Photoacoustic computed tomography for functional human brain imaging [Invited]

Unsupervised disentanglement strategy for mitigating artifact in photoacoustic tomography under extremely sparse view

Traditional methods under sparse view for reconstruction of photoacoustic tomography (PAT) often result in significant artifacts. Here, a novel image to image transformation method based on unsupervised learning artifact disentanglement network (ADN), named PAT-ADN, was proposed to address the issue. This network is equipped with specialized encoders and decoders that are responsible for encoding and decoding the artifacts and content components of unpaired images, respectively. The performance of the proposed PAT-ADN was evaluated using circular phantom data and the animal in vivo experimental data. The results demonstrate that PAT-ADN exhibits excellent performance in effectively removing artifacts. In particular, under extremely sparse view (e.g., 16 projections), structural similarity index and peak signal-to-noise ratio are improved by ∼188 % and ∼85 % in in vivo experimental data using the proposed method compared to traditional reconstruction methods. PAT-ADN improves the imaging performance of PAT, opening up possibilities for its application in multiple domains.

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.

Comprehensive framework of GPU-accelerated image reconstruction for photoacoustic computed tomography

Significance

Photoacoustic computed tomography (PACT) is a promising non-invasive imaging technique for both life science and clinical implementations. To achieve fast imaging speed, modern PACT systems have equipped arrays that have hundreds to thousands of ultrasound transducer (UST) elements, and the element number continues to increase. However, large number of UST elements with parallel data acquisition could generate a massive data size, making it very challenging to realize fast image reconstruction. Although several research groups have developed GPU-accelerated method for PACT, there lacks an explicit and feasible step-by-step description of GPU-based algorithms for various hardware platforms.

Aim

In this study, we propose a comprehensive framework for developing GPU-accelerated PACT image reconstruction (GPU-accelerated photoacoustic computed tomography), to help the research community to grasp this advanced image reconstruction method.

Approach

We leverage widely accessible open-source parallel computing tools, including Python multiprocessing-based parallelism, Taichi Lang for Python, CUDA, and possible other backends. We demonstrate that our framework promotes significant performance of PACT reconstruction, enabling faster analysis and real-time applications. Besides, we also described how to realize parallel computing on various hardware configurations, including multicore CPU, single GPU, and multiple GPUs platform.

Results

Notably, our framework can achieve an effective rate of ∼ 871 times when reconstructing extremely large-scale three-dimensional PACT images on a dual-GPU platform compared to a 24-core workstation CPU. In this paper, we share example codes via GitHub.

Conclusions

Our approach allows for easy adoption and adaptation by the research community, fostering implementations of PACT for both life science and medicine.

PA-NeRF, a neural radiance field model for 3D photoacoustic tomography reconstruction from limited Bscan data

We introduce a novel deep-learning-based photoacoustic tomography method called Photoacoustic Tomography Neural Radiance Field (PA-NeRF) for reconstructing 3D volumetric PAT images from limited 2D Bscan data. In conventional 3D volumetric imaging, a 3D reconstruction requires transducer element data obtained from all directions. Our model employs a NeRF-based PAT 3D reconstruction method, which learns the relationship between transducer element positions and the corresponding 3D imaging. Compared with convolution-based deep-learning models, such as Unet and TransUnet, PA-NeRF does not learn the interpolation process but rather gains insight from 3D photoacoustic imaging principles. Additionally, we introduce a forward loss that improves the reconstruction quality. Both simulation and phantom studies validate the performance of PA-NeRF. Further, we apply the PA-NeRF model to clinical examples to demonstrate its feasibility. To the best of our knowledge, PA-NeRF is the first method in photoacoustic tomography to successfully reconstruct a 3D volume from sparse Bscan data.

Accelerated model-based iterative reconstruction strategy for sparse-view photoacoustic tomography aided by multi-channel autoencoder priors

Photoacoustic tomography (PAT) commonly works in sparse view due to data acquisition limitations. However, reconstruction suffers from serious deterioration (e.g., severe artifacts) using traditional algorithms under sparse view. Here, a novel accelerated model-based iterative reconstruction strategy for sparse-view PAT aided by multi-channel autoencoder priors was proposed. A multi-channel denoising autoencoder network was designed to learn prior information, which provides constraints for model-based iterative reconstruction. This integration accelerates the iteration process, leading to optimal reconstruction outcomes. The performance of the proposed method was evaluated using blood vessel simulation data and experimental data. The results show that the proposed method can achieve superior sparse-view reconstruction with a significant acceleration of iteration. Notably, the proposed method exhibits excellent performance under extremely sparse condition (e.g., 32 projections) compared with the U-Net method, with an improvement of 48% in PSNR and 12% in SSIM for in vivo experimental data.

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.

Review of Deep Learning Approaches for Interleaved Photoacoustic and Ultrasound (PAUS) Imaging

Photoacoustic (PA) imaging provides optical contrast at relatively large depths within the human body, compared to other optical methods, at ultrasound (US) spatial resolution. By integrating real-time PA and US (PAUS) modalities, PAUS imaging has the potential to become a routine clinical modality bringing the molecular sensitivity of optics to medical US imaging. For applications where the full capabilities of clinical US scanners must be maintained in PAUS, conventional limited view and bandwidth transducers must be used. This approach, however, cannot provide high-quality maps of PA sources, especially vascular structures. Deep learning (DL) using data-driven modeling with minimal human design has been very effective in medical imaging, medical data analysis, and disease diagnosis, and has the potential to overcome many of the technical limitations of current PAUS imaging systems. The primary purpose of this article is to summarize the background and current status of DL applications in PAUS imaging. It also looks beyond current approaches to identify remaining challenges and opportunities for robust translation of PAUS technologies to the clinic.

Advances in photoacoustic imaging aided by nano contrast agents: special focus on role of lymphatic system imaging for cancer theranostics

Photoacoustic imaging (PAI) is a successful clinical imaging platform for management of cancer and other health conditions that has seen significant progress in the past decade. However, clinical translation of PAI based methods are still under scrutiny as the imaging quality and clinical information derived from PA images are not on par with other imaging methods. Hence, to improve PAI, exogenous contrast agents, in the form of nanomaterials, are being used to achieve better image with less side effects, lower accumulation, and improved target specificity. Nanomedicine has become inevitable in cancer management, as it contributes at every stage from diagnosis to therapy, surgery, and even in the postoperative care and surveillance for recurrence. Nanocontrast agents for PAI have been developed and are being explored for early and improved cancer diagnosis. The systemic stability and target specificity of the nanomaterials to render its theranostic property depends on various influencing factors such as the administration route and physico-chemical responsiveness. The recent focus in PAI is on targeting the lymphatic system and nodes for cancer diagnosis, as they play a vital role in cancer progression and metastasis. This review aims to discuss the clinical advancements of PAI using nanoparticles as exogenous contrast agents for cancer theranostics with emphasis on PAI of lymphatic system for diagnosis, cancer progression, metastasis, PAI guided tumor resection, and finally PAI guided drug delivery.

Photoacoustic Imaging and Characterization of Bone in Medicine: Overview, Applications, and Outlook

Photoacoustic techniques have shown promise in identifying molecular changes in bone tissue and visualizing tissue microstructure. This capability represents significant advantages over gold standards (i.e., dual-energy X-ray absorptiometry) for bone evaluation without requiring ionizing radiation. Instead, photoacoustic imaging uses light to penetrate through bone, followed by acoustic pressure generation, resulting in highly sensitive optical absorption contrast in deep biological tissues. This review covers multiple bone-related photoacoustic imaging contributions to clinical applications, spanning bone cancer, joint pathologies, spinal disorders, osteoporosis, bone-related surgical guidance, consolidation monitoring, and transsphenoidal and transcranial imaging. We also present a summary of photoacoustic-based techniques for characterizing biomechanical properties of bone, including temperature, guided waves, spectral parameters, and spectroscopy. We conclude with a future outlook based on the current state of technological developments, recent achievements, and possible new directions.

Photoacoustic digital brain and deep-learning-assisted image reconstruction

Photoacoustic tomography (PAT) is a newly developed medical imaging modality, which combines the advantages of pure optical imaging and ultrasound imaging, owning both high optical contrast and deep penetration depth. Very recently, PAT is studied in human brain imaging. Nevertheless, while ultrasound waves are passing through the human skull tissues, the strong acoustic attenuation and aberration will happen, which causes photoacoustic signals' distortion. In this work, we use 180 T1 weighted magnetic resonance imaging (MRI) human brain volumes along with the corresponding magnetic resonance angiography (MRA) brain volumes, and segment them to generate the 2D human brain numerical phantoms for PAT. The numerical phantoms contain six kinds of tissues, which are scalp, skull, white matter, gray matter, blood vessel and cerebrospinal fluid. For every numerical phantom, Monte-Carlo based optical simulation is deployed to obtain the photoacoustic initial pressure based on optical properties of human brain. Then, two different k-wave models are used for the skull-involved acoustic simulation, which are fluid media model and viscoelastic media model. The former one only considers longitudinal wave propagation, and the latter model takes shear wave into consideration. Then, the PA sinograms with skull-induced aberration is taken as the input of U-net, and the skull-stripped ones are regarded as the supervision of U-net to train the network. Experimental result shows that the skull's acoustic aberration can be effectively alleviated after U-net correction, achieving conspicuous improvement in quality of PAT human brain images reconstructed from the corrected PA signals, which can clearly show the cerebral artery distribution inside the human skull.

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.

From scalp to cortex, the whole isn't greater than the sum of its parts: introducing GetTissueThickness (GTT) to assess age and sex differences in tissue thicknesses

Noninvasive techniques to record and stimulate the brain rely on passing through the tissues in between the scalp and cortex. Currently, there is no method to obtain detailed information about these scalp-to-cortex distance (SCD) tissues. We introduce GetTissueThickness (GTT), an open-source, automated approach to quantify SCD, and unveil how tissue thicknesses differ across age groups, sexes and brain regions (n = 250). We show that men have larger SCD in lower scalp regions and women have similar-to-larger SCD in regions closer to the vertex, with aging resulting in increased SCD in fronto-central regions. Soft tissue thickness varies by sex and age, with thicker layers and greater age-related decreases in men. Compact and spongy bone thickness also differ across sexes and age groups, with thicker compact bone in women in both age groups and an age-related thickening. Older men generally have the thickest cerebrospinal fluid layer and younger women and men having similar cerebrospinal fluid layers. Aging mostly results in grey matter thinning. Concerning SCD, the whole isn't greater than the sum of its parts. GTT enables rapid quantification of the SCD tissues. The distinctive sensitivity of noninvasive recording and stimulation modalities to different tissues underscores the relevance of GTT.

Application of photoacoustic computed tomography in biomedical imaging: A literature review

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high-resolution deep-tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real-time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice.

Fast iterative reconstruction for photoacoustic tomography using learned physical model: Theoretical validation

Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-crafted parameters to achieve good performance. Many iterations are usually required to reconstruct a high-quality image, which is computationally expensive due to repeated evaluations of the physical model. While learned iterative reconstruction approaches such as model-based learning (MBLr) can reduce the number of iterations through convolutional neural networks, it still requires repeated evaluations of the physical models at each iteration. Therefore, the goal of this study is to develop a Fast Iterative Reconstruction (FIRe) algorithm that incorporates a learned physical model into the learned iterative reconstruction scheme to further reduce the reconstruction time while maintaining robust reconstruction performance. We also propose an efficient training scheme for FIRe, which releases the enormous memory footprint required by learned iterative reconstruction methods through the concept of recursive training. The results of our proposed method demonstrate comparable reconstruction performance to learned iterative reconstruction methods with a 9x reduction in computation time and a 620x reduction in computation time compared to variational reconstruction.

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

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

Recent Trend of Ultrasound-Mediated Nanoparticle Delivery for Brain Imaging and Treatment

In view of the fact that the blood-brain barrier (BBB) prevents the transport of imaging probes and therapeutic agents to the brain and thus hinders the diagnosis and treatment of brain-related disorders, methods of circumventing this problem (e.g., ultrasound-mediated nanoparticle delivery) have drawn much attention. Among the related techniques, focused ultrasound (FUS) is a favorite means of enhancing drug delivery via transient BBB opening. Photoacoustic brain imaging relies on the conversion of light into heat and the detection of ultrasound signals from contrast agents, offering the benefits of high resolution and large penetration depth. The extensive versatility and adjustable physicochemical properties of nanoparticles make them promising therapeutic agents and imaging probes, allowing for successful brain imaging and treatment through the combined action of ultrasound and nanoparticulate agents. FUS-induced BBB opening enables nanoparticle-based drug delivery systems to efficiently access the brain. Moreover, photoacoustic brain imaging using nanoparticle-based contrast agents effectively visualizes brain morphologies or diseases. Herein, we review the progress in the simultaneous use of nanoparticles and ultrasound in brain research, revealing the potential of ultrasound-mediated nanoparticle delivery for the effective diagnosis and treatment of brain disorders.

Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases

Among the most critical health issues, brain illnesses, such as neurodegenerative conditions and tumors, lower quality of life and have a significant economic impact. Implantable technology and nano-drug carriers have enormous promise for cerebral brain activity sensing and regulated therapeutic application in the treatment and detection of brain illnesses. Flexible materials are chosen for implantable devices because they help reduce biomechanical mismatch between the implanted device and brain tissue. Additionally, implanted biodegradable devices might lessen any autoimmune negative effects. The onerous subsequent operation for removing the implanted device is further lessened with biodegradability. This review expands on current developments in diagnostic technologies such as magnetic resonance imaging, computed tomography, mass spectroscopy, infrared spectroscopy, angiography, and electroencephalogram while providing an overview of prevalent brain diseases. As far as we are aware, there hasn't been a single review article that addresses all the prevalent brain illnesses. The reviewer also looks into the prospects for the future and offers suggestions for the direction of future developments in the treatment of brain diseases.

Thin ceramic PZT dual- and multi-frequency pMUT arrays for photoacoustic imaging

Miniaturized ultrasonic transducer arrays with multiple frequencies are key components in endoscopic photoacoustic imaging (PAI) systems to achieve high spatial resolution and large imaging depth for biomedical applications. In this article, we report on the development of ceramic thin-film PZT-based dual- and multi-frequency piezoelectric micromachined ultrasonic transducer (pMUT) arrays and the demonstration of their PAI applications. With chips sized 3.5 mm in length or 10 mm in diameter, square and ring-shaped pMUT arrays incorporating as many as 2520 pMUT elements and multiple frequencies ranging from 1 MHz to 8 MHz were developed for endoscopic PAI applications. Thin ceramic PZT with a thickness of 9 μm was obtained by wafer bonding and chemical mechanical polishing (CMP) techniques and employed as the piezoelectric layer of the pMUT arrays, whose piezoelectric constant d ₃₁ was measured to be as high as 140 pm/V. Benefiting from this high piezoelectric constant, the fabricated pMUT arrays exhibited high electromechanical coupling coefficients and large vibration displacements. In addition to electrical, mechanical, and acoustic characterization, PAI experiments with pencil leads embedded into an agar phantom were conducted with the fabricated dual- and multi-frequency pMUT arrays. Photoacoustic signals were successfully detected by pMUT elements with different frequencies and used to reconstruct single and fused photoacoustic images, which clearly demonstrated the advantages of using dual- and multi-frequency pMUT arrays to provide comprehensive photoacoustic images with high spatial resolution and large signal-to-noise ratio simultaneously.

Characteristics of auditory steady-state responses to different click frequencies in awake intact macaques

Background

Auditory steady-state responses (ASSRs) are periodic evoked responses to constant periodic auditory stimuli, such as click trains, and are suggested to be associated with higher cognitive functions in humans. Since ASSRs are disturbed in human psychiatric disorders, recording ASSRs from awake intact macaques would be beneficial to translational research as well as an understanding of human brain function and its pathology. However, ASSR has not been reported in awake macaques.

Results

Electroencephalograms (EEGs) were recorded from awake intact macaques, while click trains at 20–83.3 Hz were binaurally presented. EEGs were quantified based on event-related spectral perturbation (ERSP) and inter-trial coherence (ITC), and ASSRs were significantly demonstrated in terms of ERSP and ITC in awake intact macaques. A comparison of ASSRs among different click train frequencies indicated that ASSRs were maximal at 83.3 Hz. Furthermore, analyses of laterality indices of ASSRs showed that no laterality dominance of ASSRs was observed.

Conclusions

The present results demonstrated ASSRs, comparable to those in humans, in awake intact macaques. However, there were some differences in ASSRs between macaques and humans: macaques showed maximal ASSR responses to click frequencies higher than 40 Hz that has been reported to elicit maximal responses in humans, and showed no dominant laterality of ASSRs under the electrode montage in this study compared with humans with right hemisphere dominance. The future ASSR studies using awake intact macaques should be aware of these differences, and possible factors, to which these differences were ascribed, are discussed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12868-022-00741-9.

Cross-Ray Ultrasound Tomography and Photoacoustic Tomography of Cerebral Hemodynamics in Rodents

Recent advances in functional ultrasound imaging (fUS) and photoacoustic tomography (PAT) offer powerful tools for studying brain function. Complementing each other, fUS and PAT, respectively, measure the cerebral blood flow (CBF) and hemoglobin concentrations, allowing synergistic characterization of cerebral hemodynamics. Here, cross-ray ultrasound tomography (CRUST) and its combination with PAT are presented. CRUST employs a virtual point source from a spherically focused ultrasonic transducer (SFUST) to provide widefield excitation at a 4-kHz pulse repetition frequency. A full-ring-shaped ultrasonic transducer array whose imaging plane is orthogonal to the SFUST's acoustic axis receives scattered ultrasonic waves. Superior to conventional fUS, whose sensitivity to blood flow is angle-dependent and low for perpendicular flow, the crossed transmission and panoramic detection fields of CRUST provide omnidirectional sensitivity to CBF. Using CRUST-PAT, the CBF, oxygen saturation, and hemoglobin concentration changes of the mouse brain during sensory stimulation are measured, with a field of view of ≈7 mm in diameter, spatial resolution of ≈170 µm, and temporal resolution of 200 Hz. The results demonstrate CRUST-PAT as a unique tool for studying cerebral hemodynamics.

A Review of High-Frequency Ultrasonic Transducers for Photoacoustic Imaging Applications

Photoacoustic imaging (PAI) is a new and rapidly growing hybrid biomedical imaging modality that combines the virtues of both optical and ultrasonic (US) imaging. The nature of the interaction between light and ultrasound waves allows PAI to make good use of the rich contrast produced by optics while retaining the imaging depths in US imaging. High-frequency US transducers are an important part of the PAI systems, used to detect the high-frequency and broad-bandwidth photoacoustic signals excited by the target tissues irradiated by short laser pulses. Advancement in high-frequency US transducer technology has influenced the boost of PAI to broad applications. Here, we present a review on high-frequency US transducer technologies for PAI applications, including advanced piezoelectric materials and representative transducers. In addition, we discuss the new challenges and directions facing the development of high-frequency US transducers for PAI applications.

Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics

Small animal models play a fundamental role in brain research by deepening the understanding of the physiological functions and mechanisms underlying brain disorders and are thus essential in the development of therapeutic and diagnostic imaging tracers targeting the central nervous system. Advances in structural, functional, and molecular imaging using MRI, PET, fluorescence imaging, and optoacoustic imaging have enabled the interrogation of the rodent brain across a large temporal and spatial resolution scale in a non-invasively manner. However, there are still several major gaps in translating from preclinical brain imaging to the clinical setting. The hindering factors include the following: (1) intrinsic differences between biological species regarding brain size, cell type, protein expression level, and metabolism level and (2) imaging technical barriers regarding the interpretation of image contrast and limited spatiotemporal resolution. To mitigate these factors, single-cell transcriptomics and measures to identify the cellular source of PET tracers have been developed. Meanwhile, hybrid imaging techniques that provide highly complementary anatomical and molecular information are emerging. Furthermore, deep learning-based image analysis has been developed to enhance the quantification and optimization of the imaging protocol. In this mini-review, we summarize the recent developments in small animal neuroimaging toward improved translational power, with a focus on technical improvement including hybrid imaging, data processing, transcriptomics, awake animal imaging, and on-chip pharmacokinetics. We also discuss outstanding challenges in standardization and considerations toward increasing translational power and propose future outlooks.

The emerging role of photoacoustic imaging in clinical oncology

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

Background-suppressed tumor-targeted photoacoustic imaging using bacterial carriers

Photoacoustic (PA) imaging offers promise for biomedical applications due to its ability to image deep within biological tissues while providing detailed molecular information; however, its detection sensitivity is limited by high background signals that arise from endogenous chromophores. Genetic reporter proteins with photoswitchable properties enable the removal of background signals through the subtraction of PA images for each light-absorbing form. Unfortunately, the application of photoswitchable chromoproteins for tumor-targeted imaging has been hampered by the lack of an effective targeted delivery scheme; that is, photoswitchable probes must be delivered in vivo with high targeting efficiency and specificity. To overcome this limitation, we have developed a tumor-targeting delivery system in which tumor-homing bacteria (Escherichia coli) are exploited as carriers to affect the point-specific delivery of genetically encoded photochromic probes to the tumor area. To improve the efficiency of the desired background suppression, we engineered a phytochrome-based reporter protein (mDrBphP-PCMm/F469W) that displays higher photoswitching contrast than those in the current state of the art. Photoacoustic computed tomography was applied to achieve good depth and resolution in the context of in vivo (mice) imaging. The present system effectively integrates a genetically encoded phytochrome-based reporter protein, PA imaging, and synthetic biology (GPS), to achieve essentially background-suppressed tumor-targeted PA monitoring in deep-seated tissues. The ability to image tumors at substantial depths may enable target-specific cancer diagnoses to be made with greater sensitivity, fidelity, and specificity.

Wavelength and pulse energy optimization for detecting hypoxia in photoacoustic imaging of the neonatal brain: a simulation study

Cerebral hypoxia is a severe injury caused by oxygen deprivation to the brain. Hypoxia in the neonatal period increases the risk for the development of neurological disorders, including hypoxic-ischemic encephalopathy, cerebral palsy, periventricular leukomalacia, and hydrocephalus. It is crucial to recognize hypoxia as soon as possible because early intervention improves outcomes. Photoacoustic imaging, using at least two wavelengths, through a spectroscopic analysis, can measure brain oxygen saturation. Due to the spectral coloring effect arising from the dependency of optical properties of biological tissues to the wavelength of light, choosing the right wavelength-pair for efficient and most accurate oxygen saturation measurement and consequently quantifying hypoxia at a specific depth is critical. Using a realistic neonate head model and Monte Carlo simulations, we found practical wavelength-pairs that quantified regions with hypoxia most accurately at different depths down to 22 mm into the cortex neighboring the lateral ventricle. We also demonstrated, for the first time, that the accuracy of the sO₂ measurement can be increased by adjusting the level of light energy for each wavelength-pair. Considering the growing interest in photoacoustic imaging of the brain, this work will assist in a more accurate use of photoacoustic spectroscopy and help in the clinical translation of this promising imaging modality. Please note that explaining the effect of acoustic aberration of the skull is not in the scope of this study.

Recent Progress on Molecular Photoacoustic Imaging with Carbon-Based Nanocomposites

For biomedical imaging, the interest in noninvasive imaging methods is ever increasing. Among many modalities, photoacoustic imaging (PAI), which is a combination of optical and ultrasound imaging techniques, has received attention because of its unique advantages such as high spatial resolution, deep penetration, and safety. Incorporation of exogenous imaging agents further amplifies the effective value of PAI, since they can deliver other specified functions in addition to imaging. For these agents, carbon-based materials can show a large specific surface area and interesting optoelectronic properties, which increase their effectiveness and have proved their potential in providing a theragnostic platform (diagnosis + therapy) that is essential for clinical use. In this review, we introduce the current state of the PAI modality, address recent progress on PAI imaging that takes advantage of carbon-based agents, and offer a future perspective on advanced PAI systems using carbon-based agents.

Multimodal Contrast Agents for Optoacoustic Brain Imaging in Small Animals

Optoacoustic (photoacoustic) imaging has demonstrated versatile applications in biomedical research, visualizing the disease pathophysiology and monitoring the treatment effect in an animal model, as well as toward applications in the clinical setting. Given the complex disease mechanism, multimodal imaging provides important etiological insights with different molecular, structural, and functional readouts in vivo. Various multimodal optoacoustic molecular imaging approaches have been applied in preclinical brain imaging studies, including optoacoustic/fluorescence imaging, optoacoustic imaging/magnetic resonance imaging (MRI), optoacoustic imaging/MRI/Raman, optoacoustic imaging/positron emission tomography, and optoacoustic/computed tomography. There is a rapid development in molecular imaging contrast agents employing a multimodal imaging strategy for pathological targets involved in brain diseases. Many chemical dyes for optoacoustic imaging have fluorescence properties and have been applied in hybrid optoacoustic/fluorescence imaging. Nanoparticles are widely used as hybrid contrast agents for their capability to incorporate different imaging components, tunable spectrum, and photostability. In this review, we summarize contrast agents including chemical dyes and nanoparticles applied in multimodal optoacoustic brain imaging integrated with other modalities in small animals, and provide outlook for further research.

Translational Photoacoustic Imaging for Disease Diagnosis, Monitoring, and Surgical Guidance: introduction to the feature issue

This feature issue of Biomedical Optics Express covered all aspects of translational photoacoustic research. Application areas include screening and diagnosis of diseases, imaging of disease progression and therapeutic response, and image-guided treatment, such as surgery, drug delivery, and photothermal/photodynamic therapy. The feature issue also covers relevant developments in photoacoustic instrumentation, contrast agents, image processing and reconstruction algorithms.