This PDF file contains the front matter associated with SPIE Proceedings Volume 12842, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Imaging peripheral nerve morphology, function, and vascular supply is important in clinical medicine and research. In this work, we evaluate the imaging capabilities of multispectral optoacoustic tomography (MSOT) for peripheral nerves. We demonstrate how recent advances in MSOT data processing combined with data-driven unmixing overcome adverse effects of measurement noise and light fluence attenuation and provide detailed insights into the vasa nervorum and the internal structure of peripheral nerves.

In this study, a novel approach is presented to overcome the challenge of replacing conventional opaque ultrasound transducers (OUTs) with transparent ultrasound transducers (TUTs) that seamlessly integrate optical and ultrasound components. TUTs offer a design that seamlessly combines optical and ultrasound modalities, providing a convenient solution to overcome challenges such as beam combiner or off-axis problems. However, their performance has been significantly limited due to acoustic impedance mismatch. To address the acoustic impedance mismatch problem, transparent composite-based matching and backing layers are utilized with acoustic impedances exceeding 7 and 4 MRayl, respectively. These layers facilitate the development of an ultrasensitive and wideband TUT with a single resonance frequency and a pulse-echo bandwidth of over 60%, equivalent to traditional OUTs. The TUT demonstrates exceptional performance, with over 80% optical transparency, maximizing acoustic power transfer efficiency, maintaining spectrum flatness, and minimizing ringdowns. Such capabilities enable high-contrast and high-definition dual-modal ultrasound and photoacoustic imaging in both animals and humans. Notably, these imaging modalities achieve a penetration depth of over 15 mm, utilizing a 30MHz TUT. We believe this advancement opens up new possibilities for non-invasive imaging applications, offering enhanced diagnostic capabilities and potential insights into biological structures at greater depths.

This letter reports a 2D high-frequency surface-micromachined optical ultrasound transducer (HF-SMOUT) array for micro-PACT (μPACT) applications. A 11 mm × 11 mm HF-SMOUT array with 220 × 220 elements (35 μm in diameter) is designed, fabricated and characterized. The center frequency and bandwidth of the HF-SMOUT elements are ~15 MHz and ~20 MHz (133%), respectively. The noise equivalent pressure (NEP) is 156 Pa (or 19 mPa/√ Hz) within a measurement bandwidth of 5 × 75 MHz. PACT experiments are conducted to evaluate the imaging performances of the SMOUT array. Spatial resolution is estimated as 90 μm (axial) and 250—750 μm (lateral) within a 10 × 10 mm􀬶 FOV (field of view) and the imaging depth up to 16 mm. 3D PA image of a knotted human hair target is also successfully acquired. These results show the feasibility of using the HF-SMOUT array for μPACT applications.

Ultraviolet photoacoustic microscopy (UV-PAM) has emerged as a promising medical imaging technique for alternative histopathology, relying on the inherent optical absorption of DNA/RNA. However, traditional UV-PAM faces resolution challenges compared to clinical histological methods, limiting the observation of cellular structures. This limitation stems from the constraints of conventional reflection-mode UV-PAM systems, utilizing opto-ultrasound beam combiners or ring-shaped ultrasound transducers. These components impose constraints on numerical apertures (NA), thereby limiting spatial resolution. On the flip side, transmission-mode UV-PAM encounters difficulties in imaging thick specimens due to signal attenuation. In this study, we introduce an innovative solution – the development of an ultraviolet-transparent ultrasound transducer (UV-TUT) – overcoming these limitations and enabling high-resolution UV-PAM system. The UV-TUT significantly enhances both NA and lateral resolution, outperforming previous reflection-mode UV-PAM systems. With an impressive light transmission efficiency in the UV region and sensitivity four times greater than traditional ring-shaped ultrasound transducers, the UV-TUT lays the foundation for improved imaging capabilities. Leveraging the capabilities of the UV-TUT, we exploited a UV-PAM system, showcasing superior performance for imaging mouse brain tissue sections compared to conventional opto-ultrasound beam combiner-based UV-PAM. Furthermore, our application of photoacoustic histopathology on uterine cancer tissue sections demonstrated image quality comparable to microscopy images, providing valuable insights for accurate histopathological analysis. This work signifies a significant advancement in UV-PAM system, holding the promise to enhance the clinical utility of alternative histopathology with unprecedented resolution and imaging capabilities.

In photoacoustic tomography (PAT), a limited angle of detector coverage around the object affects PAT image quality. Consequently, PAT images can become challenging to interpret accurately. Although deep learning methods, such as convolutional neural networks (CNNs), have shown promising results in recovering high-quality images from limited-view data, these methods suffer from loss of fine image details. Recently, denoising diffusion probabilistic models (DDPM) are gaining interest in image generation applications. Here we explore the potential of conditional denoising diffusion probabilistic models (cDDPM) to enhance quality of limited-view PAT images. The OADAT dataset consisting of 2D PAT images of healthy forearms acquired with a semicircle array of 256 ultrasound elements is used. PAT images are reconstructed using the full array (256 elements) and also the central 128, 64 and 32 elements for limited-view. The approach showed to be able to filter out limited-view streak artifacts, accurately recover shapes of vascular structures, and preserve fine-detailed texture. Conditional DDPMs show potential in improving quality of limited-view PAT reconstructions, however, they require higher computational cost compared to conventional CNNs. Future works will include the reduction of computational time and further evaluations on different datasets and array geometries.

Ionizing radiation acoustic imaging (iRAI) provides the potential to map the radiation dose during radiotherapy in real time. Described here is the development of iRAI volumetric imaging system in mapping the three-dimensional (3D) radiation dose deposition of clinical radiotherapy treatment plan with patient receiving radiation to liver tumor. The real-time visualizations of radiation dose delivered have been archived in patients with liver tumor under a clinical linear accelerator. This proof-of-concept study demonstrated the potential of iRAI to map the dose distribution in deep body during radiotherapy, potentially leading to personalized radiotherapy with optimal efficacy and safety.

Sentinel lymph node biopsy (SLNb) plays an important role in determining whether breast cancer has metastasized. The current standard method for SLNb is to use radioactive material and blue dye to detect sentinel lymph nodes (SLNs). However, this method has limitations such as radiation exposure, radioactive material disposal, and subjective evident interpretation of the blue dye. To overcome these limitations, we developed a non-radioactive detector, the photoacoustic finder (PAF), which utilizes the photoacoustic (PA) signal from the SLN's blue dye to identify SLNs instead of radioactive material. For evaluating the PAF, in this ex vivo clinical study, we compared the detection rate of standard SLN detection methods and PAF in resected SLNs from breast cancer patients. A total of 92 breast cancer patients were enrolled in the study, and 164 SLNs resected from the patients were analyzed. The detection rate was similar for gamma probe (85%, 139 of 164 SLNs) and PAF (85%, 139 of 164 SLNs), while the detection rate using blue dye visual inspection was 74% (122 of 164 SLNs), which was lower than gamma probe and PAF. These results affirm the validity of PAF as a non-radioactive alternative for detecting SLNs, indicating the potential feasibility of non-radioactive SLNb in future applications.

Photoacoustic tomography is an emerging technique in the field of biomedical imaging that combines the advantages of optics and acoustics. Unlike conventional imaging modalities, which are limited in their ability to provide diverse types of diagnostic information, PAT can offer structural, functional, and molecular biometric imaging using a single modality. This advantage can be utilized in that multiparametric information is required to analyze various aspects of tumor. In this study, we have developed a versatile PAT system for tumor imaging which can provide high-definition and high-speed images. Our system can identify tumor characteristics such as angiogenesis, pharmacokinetics, and physiological functions for both primary and metastatic tumors. During 14 days after tumor cell inoculations, we visualize the angiogenesis and increased tortuosity of blood vessels surrounding the tumor. Additionally, we quantify changes in the oxygen saturation within the entire tumor region, revealing the presence of hypoxia in the tumor core. These findings highlight the ability of our system to provide valuable functional information about tumor physiology. Moreover, our versatile PAT system allows us to observe the organ accumulation characteristics of different contrast agents. With its ability to generate high-quality structural, functional, and molecular photoacoustic images, our system holds promise for advancing the field of biomedical imaging.

Multispectral optoacoustic tomography (MSOT) provides anatomical and functional imaging of tissues without the need for reporter molecules or transfection. We examined the acute vascular disrupting activity of a new microtubule disrupting agent (OXi8007) using MSOT on syngeneic mouse RENCA-luc, and human XP258 orthotopic kidney tumors. In both tumor types, an oxygen gas breathing challenge showed reduced tumor oxygenation and response within 4h of treatment. In RENCA-luc tumors this matched vascular shutdown assessed by dynamic BLI. MSOT additionally confirmed that VDA did not significantly affect the contralateral normal kidney or spine.

Enhancing the monitoring of dynamic changes in organs is crucial for understanding biological processes and diseases. Current small-animal imaging techniques have limitations in contrast, sensitivity, and spatial/temporal resolution. We propose a rapid rotary-scanning photoacoustic computed tomography (PACT) approach that addresses these limitations. Using a rapid rotary-scanning technique with a hemispherical transducer array, we monitor dynamic change in mice. Leveraging the near-infrared spectral window, our method enables visualization of deep-seated structures across multiple planes in living mammalian organs. Our results demonstrate high image quality, rich spectroscopic contrast, and improved temporal resolution. PACT holds significant potential as a valuable tool for studying pharmacokinetics in preclinical research, offering insights into complex biological processes and facilitating the development of targeted therapeutics.

Transcranial photoacoustic computed tomography (PACT) is an emerging human neuroimaging modality that holds significant potential for clinical and scientific applications. However, accurate image reconstruction remains challenging due to skull-induced aberration of the measurement data. Model-based image reconstruction methods have been proposed that are based on the elastic wave equation. To be effective, such methods require that the elastic and acoustic properties of the skull are known accurately, which can be difficult to achieve in practice. Additionally, such methods are computationally burdensome. To address these challenges, a novel learningbased image reconstruction was proposed. The method involves the use of a deep neural network to map a preliminary image that was computed by use of a computationally efficient but approximate reconstruction method to a high-quality, de-aberrated, estimate of the induced initial pressure distribution within the cortical region of the brain. The method was systematically evaluated via computer-simulations that involved realistic, full-scale, three-dimensional stochastic head phantoms. The phantoms contained physiologically relevant optical and acoustic properties and stochastically synthesized vasculature. The results demonstrated that the learning-based method could achieve comparable performance to a state-of-the-art model-based method when the assumed skull parameters were accurate, and significantly outperformed the model-based method when uncertainty in the skull parameters was present. Additionally, the method can reduce image reconstruction times from days to tens of minutes. This study represents an important contribution to the development of transcranial PACT and will motivate the exploration of learning-based methods to help advance this important technology.

Multispectral optoacoustic tomography requires real-time image feedback during clinical use. Herein, we present DeepMB, a deep learning framework to express the model-based reconstruction operator with a deep neural network and reconstruct high-quality optoacoustic images from arbitrary experimental input data at speeds that enable live imaging (31ms per image).

Photoacoustic (PA) imaging combines optical spectroscopic contrast with deep tissue penetration, offering valuable functional, molecular, and structural information about tissue. However, a long-standing challenge with PA imaging has been that the quantification accuracy of tissue chromophores concentrations remains limited due to the spectral colouring effect. Monte Carlo (MC) simulation is regarded as the gold standard to model light transportation in tissue but can be computationally demanding, thus not suitable for real-time applications. We propose a time-efficiency solution using conditional generative adversarial networks (cGANs) to generate light fluence distributions within tissue towards real-time spectral decolouring in PA imaging. The networks were trained to predict light fluence distribution from realistic tissue anatomy and optical properties using MC simulation as ground truth. We achieved high-quality light fluence synthesis, with a peak signal-to-noise ratio of 31.9 dB using in vivo segmentation. We also demonstrated the validity of spectral decolouring for PA quantification, with an error of absorption efficient estimation around 0.05 using numerical phantoms. Thus, this approach holds promise for enhancing the quantification performance of PA imaging in real-time.

Amongst the several biomedical imaging modalities, Photoacoustic imaging stands out due to its advantage of providing optical contrast at ultrasound resolution from deeper tissues. The optical illumination is traditionally provided by the nanosecond-pulse width lasers, but they are costly, bulky, and non-portable. Light Emitting Diode-based systems can circumvent all these issues, but they deliver low-energy that brings forth another problem of low signal-to-noise-ratio (SNR) images. Averaging several frames at the same cross-section over time removes the noise, but real-time dynamic functionalities might not be captured. The tradeoff between SNR and real-time acquisition can be mitigated with a downstream noise removal algorithm. The traditional algorithms are not efficient and require prior knowledge about the noise type distribution for which deep learning-based architectures such as U-Net and generative adversarial network (GAN) are implemented. One of the issues of these supervised networks is the requirement of paired training input-label dataset which is highly cumbersome to capture or sometimes is unavailable. The pixel-wise correspondence will act as a pre-processing overburden for acquiring training data. To mitigate this issue, we implemented a Cycle-consistent GAN denoising (DenCyc-GAN) algorithm which works on unpaired training data. We compared our network’s outputs with other traditional non-learning and deep learning network and found that our network performed similar to the supervised networks with respect to image quality metrics such as Peak SNR and structural similarity index.

Optoacoustic tomography is typically implemented with bulky solid-state lasers delivering per-pulse energies in the millijoule range. Light emitting diodes (LEDs) represent a cost-effective and portable alternative for signal excitation further offering excellent pulse-to-pulse stability. Herein, we describe a full-view LED-based optoacoustic tomography (FLOAT) system for deep-tissue in vivo imaging. A custom-made electronic unit driving a stacked array of LEDs attains stable light pulses with total per-pulse energy of 0.48 mJ and 100 ns pulse width. The LED array was arranged on a circular configuration and integrated in a full-ring ultrasound array enabling full-view tomographic imaging performance in cross-sectional (2D) geometry. As a proof of concept, we scanned the medial phalanx of the index finger without extrinsic administration of a contrast agent. We anticipate that this compact, affordable, and versatile illumination technology will facilitate dissemination of the optoacoustic technology in resource-limited settings.

Optoacoustic tomography (OAT) has made major advances towards clinical diagnostics in recent years. One major obstacle inhibiting the establishment of this non-invasive non-ionizing technique as a routine diagnostic device is the unfamiliarity of clinicians to OAT images. Several works have already been dedicated to combining Optoacoustic and Ultrasound imaging (OPUS). However, thus far, dual mode 1D arrays have mostly been employed. Not only are the resulting 2D OAT images subject to out-of-plane artefacts, but as the transducer specifications are typically optimized for OA imaging, the US image quality tended to be comparatively poor. Here, we present a concave spherical detector with dedicated OAT and US transducer, where the optimized transducer design boasts excellent image resolution for both modalities. Real-time OPUS acquisitions were performed on healthy human subjects in several regions, including the neck and forearm. 3D OAT volumes were supplemented with a 2D US cross-sections, enabling the complementary identification of key anatomical structures. The contextual structural information offered by US allows for the further exploitation of the rich OA molecular contrast. This showcase demonstration is an important step towards establishing OAT as a clinical point-of-care device.

We present the development of a photoacoustic tomography (PAT) imaging system with the demonstrated capability of obtaining high-throughput scans at a sustained rate of under 1 minute per animal using integrated robotics to assist in 3D PAT collection. This is a considerable achievement as there is currently no existing commercial or research PAT whole-body imaging system capable of high-throughput applications (15-20 animals per hour). High-throughput experimentation is imperative in the development, characterization, and use of rodent models of human diseases as it increases the number of animals that can be evaluated within a single experiment and may reduce the time under anesthesia for each animal, thereby improving the stability, duration, and confidence of longitudinal studies The developed system features coordinated automation for robotic animal manipulation, anesthesia distribution, temperature regulation, water management, laser excitation, and photoacoustic detection. Furthermore, as shown in validation studies using phantoms and live murine models, the prototype imaging platform demonstrates high-throughput performance while retaining high sensitivity and high resolution.

Photoacoustic tomography of calcium activity in the mouse brain could potentially provide whole-brain coverage of neural activity and therefore offer new insights into brain function. Here we report the development and characterization of a novel photoacoustic calcium-sensitive probe based on the HaloTag protein which is suitable for in vivo imaging in mice. The photoacoustic brightness and signal enhancement upon calcium binding were measured using a custom-built spectroscopy setup and compared to the available far-red calcium indicator NIR-GECO1. Additionally, we conducted validation experiments on tissue-mimicking phantoms using a Fabry-Perot-based photoacoustic tomography setup to determine the depth limit and concentration detection threshold of the imaged probes. Furthermore, we tested various in vivo delivery methods, by analyzing brain slices from mice labeled with the photoacoustic probe. These experiments demonstrated that we are able to specifically label neurons targeted brain regions, confirming the suitability of these photoacoustic probes for in vivo calcium imaging applications.

Gliomas, malignant brain tumors accounting for approximately 30% of primary brain tumors, are typically treated with gross total resection (GTR) followed by radiation therapy (RT) and chemotherapy. Nonetheless, certain conditions render GTR unfeasible, necessitating alternative therapies like MRI-guided laser interstitial thermal therapy (LITT). Although MRI-guided LITT can monitor the temperature distribution in the tissue by using an MRI thermometer and estimate the resulting necrosis prognosis based on a necrosis formation model, fixed model parameters are usually used for patients universally, resulting in necrosis estimation error. Hence, spectroscopic photoacoustic (sPA) imaging is considered for direct intraoperative necrosis monitoring. While sPA’s utility has been explored in organs like the heart and liver, it seems no studies have been conducted in the brain yet. In this study, we evaluate the feasibility of sPA in characterizing ablation-induced brain necrosis, using brain-specific spectra from ablated and non-ablated areas in the goat’s grey matter. With the aim to quantify the extent of necrosis, we implement the Necrotic Extent (NE) index defined as the photoacoustic intensity ratio between ablated and non-ablated tissue, and generate an NE map to visualize the result. Results showed statistically significant differences between the spectrum of the ablated and non-ablated regions, indicating that sPA can differentiate between them. In the NE map, the regions showing high NE values correspond to the ablated area, supporting the feasibility of the technique for the brain domain. The study concludes that sPA-based direct necrosis monitoring is feasible for the grey matter of the goat brain. As future work, it is necessary to conduct further investigations including data collection for white matter and bridging the gap between goat and human applications for actual clinical use.

Real-time 3-D photoacoustic (PA) imaging plays a significant role in volumetric imaging applications, such as breast imaging where PA has demonstrated significant potential. Challenges in 3-D PA imaging include long data acquisition time and limited compatibility with commonly used data acquisition systems. This paper introduces a new real-time 3-D PA data acquisition system using a matrix array transducer. Furthermore, we present a 3-D Delay and Glow (DAG) method for source localization that extends upon recently developed 2-D DAG. The experimental results show the functionality of the 3-D PA system. The DAG outperformed the conventional delay and sum (DAS) where axial, lateral, and elevational resolutions, respectively, are 0.06±0.00, 0.25±0.15, and 0.24±0.18mm for DAG and 0.14±0.06, 3.87±0.30, and 2.81±0.62mm for DAS.

Quantitative photoacoustic computed tomography (qPACT) holds great promise to advance a variety of important clinical applications with its potential to estimate vital physiological properties such as oxygen saturation. However, the qPACT reconstruction problem is highly nonlinear and ill-posed. Conventional spectral unmixing methods often oversimplify the problem, resulting in suboptimal accuracy. Alternatively, more principled image reconstruction approaches that comprehensively model the imaging physics are computationally burdensome and require the design of effective regularization strategies. To overcome these limitations, learning-based methods have been proposed. To date, however, the effectiveness of such methods on full-scale problems in which clinically relevant variability in anatomy and physiological parameters is considered has not been established. To address this, we investigated the use of a convolutional neural network with spatial and channel attention modules to estimate the three-dimensional (3D) distribution of tissue oxygenation within vessels and lesions in the female breast. The network was provided with input data comprising noise-corrupted 3D initial pressure distributions corresponding to three wavelengths (757, 800, 850 nm). An additional novel aspect of our study was the use of realistic 3D numerical breast phantoms that described stochastic variations in breast anatomy and functional properties, which enabled a meaningful, quantitative, and systematic evaluation of the proposed method. This study represents an important contribution to the field of qPACT and will guide the exploration of learning-based methods to help translate this important technology by delineating potential prospects and limitations.

The X-ray free-electron laser (XFEL) has revolutionized X-ray imaging with its high power, short pulse width, low emittance, and high coherence. We introduce X-ray-induced acoustic microscopy (XFELAM), utilizing the X-ray induced acoustic (XA) effect. We verified the XA effect and achieved micron-scale resolution by imaging patterned tungsten targets with drilled circles. XFELAM expands XFEL capabilities, enabling high-resolution visualization of materials and systems. This technique complements existing XFEL methods and promises advancements in fundamental research across fields. XAM’s unique features benefit materials science, nanotechnology, and biophysics, contributing to a deeper understanding of scientific phenomena and discoveries.

Laser parameters deftly govern the conversion of electromagnetic pulse energy into acoustic waves. Despite advancements in experimental techniques and pulsed lasers, an accurate theoretical model is still lacking for spectrum analysis of the acoustic waves generated upon irradiation of laser pulses. Here, we have studied the behavior of Photoacoustic (PA) waves in the medium upon laser pulse irradiation with varying pulse widths and repetition rates and observe the impact on frequency characteristics by variation of absorption coefficient via imaginary part of the refractive index at constant wavelength followed by wavelength variation, thereby changing the absorption coefficient of the medium following its wavelength dependence. An acoustic wave scatterer is placed inside the medium and reconstructed using Synthetic Aperture Focusing Technique (SAFT). Upon reflection from scatterers, these resultant acoustic waves return to the surface at distinct time intervals and are detected via transducers or optical techniques. In this study, a time-domain Finite Element Method (FEM) simulation has been performed for generation, propagation, and detection of acoustic waves near the medium-air interface. The framework consists of self-consistent solution of the light diffusion equation, heat equation, Poila-Kirchoff stress equation, and pressure-wave equation. The detected signals near the surface of the medium are imported to MATLAB to obtain high-resolution images using SAFT.

This paper reports the development of dual-modal all-optical photoacoustic microscopy (PAM) and photoacoustic viscoelasticity testing (PAVT) based on a common setup with tunable annular-beam excitation and wideband laser-vibrometer detection. For PAM, the annular beam is reduced to a small diameter to excite longitudinal bulk acoustic waves (BAWs) from light-absorbing targets buried in the sample, and the imaging quality is improved by a specified synthetic aperture focusing technique (SAFT). For PAVT, circularly converging surface acoustic waves (SAWs) are generated on the sample surface by annular beams with larger and different diameters. Both the induced BAWs and SAWs are detected at the center of the annular beam in a non-contact fashion by a broad-band laser vibrometer. Experiments have been conducted on the tissue-mimicking agar phantoms as well as animal tissues and have successfully demonstrated the initial concept of dual-modal all-optical PAM and PAVT.

The limited absorption and inadequate tissue penetration of gold (Au) nanoparticles, despite their exceptional photothermal conversion efficiency, restrict their potential in photoacoustic imaging and photothermal therapy. To overcome these limitations, we have developed modified Au-platinum nanoparticles that can be effectively utilized for photoacoustic analysis. Through the surface plasmon resonance coupling, we can considerably increase the absorption and bandwidth of the near-infrared light by modifying nanoparticles by adding Pt nanodots to the spherical Au nanoparticles’ surface. Moreover, hyaluronate makes it easier to administer developed nanoparticles transdermally, permitting effective passage across the epidermal and allowing effective skin tumor PA imaging. This achievement underscores the potential of developed hyaluronate-Au-platinum nanoparticles as a noninvasive agent for NIR light-mediated skin cancer theranostics. Also, we verify that the developed nanoparticles effectively penetrate the skin through photoacoustic imaging. By applying particles to the skin of a skin cancer mouse model and analyzing the depth of the photoacoustic signal generated by the material, the ability of the developed material to penetrate the skin and its performance as a photoacoustic exogenous contrast agent is confirmed.

2-D Ultrasound (US) Transducer (2D-UST) arrays facilitate scan-less volumetric photoacoustic imaging (3D-PAI), but are typically high-cost, involve laborious fabrication process, and permit limited scalability in design with respect to array parameters like element count, aperture size, center frequency ( 𝑓_c) and array pitch. In this work, we report a novel, 2-D matrix UST array fabricated on a printed circuit board (PCB) substrate (2D-PCB-UST array) at low-cost and without the need of advanced cleanroom fabrication technologies. Further, the 2D-PCB-UST array parameters can be easily modified with PCB design software. We demonstrate the scalability by fabricating two arrays, (i) an 8×8 array with 1.5 mm pitch and 𝑓_c 40 MHz, and (ii) an 4×4 array with 1.2 mm pitch and 𝑓_c 11 MHz. Initial characterization results demonstrate wideband PA receive sensitivity, characterized by the 6-dB fractional bandwidth for both low and high frequency UST arrays. Phantom imaging results demonstrate 3D-PAI capabilities despite low element count and sparse array geometry.

Thermoacoustic imaging (TAI) is a promising new technology for biomedical diagnostics. It combines the high contrast of electromagnetic absorption with the high resolution of ultrasound imaging. Traditional TAI systems use circular scanning modes with single or arc detectors, which can be slow and inefficient for body scanning. A linear-array detector, which is commonly used in medical ultrasound imaging systems, can be used to scan biological tissues more efficiently. In this study, we developed a novel linear-array TAI system (LATIS) for the detection of hemorrhage in the brain through fontanelle in neonates. The LATIS uses a linear-array transducer with multiple elements, which enables rapid data acquisition and real-time imaging. A custom-designed trigger mechanism synchronizes the microwave signal generation and data acquisition process, ensuring accurate timing for optimal image quality. We evaluated the LATIS performance by conducting several ex-vivo sheep brain hemorrhage of different amounts of artificially induced blood. The system was able to successfully detect lower grades of intraventricular hemorrhages in ex-vivo experiments. These results demonstrate the potential of LATIS for clinical imaging of brain hemorrhage in neonates as they are vulnerable to intraventricular hemorrhage.

We investigated application of speckle illumination to a heterogeneous sample where small optical absorbers are sparsely distributed. Although such sample is difficult to visualize by homogeneous illumination, speckle illumination has advantages. For example, speckle light has a heterogeneous and granular intensity distribution, which is similar to that of optical absorbers in a heterogeneous sample. In addition, speckle light has higher intensity spots compared to homogeneous illumination. These characteristics can be used for signal enhancement compared to homogeneous illumination. Moreover, speckle illumination enables us to perform heterogeneity evaluation of the heterogeneous sample since the signal is varied depending on spatial overlap between the speckle light and the optical absorbers. In this research, we used acoustic resolution photoacoustic microscope (AR-PAM) to investigate application of speckle illumination to a heterogeneous sample. In the AR-PAM system, speckle light is generated by using a diffuser. As heterogeneous samples, black-dyed microspheres and red blood cells (RBCs) in Matrigel were used. By illuminating speckle light to the sample and changing the speckle pattern, variation of the signal was observed. In the measurement of the microspheres, we confirmed that some speckle patterns provide higher signals compared to homogeneous illumination. In addition, we also confirmed that normalized signal variance is depended on concentration of RBCs. This can be used as heterogeneity evaluation.

Photoacoustic computed tomography (PACT) is being actively developed for breast cancer imaging. In 3D PACT imagers for breast imaging, a hemispherical measurement geometry that encloses the breast has been employed. Such measurement data are referred to as “half-scan” data. Existing closed-form reconstruction methods assume a closed measurement aperture; however, the direct application of these methods to half-scan data results in inaccurate images with artifacts. Previous studies have demonstrated that half-scan data are “complete” in the sense that they contain sufficient information for accurate and stable reconstruction of an object contained within a hemispherical measurement aperture. However, direct closed-form methods for use with half-scan data have not been reported. Although optimization-based iterative image reconstruction methods are applicable, they are computationally intensive. In this work, for the first time, a semi-analytic image reconstruction method of filtered backprojection (FBP) form was proposed for use with half-scan PACT data. To accomplish this, the unknown data filtering operation is learned in a data-driven way by use of a linear U-Net neural network. To investigate the method, stochastic 3D numerical breast phantoms (NBPs) were used for model training and testing. As a result of the completeness of the half-scan data, we demonstrate that the learned FBP method can be widely applied, even when the to-be-reconstructed object differs considerably from those that were used to learn the data filtering. This is a key feature of the method that will enable it to have an important practical impact on PACT.

Atrial fibrillation (A-fib) affects millions of patients in the US, and percutaneous catheter radiofrequency (RF) ablation is a common treatment. However, the lack of intraoperative feedback on ablation-induced lesions can lead to complications or recurrence. This study investigates the feasibility of using photoacoustic (PA) frequency analysis to identify ablation-induced necrotic lesions in ex vivo liver tissue samples. PA imaging, employing laser-generated ultrasound (US), enables monitoring and mapping of ablation-induced lesions by exploiting spectral differences between ablated and non-ablated tissue. Spectral unmixing techniques in multi-wavelength PA imaging provide real-time monitoring but are impractical due to extended acquisition times. Acoustic frequency-based tissue characterization has previously been reported to examine different contrast sources. In this study, porcine liver tissue samples underwent RF ablation, followed by US/PA imaging scanning. PA signals are processed using Fast Fourier Transformation (FFT) for frequency information extraction. Spectrum unmixing confirms the presence of ablation-induced necrosis. Preliminary results from seven ablation samples demonstrate effective tissue boundary capture and identification of ablated necrotic regions using PA imaging. Frequency spectra analysis shows distinct differences (double-sided P-value < 0.01), with ablated tissue exhibiting lower frequencies. These findings suggest the feasibility of frequency-based PA tissue identification for monitoring ablation procedures. Future work involves developing a tissue characterization algorithm based on frequency analysis to enhance real-time feedback during RF ablation therapy.

This letter presents a method for the release and sorting of gold nanoparticles (AuNP) from a soft substrate with an optothermal mechanical (OTM) method. The OTM method relies on the heating of AuNPs on a soft substrate via a continuous-wave laser. An AuNP absorbs the energy from the focused beam and transfers the heat to the substrate beneath it. The induced heat causes a rapid thermal expansion of the substrate, imparting an impulse to the AuNP and releasing it from the substrate. The release of an AuNP from a PMMA substrate of different thicknesses is studied. The release angle is determined by the polymer surface thickness, which affects the printing accuracy. Therefore, the release of an AuNP from a soft substrate of different thicknesses is investigated. The heat that can be generated within an AuNP depends on its size upon absorption. Generally, a smaller AuNP needs higher laser intensity to overcome the Van der Waal force to be released from the substrate. Therefore, the mixed sizes of AuNPs can be selected and sorted by their different release threshold. In this paper, the successful sorting of two types of AuNPs from a substrate to a receiver substrate in air condition is demonstrated. The OTM method paves a new way to separate and purify nanoparticles directly in a gaseous environment.

Accurate assessment of microvasculature and oxygen saturation is vital for diagnosing and monitoring diseases, including cancer. However, the current clinical need for point-of-care (POC), non-invasive, and cost-effective imaging approaches remains unmet. Photoacoustic imaging, offering natural blood contrast, holds potential for high-resolution vascular imaging. Yet, the requirement for bulky and expensive lasers impedes its clinical translation, particularly in resource-limited settings. Recent advances in using high-power LED arrays for photoacoustic imaging are promising due to their portability, affordability, and ease-of-use in clinical settings. In this work, we demonstrate the potential of LED-based photoacoustic imaging for microvascular health assessment through in vivo human volunteer imaging. Real-time 2D and 3D experiments evaluated LED-based photoacoustic imaging in assessing vascular density, arterial distensibility, and blood oxygen saturation with high resolution. Our results confirm that LED-based photoacoustic imaging may serve as an invaluable POC tool for microvascular health assessment in resource-limited settings. The affordability and simplicity of LED arrays present a compelling alternative to laser-based approaches, expanding accessibility in clinical practice. This advancement has the potential to enhance early disease detection and treatment monitoring, particularly in areas with limited access to sophisticated imaging technologies.

Ultrasound is a powerful tool for performing cross sectional imaging. Non-contact detection of ultrasound via light is important when physical coupling to the sample is precluded by sample sensitivity and has applications in metrology and medical imaging. Optical coherence tomography provides similar structural information to ultrasound, typically with higher resolution and lower penetration depths. The phase sensitivity of optical coherence tomography lends itself well to detection of acoustic waves. Furthermore, swept source optical coherence tomography has demonstrated sensitivity to megahertz frequency acoustic waves by monitoring changes in optical pathlength as a function of wavelength during the sweep. Recent advances in swept source laser technology have improved the ability to detect and isolate ultrasound acoustic signals. Swept source optical coherence tomography has ultimate sensitivity to acoustic waves defined by the shot-noise limit of the imaging system and can achieve theoretical sensitivities as low as ~10 pm from ultrasonic waves from an ideal reflector. Measurement of ultrasound via optical coherence tomography is complicated by tissue dispersion, signal crosstalk between imaging depths, non-ideal tissue reflectors, and laser stability. Here, we present and compare methods for extracting ultrasound signals from OCT datasets based on techniques for demodulation of frequency modulated signals. The overall sensitivity, signal to noise ratio, and signal isolation are compared between methods of quadrature demodulation, Hilbert transform based signal extraction, and phase locked loops, and future directions of this technology are discussed.

Thermoacoustic imaging (TAI) combines microwave energy's penetration depth with ultrasound's spatial resolution for medical imaging. Denoising is crucial in TAI to refine low energy thermoacoustic signals, overcoming depth limitations and improving imaging precision. We utilized the MI-TAT system to capture signals from different phantoms and gather data for training and validation. Our architectural approach harnesses both time and spatial signal features, enabling the design of an advanced deep-learning model.

Lymphedema is tissue swelling caused by dysfunction of the lymphatic drainage system and is a common side effect after surgery and radiotherapy for malignant tumors. Preoperative lymphatic mapping is desired for lymphedema surgery. To date, several groups have applied photoacoustic (PA) imaging (PAI) using indocyanine green (ICG) to lymphedema patients for this purpose. PAI of lymphatic vessels is also useful for basic research using small animals, such as evaluating therapeutic techniques and analyzing tissue degeneration. To this end, we developed a PAI with a high-frequency linear array sensor that can visualize small lymph vessels in small animals. Furthermore, we have developed a PA microscopy (PAM) that can obtain cell-resolution images of surface tissues. PAI and PAM were tested by imaging lymphatic vessels in rabbit ears with lymphedema. PAI clearly visualized lymphatic vessels parallel to blood vessels. PAM was able to visualize ICG flowing back into the superficial lymph capillaries and dermis due to dermal backflow that occurs in lymphedema.

We introduce a compact, non-contact multimodal imaging platform that integrates ultrasound (US) imaging, inclusive of photoacoustic (PA) detection, with optical coherence tomography (OCT). This integration is achieved through a novel virtual acoustic detector array (VADA) technique for all-optical US sensing, utilizing the temporal and spatial resolving capabilities of swept-source optical interferometry. The technique extracts US signals from the phase time evolution of a swept-source OCT's spectral sweep. It enables the virtual construction of the VADA along both lateral and depth directions on the imaging target for non-contact detection of acoustic waves from surrounding US sources. The platform's high-speed scanning (MHz OCT A-scan rate) and ultra-sensitive phase detection (nm displacement sensitivity) allow for the customization of the spatial density of the VADA and the collection of wideband acoustic signals, which are essential for the reconstruction of US images. In our pilot study, we successfully demonstrated the feasibility of this technique. We used a conventional US transducer as an acoustic source. The acoustic field distribution within the imaging target and the morphology and position of the piezoelectric layer were successfully reconstructed, which is based on US waveforms obtained from the VADA.

Photoacoustic imaging offers high spatial resolution, imaging depth, and molecular information, emerging as a promising biomedical imaging modality. In particular, when using exogenous contrast, the advantages of photoacoustic imaging can be more effectively utilized in preclinical and clinical studies. We provide a novel approach to screen and identify efficient photoacoustic performance as contrast agents of the metals. To accomplish this, we introduce a novel figure of merit that quantifies the potential performance of contrast agents. As a result of the quantification, we discover that Ti nanodiscs outperform Pt nanodiscs in terms of photoacoustic ability, which shows a similar level to Au nanodiscs. We compare these results by performing a photoacoustic phantom imaging experiment. The photoacoustic performance of the three materials is compared by comparing the signal intensity of the materials measured on the photoacoustic image for various wavelengths. The imaging results further support our findings, demonstrating the superior performance of Ti nanodiscs as contrast agents.

Needle insertion is a vital procedure in both clinical diagnosis and therapeutical treatment. To ensure the accurate placement of needle, ultrasound (US) imaging is generally used to guide the needle insertion. However, due to depthdependent attenuation and angular dependency, US imaging always face the challenge in consistently and precisely visualizing the needle, necessitating the development of reliable methods to track the needle. Deep learning, an advanced tool that has proven effective and efficient in addressing imaging challenges, has shown promise in enhancing needle visibility in US images. But the existing approaches often rely on manual annotation or simulated data as ground truth, leading to heavy human workload and bias or difficulties in generalizing to real US images. Recently, photoacoustic (PA) imaging has shown the capability of high-contrast needle visualization. In this study, we explore the potential of PA imaging as reliable ground truth for training deep learning networks, eliminating the need for expert annotation. Our network, trained on ex vivo image datasets, demonstrated the abilities of precise needle localization in US images. This research represents a significant advancement in the application of deep learning and PA imaging in clinical settings, with the potential to enhance the accuracy and safety of needle-based procedures.

Colorectal cancer claimed nearly 1 million lives in 2022. According to World Health Organization, the prevalence and mortality rates of this disease are on the rise in the world, mainly due to an unhealthy diet, low in fiber. Recently, neoadjuvant therapy, which is a combination of chemo- and radiotherapy, has gained more attention over radical surgery for responsive patients. This is because if the patient responds excellently to neoadjuvant therapy, through monitoring, radical surgery could be avoided, saving the patient’s organ and bettering their quality of life. However, presently, monitoring is limited using MRI and colonoscopy, making decisions about the patient’s status difficult after therapy. New modalities such as photoacoustic (PA) imaging may help improve the monitoring by distinguishing between malignant and healthy or fibrotic tissue. In this work, we carry out a preliminary study on the use of LED-based PA imaging on colorectal samples ex vivo, in a preclinical setting. Our analysis shows that the PA image intensity is lower in the malignant tissue than the fatty tissue. However, our results are inconclusive about the difference between tumor and healthy colorectal tissue due to limited data and the effect of depth on the PA signal. For future research, collecting more data and the use of a tunable laser source are recommended.

Continuous monitoring of total hemoglobin (THb) for the patients suffering from hematological or non-hematological diseases, snake bite, going through surgeries etc., finds immense clinical importance since Hb transports oxygen to the living tissues while being encapsulated within a red blood cell (RBC). Several techniques based on the electrical or chemical and or optical measurements have already been developed to determine total hemoglogin (THb) in blood. Many of them are clinically practiced. But, the very first step of processing which is common to all of them requires extraction of blood sample through venipuncture. That process is invasive, needs trained professional. A non-invasive, real-time, diagnostic tool is rather preferred especially for repeated testing. Having above two capabilities, a photoacoustic (PA) system with near-infrared illumination was previously proposed for THb determination. But a recent study on hemolysis monitoring with a low-cost NIR-PA system suggests that THb determination through NIR-PA requires apriori knowledge of hemolysis status of the sample. The question therefore remains if PA is at all suitable for this purpose. Additionally, in order to become more accessible to the patients, any such device must be portable, ergonomic and cost effective enough, which, in PA, rejects the use of bulky, expensive Nd:YAG or dye LASERs, leaving the power of the optical source limited. The present study reports a high-power LED based low-cost PA system with blue (456.5 nm) illumination that enables PA to determine total hemoglobin in blood irrespective of hemolysis status.

Transparent ultrasound transducers (TUTs) have gained significant traction in the fields of photoacoustic (PA) and ultrasound (US) applications. TUTs possess the unique capability to transmit and receive ultrasound waves while maintaining optical transparency. As a result, TUTs simplify the PA imaging process and facilitate seamless integration with other optical imaging modalities. However, the limited sensitivity of TUTs has been a primary challenge hampering their widespread adoption in PA setups. One often overlooked factor contributing to this limitation is the electrical impedance mismatch between the transducer and the data acquisition system. Here, we designed and studied the utilization of a filter-based electrical impedance matching (EIM) circuits to enhance the sensitivity of lithium niobate-based TUTs. In our approach, the fabricated TUTs incorporate a quarter-wavelength Parylene-C matching layer and epoxy as a backing layer. Our results demonstrate that the integration of the EIM circuit yields substantial improvements in the sensitivity, bandwidth and axial resolution of both pulse-echo US signals and PA signals. PA imaging of leaf phantoms were compared with and without EIMs to further showcase the performance enhancements that can be achieved by integrating EIM with TUTs. Overall, these results demonstrate that EIM circuits can be employed to improve the performance of TUTs.

Acousto-optic imaging of absorbing objects embedded in highly scattering media remains challenging since the detectable signal which is suitable for image reconstruction is weak. Yet, significant improvements were made possible by the joint use of (i) a newly developed and characterized high peak-power laser diode source and (ii) the Fourier Transform Acousto-Optic Imaging (FT-AOI) technique. Albeit FT-AOI was previously reported and demonstrated state-of-the-art performances in real-time imaging, the technique was nevertheless only remonstrated for low-scattering phantoms. Here, we highlight that using a 9 W high-peak power, while maintaining an average power below 1W, proved the ability of the overall setup to probe highly scattering media at video frame rate.

Photoacoustic microscopy (PAM) is a high-resolution imaging modality of photoacoustic imaging. Laser light interacts differently with the tissue based on its wavelength. Typically, in PAM systems, multiple wavelengths are employed to extract functional and molecular information from the tissue by targeting different absorbers like oxyhemoglobin, deoxyhemoglobin, lipids, melanin, water etc. This is done either by using multiple lasers of different wavelengths or more recently with one laser that produces different wavelengths through stimulated Raman scattering (SRS) phenomena induced in polarization maintaining single mode fibers (PM-SMF). However existing multispectral PAM (MS-PAM) systems are slow. This is because these systems utilize mechanical scanning where transducer is held on x-y stage and mechanical moved from one point to the other. Here, we describe the development of a laser scanning multispectral PAM (LS-MS-PAM), where a unique spiral optical scanning is employed, and transducer is placed in a fixed position. This makes the multispectral PAM system faster along with functional and molecular imaging capability. With the developed system, oxygen saturation, hemoglobin concentration, blood flow and vascular diameter measurement can be acquired with a frame rate of less than 1 second. Phantom study and animal study were performed to validate fast multispectral imaging characteristics of our developed system.

Skin diseases are a significant health concern, necessitating early and accurate diagnosis for improved patient outcomes. Non-invasive techniques have been explored to reduce patient discomfort and complications, since they eliminate the need for surgical interventions and tissue sampling. One of those modalities is ultrasound imaging which allows the visualization of skin structures, like the layers, providing crucial anatomical information without an intervention. Photoacoustic imaging, another non-invasive modality, utilizes light to produce ultrasound waves within the tissue, collecting functional information based on absorption properties, like vasculature distribution. In this study, we present a high frequency linear array tumor margin assessment system designed for skin imaging, utilizing a 44 MHz central frequency transducer with a bandwidth between 32 and 56 MHz, and a tunable laser with a repetition rate of 10 Hz and range from 690 to 950 nm. The system was characterized in both photoacoustic and ultrasound modes using wire phantoms. Using a 3D stage, the photoacoustic/ultrasound probe scanned the area of interest to obtain volumetric images in both modalities and get a better visualization of the tissue. In addition, the tunable laser's capability for multispectral analysis can be used for the improvement of the system, complementing anatomical information, and facilitating comprehensive assessment of skin abnormalities, particularly in tumor margin evaluation. The developed system holds great promise in enhancing tumor margin assessment, providing a powerful and non-invasive tool for skin imaging with the potential for broad clinical applications.

This paper introduces an innovative approach to enhance the circular scanning-based photoacoustic tomography (CSPAT) system for photoacoustic imaging. The proposed method involves using a circular detection geometry with three carefully placed ultrasound transducers (USTs). By strategically selecting the angles of the USTs, the field of view (FOV) is expanded, and tangential resolution is improved without requiring additional imaging time. The new CS-PAT system demonstrates practicality and convenience, providing higher signal-to-noise ratio and better structural similarity compared to the conventional system. This approach overcomes the limitations of the limited size of USTs and widens the application potential of CS-PAT in a straightforward and efficient manner.

During medical investigations of the head, the presence of skull bone constitutes a major challenge in generating accurate diagnostics. Photoacoustic imaging technology, with its functional imaging capabilities, has demonstrated the potential for brain imaging at low cost and with low maintenance requirements. While photoacoustic signal generation in deep tissue and through the skull has been demonstrated, an effective method of aberration correction for transcranial photoacoustic imaging has not yet been developed. In this study, we present a method based on enfolded deep learning algorithms that accurately compensates for acoustic aberrations caused by the head layers, allowing hemorrhage detection. Using a realistic simulated framework, a large quantity of aberrated images is acquired, reconstructed, and corrected.

Multispectral photoacoustic tomography (sPAT) is a technique within photoacoustic imaging that aims to separate different types of chromophores using multiwavelength measurements. In this study, we conducted sPAT simulations for circular scanning detection setup using the k-wave toolbox, focusing on two dominant absorbers in biological tissue: HbO2 and HbR. A phantom with three different concentrations (100%, 70%, and 30%) were simulated for five pairs of wavelengths (700nm,900nm; 756nm,900nm; 700nm,796nm; 756nm,796nm and 900nm,796nm, respectively). Subsequently, supervised unmixing (Spectral Fitting) and unsupervised unmixing algorithms, namely Principal Component Analysis (PCA), Independent Component Analysis (ICA), and non-negative matrix factorization (NNMF), were applied. The unmixing results were then quantitatively compared with the unmixed results to evaluate their performance in terms of recovering the concentration of the chromophores into the simulation environment. The simulation study indicated that the unsupervised based unmixing algorithm such as ICA performance was superior to others in unmixing them with two wavelengths pair.

Flexible transducer arrays have the potential to conform to various organ shapes and sizes during photoacoustic image-guided interventions. However, incorrect sound speeds and array shapes can interfere with photoacoustic target localization and degrade image quality. We propose a metric to estimate the sound speed surrounding a target and the radii of curvature of flexible arrays with approximately concave shapes. The metric is defined as the maximum lag-one spatial coherence of the time-delayed, zero-mean channel data received from a region of interest surrounding a photoacoustic target (which we abbreviate as mLOC). Performance is demonstrated with simulated and experimental phantom data. Three photoacoustic targets were simulated in k-Wave with 1540 m/s medium sound speed, and photoacoustic signals were received by a transducer with a flat shape and an 81.3 mm radius of curvature. To acquire experimental photoacoustic data with the flexible array placed on flat and curved surfaces, an optical fiber paired with a hollow metal needle was inserted into an 83-mm-radius hemispherical plastisol phantom at three locations. When implementing beamforming time delays to calculate mLOC, the associated sound speed and radii of curvature ranged 1080-2000 m/s and 60-120 mm, respectively. The sound speed and array curvature estimated by the maximized mLOC were 1540 m/s and 81 mm, respectively, in simulation, resulting in accuracies of 100% and 99.63%, respectively. The sound speed in the phantom was empirically estimated by the maximum of mLOC as 1543 m/s, which led to the array curvature estimation of 85 mm and the corresponding accuracy of 97.59%. Results demonstrate the potential of mLOC to approximate sound speeds and array radii when these variables are unknown in future flexible array imaging scenarios.

Medical ultrasound is a diagnostic and treatment method that employs ultrasonic signals as carriers of information. It boasts a broad range of applications, including the visualization of internal bodily structures, the detection of underlying diseases and cellular stimulation. Presently, the most employed ultrasound transducer relies on the principles of piezoelectricity. Nonetheless, piezoelectric transducers may encounter limitations in terms of bandwidth. However, the ultrasound generated by laser through the optoacoustic effect has a large bandwidth, and by using high power laser diodes we can reduce the size of the transducer, enabling endoscopy ultrasound applications. We have designed and implemented a portable endoscopic ultrasonic generator using high power diode lasers and ultrasound generating bi-composites (candle soot-PDMS). We have reduced the size of the ultrasound generating system (laser diode, laser driver and composite) to a width of 5.5 mm making it suitable for an endoscopy application. We have designed and manufactured the control instrumentation of the ultrasonic generation system in a single small instrument (generation of electrical pulses and voltage control). The ultrasonic generation system was characterized, obtaining ultrasonic signals with a bandwidth of 40 MHz, pressures of 264.29 kPa and an optoacoustic conversion efficiency of 2.5x10^-3 Pa/(W/m²).

This work explores the use of quantitative photoacoustic microscopy to map the concentrations of methylene blue in agar phantoms. Our investigation covers wavelengths from 700 nm to 750 nm and looks at concentrations of 5 mM, 10 mM, and 15 mM. Through a detailed investigation of the photoacoustic response, the multi-wavelength method provides information about molecule distributions. Our results highlight this methodology’s potential for accurate concentration mapping, with prospective applications in the clinical and biological areas. By giving a systematic investigation of methylene blue concentrations, this work adds to the growing area of photoacoustic microscopy and highlights the value and adaptability of multi-wavelength imaging for molecular mapping. The findings could lead to improved molecular imaging and have consequences for researchers and practitioners in the fields of biomedical optics, spectroscopy, and photoacoustic imaging.

Photoacoustic imaging (PAI) is now a very promising medical imaging technology that provides structural, functional, and molecular information based on the optical absorption of endogenous or exogenous contrast agents. A conventional PAI system using an array of ultrasonic transducers to detect photoacoustic (PA) signals. Each element of the transducer requires an amplifier to enhance the detected signal which makes it bulky. To overcome this problem, we introduced optical sensor alternative to piezoelectric ultrasound detector in PA signal detection. This study aims to illustrate the entire process of PA signal generation and its detection using an optical sensor using Finite Element software (COMSOL). Fiber Bragg grating (FBG) is one of the optical sensors that may be utilized in some applications in place of acoustic ones. FBG provides the change in acoustic pressure as a function of the shift of Bragg wavelength. Our study demonstrated that FBG achieves to detect photoacoustic (PA) signals as an alternative of US transducer, with superior performance in terms of sensitivity, and being more light-weight, flexible, and cost-effective. This implies that these technologically novel qualities hold promise for the use of FBG (either single or multiple units on a single fiber) as an acoustic sensor in PAI systems in place of the conventional piezoelectric-based bulk array transducer. An intensity-based demodulation was performed to extract the US signal. The preliminary study demonstrates that the integration of FBG in PA imaging modality offers potential as a future (imaging) technology both for biological studies and clinical applications.