Photoacoustic Imaging for Cancer Detection and Staging

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.

Photoacoustic Imaging in Prostate Cancer: A New Paradigm for Diagnosis and Management

The global health issue of prostate cancer (PCa) requires better diagnosis and treatment. Photoacoustic imaging (PAI) may change PCa management. This review examines PAI's principles, diagnostic role, and therapeutic guidance. PAI uses optical light excitation and ultrasonic detection for high-resolution functional and molecular imaging. PAI uses endogenous and exogenous contrast agents to distinguish cancerous and benign prostate tissues with greater sensitivity and specificity than PSA testing and TRUS-guided biopsy. In addition to diagnosing, PAI can guide and monitor PCa therapy. Its real-time imaging allows precise biopsies and brachytherapy seed placement. Photoacoustic temperature imaging allows non-invasive monitoring of thermal therapies like cryotherapy, improving treatment precision and success. Transurethral illumination probes, innovative contrast agents, integration with other imaging modalities, and machine learning analysis are being developed to overcome depth and data complexity restrictions. PAI could become an essential tool for PCa diagnosis and therapeutic guidance as the field advances.

Activity-Based Fluorescence Diagnostics for Cancer

Fluorescence imaging is one of the most promising approaches to achieve intraoperative assessment of the tumor/normal tissue margins during cancer surgery. This is critical to improve the patients' prognosis, and therefore various molecular fluorescence imaging probes have been developed for the identification of cancer lesions during surgery. Among them, "activatable" fluorescence probes that react with cancer-specific biomarker enzymes to generate fluorescence signals have great potential for high-contrast cancer imaging due to their low background fluorescence and high signal amplification by enzymatic turnover. Over the past two decades, activatable fluorescence probes employing various fluorescence control mechanisms have been developed worldwide for this purpose. Furthermore, new biomarker enzymatic activities for specific types of cancers have been identified, enabling visualization of various types of cancers with high sensitivity and specificity. This Review focuses on recent advances in the design, function and characteristics of activatable fluorescence probes that target cancer-specific enzymatic activities for cancer imaging and also discusses future prospects in the field of activity-based diagnostics for cancer.

Caliper, contrast enhanced-ultrasound or laser speckle contrast imaging: Techniques to follow mice melanoma growth

Due to morphological characteristics, metastatic melanoma is a cancer for which vascularization is not a diagnostic criterion. Laser speckle contrast imaging (LSCI) and contrast enhanced ultrasound (CEUS) are two imaging techniques that will be explored in this study, which aims to confirm these two techniques for monitoring tumor vascularization. B16F10 cells were xenografted to C57BL/6 mice treated with anti-PD1 or 0.9% NaCl. Tumor volume was measured daily while CEUS and LSCI were performed weekly. LSCI and CEUS analyses showed a decrease in tumor perfusion in both groups of mice. Although both CEUS and LSCI are useful for measuring tumor volume, LSCI appears to be more robust and effective for monitoring tumor microcirculation. Non-invasive investigations are needed to better predict tumor vascularization: CEUS and LSCI have a good applicability in a mice model.

Machine Learning Enabled Photoacoustic Spectroscopy for Noninvasive Assessment of Breast Tumor Progression In Vivo: A Preclinical Study

Breast cancer is a dreaded disease affecting women the most in cancer-related deaths over other cancers. However, early diagnosis of the disease can help increase survival rates. The existing breast cancer diagnosis tools do not support the early diagnosis of the disease. Therefore, there is a great need to develop early diagnostic tools for this cancer. Photoacoustic spectroscopy (PAS), being very sensitive to biochemical changes, can be relied upon for its application in detecting breast tumors in vivo. With this motivation, in the current study, an aseptic chamber integrated photoacoustic (PA) probe was designed and developed to monitor breast tumor progression in vivo, established in nude mice. The device served the dual purpose of transporting tumor-bearing animals to the laboratory from the animal house and performing PA experiments in the same chamber, maintaining sterility. In the current study, breast tumor was induced in the nude mice by MCF-7 cells injection and the corresponding PA spectra at different time points (day 0, 5, 10, 15, and 20) of tumor progression in vivo in the same animals. The recorded photoacoustic spectra were subsequently preprocessed, wavelet-transformed, and subjected to filter-based feature selection algorithm. The selected top 20 features, by minimum redundancy maximum relevance (mRMR) algorithm, were then used to build an input feature matrix for machine learning (ML)-based classification of the data. The performance of classification models demonstrated 100% specificity, whereas the sensitivity of 95, 100, 92.5, and 85% for the time points, day 5, 10, 15, and 20, respectively. These results suggest the potential of PA signal-based classification of breast tumor progression in a preclinical model. The PA signal contains information on the biochemical changes associated with disease progression, emphasizing its translational strength toward early disease diagnosis.

Photoacoustic imaging for cutaneous melanoma assessment: a comprehensive review

Significance

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

Aim

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

Approach

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

Results

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

Conclusions

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

Review of low-cost light sources and miniaturized designs in photoacoustic microscopy

Significance

Photoacoustic microscopy (PAM) is a promising imaging technique to provide structural, functional, and molecular information for preclinical and clinical studies. However, expensive and bulky lasers and motorized stages have limited the broad applications of conventional PAM systems. A recent trend is to use low-cost light sources and miniaturized designs to develop a compact PAM system and expand its applications from benchtop to bedside.

Aim

We provide (1) an overview of PAM systems and their limitations, (2) a comprehensive review of PAM systems with low-cost light sources and their applications, (3) a comprehensive review of PAM systems with miniaturized and handheld scanning designs, and (4) perspective applications and a summary of the cost-effective and miniaturized PAM systems.

Approach

Papers published before July 2023 in the area of using low-cost light sources and miniaturized designs in PAM were reviewed. They were categorized into two main parts: (1) low-cost light sources and (2) miniaturized or handheld designs. The first part was classified into two subtypes: pulsed laser diode and continuous-wave laser diode. The second part was also classified into two subtypes: galvanometer scanner and micro-electro-mechanical system scanner.

Results

Significant progress has been made in the development of PAM systems based on low-cost and compact light sources as well as miniaturized and handheld designs.

Conclusions

The review highlights the potential of these advancements to revolutionize PAM technology, making it more accessible and practical for various applications in preclinical studies, clinical practice, and long-term monitoring.

Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data

Machine learning and digital health sensing data have led to numerous research achievements aimed at improving digital health technology. However, using machine learning in digital health poses challenges related to data availability, such as incomplete, unstructured, and fragmented data, as well as issues related to data privacy, security, and data format standardization. Furthermore, there is a risk of bias and discrimination in machine learning models. Thus, developing an accurate prediction model from scratch can be an expensive and complicated task that often requires extensive experiments and complex computations. Transfer learning methods have emerged as a feasible solution to address these issues by transferring knowledge from a previously trained task to develop high-performance prediction models for a new task. This survey paper provides a comprehensive study of the effectiveness of transfer learning for digital health applications to enhance the accuracy and efficiency of diagnoses and prognoses, as well as to improve healthcare services. The first part of this survey paper presents and discusses the most common digital health sensing technologies as valuable data resources for machine learning applications, including transfer learning. The second part discusses the meaning of transfer learning, clarifying the categories and types of knowledge transfer. It also explains transfer learning methods and strategies, and their role in addressing the challenges in developing accurate machine learning models, specifically on digital health sensing data. These methods include feature extraction, fine-tuning, domain adaptation, multitask learning, federated learning, and few-/single-/zero-shot learning. This survey paper highlights the key features of each transfer learning method and strategy, and discusses the limitations and challenges of using transfer learning for digital health applications. Overall, this paper is a comprehensive survey of transfer learning methods on digital health sensing data which aims to inspire researchers to gain knowledge of transfer learning approaches and their applications in digital health, enhance the current transfer learning approaches in digital health, develop new transfer learning strategies to overcome the current limitations, and apply them to a variety of digital health technologies.

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.

Laparoscopic Photoacoustic Imaging System Based on Side-Illumination Diffusing Fibers

OBJECTIVE

To develop a flexible miniaturized photoacoustic (PA) imaging probe for detecting anatomical structures during laparoscopic surgery. The proposed probe aimed to facilitate intraoperative detection of blood vessels and nerve bundles embedded in tissue not directly visible to the operating physician to preserve these delicate and vital structures.

METHODS

We modified a commercially available ultrasound laparoscopic probe by incorporating custom-fabricated side-illumination diffusing fibers that illuminate the probe's field of view. The probe geometry, including the position and orientation of the fibers and the emission angle, was determined using computational models of light propagation in the simulation and subsequently validated through experimental studies.

RESULTS

In wire phantom studies within an optical scattering medium, the probe achieved an imaging resolution of 0.43 ±0.09 mm and a signal-to-noise ratio of 31.2±1.84 dB. We also conducted an ex vivo study using a rat model, demonstrating the successful detection of blood vessels and nerves.

CONCLUSION

Our results indicate the viability of a side-illumination diffusing fiber PA imaging system for guidance during laparoscopic surgery.

SIGNIFICANCE

The potential clinical translation of this technology could enhance the preservation of critical vascular structures and nerves, thereby minimizing post-operative complications.

Full-optical photoacoustic imaging using speckle analysis and resolution enhancement by orthogonal pump patterns projection

This paper presents an approach for achieving full optical photoacoustic imaging with enhanced resolution utilizing speckle pattern analysis. The proposed technique involves projecting patterns derived from binary masks corresponding to orthogonal functions onto the target to elicit a photoacoustic signal. The resulting signal is then recorded using a high-speed camera and analyzed using correlation analysis of the speckle motion. Our results demonstrate the feasibility of this optical approach to achieve imaging with enhanced resolution without the need for physical contact with the target, opening up new possibilities for non-invasive medical imaging and other applications.

Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration

As a non-invasive hybrid biomedical imaging technology, photoacoustic tomography combines high contrast of optical imaging and high penetration of acoustic imaging. However, the conventional standard reconstruction under sparse view could result in low-quality image in photoacoustic tomography. Here, a novel model-based sparse reconstruction method for photoacoustic tomography via diffusion model was proposed. A score-based diffusion model is designed for learning the prior information of the data distribution. The learned prior information is utilized as a constraint for the data consistency term of an optimization problem based on the least-square method in the model-based iterative reconstruction, aiming to achieve the optimal solution. Blood vessels simulation data and the animal in vivo experimental data were used to evaluate the performance of the proposed method. The results demonstrate that the proposed method achieves higher-quality sparse reconstruction compared with conventional reconstruction methods and U-Net. In particular, under the extreme sparse projection (e.g., 32 projections), the proposed method achieves an improvement of ∼ 260 % in structural similarity and ∼ 30 % in peak signal-to-noise ratio for in vivo data, compared with the conventional delay-and-sum method. This method has the potential to reduce the acquisition time and cost of photoacoustic tomography, which will further expand the application range.

Intraoperative laparoscopic photoacoustic image guidance system in the da Vinci surgical system

This paper describes a framework allowing intraoperative photoacoustic (PA) imaging integrated into minimally invasive surgical systems. PA is an emerging imaging modality that combines the high penetration of ultrasound (US) imaging with high optical contrast. With PA imaging, a surgical robot can provide intraoperative neurovascular guidance to the operating physician, alerting them of the presence of vital substrate anatomy invisible to the naked eye, preventing complications such as hemorrhage and paralysis. Our proposed framework is designed to work with the da Vinci surgical system: real-time PA images produced by the framework are superimposed on the endoscopic video feed with an augmented reality overlay, thus enabling intuitive three-dimensional localization of critical anatomy. To evaluate the accuracy of the proposed framework, we first conducted experimental studies in a phantom with known geometry, which revealed a volumetric reconstruction error of 1.20 ± 0.71 mm. We also conducted an ex vivo study by embedding blood-filled tubes into chicken breast, demonstrating the successful real-time PA-augmented vessel visualization onto the endoscopic view. These results suggest that the proposed framework could provide anatomical and functional feedback to surgeons and it has the potential to be incorporated into robot-assisted minimally invasive surgical procedures.

Versatile multimodal modality based on Brillouin light scattering and the photoacoustic effect

Multimodal optical techniques are useful for the comprehensive characterization of material properties. In this work, we developed a new, to the best of our knowledge, multimodal technology that can simultaneously measure a subset of mechanical, optical, and acoustical properties of the sample and is based on the integration of Brillouin (Br) and photoacoustic (PA) microscopy. The proposed technique can acquire co-registered Br and PA signals from the sample. Importantly, using synergistic measurements of the speed of sound and Brillouin shift, the modality offers a new approach to quantifying the optical refractive index, which is a fundamental property of a material and is not accessible by either technique individually. As a proof of concept, we demonstrated the feasibility of integrating the two modalities and acquired the colocalized Br and time-resolved PA signals in a synthetic phantom made out of kerosene and CuSO₄ aqueous solution. In addition, we measured the refractive index values of saline solutions and validated the result. Comparison with previously reported data showed a relative error of 0.3%. This further allowed us to directly quantify the longitudinal modulus of the sample with the colocalized Brillouin shift. While the scope of the current work is limited to introducing the combined Br-PA setup for the first time, we envision that this multimodal modality could open a new path for the multi-parametric analysis of material properties.

Photoacoustic imaging for investigating tumor hypoxia: a strategic assessment

Hypoxia causes the expression of signaling molecules which regulate cell division, lead to angiogenesis, and further, in the tumor microenvironment, promote resistance to chemotherapy and radiotherapy, and induce metastasis. Photoacoustic imaging (PAI) takes advantage of unique absorption characteristics of chromophores in tissues and provides the opportunity to construct images with a high degree of spatial and temporal resolution. In this review, we discuss the physiologic characteristics of tumor hypoxia, and current applications of PAI using endogenous (label free imaging) and exogenous (organic and inorganic) contrast agents. Features of various methods in terms of their efficacy for determining physiologic and proteomic phenomena are analyzed. This review demonstrates that PAI has the potential to understand tumor growth and metastasis development through measurement of regulatory molecule concentrations, oxygen gradients, and vascular distribution.

The location of metastatic lymph nodes and the evaluation of lymphadenectomy by near-infrared photoacoustic imaging with iridium complex nanoparticles

Histopathology evaluation and lymphadenectomy of node-positive patients is the usual procedure in clinical therapy. However, it requires days for the histopathology result analysis, which impedes intraoperative decision-making and immediate treatment. Noninvasive real-time imaging of metastatic lymph nodes can overcome these defects and help medical workers evaluate lymph nodes and make the operation decision more efficiently. Herein we developed iridium(III)-cyanine complex/bovine serum albumin (BSA)-based nanoparticles which are conjugated with folic acid (FA) (IrCy-FA NPs). The synthesized IrCy-FA NPs exhibit good biocompatibility, strong near-infrared absorption, and impressive lymph node accumulation and can serve as a photoacoustic (PA) imaging probe for lymph node imaging. Besides, the lymph nodes enriched with IrCy-FA NPs showing green color are easily visible to the naked eye, suggesting their potential as an intraoperative indicator. The real-time PA imaging with excellent contrast and high spatial resolution can promote efficient and reliable quantitative analysis of lymph nodes in vivo. By employing IrCy-FA NPs as the PA agent for lymph node imaging, we achieve effective pre-operative and post-operative evaluations of metastatic lymph nodes in lymphadenectomy. This study may provide helpful information for PA imaging guided colocalization and evaluation of lymph nodes and facilitate this method towards clinical trials.

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.

Integrated Ultrasound and Photoacoustic-Guided Laser Ablation Theranostic Endoscopic System

Advancements in ablation techniques have paved the way towards the development of safer and more effective clinical procedures for treating various maladies such as atrial fibrillation (AF). AF is characterized by rapid, chaotic atrial activation and is commonly treated using radiofrequency applicators or laser ablation catheters. However, the lack of thermal lesion formation and temperature monitoring capabilities in these devices prevents them from measuring the treatment outcome directly. In addition, poor differentiation between healthy and ablated tissues leads to incomplete ablation, which reduces safety and causes complications in patients. Hence, a novel photoacoustic (PA)-guided laser ablation theranostic device was developed around a traditional phased-array endoscope. The proposed technology provides lesion formation, tissue distinguishing, and temperature monitoring capabilities. Our results have validated the lesion monitoring capability of the proposed technology through PA correlation maps. The tissue distinguishing capability of the theranostic device was verified by the measurable differences in the PA signal between pre-and post-ablated mice myocardial tissue. The increase in the PA signal with temperature variations caused by the ablation laser confirmed the ability of the proposed device to provide temperature feedback.

Beyond fundamental resonance mode: high-order multi-band ALN PMUT for in vivo photoacoustic imaging

This paper reports on an aluminum nitride (AlN) piezoelectric micromachined ultrasound transducer (PMUT) array for photoacoustic (PA) imaging, where the high-order resonance modes of the PMUT are utilized to improve imaging resolution. A flexural vibration mode (FVM) PMUT is fabricated and applied in a photoacoustic imaging (PAI) system. Specifically, the microelectromechanical system (MEMS)-based PMUT is suitable for PA endoscopic imaging of blood vessels and bronchi due to its miniature size and high sensitivity. More importantly, AlN is a nontoxic material, which makes it harmless for biomedical applications. In the PAI system, the AlN PMUT array is used to detect PA signals, and the acousto-mechanical response is designed and optimized at the PMUT's fundamental resonance. In this work, we focus on the high-order resonance performance of the PMUT PAI beyond the fundamental resonance. The acoustic and electrical responses of the PMUT's high-order resonance modes are characterized and analyzed. The fundamental and three high-order resonance bandwidths are 2.2, 8.8, 18.5, and 48.2 kHz. Compared with the resolution at the fundamental resonance mode, the resolutions at third- and fourth-order resonance modes increase by 38.7% and 76.9% in a phantom experiment. The high-order resonance modes of the AlN PMUT sensor array provide higher central frequency and wider bandwidth for PA signal detection, which increase the resolution of PAI compared to the PMUT working at the fundamental resonance mode.

Photoacoustic imaging for microcirculation

Microcirculation facilitates the blood-tissue exchange of nutrients and regulates blood perfusion. It is, therefore, essential in maintaining tissue health. Aberrations in microcirculation are potentially indicative of underlying cardiovascular and metabolic pathologies. Thus, quantitative information about it is of great clinical relevance. Photoacoustic imaging (PAI) is a capable technique that relies on the generation of imaging contrast via the absorption of light and can image at micron-scale resolution. PAI is especially desirable to map microvasculature as hemoglobin strongly absorbs light and can generate a photoacoustic signal. This paper reviews the current state of the art for imaging microvascular networks using photoacoustic imaging. We further describe how quantitative information about blood dynamics such as the total hemoglobin concentration, oxygen saturation, and blood flow rate is obtained using PAI. We also discuss its importance in understanding key pathophysiological processes in neurovascular, cardiovascular, ophthalmic, and cancer research fields. We then discuss the current challenges and limitations of PAI and the approaches that can help overcome these limitations. Finally, we provide the reader with an overview of future trends in the field of PAI for imaging microcirculation.

Time-domain ultrasound as prior information for frequency-domain compressive ultrasound for intravascular cell detection: A 2-cell numerical model

This study proposes a new method for the detection of a weak scatterer among strong scatterers using prior-information ultrasound (US) imaging. A perfect application of this approach is in vivo cell detection in the bloodstream, where red blood cells (RBCs) serve as identifiable strong scatterers. In vivo cell detection can help diagnose cancer at its earliest stages, increasing the chances of survival for patients. This work combines time-domain US with frequency-domain compressive US imaging to detect a 20-μ MCF-7 circulating tumor cell (CTC) among a number of RBCs within a simulated venule inside the mouth. The 2D image reconstructed from the time-domain US is employed to simulate the reflected and scattered pressure field from the RBCs, which is then measured at the location of the receivers. The RBCs are tagged one time by a human operator and another time, automatically, by template-based computer vision. Next, the resulting signal from the RBCs is subtracted from the measured total signal in frequency domain to generate the scattered-field data, coming from the CTC alone. Feeding that signal and the background pressure field into a norm-one-based compressive sensing code enables detecting the CTC at various locations. As errors could arise in determining the location of the RBCs and their acoustic properties in the real world, small errors (up to 10% in the former and 5% in the latter) are purposefully introduced to the model, to which the proposed method is shown to be resilient. Localization errors are smaller than 12 μ when a human tags the RBCs and smaller than 25 μ when computer vision is applied. Despite its limitations, this study, for the first time, reports the results of combining two US modalities aimed at cell detection and introduces a unique and useful application for ultrahigh-frequency US imaging. It should be noted that this method can be used in detecting weak scatterers with ultrasound waves in other applications as well.

Assessment of Nanoparticle-Mediated Tumor Oxygen Modulation by Photoacoustic Imaging

Photoacoustic imaging (PAI) is an invaluable tool in biomedical imaging, as it provides anatomical and functional information in real time. Its ability to image at clinically relevant depths with high spatial resolution using endogenous tissues as contrast agents constitutes its major advantage. One of the most important applications of PAI is to quantify tissue oxygen saturation by measuring the differential absorption characteristics of oxy and deoxy Hb. Consequently, PAI can be utilized to monitor tumor-related hypoxia, which is a crucial factor in tumor microenvironments that has a strong influence on tumor invasiveness. Reactive oxygen species (ROS)-based therapies, such as photodynamic therapy, radiotherapy, and sonodynamic therapy, are oxygen-consuming, and tumor hypoxia is detrimental to their efficacy. Therefore, a persistent demand exists for agents that can supply oxygen to tumors for better ROS-based therapeutic outcomes. Among the various strategies, NP-mediated supplemental tumor oxygenation is especially encouraging due to its physio-chemical, tumor targeting, and theranostic properties. Here, we focus on NP-based tumor oxygenation, which includes NP as oxygen carriers and oxygen-generating strategies to alleviate hypoxia monitored by PAI. The information obtained from quantitative tumor oxygenation by PAI not only supports optimal therapeutic design but also serves as a highly effective tool to predict therapeutic outcomes.

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.

Photoacoustic-MR Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitations of the current imaging modalities, accurate brain shift compensation continues to be a challenging task. In this study, the application of intra-operative photoacoustic imaging and registration of the intra-operative photoacoustic with pre-operative MR images are proposed to compensate for brain deformation. Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation. In this study, the co-sparse analysis model is proposed for photoacoustic-MR image registration, which can capture the interdependency of the two modalities. The proposed algorithm works based on the minimization of mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using an experimental phantom and ex vivo data obtained from a mouse brain. The results of the phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. The results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidates pre-operative MRI.

Exogenous Contrast Agents in Photoacoustic Imaging: An In Vivo Review for Tumor Imaging

The field of cancer theranostics has grown rapidly in the past decade and innovative ‘biosmart’ theranostic materials are being synthesized and studied to combat the fast growth of cancer metastases. While current state-of-the-art oncology imaging techniques have decreased mortality rates, patients still face a diminished quality of life due to treatment. Therefore, improved diagnostics are needed to define in vivo tumor growths on a molecular level to achieve image-guided therapies and tailored dosage needs. This review summarizes in vivo studies that utilize contrast agents within the field of photoacoustic imaging—a relatively new imaging modality—for tumor detection, with a special focus on imaging and transducer parameters. This paper also details the different types of contrast agents used in this novel diagnostic field, i.e., organic-based, metal/inorganic-based, and dye-based contrast agents. We conclude this review by discussing the challenges and future direction of photoacoustic imaging.

Photoacoustic-guided endovenous laser ablation: Characterization and in vivo canine study

Endovenous laser ablation (EVLA) is a minimally invasive surgical procedure, often guided by ultrasound (US) imaging, for treating venous insufficiencies. US imaging limitations in accurately visualizing the catheter and the lack of a temperature monitoring system can lead to sub-optimal outcomes. An integrated photoacoustic (PA)-guided EVLA system has been previously developed and reported to overcome the shortcomings of US-guided procedure. In this study, we further characterized the system and tested the in vivo utility. In addition, PA thermometry was further explored by compensating the variation of PA signal with temperature with respect to the temperature-dependent absorption of blood and water. In vivo imaging results indicated that the PA-guided EVLA system can provide high contrast and accurate images of the ablation catheter tip overlaid on US images of the background tissue. Additionally, absorption-compensated PA signal amplitudes over a relevant range of temperature were measured and demonstrated.

Morphology-dependent resonance enhanced nonlinear photoacoustic effect in nanoparticle suspension: a temporal-spatial model

The morphology-dependent resonances (MDRs) hotspot, ubiquity formed between the pairs of nanoparticles in close vicinity, has garnered considerable recent attention. By extending this phenomenon to pulse-laser irradiated nanoparticle suspension, we demonstrate that such collective optical/thermal enhancement can give rise to the nonlinear photoacoustic (PA) generation. In this study, a temporal-spatial analytical expression is derived to quantitatively describe the nonlinear PA signal generation from nanoparticles, incorporating the Grüneisen increase at the microscopic individual particle level and MRDs enhancement at the macroscopic suspension level. The dependence of PA nonlinearity on the critical contributors, including the laser pulse width, the particle size, and the statistical interparticle spacing, is quantitatively discussed. The theory is well validated with the finite element method (FEM) and experimentally proved with semiconducting polymer nanoparticles (SPN) suspension. This work may pave a new direction towards effective MDR based nonlinear PA contract agent design.

Endocavity ultrasound and photoacoustic system for fetal and maternal imaging: design, implementation, and ex-vivo validation

Purpose: Transvaginal ultrasound (TVUS) is a widely used real-time and non-invasive imaging technique for fetal and maternal care. It can provide structural and functional measurements about the fetal brain, such as blood vessel diameter and blood flow. However, it lacks certain biochemical estimations, such as hemoglobin oxygen saturation ( SO 2 ), which limits its ability to indicate a fetus at risk of birth asphyxia. Photoacoustic (PA) imaging has been steadily growing in recognition as a complement to ultrasound (US). Studies have shown PA imaging is capable of providing such biochemical estimations as SO 2 at relatively high penetration depth (up to 30 mm). Approach: In this study, we have designed and developed a multi-modal (US, PA, and Doppler) endocavity imaging system (ECUSPA) around a commercialized TVUS probe (Philips ATL C9-5). Results: The integrated system was evaluated through a set of in-vitro, ex-vivo, and in-vivo studies. Imaging of excised sheep brain tissue demonstrated the system's utility and penetration depth in transfontanelle imaging conditions. The accuracy of using the spectroscopic PA imaging (sPA) method to estimate SO 2 was validated by comparing sPA oximetry results with the gold standard measurements indicated by a blood gas analyzer. The ability of US and Doppler to measure moving blood volume was evaluated in-vivo. Spectral unmixing capabilities were tested using fluorophores within sheep brains. Conclusion: The developed system is a high resolution (about 200    μ m at 30 mm depth), real-time (at 30 Hz), and quantitative ( SO 2 estimation error < 10 % ) imaging tool with a total diameter less than 30 mm, making it suitable for intrapartum applications such as fetal and maternal diagnostics.

Model-based optical and acoustical compensation for photoacoustic tomography of heterogeneous mediums

Photoacoustic tomography (PAT) is a non-invasive, high-resolution imaging modality, capable of providing functional and molecular information of various pathologies, such as cancer. One limitation of PAT is the depth and wavelength dependent optical fluence, which results in reduced PA signal amplitude from deeper tissue regions. These factors can therefore introduce errors into quantitative measurements such as oxygen saturation (sO₂) or the localization and concentration of various chromophores. The variation in the speed-of-sound between different tissues can also lead to distortions in object location and shape. Compensating for these effects allows PAT to be used more quantitatively. We have developed a proof-of-concept algorithm capable of compensating for the heterogeneity in speed-of-sound and depth dependent optical fluence. Speed-of-sound correction was done by using a straight ray-based algorithm for calculating the family of iso-time-of-flight contours between the transducers and every pixel in the imaging grid, while fluence compensation was done by utilizing the graphics processing unit (GPU) accelerated software MCXCL for Monte Carlo modeling of optical fluence variation. This algorithm was tested on a polyvinyl chloride plastisol (PVCP) phantom, which contained cyst mimics and blood inclusions to test the algorithm under relatively heterogeneous conditions. Our results indicate that our PAT algorithm can compensate for the speed-of-sound variation and depth dependent fluence effects within a heterogeneous phantom. The results of this study will pave the way for further development and evaluation of the proposed method in more complex in-vitro and ex-vivo phantoms, as well as compensating for the wavelength-dependent optical fluence in spectroscopic PAT.

Seeing through the Skin: Photoacoustic Tomography of Skin Vasculature and Beyond

Skin diseases are the most common human diseases and manifest in distinct structural and functional changes to skin tissue components such as basal cells, vasculature, and pigmentation. Although biopsy is the standard practice for skin disease diagnosis, it is not sufficient to provide in vivo status of the skin and highly depends on the timing of diagnosis. Noninvasive imaging technologies that can provide structural and functional tissue information in real time would be invaluable for skin disease diagnosis and treatment evaluation. Among the modern medical imaging technologies, photoacoustic (PA) tomography (PAT) shows great promise as an emerging optical imaging modality with high spatial resolution, high imaging speed, deep penetration depth, rich contrast, and inherent sensitivity to functional and molecular information. Over the last decade, PAT has undergone an explosion in technical development and biomedical applications. Particularly, PAT has attracted increasing attention in skin disease diagnosis, providing structural, functional, metabolic, molecular, and histological information. In this concise review, we introduce the principles and imaging capability of various PA skin imaging technologies. We highlight the representative applications in the past decade with a focus on imaging skin vasculature and melanoma. We also envision the critical technical developments necessary to further accelerate the translation of PAT technologies to fundamental skin research and clinical impacts.

Simultaneous Denoising and Localization Network for Photoacoustic Target Localization

A significant research problem of recent interest is the localization of targets like vessels, surgical needles, and tumors in photoacoustic (PA) images.To achieve accurate localization, a high photoacoustic signal-to-noise ratio (SNR) is required. However, this is not guaranteed for deep targets, as optical scattering causes an exponential decay in optical fluence with respect to tissue depth. To address this, we develop a novel deep learning method designed to explicitly exhibit robustness to noise present in photoacoustic radio-frequency (RF) data. More precisely, we describe and evaluate a deep neural network architecture consisting of a shared encoder and two parallel decoders. One decoder extracts the target coordinates from the input RF data while the other boosts the SNR and estimates clean RF data. The joint optimization of the shared encoder and dual decoders lends significant noise robustness to the features extracted by the encoder, which in turn enables the network to contain detailed information about deep targets that may be obscured by noise. Additional custom layers and newly proposed regularizers in the training loss function (designed based on observed RF data signal and noise behavior) serve to increase the SNR in the cleaned RF output and improve model performance. To account for depth-dependent strong optical scattering, our network was trained with simulated photoacoustic datasets of targets embedded at different depths inside tissue media of different scattering levels. The network trained on this novel dataset accurately locates targets in experimental PA data that is clinically relevant with respect to the localization of vessels, needles, or brachytherapy seeds. We verify the merits of the proposed architecture by outperforming the state of the art on both simulated and experimental datasets.

Plasmonic Gold Nanomaterials as Photoacoustic Signal Resonant Enhancers for Cysteine Detection

The development of photoacoustic systems is important for the real-time detection of cysteine (Cys), a biothiol in biological systems that serves as a significant biomarker for human health. Advanced photoacoustic (PA) signals with colloidal plasmonic Au nanomaterials rely on the efficient conversion of light to energy waves under moderately pulsed laser irradiation. In this study, we synthesized Cys-capped Au nanorods (Au@Cys NRs) and Cys-capped Au nanoparticles (Au@Cys NPs) through a conjugate of three Cys concentrations (10, 100, and 1000 μM). These plasmonic Au nanomaterials can be used as a PA resonance reagent due to their maximum localized surface plasmon resonance (LSPR) absorption bands at 650 nm and 520 nm in Au NRs and Au NPs, respectively. Subsequently, the PA signals were noticeably increased proportionally to the concentrations in the Au@Cys NRs and Au@Cys NPs under 658 nm and 520 nm laser irradiation, respectively, according to our portable photoacoustic system. Furthermore, PA signal amplitudes in Cys detection are boosted by ~233.01% with Au@Cys NRs and ~102.84% with Au@Cys NPs enhancement, compared to free Cys, according to ultrasound transducers at frequencies of 3 MHz.

Real-time ultrasound sensing with a mode-optimized photonic crystal slab

Integrated photonic sensors can provide large scale, flexible detection schemes. Photonic crystal slabs (PCSs) offer a miniaturized platform for wideband, sensitive ultrasound detection by exploiting the photoelastic effect in water. However, poor modal overlap with the sensing medium and non-negligible absorption loss of the aqueous medium have previously limited PCS sensor performance. In this study, we detail the development and optimization of a PCS-based acoustic sensor by adding to it a low-loss high-index polymer cladding layer. Exploiting a mode-optimized TM-like optical resonance present in a PCS, with high bulk index sensitivity (>600nm/RIU) and quality factor Q (>8000), we demonstrate real-time ultrasound sensing at a noise equivalent pressure of 170 Pa (1.9Pa/Hz). The PCS sensor is backside-coupled to an optical fiber, which, along with its intensity-based ultrasound-sensing architecture, will allow us to scale up easily to a 2D array. This work paves the way to a sensitive compact ultrasound detector for photoacoustic-based diagnostics and monitoring of tissue.

Efficacy of High Temporal Frequency Photoacoustic Guidance of Laser Ablation Procedures

Inaccurate placement of the ablation catheter and the inability to monitor the real-time temperature within the tissue of interest such as veins curbs the treatment efficacy of laser ablation procedures during thermal therapies. Our previous studies have validated the efficacy of photoacoustic (PA) imaging during endovenous laser ablation (EVLA) procedures. However, the PA-guided therapies suffer from low temporal resolution, due to the low pulse repetition rates of pulsed lasers, which could cause a problem during fast catheter motion and rapid temperature changes. Herein, to enhance the accuracy and sensitivity for tracking the ablation catheter tip and temperature monitoring, we proposed to develop a high frame rate (500 Hz), combined ultrasound (US), and PA-guided ablation system. The proposed PA-guided ablation system was evaluated in a set of ex vivo tissue studies. The developed system provides a 2 ms temporal resolution for tracking and monitoring the ablation catheter tip's location and temperature, which is 50 times higher temporal resolution compared to the previously proposed 10 Hz system. The proposed system also provided more accurate feedback about the temperature variations during rapid temperature increments of 10°C per 250 ms. The co-registered US and PA images have an imaging resolution of about 200 μm and a field of view of 45 × 40 mm². Tracking the ablation catheter tip in an excised tissue layer shows higher accuracy during a relatively fast catheter motion (0.5-3 mm/s). The fast US/PA-guided ablation system will potentially enhance the outcome of ablation procedures by providing location and temperature feedback.

Spectroscopic photoacoustic imaging of cervical tissue composition in excised human samples

Objective

Cervical remodeling is an important component in determining the pathway of parturition; therefore, assessing changes in cervical tissue composition may provide information about the cervix’s status beyond the measurement of cervical length. Photoacoustic imaging is a non-invasive ultrasound-based technology that captures acoustic signals emitted by tissue components in response to laser pulses. This optical information allows for the determination of the collagen-to-water ratio (CWR). The purpose of this study was to compare the CWR evaluated by using spectroscopic photoacoustic (sPA) imaging in cervical samples obtained from pregnant and non-pregnant women.

Methods

This cross-sectional study comprised cervical biopsies obtained at the time of hysterectomy (n = 8) and at the scheduled cesarean delivery in pregnant women at term who were not in labor (n = 8). The cervical CWR was analyzed using a fiber-optic light-delivery system integrated to an ultrasound probe. The photoacoustic signals were acquired within the range of wavelengths that cover the peak absorption of collagen and water. Differences in the CWR between cervical samples from pregnant and non-pregnant women were analyzed. Hematoxylin and eosin and Sirius Red stains were used to compare the collagen content of cervical samples in these two groups.

Results

Eight cervix samples were obtained after hysterectomy, four from women ≤41 years of age and four from women ≥43 years of age; all cervical samples (n = 8) from pregnant women were obtained after 37 weeks of gestation at the time of cesarean section. The average CWR in cervical tissue samples from pregnant women was 18.7% (SD 7.5%), while in samples from non-pregnant women, it was 55.0% (SD 20.3%). There was a significantly higher CWR in the non-pregnant group compared to the pregnant group with a p-value <0.001. A subgroup analysis that compared the CWR in cervical samples from pregnant women and non-pregnant women ≤41 years of age (mean 46.3%, SD 23.1%) also showed a significantly higher CWR (p <0.01). Lower collagen content in the pregnancy group was confirmed by histological analysis, which revealed the loss of tissue composition, increased water content, and collagen degradation.

Conclusion

The proposed bimodal ultrasound and sPA imaging system can provide information on the biochemical composition of cervical tissue in pregnant and non-pregnant women. Photoacoustic imaging showed a higher collagen content in cervical samples from non-pregnant women as compared to those from pregnant women, which matched with the histological analysis. This novel imaging method envisions a new potential for a sensitive diagnostic tool in the evaluation of cervical tissue composition.

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.

Dual-Illumination Ultrasound/ Photoacoustic System for Cervical Cancer imaging

Early stage cancer detection technologies can provide functional information and potentially decrease the mortality rate caused by cervical cancer. In our previous work, a miniaturized ultrasound and photoacoustic endoscopic system has been developed to image the cervical tissue through the cervical canal to fulfills the need for a safe, low-cost, and high-resolution functional diagnostic system. However, the miniaturized size of endoscope and American National Standards Institute safety limits cause constraints of using high-intensity illumination during imaging. In addition, the strong light scattering of tissues limits the light penetration depth. Fortunately, the cervix anatomy allows for the delivery of additional light from the ectocervix by using an external illumination system. Here we propose a dual, co-planar illumination system, which can provide adequate illumination to the cervical tissue via combined internal and external light delivery strategies. Therefore, an increase in the area of light-tissue interaction allows us to raise the laser light energy while keeping fluence under safety limits. Thus, a reliable PA imaging can be obtained for the whole cervical tissue thickness. The system performance was tested using a Monte Carlo simulation, and laser-light fluence was calculated and compared at different depths within a simulated cervical-tissue model. The results indicated a higher and more uniform fluence in the Monte Carlo simulations. In addition, the photoacoustic imaging of the proposed system was evaluated by two cervical tissue-mimicking phantoms with human blood and graphite rods as inclusions inside it. In accordance with the simulations, the phantom study revealed a more reliable photoacoustic signal for the entire depth of the phantoms with an improved contrast to noise ratio and signal to noise ratio, and a higher coverage ratio of the imaging field of view. In summary, the dual-mode illumination system can provide more realistic information of inclusions within the tissue while considering safety limits, which can lead to more accuracy in biomarker detection for cervical cancer diagnostics.

Photoacoustic Tomography Opening New Paradigms in Biomedical Imaging

After the emergence of the ultrasound, X-ray CT, PET, and MRI, photoacoustic tomography (PAT) is now in the phase of its exponential growth, with its expected full maturation being another form of mainstream clinical imaging modality. By combining the high contrast benefit of optical imaging and the high-resolution deep imaging capability of ultrasound, PAT can provide unprecedented anatomical image contrasts at clinically relevant depths as well as enable the use of a variety of functional and molecular imaging information, which is not possible with conventional imaging modalities. With these strengths, PAT has achieved numerous breakthroughs in various biomedical applications and also provided new technical platforms that may be able to resolve unmet issues in clinics. In this chapter, we provide an overview of the development of PAT technology for several major biomedical applications and provide an approximate projection of the future of PAT.

The Influence of Diode Laser Intensity Modulation on Photoacoustic Image Quality for Oral Soft Tissue Imaging

Introduction: Imaging technologies have been developed to assist physicians and dentists in detecting various diseases. Photoacoustic imaging (PAI) is a new technique that shows great applicability to soft tissues. This study aimed to investigate the effect of diode laser intensity modulation on photoacoustic (PA) image quality. Methods: The prototype of the PAI system in this study utilized a non-ionizing 532 nm continuouswave (CW) diode laser illumination. Samples in this study were oral soft tissues of Sprague-Dawley rats fixed in 10% formalin solution. PA images were taken ex vivo by using the PAI system. The laser exposure for oral soft tissue imaging was set in various duty cycles (16%, 24%, 31%, 39%, and 47%). The samples were embedded in paraffin, and PA images were taken from the paraffinembedded tissue blocks in a similar method by using duty cycles of 40%, 45%, 50%, 55%, 60% respectively to reveal the influence of the laser duty cycle on PA image quality. Results: The oral soft tissue is clearly shown as a yellow to red area in PA images, whereas the nonbiological material appears as a blue background. The color of the PA image is determined by the PA intensity. Hence, the PA intensity of oral soft tissue was generally higher than that of the nonbiological material around it. The Kruskal-Wallis test followed by Mann-Whitney post-hoc analysis revealed significant differences (P<0.05) in the quality of PA images produced by using a 16%-47% duty cycle of laser intensity modulation for direct imaging of oral soft tissue fixed in 10% formalin solution. The PA image quality of paraffin-embedded tissue was higher than that of direct oral soft tissue images, but no significant differences in PA image quality were found between the groups. Conclusion: The PAI system built in this study can image oral soft tissue. The sample preparation and the diode laser intensity modulation may influence the PA image quality for oral soft tissue imaging. Nonetheless, the influence of diode laser intensity modulation is not significant for the PA image quality of paraffin-embedded tissue.

Noninvasive multiparametric charac-terization of mammary tumors with transmission-reflection optoacoustic ultrasound

Development of imaging methods capable of furnishing tumor-specific morphological, functional, and molecular information is paramount for early diagnosis, staging, and treatment of breast cancer. Ultrasound (US) and optoacoustic (OA) imaging methods exhibit excellent traits for tumor imaging in terms of fast imaging speed, ease of use, excellent contrast, and lack of ionizing radiation. Here, we demonstrate simultaneous tomographic whole body imaging of optical absorption, US reflectivity, and speed of sound (SoS) in living mice. In vivo studies of 4T1 breast cancer xenografts models revealed synergistic and complementary value of the hybrid imaging approach for characterizing mammary tumors. While neovasculature surrounding the tumor areas were observed based on the vascular anatomy contrast provided by the OA data, the tumor boundaries could be discerned by segmenting hypoechoic structures in pulse-echo US images. Tumor delineation was further facilitated by enhancing the contrast and spatial resolution of the SoS maps with a full-wave inversion method. The malignant lesions could thus be distinguished from other hypoechoic regions based on the average SoS values. The reported findings corroborate the strong potential of the hybrid imaging approach for advancing cancer research in small animal models and fostering development of new clinical diagnostic approaches.

Eigenspace-based minimum variance beamformer combined with sign coherence factor: Application to linear-array photoacoustic imaging

Photoacoustic (PA) imaging combining the advantages of high resolution of ultrasound imaging and high contrast of optical imaging provides images with good quality. PA imaging often suffers from disadvantages such as clutter noises and decreased signal-to-noise-ratio at higher depths. One studied method to reduce clutter noises is to use weighting factors such as coherence factor (CF) and its modified versions that improve resolution and contrast of images. In this study, we combined the Eigen-space based minimum variance (EIBMV) beamformer with the sign coherence factor (SCF) and show the ability of these methods for noise reduction when they are used in combination with each other. In addition, we compared the proposed method with delay-and-sum (DAS) and minimum variance (MV) beamformers in simulated and experimental studies. The simulation results show that the proposed EIBMV-SCF method improves the SNR about 94 dB, 87.65 dB, and 62.29 dB compared to the DAS, MV, and EIBMV, respectively, and the corresponding improvements were 79.37/34.43 dB, 77.25/26.96 dB, and 33.19/25.56 dB in the ex vivo/in vivo experiments.

MEMS Ultrasound Transducers for Endoscopic Photoacoustic Imaging Applications

Photoacoustic imaging (PAI) is drawing extensive attention and gaining rapid development as an emerging biomedical imaging technology because of its high spatial resolution, large imaging depth, and rich optical contrast. PAI has great potential applications in endoscopy, but the progress of endoscopic PAI was hindered by the challenges of manufacturing and assembling miniature imaging components. Over the last decade, microelectromechanical systems (MEMS) technology has greatly facilitated the development of photoacoustic endoscopes and extended the realm of applicability of the PAI. As the key component of photoacoustic endoscopes, micromachined ultrasound transducers (MUTs), including piezoelectric MUTs (pMUTs) and capacitive MUTs (cMUTs), have been developed and explored for endoscopic PAI applications. In this article, the recent progress of pMUTs (thickness extension mode and flexural vibration mode) and cMUTs are reviewed and discussed with their applications in endoscopic PAI. Current PAI endoscopes based on pMUTs and cMUTs are also introduced and compared. Finally, the remaining challenges and future directions of MEMS ultrasound transducers for endoscopic PAI applications are given.

Photoacoustic image improvement based on a combination of sparse coding and filtering

SIGNIFICANCE

Photoacoustic imaging (PAI) has been greatly developed in a broad range of diagnostic applications. The efficiency of light to sound conversion in PAI is limited by the ubiquitous noise arising from the tissue background, leading to a low signal-to-noise ratio (SNR), and thus a poor quality of images. Frame averaging has been widely used to reduce the noise; however, it compromises the temporal resolution of PAI.

AIM

We propose an approach for photoacoustic (PA) signal denoising based on a combination of low-pass filtering and sparse coding (LPFSC).

APPROACH

LPFSC method is based on the fact that PA signal can be modeled as the sum of low frequency and sparse components, which allows for the reduction of noise levels using a hybrid alternating direction method of multipliers in an optimization process.

RESULTS

LPFSC method was evaluated using in-silico and experimental phantoms. The results show a 26% improvement in the peak SNR of PA signal compared to the averaging method for in-silico data. On average, LPFSC method offers a 63% improvement in the image contrast-to-noise ratio and a 33% improvement in the structural similarity index compared to the averaging method for objects located at three different depths, ranging from 10 to 20 mm, in a porcine tissue phantom.

CONCLUSIONS

The proposed method is an effective tool for PA signal denoising, whereas it ultimately improves the quality of reconstructed images, especially at higher depths, without limiting the image acquisition speed.

Tetrazine-Derived Near-Infrared Dye as a Facile Reagent for Developing Targeted Photoacoustic Imaging Agents

A new photoacoustic (PA) dye was developed as a simple-to-use reagent for creating targeted PA imaging agents. The lead molecule was prepared via an efficient two-step synthesis from an inexpensive commercially available starting material. With the dye's innate albumin-binding properties, the resulting tetrazine-derived dye is capable of localizing to tumor and exhibits a biological half-life of a few hours, allowing for an optimized distribution profile. The presence of tetrazine in turn makes it possible to link the albumin-binding optoacoustic signaling agent to a wide range of targeting molecules. To demonstrate the utility and ease of use of the platform, a novel PA probe for imaging calcium accretion was generated using a single-step bioorthogonal coupling reaction where high-resolution PA images of the knee joint in mice were obtained as early as 1 h post injection. Whole-body distribution was subsequently determined by labeling the probe with ^99mTc and performing tissue counting following necropsy. These studies, along with tumor imaging and in vitro albumin binding studies, revealed that the core PA contrast agent can be imaged in vivo and can be easily linked to targeting molecules for organ-specific uptake.