can lead to the loss of crucial information. Addressing the reconstruction of photoacoustic sensor signals in limited-view detection spaces has become a focal point of current research. In this study, we introduce a self-supervised network termed HIgh-quality Self-supervised neural representation (HIS), which tackles the inverse problem of photoacoustic imaging to reconstruct high-quality photoacoustic images from sensor data acquired under limited viewpoints. We regard the desired reconstructed photoacoustic image as an implicit continuous function in 2D image space, viewing the pixels of the image as sparse discrete samples. The HIS's objective is to learn the continuous function from limited observations by utilizing a fully connected neural network combined with Fourier feature position encoding. By simply minimizing the error between the network's predicted sensor data and the actual sensor data, HIS is trained to represent the observed continuous model. The results indicate that the proposed HIS model offers superior image reconstruction quality compared to three commonly used methods for photoacoustic image reconstruction.

Nanophotonic-enhanced photoacoustic imaging for brain tumor detection

Photoacoustic brain imaging (PABI) has emerged as a promising biomedical imaging modality, combining high contrast of optical imaging with deep tissue penetration of ultrasound imaging. This review explores the application of photoacoustic imaging in brain tumor imaging, highlighting the synergy between nanomaterials and state of the art optical techniques to achieve high-resolution imaging of deeper brain tissues. PABI leverages the photoacoustic effect, where absorbed light energy causes thermoelastic expansion, generating ultrasound waves that are detected and converted into images. This technique enables precise diagnosis, therapy monitoring, and enhanced clinical screening, specifically in the management of complex diseases such as breast cancer, lymphatic disorder, and neurological conditions. Despite integration of photoacoustic agents and ultrasound radiation, providing a comprehensive overview of current methodologies, major obstacles in brain tumor treatment, and future directions for improving diagnostic and therapeutic outcomes. The review underscores the significance of PABI as a robust research tool and medical method, with the potential to revolutionize brain disease diagnosis and treatment.

Quantitative photoacoustic imaging using known chromophores as fluence marker

Photoacoustic imaging offers optical contrast images of human tissue at acoustic resolution, making it valuable for diverse clinical applications. However, quantifying tissue composition via optical contrast remains challenging due to the unknown light fluence within the tissue. Here, we propose a method that leverages known chromophores (e.g., arterial blood) to improve the accuracy of quantitative photoacoustic imaging. By using the optical properties of a known chromophore as a fluence marker and integrating it into the optical inversion process, we can estimate the unknown fluence within the tissue. Experimentally, we demonstrate that this approach successfully recovers both the spectral shape and magnitude of the optical absorption coefficient of an unknown chromophore. Additionally, we show that the fluence marker method enhances conventional optical inversion techniques, specifically (i) a straightforward iterative approach and (ii) a gradient-based method. Our results indicate an improvement in accuracy of up to 24.4% when comparing optical absorption recovery with and without the fluence marker. Finally, we present the method's performance and illustrate its applications in carotid plaque quantification.

All-optical image transmission through a dynamically perturbed multimode fiber and a ring-core fiber using diffractive deep neural networks

In this study, we present an all-optical image reconstruction technique leveraging a diffractive deep neural network (D2NN) within a ring-core fiber (RCF) architecture. Orbital angular momentum (OAM) modes are employed to facilitate imaging transmission. We experimentally validate the efficacy of our approach for complex field diffractive image reconstruction through a multimode fiber (MMF) and RCF at a 1550 nm operating wavelength. The experimental results demonstrate the superior performance of the proposed method in mitigating RCF scattering-to-restoration transformation issues, significantly outperforming traditional MMF-based imaging correction techniques.

Potential applications for photoacoustic imaging using functional nanoparticles: A comprehensive overview

This paper presents a comprehensive overview of the potential applications for Photo-Acoustic (PA) imaging employing functional nanoparticles. The exploration begins with an introduction to nanotechnology and nanomaterials, highlighting the advancements in these fields and their crucial role in shaping the future. A detailed discussion of the various types of nanomaterials and their functional properties sets the stage for a thorough examination of the fundamentals of the PA effect. This includes a thorough chronological review of advancements, experimental methodologies, and the intricacies of the source and detection of PA signals. The utilization of amplitude and frequency modulation, design of PA cells, pressure sensor-based signal detection, and quantification methods are explored in-depth, along with additional mechanisms induced by PA signals. The paper then delves into the versatile applications of photoacoustic imaging facilitated by functional nanomaterials. It investigates the influence of nanomaterial shape, size variation, and the role of composition, alloys, and hybrid materials in harnessing the potential of PA imaging. The paper culminates with an insightful discussion on the future scope of this field, focusing specifically on the potential applications of photoacoustic (PA) effect in the domain of biomedical imaging and nanomedicine. Finally, by providing the comprehensive overview, the current work provides a valuable resource underscoring the transformative potential of PA imaging technique in biomedical research and clinical practice.

Recent Advances in Photoacoustic Imaging: Current Status and Future Perspectives

Photoacoustic imaging (PAI) is an emerging hybrid imaging modality that combines high-contrast optical imaging with high-spatial-resolution ultrasound imaging. PAI can provide a high spatial resolution and significant imaging depth by utilizing the distinctive spectroscopic characteristics of tissue, which gives it a wide variety of applications in biomedicine and preclinical research. In addition, it is non-ionizing and non-invasive, and photoacoustic (PA) signals are generated by a short-pulse laser under thermal expansion. In this study, we describe the basic principles of PAI, recent advances in research in human and animal tissues, and future perspectives.

Photoacoustic image reconstruction with an objective function using TGV and ESTGV as a regularization functional

Photoacoustic tomographic imaging is a non-invasive medical diagnostic technology for visualizing biological tissue. However, the inverse problem and noise in photoacoustic signals often cause blurred images. Existing regularization methods struggle with staircasing artifacts and edge preservation. To overcome this, an objective function incorporating total generalized variation (TGV) is proposed. However, it failed with high-density Gaussian noise. To address this, an extended version called edge-guided second-order TGV (ESTGV) is introduced. For sparsification, wavelet transform and discrete cosine transform are introduced, while the fast-composite-splitting algorithm is employed for the inverse problem solution. Experimental validation demonstrates the potential of these approaches.

Handheld interventional ultrasound/photoacoustic puncture needle navigation based on deep learning segmentation

Interventional ultrasound (US) has challenges in accurate localization of the puncture needle due to intrinsic acoustic interferences, which lead to blurred, indistinct, and even invisible needles in handheld linear array transducer-based US navigation, especially the incorrect needle tip positioning. Photoacoustic (PA) imaging can provide complementary image contrast, without additional data acquisition. Herein, we proposed an internal illumination to solely light up the needle tip in PA imaging. Then deep-learning-based feature segmentation alleviates acoustic interferences, enhancing the needle shaft-tip visibility. Further, needle shaft-tip compensation aligned the needle shaft in US image and the needle tip in the PA image. The experiments on phantom, ex vivo chicken breast, preclinical radiofrequency ablation and in vivo biopsy of sentinel lymph nodes were piloted. The target registration error can reach the submillimeter level, achieving precise puncture needle tracking ability with in-plane US/PA navigation.

3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks

Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hindered by the high acoustic impedance contrast between the skull and soft tissue. This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and deep learning for precise brain ultrasound reconstruction. We constructed a network comprising one input layer, four convolution layers, and one pooling layer to train our algorithm. In the simulation experiment, the Pearson correlation coefficient between the reconstructed and true images was exceptionally high. In the laboratory, the results showed a slightly lower but still impressive coincidence degree for 3D reconstruction, with pure water serving as the initial model and no prior information required. The 3D network can be trained in 8 h, and 10 samples can be reconstructed in just 12.67 s. The proposed 3D BIFCN algorithm provides a highly accurate and efficient solution for mapping wavefield frequency domain data to 3D brain models, enabling fast and precise brain tissue imaging. Moreover, the frequency shift phenomenon of blood may become a hallmark of BIFCN learning, offering valuable quantitative information for whole-brain blood 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.

Multispectral optoacoustic tomography (MSOT): Monitoring neurovascular changes in a mouse repetitive traumatic brain injury model

BACKGROUND

Evidence suggests that mild TBI injuries, which comprise > 75% of all TBIs, can cause chronic post-concussive symptoms, especially when experienced repetitively (rTBI). rTBI is a major cause of cognitive deficit in athletes and military personnel and is associated with neurovascular changes. Current methods to monitor neurovascular changes in detail are prohibitively expensive and invasive for patients with mild injuries.

NEW METHOD

We evaluated the potential of multispectral optoacoustic tomography (MSOT) to monitor neurovascular changes and assess therapeutic strategies in a mouse model of rTBI. Mice were subjected to rTBI or sham via controlled cortical impact and administered pioglitazone (PG) or vehicle. Oxygenated and deoxygenated hemoglobin were monitored using MSOT. Indocyanine green clearance was imaged via MSOT to evaluate blood-brain-barrier (BBB) integrity.

RESULTS

Mice subjected to rTBI show a transient increase in oxygenated/total hemoglobin ratio which can be mitigated by PG administration. rTBI mice also show BBB disruption shortly after injury and reduction of oxygenated/total hemoglobin in the chronic stage, neither of which were affected by PG intervention.

COMPARISON WITH EXISTING METHODS

MSOT imaging has the potential as a noninvasive in vivo imaging method to monitor neurovascular changes and assess therapeutics in mouse models of rTBI. In comparison to standard methods of tracking inflammation and BBB disruption, MSOT can be used multiple times throughout the course of injury without the need for surgery. Thus, MSOT is especially useful in research of rTBI models for screening therapeutics, and with further technological improvements may be extended for use in rTBI patients.

Invariant representations in deep learning for optoacoustic imaging

Image reconstruction in optoacoustic tomography (OAT) is a trending learning task highly dependent on measured physical magnitudes present at sensing time. A large number of different settings and also the presence of uncertainties or partial knowledge of parameters can lead to reconstruction algorithms that are specifically tailored and designed to a particular configuration, which could not be the one that will ultimately be faced in a final practical situation. Being able to learn reconstruction algorithms that are robust to different environments (e.g., the different OAT image reconstruction settings) or invariant to such environments is highly valuable because it allows us to focus on what truly matters for the application at hand and discard what are considered spurious features. In this work, we explore the use of deep learning algorithms based on learning invariant and robust representations for the OAT inverse problem. In particular, we consider the application of the ANDMask scheme due to its easy adaptation to the OAT problem. Numerical experiments are conducted showing that when out-of-distribution generalization (against variations in parameters such as the location of the sensors) is imposed, there is no degradation of the performance and, in some cases, it is even possible to achieve improvements with respect to standard deep learning approaches where invariance robustness is not explicitly considered.

PATLAB: A graphical computational software package for photoacoustic computed tomography research

Photoacoustic tomography (PAT) provides high resolution optical images of tissue at depths of up to several centimetres. This modality has been of interest to researchers for at least 30 years and is still the subject of intensive research. However, PAT researchers lack access to a comprehensive open-source graphical simulation and reconstruction software package. In this article, we introduce PATLAB, an open-source MATLAB-based graphical software package that can perform both PAT simulation and image reconstruction. PATLAB is simple to use yet is capable of complex PAT data processing tasks and offers advanced users a framework to build and test new methods.

Multistage adaptive noise reduction technique for optical resolution photoacoustic microscopy

Photoacoustic microscopy has received great attention due to the benefits of the optical resolution contrast as well as its superior spatial resolution and relatively deep depth. Like other imaging modalities, photoacoustic images suffer from noise, and filtering techniques are required to remove them. To overcome the noise, we proposed a combination of filters, including an adaptive median filter, an effective filter for impulsive noise, and a nonlocal means filter, an effective filter for background noise, for noise removal and image quality enhancement. Our proposed method enhanced the signal-to-noise ratio by 16 dB in an in vivo study compared to the traditional image reconstruction approach and preserved the image detail with minimal blurring, which usually occurs when filtering. These experimental results verified that the proposed adaptive multistage denoising techniques could effectively improve image quality under noisy data acquisition conditions, providing a strong foundation for photoacoustic microscopy with limited laser power.

Motion Compensation for 3D Multispectral Handheld Photoacoustic Imaging

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

Contrast Agents for Photoacoustic Imaging: A Review Focusing on the Wavelength Range

Photoacoustic imaging using endogenous chromophores as a contrast has been widely applied in biomedical studies owing to its functional imaging capability at the molecular level. Various exogenous contrast agents have also been investigated for use in contrast-enhanced imaging and functional analyses. This review focuses on contrast agents, particularly in the wavelength range, for use in photoacoustic imaging. The basic principles of photoacoustic imaging regarding light absorption and acoustic release are introduced, and the optical characteristics of tissues are summarized according to the wavelength region. Various types of contrast agents, including organic dyes, semiconducting polymeric nanoparticles, gold nanoparticles, and other inorganic nanoparticles, are explored in terms of their light absorption range in the near-infrared region. An overview of the contrast-enhancing capacity and other functional characteristics of each agent is provided to help researchers gain insights into the development of contrast agents in photoacoustic imaging.

Burst-mode pulse interferometry for enabling low-noise multi-channel optical detection of ultrasound

Ultrasound detection via optical resonators can achieve high levels of miniaturization and sensitivity as compared to piezoelectric detectors, but its scale-up from a single detector to an array is highly challenging. While the use of wideband sources may enable parallel interrogation of multiple resonators, it comes at the cost of reduction in the optical power, and ultimately in sensitivity, per channel. In this work we have developed a new interferometric approach to overcome this signal loss by using high-power bursts that are synchronized with the time window in which ultrasound detection is performed. Each burst is composed of a train of low-noise optical pulses which are sufficiently wideband to interrogate an array of resonators with non-overlapping spectra. We demonstrate our method, termed burst-mode pulse interferometry, for interrogating a single resonator in which the optical power was reduced to emulate the power loss per channel that occurs in parallel interrogation of 20 to 200 resonators. The use of bursts has led to up 25-fold improvement in sensitivity without affecting the shape of the acoustic signals, potentially enabling parallel low-noise interrogation of resonator arrays with a single source.

Alginate beads as a highly versatile test-sample for optoacoustic imaging

Test-samples are necessary for the development of emerging imaging approaches such as optoacoustics (OA); these can be used to benchmark new labeling agents and instrumentation, or to characterize image analysis algorithms or the inversion required to form the three-dimensional reconstructions. Alginate beads (AlBes) loaded with labeled mammalian or bacterial cells provide a method of creating defined structures of controllable size and photophysical characteristics and are well-suited for both in vitro and in vivo use. Here we describe a simple and rapid method for efficient and reproducible production of AlBes with specific characteristics and show three example applications with multispectral OA tomography imaging. We show the advantage of AlBes for studying and eventually improving photo-switching OA imaging approaches. As highly defined, homogeneous, quasi point-like signal sources, AlBes might hold similar advantages for studying other agents, light-fluence models, or the impact of detection geometries on correct image formation in the near future.

Toward Real-Time Giga-Voxel Optoacoustic/Photoacoustic Microscopy: GPU-Accelerated Fourier Reconstruction with Quasi-3D Implementation

We propose a GPU-accelerated implementation of frequency-domain synthetic aperture focusing technique (SAFT) employing truncated regularized inverse k-space interpolation. Our implementation achieves sub-1s reconstruction time for data sizes of up to 100 M voxels, providing more than a tenfold decrease in reconstruction time as compared to CPU-based SAFT. We provide an empirical model that can be used to predict the execution time of quasi-3D reconstruction for any data size given the specifications of the computing system.

On the robustness of model-based algorithms for photoacoustic tomography: Comparison between time and frequency domains

For photoacoustic image reconstruction, certain parameters such as sensor positions and speed of sound have a major impact on the reconstruction process and must be carefully determined before data acquisition. Uncertainties in these parameters can lead to errors produced by a modeling mismatch, hindering the reconstruction process and severely affecting the resulting image quality. Therefore, in this work, we study how modeling errors arising from uncertainty in sensor locations affect the images obtained by matrix model-based reconstruction algorithms based on time domain and frequency domain models of the photoacoustic problem. The effects on the reconstruction performance with respect to the uncertainty in the knowledge of the sensors location are compared and analyzed both in a qualitative and quantitative fashion for both time and frequency models. Ultimately, our study shows that the frequency domain approach is more sensitive to this kind of modeling errors. These conclusions are supported by numerical experiments and a theoretical sensitivity analysis of the mathematical operator for the direct problem.

Multi-Scale Photoacoustic Assessment of Wound Healing Using Chitosan-Graphene Oxide Hemostatic Sponge

Hemostasis is vital to save lives, reducing risks of organ failure and hemorrhagic shock. Exploring novel hemostatic materials and precise monitoring of the hemostatic status is of great importance for efficient hemostasis. We present the development of chitosan-graphene oxide-based hemostatic composite and multi-scale photoacoustic evaluation of the hemostatic performance. The hemostatic sponge can quickly and efficiently absorb the blood with its porous cavity and specific surficial property. We inspect the hemostatic performance via an in vitro blood absorption test and in vivo mouse bleeding injury experiments. Results show that the synthesized hemostatic sponge can not only absorb plasma in blood fast with its interior porous structure but also stimulate the interfacial reaction with erythrocytes and platelets. The superiority of multi-scale photoacoustic imaging for guiding, monitoring, and evaluating the hemostatic stages of sponges is demonstrated with high spatial resolution and great sensitivity at depths. Photoacoustic evaluation of a chitosan-graphene oxide-based hemostatic sponge has the potential to be transferred toward the clinical assessment of wound healing.

A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data

Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of such data is often hampered by opaque processing algorithms, which are challenging to verify and validate from a user perspective. Furthermore, such tools are inflexible, often locking users into a restricted set of processing motifs, which may not be able to accommodate the demands of diverse experiments. To address these needs, we have developed a Reconstruction, Analysis, and Filtering Toolbox to support the analysis of photoacoustic imaging data. The toolbox includes several algorithms to improve the overall quantification of photoacoustic imaging, including non-negative constraints and multispectral filters. We demonstrate various use cases, including dynamic imaging challenges and quantification of drug effect, and describe the ability of the toolbox to be parallelized on a high performance computing cluster.

Label-free concurrent 5-modal microscopy (Co5M) resolves unknown spatio-temporal processes in wound healing

The non-invasive investigation of multiple biological processes remains a methodological challenge as it requires capturing different contrast mechanisms, usually not available with any single modality. Intravital microscopy has played a key role in dynamically studying biological morphology and function, but it is generally limited to resolving a small number of contrasts, typically generated by the use of transgenic labels, disturbing the biological system. We introduce concurrent 5-modal microscopy (Co5M), illustrating a new concept for label-free in vivo observations by simultaneously capturing optoacoustic, two-photon excitation fluorescence, second and third harmonic generation, and brightfield contrast. We apply Co5M to non-invasively visualize multiple wound healing biomarkers and quantitatively monitor a number of processes and features, including longitudinal changes in wound shape, microvascular and collagen density, vessel size and fractality, and the plasticity of sebaceous glands. Analysis of these parameters offers unique insights into the interplay of wound closure, vasodilation, angiogenesis, skin contracture, and epithelial reformation in space and time, inaccessible by other methods. Co5M challenges the conventional concept of biological observation by yielding multiple simultaneous parameters of pathophysiological processes in a label-free mode.

Photoacoustic 3-D imaging of polycrystalline microstructure improved with transverse acoustic waves

Non-invasive fast imaging of grain microstructure of polycrystalline ceria with sub-micrometric spatial resolution is performed via time-domain Brillouin scattering. The propagation of a nanoacoustic pulse is monitored down to 8 μm deep in a 30 × 30 μm2 area. Grains boundaries are reconstructed in three-dimensions via a two-step processing method, relying on the wavelet synchro-squeezed transform and the alphashape algorithm. Imaging contrast is improved by taking advantage of stronger sensitivity to anisotropy of transverse acoustic waves, compared with longitudinal waves. Utilization of transverse waves in the image processing reveals additional boundaries, confirmed by an electron backscattering diffraction pattern but not discerned using longitudinal waves. A buried inclined interface between differently oriented grains is identified by monitoring changes in amplitude (phase) of the portion of the signal associated with transverse (longitudinal) waves. Estimates of the inclination angle of this interface prove the sensitivity of our laser ultrasonic method to image inclined boundaries.

Photoacoustic computed tomography for functional human brain imaging [Invited]

The successes of magnetic resonance imaging and modern optical imaging of human brain function have stimulated the development of complementary modalities that offer molecular specificity, fine spatiotemporal resolution, and sufficient penetration simultaneously. By virtue of its rich optical contrast, acoustic resolution, and imaging depth far beyond the optical transport mean free path (∼1 mm in biological tissues), photoacoustic computed tomography (PACT) offers a promising complementary modality. In this article, PACT for functional human brain imaging is reviewed in its hardware, reconstruction algorithms, in vivo demonstration, and potential roadmap.

Emerging contrast agents for multispectral optoacoustic imaging and their biomedical applications

Optoacoustic imaging is a hybrid biomedical imaging modality which collects ultrasound waves generated via photoexciting contrast agents in tissues and produces images of high resolution and penetration depth. As a functional optoacoustic imaging technique, multispectral optoacoustic imaging, which can discriminate optoacoustic signals from different contrast agents by illuminating samples with multi-wavelength lasers and then processing the collected data with specific algorithms, assists in the identification of a specific contrast agent in target tissues and enables simultaneous molecular and physiological imaging. Moreover, multispectral optoacoustic imaging can also generate three-dimensional images for biological tissues/samples with high resolution and thus holds great potential in biomedical applications. Contrast agents play essential roles in optoacoustic imaging, and they have been widely explored and applied as probes and sensors in recent years, leading to the emergence of a variety of new contrast agents. In this review, we aim to summarize the latest advances in emerging contrast agents, especially the activatable ones which can respond to specific biological stimuli, as well as their preclinical and clinical applications. We highlight their design strategies, discuss the challenges and prospects in multispectral optoacoustic imaging, and outline the possibility of applying it in clinical translation and public health services using synthetic contrast agents.

Photoacoustic Neuroimaging - Perspectives on a Maturing Imaging Technique and its Applications in Neuroscience

A prominent goal of neuroscience is to improve our understanding of how brain structure and activity interact to produce perception, emotion, behavior, and cognition. The brain's network activity is inherently organized in distinct spatiotemporal patterns that span scales from nanometer-sized synapses to meter-long nerve fibers and millisecond intervals between electrical signals to decades of memory storage. There is currently no single imaging method that alone can provide all the relevant information, but intelligent combinations of complementary techniques can be effective. Here, we thus present the latest advances in biomedical and biological engineering on photoacoustic neuroimaging in the context of complementary imaging techniques. A particular focus is placed on recent advances in whole-brain photoacoustic imaging in rodent models and its influential role in bridging the gap between fluorescence microscopy and more non-invasive techniques such as magnetic resonance imaging (MRI). We consider current strategies to address persistent challenges, particularly in developing molecular contrast agents, and conclude with an overview of potential future directions for photoacoustic neuroimaging to provide deeper insights into healthy and pathological brain processes.

Optoacoustic imaging in endocrinology and metabolism

Imaging is an essential tool in research, diagnostics and the management of endocrine disorders. Ultrasonography, nuclear medicine techniques, MRI, CT and optical methods are already used for applications in endocrinology. Optoacoustic imaging, also termed photoacoustic imaging, is emerging as a method for visualizing endocrine physiology and disease at different scales of detail: microscopic, mesoscopic and macroscopic. Optoacoustic contrast arises from endogenous light absorbers, such as oxygenated and deoxygenated haemoglobin, lipids and water, or exogenous contrast agents, and reveals tissue vasculature, perfusion, oxygenation, metabolic activity and inflammation. The development of high-performance optoacoustic scanners for use in humans has given rise to a variety of clinical investigations, which complement the use of the technology in preclinical research. Here, we review key progress with optoacoustic imaging technology as it relates to applications in endocrinology; for example, to visualize thyroid morphology and function, and the microvasculature in diabetes mellitus or adipose tissue metabolism, with particular focus on multispectral optoacoustic tomography and raster-scan optoacoustic mesoscopy. We explain the merits of optoacoustic microscopy and focus on mid-infrared optoacoustic microscopy, which enables label-free imaging of metabolites in cells and tissues. We showcase current optoacoustic applications within endocrinology and discuss the potential of these technologies to advance research and clinical practice.

A method for the calibration of wideband ultrasonic sensors for optoacoustics

A method for calibration of ultrasonic sensors for optoacoustics that provides both frequency response and sensitivity is presented. In order to obtain the bandwidth and the frequency response of an uncalibrated sensor, a point source with broadband spectra generated by a laser-induced bubble on a copper wire submerged in water is employed. On the other hand, the sensitivity measurement relies on the spatial symmetry of the pressure pulse and on a calibrated transducer. Therefore, two sensors are employed to detect the pressure pulse at the same distance from the source. The symmetry of the acoustic field that arrives at both transducers is adjusted and verified by means of an optical interferometer that provides a null signal when the copper wire is placed at the right position. The method is tested on the characterization of a thin-film polymeric piezoelectric transducer with a cylindrical focused shape.

Deep learning in photoacoustic imaging: a review

SIGNIFICANCE

Photoacoustic (PA) imaging can provide structural, functional, and molecular information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal detection deteriorates image quality, and quantitative PAI (QPAI) remains challenging due to the unknown light fluence spectra in deep tissue. In recent years, deep learning (DL) has shown outstanding performance when implemented in PAI, with applications in image reconstruction, quantification, and understanding.

AIM

We provide (i) a comprehensive overview of the DL techniques that have been applied in PAI, (ii) references for designing DL models for various PAI tasks, and (iii) a summary of the future challenges and opportunities.

APPROACH

Papers published before November 2020 in the area of applying DL in PAI were reviewed. We categorized them into three types: image understanding, reconstruction of the initial pressure distribution, and QPAI.

RESULTS

When applied in PAI, DL can effectively process images, improve reconstruction quality, fuse information, and assist quantitative analysis.

CONCLUSION

DL has become a powerful tool in PAI. With the development of DL theory and technology, it will continue to boost the performance and facilitate the clinical translation of PAI.

Deep Learning for Automatic Segmentation of Hybrid Optoacoustic Ultrasound (OPUS) Images

The highly complementary information provided by multispectral optoacoustics and pulse-echo ultrasound have recently prompted development of hybrid imaging instruments bringing together the unique contrast advantages of both modalities. In the hybrid optoacoustic ultrasound (OPUS) combination, images retrieved by one modality may further be used to improve the reconstruction accuracy of the other. In this regard, image segmentation plays a major role as it can aid improving the image quality and quantification abilities by facilitating modeling of light and sound propagation through the imaged tissues and surrounding coupling medium. Here, we propose an automated approach for surface segmentation in whole-body mouse OPUS imaging using a deep convolutional neural network (CNN). The method has shown robust performance, attaining accurate segmentation of the animal boundary in both optoacoustic and pulse-echo ultrasound images, as evinced by quantitative performance evaluation using Dice coefficient metrics.

Real-time interleaved spectroscopic photoacoustic and ultrasound (PAUS) scanning with simultaneous fluence compensation and motion correction

For over two decades photoacoustic imaging has been tested clinically, but successful human trials have been limited. To enable quantitative clinical spectroscopy, the fundamental issues of wavelength-dependent fluence variations and inter-wavelength motion must be overcome. Here we propose a real-time, spectroscopic photoacoustic/ultrasound (PAUS) imaging approach using a compact, 1-kHz rate wavelength-tunable laser. Instead of illuminating tissue over a large area, the fiber-optic delivery system surrounding an US array sequentially scans a narrow laser beam, with partial PA image reconstruction for each laser pulse. The final image is then formed by coherently summing partial images. This scheme enables (i) automatic compensation for wavelength-dependent fluence variations in spectroscopic PA imaging and (ii) motion correction of spectroscopic PA frames using US speckle tracking in real-time systems. The 50-Hz video rate PAUS system is demonstrated in vivo using a murine model of labelled drug delivery.

Photoacoustic and high-frequency ultrasound imaging of systemic sclerosis patients

Introduction

Systemic sclerosis starts with an early phase characterized by Raynaud’s phenomenon, puffy fingers/hands, autoantibodies, and a scleroderma nailfold microscopic pattern. Alterations in the nailfold microscopic pattern are not evident in all early SSc patients. Photoacoustics (PA) and high-frequency ultrasound (HFUS) could fulfill this need. The former can measure oxygen saturation while the latter can measure skin thickening. We hypothesize that photoacoustics and high-frequency ultrasound can distinguish (early) SSc patients from individuals with primary Raynaud’s phenomenon (PRP) by measuring oxygenation of the fingertip and skin thickening.

Methods

We compared measurements of oxygenation and skin thickness of the third finger between (early) SSc patients and PRP individuals and healthy controls. The spearman rank correlation was used to analyze an association between capillary density and oxygen saturation of the fingers.

Results

Thirty-one adult subjects participated in this study: twelve patients with SSc, 5 patients with early SSc, 5 volunteers with PR, and 9 healthy controls.

We found a significant difference in oxygen saturation between (early) SSc patients (80.8% ± 8.1 and 77.9% ± 10.5) and individuals with PRP (93.9% ± 1.1).

Measurements of skin thickening showed a significant difference in (early) SSc patients compared to individuals with PRP (0.48 ± 0.06 mm and 0.51 ± 0.16 mm vs. 0.27 ± 0.01 mm). There was no significant difference between healthy and PRP individuals in oxygenation or skin thickening.

Conclusion

Photoacoustic and high-frequency ultrasound could help to distinguish between (early) SSc, PRP, and healthy individuals in both oxygenation and skin thickening.

Photoacoustic Imaging

Photoacoustic imaging (PAI) is an emerging imaging modality that shows great potential for preclinical research and clinical practice. As a hybrid technique, PAI uniquely combines the advantages of optical excitation and of acoustic detection. Optical excitation provides a rich contrast mechanism from either endogenous or exogenous chromophores, allowing PAI to perform biochemical, functional, and molecular imaging. Acoustic detection benefits from the low scattering of ultrasound in biological tissue, enabling PAI to generate high-resolution images in both the optical ballistic and diffusive regimes. Accordingly, this hybrid imaging modality features high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth. Over the past two decades, the photoacoustic technique has led to a variety of exciting discoveries and applications from laboratory research to clinical patient care. In biological research, PAI has become an irreplaceable tool, providing functional optical contrast with high spatiotemporal resolution. Translational PAI also attracted growing interest in clinical applications including tumor margin examination, internal organ imaging, breast cancer screening, and sentinel lymph node mapping, among others.

Portable and Affordable Light Source-Based Photoacoustic Tomography

Photoacoustic imaging is a hybrid imaging modality that offers the advantages of optical (spectroscopic contrast) and ultrasound imaging (scalable spatial resolution and imaging depth). This promising modality has shown excellent potential in a wide range of preclinical and clinical imaging and sensing applications. Even though photoacoustic imaging technology has matured in research settings, its clinical translation is not happening at the expected pace. One of the main reasons for this is the requirement of bulky and expensive pulsed lasers for excitation. To accelerate the clinical translation of photoacoustic imaging and explore its potential in resource-limited settings, it is of paramount importance to develop portable and affordable light sources that can be used as the excitation light source. In this review, we focus on the following aspects: (1) the basic theory of photoacoustic imaging; (2) inexpensive light sources and different implementations; and (3) important preclinical and clinical applications, demonstrated using affordable light source-based photoacoustics. The main focus will be on laser diodes and light-emitting diodes as they have demonstrated promise in photoacoustic tomography-the key technological developments in these areas will be thoroughly reviewed. We believe that this review will be a useful opus for both the beginners and experts in the field of biomedical photoacoustic imaging.

Full-frequency correction of spatial impulse response in back-projection scheme using space-variant filtering for optoacoustic mesoscopy

The fidelity and quality of reconstructed images in optoacoustic mesoscopy (OPAM) can be significantly improved by considering the spatial impulse response (SIR) of the employed focused transducer into reconstruction. However, the traditional method fully taking the SIR into account can hardly meet the data-intensive requirements of high resolution OPAM because of excessive memory and time consumption. Herein, a modified back-projection method using a space-variant filter for full-frequency correction of the SIR is presented, and applied to the OPAM system with a sphere-focused transducer. The proposed method can readily manage the large datasets of the OPAM and effectively reduce the extra time consumption. The performance of the proposed method is showcased by simulations and experiments of phantoms and biological tissue. The results demonstrate that the modified back-projection method exhibits better image fidelity, resolution and contrast compared to the common and weighted back-projection methods that are not or not fully accounting for the SIR.

Optical Imaging Modalities: Principles and Applications in Preclinical Research and Clinical Settings

With the ability to noninvasively image and monitor molecular processes within tumors, molecular imaging represents a fundamental tool for cancer scientists. In the current review, we describe emergent optical technologies for molecular imaging. We aim to provide the reader with an overview of the fundamental principles on which each imaging strategy is based, to introduce established and future applications, and to provide a rationale for selecting optical technologies for molecular imaging depending on disease location, biology, and anatomy. To accelerate clinical translation of imaging techniques, we also describe examples of practical applications in patients. Elevating these techniques into standard-of-care tools will transform patient stratification, disease monitoring, and response evaluation.

Tomographic imaging with an ultrasound and LED-based photoacoustic system

Pulsed lasers in photoacoustic tomography systems are expensive, which limit their use to a few clinics and small animal labs. We present a method to realize tomographic ultrasound and photoacoustic imaging using a commercial LED-based photoacoustic and ultrasound system. We present two illumination configurations using LED array units and an optimal number of angular views for tomographic reconstruction. The proposed method can be a cost-effective solution for applications demanding tomographic imaging and can be easily integrated into conventional linear array-based ultrasound systems. We present a potential application for finger joint imaging in vivo, which can be used for point-of-care rheumatoid arthritis diagnosis and monitoring.

Quantitative PA tomography of high resolution 3-D images: Experimental validation in a tissue phantom

Quantitative photoacoustic tomography aims to recover the spatial distribution of absolute chromophore concentrations and their ratios from deep tissue, high-resolution images. In this study, a model-based inversion scheme based on a Monte-Carlo light transport model is experimentally validated on 3-D multispectral images of a tissue phantom acquired using an all-optical scanner with a planar detection geometry. A calibrated absorber allowed scaling of the measured data during the inversion, while an acoustic correction method was employed to compensate the effects of limited view detection. Chromophore- and fluence-dependent step sizes and Adam optimization were implemented to achieve rapid convergence. High resolution 3-D maps of absolute concentrations and their ratios were recovered with high accuracy. Potential applications of this method include quantitative functional and molecular photoacoustic tomography of deep tissue in preclinical and clinical studies.

Toroidally focused sensor array for real-time laser-ultrasonic imaging: The first experimental study

In this paper we report on the first toroidally focused 2D real-time laser-ultrasonic imaging system and a modified filtered back projection algorithm that can be used in the region near the waist of the astigmatic laser-ultrasonic probe beam. The system is capable of visualizing an acupuncture needle 0.2 mm in diameter located at ∼4 cm depth in water. The lateral spatial resolution is better than ∼0.32 mm and axial spatial resolution is ∼30 μm. The achieved frame rate is up to 30 Hz. The depth dependency of the sensitivity region width and lateral resolution are experimentally measured and discussed. The array is intended to be used as a part of combined real-time photoacoustic and laser-ultrasonic imaging system.

Photoacoustic Imaging in Tissue Engineering and Regenerative Medicine

Several imaging modalities are available for investigation of the morphological, functional, and molecular features of engineered tissues in small animal models. While research in tissue engineering and regenerative medicine (TERM) would benefit from a comprehensive longitudinal analysis of new strategies, researchers have not always applied the most advanced methods. Photoacoustic imaging (PAI) is a rapidly emerging modality that has received significant attention due to its ability to exploit the strong endogenous contrast of optical methods with the high spatial resolution of ultrasound methods. Exogenous contrast agents can also be used in PAI for targeted imaging. Applications of PAI relevant to TERM include stem cell tracking, longitudinal monitoring of scaffolds in vivo, and evaluation of vascularization. In addition, the emerging capabilities of PAI applied to the detection and monitoring of cancer and other inflammatory diseases could be exploited by tissue engineers. This article provides an overview of the operating principles of PAI and its broad potential for application in TERM. Impact statement Photoacoustic imaging, a new hybrid imaging technique, has demonstrated high potential in the clinical diagnostic applications. The optical and acoustic aspect of the photoacoustic imaging system works in harmony to provide better resolution at greater tissue depth. Label-free imaging of vasculature with this imaging can be used to track and monitor disease, as well as the therapeutic progression of treatment. Photoacoustic imaging has been utilized in tissue engineering to some extent; however, the full benefit of this technique is yet to be explored. The increasing availability of commercial photoacoustic systems will make application as an imaging tool for tissue engineering application more feasible. This review first provides a brief description of photoacoustic imaging and summarizes its current and potential application in tissue engineering.

Sensitivity Enhanced Photoacoustic Imaging Using a High-Frequency PZT Transducer with an Integrated Front-End Amplifier

Photoacoustic (PA) imaging is a hybrid imaging technique that can provide both structural and functional information of biological tissues. Due to limited permissible laser energy deposited on tissues, highly sensitive PA imaging is required. Here, we developed a 20 MHz lead zirconium titanate (PZT) transducer (1.5 mm × 3 mm) with front-end amplifier circuits for local signal processing to achieve sensitivity enhanced PA imaging. The electrical and acoustic performance was characterized. Experiments on phantoms and chicken breast tissue were conducted to validate the imaging performance. The fabricated prototype shows a bandwidth of 63% and achieves a noise equivalent pressure (NEP) of 0.24 mPa/√Hz and a receiving sensitivity of 62.1 μV/Pa at 20 MHz without degradation of the bandwidth. PA imaging of wire phantoms demonstrates that the prototype is capable of improving the detection sensitivity by 10 dB compared with the traditional transducer without integrated amplifier. In addition, in vitro experiments on chicken breast tissue show that structures could be imaged with enhanced contrast using the prototype and the imaging depth range was improved by 1 mm. These results demonstrate that the transducer with an integrated front-end amplifier enables highly sensitive PA imaging with improved penetration depth. The proposed method holds the potential for visualization of deep tissue structures and enhanced detection of weak physiological changes.

Software-defined optoacoustic tomography

In this work we present what we believe is the first application of software-defined optoelectronics (SDO) for bidimensional optoacoustic tomography (OAT). The SDO concept refers to optoelectronic systems where the functionality associated with the conditioning and processing of optical and electrical signals are digitally implemented and controlled by software. This paradigm takes advantage of the flexibility of software-defined hardware platforms to develop adaptive instrumentation systems. We implement an OAT system based on a heterodyne interferometer in a Mach-Zehnder configuration and a commercial software-defined radio platform (SDR). Here the SDR serves as a function generator and oscilloscope, while at the same time providing perfect carrier synchronization between its transmitter and receiver in a coherent baseband modulator scheme. This carrier synchronization enables us to have much better phase recovery. We study the performance of the OAT SDO system using different bidimensional phantoms and carry out an analysis of the reconstructed images.

Recent technological advancements in thermometry

Thermometry is the key factor for achieving successful thermal therapy. Although invasive thermometry with a probe has been used for more than four decades, this method can only detect the local temperature within the probing volume. Noninvasive temperature imaging using a tomographic technique is ideal for monitoring hot-spot formation in the human body. Among various techniques, such as X-ray computed tomography, microwave tomography, echo sonography, and magnetic resonance (MR) imaging, the proton resonance frequency shift method of MR thermometry is the only method currently available for clinical practice because its temperature sensitivity is consistent in most aqueous tissues and can be easily observed using common clinical scanners. New techniques are being proposed to improve the robustness of this method against tissue motion. MR techniques for fat thermometry were also developed based on relaxation times. One of the latest non-MR techniques to attract attention is photoacoustic imaging.

Current and future trends in photoacoustic breast imaging

Non-invasive detection of breast cancer has been regarded as the holy grail of applications for photoacoustic (optoacoustic) imaging right from the early days of re-discovery of the method. Two-and-a-half decades later we report on the state-of-the-art in photoacoustic breast imaging technology and clinical studies. Even within the single application of breast imaging, we find imagers with various measurement geometries, ultrasound detection characteristics, illumination schemes, and image reconstruction strategies. We first analyze the implications on performance of a few of these design choices in a generic imaging system, before going into detailed descriptions of the imagers. Per imaging system we present highlights of patient studies, which barring a couple are mostly in the nature of technology demonstrations and proof-of-principle studies. We close this work with a discussion on several aspects that may turn out to be crucial for the future clinical translation of the method.

Fast and High-Resolution Three-Dimensional Hybrid-Domain Photoacoustic Imaging Incorporating Analytical-Focused Transducer Beam Amplitude

Recently, many reconstruction methods have been developed to improve the lateral resolution of acoustic-resolution photoacoustic microscopy (ARPAM) in out-of-focus regions. Though these methods enhance image resolution to some extent, they require advanced computational hardware and large computational time, especially for three-dimensional (3-D) cases. However, some methods do not consider the finite size of a transducer, while others employ numerical discretization to build a focused transducer model that is less efficient and accurate. To overcome these problems, we propose a 3-D ARPAM imaging reconstruction method with high precision, high efficiency, and low memory cost. It inherits the framework of model-based reconstructions and incorporates the forward acoustic model in the hybrid domain. This hybrid-domain acoustic model promotes an analytical solution to establish a focused transducer model. Furthermore, the non-uniform fast Fourier transform (NUFFT) and deconvolution methods are introduced to reduce the required computational time and memory volume for 3-D reconstructions. According to the experimental results reconstructed by the proposed method, the lateral resolution of an ARPAM image recorded by a 20-MHz focused transducer (NA 0.393) can reach 88.39 [Formula: see text]. This resolution exceeds the diffraction limitation of the focused transducer ( [Formula: see text]). When reconstructing a 3-D image with 200×200×150 pixels, the proposed method takes only 8.15 s using a laptop loaded with Intel Core i7-8550U CPU at 1.8 GHz and 1.06-GB memory.

Modelling of errors due to speed of sound variations in photoacoustic tomography using a Bayesian framework

Inverse problem of estimating initial pressure in photoacoustic tomography is ill-posed and thus sensitive to errors in modelling and measurements. In practical experiments, accurate knowledge of the speed of sound of the imaged target is commonly not available, and therefore an approximate speed of sound is used in the computational model. This can result in errors in the solution of the inverse problem that can appear as artefacts in the reconstructed images. In this paper, the inverse problem of photoacoustic tomography is approached in a Bayesian framework. Errors due to uncertainties in the speed of sound are modelled using Bayesian approximation error modelling. Estimation of the initial pressure distribution together with information on the reliability of these estimates are considered. The approach was studied using numerical simulations. The results show that uncertainties in the speed of sound can cause significant errors in the solution of the inverse problem. However, modelling of these uncertainties improves the accuracy of the solution.

Dual-Polarized Fiber Laser Sensor for Photoacoustic Microscopy

Optical resolution photoacoustic microscopy (OR-PAM) provides high-resolution, label-free and non-invasive functional imaging for broad biomedical applications. Dual-polarized fiber laser sensors have high sensitivity, low noise, a miniature size, and excellent stability; thus, they have been used in acoustic detection in OR-PAM. Here, we review recent progress in fiber-laser-based ultrasound sensors for photoacoustic microscopy, especially the dual-polarized fiber laser sensor with high sensitivity. The principle, characterization and sensitivity optimization of this type of sensor are presented. In vivo experiments demonstrate its excellent performance in the detection of photoacoustic (PA) signals in OR-PAM. This review summarizes representative applications of fiber laser sensors in OR-PAM and discusses their further improvements.

Listening to tissues with new light: recent technological advances in photoacoustic imaging

Photoacoustic tomography (PAT), or optoacoustic tomography, has achieved remarkable progress in the past decade, benefiting from the joint developments in optics, acoustics, chemistry, computing and mathematics. Unlike pure optical or ultrasound imaging, PAT can provide unique optical absorption contrast as well as widely scalable spatial resolution, penetration depth and imaging speed. Moreover, PAT has inherent sensitivity to tissue's functional, molecular, and metabolic state. With these merits, PAT has been applied in a wide range of life science disciplines, and has enabled biomedical research unattainable by other imaging methods. This Review article aims at introducing state-of-the-art PAT technologies and their representative applications. The focus is on recent technological breakthroughs in structural, functional, molecular PAT, including super-resolution imaging, real-time small-animal whole-body imaging, and high-sensitivity functional/molecular imaging. We also discuss the remaining challenges in PAT and envisioned opportunities.

The Impulse Response of Negatively Focused Spherical Ultrasound Detectors and Its Effect on Tomographic Optoacoustic Reconstruction

In optoacoustic tomography, negatively focused detectors have been shown to improve the tangential image resolution without sacrificing sensitivity. Since no exact inversion formulas exist for optoacoustic image reconstruction with negatively focused detectors, image reconstruction in such cases is based on using the virtual-detector approximation, in which it is assumed that the response of the negatively focused detector is identical, up to a constant time delay, to that of a point-like detector positioned in the detector's center of curvature. In this paper, we analyze the response of negatively focused spherical ultrasound detectors in three dimensions and demonstrate how their properties affect the optoacoustic reconstruction. Our analysis sheds new light on commonly reported experimental reconstruction artifacts in optoacoustic systems that employ negatively focused detectors. Based on our analysis, we introduce a simple correction to the virtual-detector approximation that significantly enhances image contrast and reduces artifacts.