This PDF file contains the front matter associated with SPIE Proceedings Volume 11642 including the Title Page, Copyright information, and Table of Contents.

The impact of optical absorption in the spacer layer of Fabry-Pérot (FP) ultrasound sensors is discussed. It is shown that absorption significantly limits the sensitivity of planoconcave microresonators (PCMRs; FP type sensors with a planoconcave geometry). Using materials of lower absorption or selecting sensor interrogation wavelengths to avoid absorption peaks in existing spacer materials could provide at least an order of magnitude higher sensitivity, paving the way to multi-cm deep-tissue PA imaging applications.

In this presentation, we introduce the initial patient imaging results of our dual-scan mammoscope system. The goal is to verify whether the system can differentiate malignant and healthy cases. We have imaged 38 patients with various cancer types and compared results of tumor breast with healthy breast for each patient. At 95% confidence level, we found that tumor breasts exhibit higher average photoacoustic signal amplitude, higher vessel signal amplitude, and stronger variation in background signals. We could also visualize different vascular features in and around the tumor region for different subtypes of tumors. Our preliminary results indicate that photoacoustic technology has a high potential for breast imaging.

Development of a number of diseases is accompanied by changes in the blood vessels’ structure and the investigation of tissue vascular pattern remains one of the most essential problems in experimental and clinical medicine. Hybrid methods of optoacoustic (OA) imaging enable label-free optical-contrast angiography at optical penetration depths with ultrasonic resolution. We used OA to study vascular network of experimental tumor during growth and after treatment as well as to study the dynamics of blood content of human skin during functional tests. Optoacoustic angiography was performed using raster-scan system in reflection mode with 532 nm laser source and wideband PVDF detector. The sensitivity of the system allowed to visualize 50 µm blood vessels at up to 2.1 mm depth. Minimally detected diameter of blood vessel located at the surface of a soft tissue was 15 µm. Imaging of colon tumor models CT26 and HT-29 revealed peculiarities of vascular system development. Irradiation-induced increase of small tumor vessels segments number and parallel decrease in the number of large hemoglobin-containing structures were demonstrated. The fraction of blood-filled vessels of the human skin was assessed during cuff occlusion and temporarily filling with blood became clearly visible on OA images. To study the effects of local mechanical compression on human skin vasculature we varied external pressure and revealed the gradual drop in OA signal from blood vessels. We demonstrated the possibilities of raster-scan angiography for in vivo analysis of vessels structure, for monitoring of neoangiogenesis and for dynamical investigation of blood content under external actions.

Visualizing whole-body dynamics across entire living organisms is crucial for understanding complex biology, disease progression as well as evaluating efficacy of new drugs and therapies. Existing small animal functional and molecular imaging modalities either suffer from low spatial and temporal resolution, limited penetration depth or poor contrast. In this work, we present flash scanning volumetric optoacoustic tomography (fSVOT) imaging system that enables the acquisition speeds required for visualizing fast kinetics and biodistribution of optical contrast agents across whole mice. fSVOT can render images of intricate vascular and organ anatomy with rich contrast by capitalizing on the large angular coverage of a spherical matrix array transducer rapidly scanned around the mouse. Volumetric (three-dimensional) images with 200 µm resolution can be acquired within 45 seconds, which corresponds to an imaging speed gain of an order of magnitude with respect to existing state-of-the-art modalities offering comparable resolution performance. We demonstrate volumetric tracking and quantification of gold nanorod kinetics and their differential uptake across the spleen, liver and kidneys. Overall, fSVOT offers unprecedented capabilities for multi-scale imaging of pharmacokinetics and bio-distribution of agents with high contrast, resolution and image acquisition speed.

Multi-modal imaging technique has significantly spotlighted since it can provide a variety of information by combining the complementary merits of several single-modal imaging. In particular, in order to compensate for each shortcoming and improve image quality, an integrated optical and ultrasonic imaging system is being actively researched. However, the non-transparency of the ultrasound transducer made it difficult to integrate the optical and ultrasound imaging system. In previous study, we introduced the transparent ultrasound transducer (TUT) and dual-modal photoacoustic imaging (PAI)/ultrasound imaging (USI) system using the TUT. In this study, we present the multi-modal imaging system integrated with PA, US and optical coherence tomography (OCT). OCT has the advantage of acquiring anatomical information at optical resolution under subsurface and transparent media. To explore the usefulness of the multi-modal imaging system, we have successfully performed in vivo animal experiments: 1) eye imaging experiments and 2) subcutaneous melanoma imaging. In PAI, blood vessels and melanoma are clearly visualized. In OCT, the morphological information in shallow depth are observed in detail. In USI, the melanoma boundary and surrounding tissues are clearly confirmed. These results show that TUT based multi-modal imaging system can serve as a comprehensive in various applications.

Optoacoustic tomography (OAT) and magnetic resonance imaging (MRI) are both endorsed with powerful imaging capabilities. Yet, their seamless integration into a hybrid system may additionally offer highly synergistic and complementary information for concurrent anatomical and functional imaging of living organisms. Herein, we investigate on the possibility of concurrent OAT-MRI image acquisition and provide experimental validation in phantom studies. Simultaneous recording was enabled by designing an MR-compatible copper-shielded spherical ultrasound array that provided real-time volumetric OAT imaging and could be safely introduced into a high-field 9.4 T MRI scanner. The interference between the two modalities was evaluated under commonly employed FLASH and EPI sequences. Phantom experiments revealed that the OAT probe caused minimal distortion in the MRI images, while synchronization of the laser and the MRI pulse sequences enabled defining artifact-free OAT acquisition windows. Good dynamic OAT contrast from superparamagnetic iron oxide nanoparticles, a widely used agent for MRI contrast enhancement, was also observed. The hybrid OAT-MRI system thus provides an excellent platform for cross-validating functional readings of both modalities. Overall, this initial study serves to establish the technical feasibility of developing hybrid OAT-MRI system for biomedical research.

Optoacoustic tomography (OAT) conventionally relies on curved detectors to maximize the sensitivity and lateral resolution. Here, we present an alternative paradigm to OAT that creates a virtual detector array with a high angular acceptance and sensitivity by using coded acoustic apertures and a flat piezoelectric detector. Using this approach, we created a 2D virtual array with 1763 elements and performed OAT of a complex 3D object with approximate axial and lateral resolutions of 150 μm and 500 μm in a flat detection geometry, demonstrating an image quality comparable to the one achieved with curved detection geometries.

We introduce a three-dimensional photoacoustic computed tomography (3D-PACT) system with unparalleled imaging depth, clarity, and speed, and demonstrate that the imaged structural and functional optical contrast provide a unique tool for preclinical research and an appealing prototype for clinical translation. 3D-PACT allows for multipurpose imaging of biological tissues ranging from the rodent brain to the human breast. In the rat brain, we visualized whole brain vasculatures, oxygenation dynamics, intrinsic functional connectivity, and electrical-stimulation-induced hemodynamics. In the human breast, an in vivo imaging depth of 4 cm has been achieved by scanning the breast within a single breath hold of 10 seconds. 3D-PACT holds a high reliability to reproducibly generate detailed images with a contrast similar to that provided by contrast enhanced magnetic resonance imaging, yet with higher spatiotemporal resolution and without using exogenous contrast agents.

Photoacoustic computed tomography (PACT) has been extensively explored in animal brains but never in the human brain due to its limited field of view (FOV), imaging speed, penetration depth, and sensitivity. Here, we present the first application of PACT in functional human brain imaging. Motor and language functional tasks were employed and performed by post-hemicraniectomy patients. The brain activities were recorded at a 10-cm–diameter FOV, 350-μm/2-s spatiotemporal resolution, and ~2-cm penetration depth using a newly developed massively parallel three-dimensional PACT system. Quantitative validation of the PACT results against 7 Tesla MRI revealed comparable angiographic structures and functional activation in the same FOV. The obtained results represent a critical step toward broader-scope human brain imaging applications using PACT technology.

Photoacoustic imaging holds potential in diagnosis and treatment monitoring of breast cancer, but clinical translation of this technology has often been hindered by bulky and expensive excitation sources. In this work, the potential of a portable, dual-mode multispectral LED-based photoacoustic and ultrasound system (AcousticX) in breast imaging is investigated for the first time. The AcousticX system comprises a linear array ultrasound probe (7 MHz) and two dualwavelength LED arrays (750/850 nm) placed on both sides of the probe. Two experiments were performed to investigate the potential of the system in imaging the breast. In the first instance, interleaved photoacoustic and ultrasound imaging was performed on a semi-anthropomorphic multi-layered 3D breast phantom with possibility to tune oxygen saturation in blood vessel structures. In the second experiment, vasculature of a healthy human breast was imaged in vivo. Skin and multiple vascular features along with its relative oxygen saturation are visualized using photoacoustic imaging and the ultrasound images offered valuable structural information including fat, fibroglandular tissue and pectoral muscles. In human in vivo experiments, we achieved an imaging depth of around 1.7 cm at a display frame rate of 10 Hz, the highest in vivo imaging depth reported in LED-based photoacoustic imaging using a 7 MHz probe. With the capability of providing real-time structural and functional information, AcousticX holds clinical translation potential in non-invasive breast imaging.

Multimodal photoacoustic microscopy (PAM) and optical coherence tomography (OCT) have been developed for visualization of different retinal tissues such as retinal pigment endothelium (RPE), retinal and choroidal vessels, and retinal neovascularization (RNV) with promising results. However, one limitation of these studies is that it is hard to distinguish abnormal and healthy retinal vessels. To address such limitations, this study focused on the development of novel ultrapure chain-like cluster gold nanoparticles (CGNPs) to boost the PAM and OCT image contrast for enhanced visualization of RNV. CGNPs have a redshift plasmonic absorption peak at 650 nm where blood vessels generate a very low intrinsic photoacoustic signal, resulting in enhanced signal-to-noise ratio, and thus allowing for distinguishing RNV. Toxicity of CGNPs was tested on three different cells: bovine retinal endothelial cells (BRECs), HeLa cells, and brain endothelial cells (b.End3). The ability of CGNPs for contrast

Development of a noninvasive glucose meter is of great importance for hundreds of millions of diabetics to dramatically improve their lifestyle and quality of life. We have successfully developed an ultrasound-modulated optical sensing system, consisting of an infrared laser and a single-element ultrasound transducer, for noninvasive glucose measurement. Using focused ultrasound as an optical modulator, strong optical absorption contrast at high spatial resolution could be achieved in a scattering medium. Modulation efficiency was improved by 2.5 times using ultrasound bursts. Further, the proposed system successfully measured glucose concentration in a tissue-mimicking phantom with 26.6% accuracy.

Undoubtedly, photoacoustic tomography (PAT) is a promising technique unveiling physiological information in the biomedical imaging field. However, targeting optically/acoustically non-uniform biological tissues and receiving signals with finite aperture/band-limited ultrasonic transducers have been practical limitations that hinder the clinical application of PAT. This study closely analyzes the effects of four main limiting factors named limited view (LV), limited bandwidth (LB), lossy medium (LM), and heterogeneous medium (HM) and compared the adverse effects given from the four factors. First, radiofrequency (RF) data was generated assuming a realistic situation using k-Wave, a MATLAB-based wave propagation-simulating tool. A single 4 mm-sized circular target was used, and physical parameters of the detector array were designed referring to a commercial linear probe (GE9LD, General Electric). Supposing double-aperture, full-band signal reception from the lossless, homogeneous medium as a baseline, RF data were acquired under a successive accumulation of the limiting factors in order of LV, LB, LM, and HM. Second, the obtained RF datasets were reconstructed with 7 representative beamforming algorithms; delay and sum (DAS), delay multiply and sum, pth root DAS, minimum variance, filtered back-projection, frequency-domain reconstruction, and time reversal. Among obtained images, common graphical features for each limiting factor were specified. Lastly, we quantitatively assessed the similarity between the image and the actual target with peak signal-to-noise ratio and structural similarity as performance indices. As a result, the characteristic features from each limiting factor were commonly identified on the reconstructed image, and the performance indices sequentially degraded following the sequence of practical conditions.

Blood flow can be a crucial diagnostic parameter for different pathologies. Photoacoustic imaging, unlike other imaging modalities, could play a role in enhancing blood flow measurements in smaller vessels without resorting to contrast agents. In this study, we show that differential phase analysis on photoacoustic signals acquired at a high frame rate (2 kHz) generated from flowing absorbers provides a good estimate of their velocities. Flow phantoms based on diluted Indian ink solutions with preset velocities ranging between 6 and 19 mm/s were imaged and profiled based on this method.

We report a novel photoacoustic (PA) scoring method for the risk stratification of thyroid nodules, which is combination of the American Thyroid Association (ATA) and PA malignancy probability. We performed multi-spectral PA imaging and multi-parametric PA analysis for thyroid cancer patients (23 malignancy and 29 benign cases). Initial multi-parametric PA analysis showed that malignancy of the thyroid nodules can be diagnosed with a 78% sensitivity and 93% specificity. Moreover, our novel score called ATAP improved the sensitivity to 83% while maintaining the specificity. The results suggest that the ATAP may help physicians examine thyroid nodules, thus reducing unnecessary biopsies.

Ultraviolet photoacoustic microscopy (UV-PAM) provides label-free imaging of cell nuclei with the superior optical absorption of DNAs and RNAs. UV-PAM does not require any additional staining process to visualize the structures of tissues and cells. However, conventional UV-PAM is limited in imaging speed to be used in real pre-clinical and clinical situations. To overcome this limitation, we developed an UV-PAM adopting a high-speed scanning module. We demonstrated the applicability of the system as an intraoperative surgical margin assessment tool by imaging formalinfixed paraffine-embedded (FFPE) sections of human colon cancer tissues and comparing these results to conventional optical microscopic images. Additionally, three more types of cancerous tissue such as liver, uterus, and kidney were photoacoustically examined. The imaging results successfully showed the characteristic features of cancerous and normal tissues, allowing rapid diagnosis of cancer. UV-PAM has achieved sufficient spatial resolution to distinguish the individual nuclei in human tissue, but it is challenging to resolve the closely adjacent nuclei. Therefore, we applied tissue expansion technology, which enables nanoscale imaging of subcellular components beyond the resolution of optical microscopy, to our developed system. A mouse brain section was physically expanded by hydrogel-tissue hybridization, and consequently distances between cell nuclei in the tissue increased. We could separate densely distributed nuclei in the hippocampus of mouse brain better compared to conventional UV-PAM. In short, we developed a novel PA imaging system with the enhanced temporal and spatial resolution by combining fast scanning modality and tissue expansion technology with UV-PAM.

X-ray induced acoustic computed tomography (XACT) is an emerging biomedical imaging technique combining X-ray absorption contrast with high ultrasound resolution. In this study, we showed the potential of in vivo XACT imaging with a conventional X-ray contrast agent. The developed software based on a graphics processor unit reconstructed the 3D volumetric XACT images. We successfully acquired the 3D XACT image of the conventional X-ray contrast agent in biological tissues.

At present, there is no reliable non-invasive imaging modality accepted as the routine method to assess response to neoadjuvant chemotherapy (NAC). Using photoacoustic computed tomography (PACT), we imaged breast cancer patients at three time points: before, during, and after NAC. We measured the tumor size, blood vascular density, and irregularity in the distribution and morphology of the blood vessels on PACT. We used these measurements to accurately identify response to NAC as confirmed by the histopathological diagnosis. We demonstrate PACT’s near-term potential as a diagnostic tool for assessing breast cancer response to systemic treatment by non-invasively measuring the changes in cancer-associated angiogenesis.

We demonstrate an agent-free multi-structural peripheral angiography technique based on the volumetric photoacoustic (PA) and ultrasound (US) images. The volumetric images are obtained by stacking B-mode PA/US images along the elevational direction using a motorized scanner. Three structural features such as skin, bone, and vasculature are extracted from the volumetric US image and combined with the PA microvasculature image to provide a multi-structural vascular image of the foot. For quantitative PA imaging, we have tested the reliability of the PA images. The method can be used to provide a comprehensive anatomic and functional analysis of the extremity.

Skin aging caused by ultraviolet light exposure is one of the serious problems from the viewpoint of beauty and healthcare. This is because ultraviolet light can cause age spot, wrinkles, at the worst case, skin cancer and so on. To evaluate skin aging, various modalities are being used, such as histopathological diagnosis, optical imaging (e.g. optical coherence tomography (OCT), second harmonic tomography (SHG)) and ultrasound examination (B-mode imaging). However, they have disadvantages in terms of invasiveness, penetration depth and tissue specificity, respectively. To overcome these defects, photoacoustic imaging (PAI), a novel modality was used in this work. This modality can portray differences of tissue characteristics non-invasively. In this work, human skin tissues in various degrees of photoaging (8 subjects, 2 kind of site each) were measured by using acoustic resolution photoacoustic microscopy (AR-PAM) to verify the feasibility of quantitative skin aging evaluation with PA technique. The effects of photoaging progress on the signal intensity were investigated. The results demonstrated that the PA signal from the dermis increases as photoaging progresses. These analyses demonstrate the feasibility of quantitative skin aging evaluation with a PA imaging system.

In recent years, skin aging caused by ultraviolet light exposure has garnered attention in the fields of beauty and health care because photoaging accelerates skin aging. Elastin is closely related to photoaging. In conventional methods for evaluating the elastin degeneration of photoaging skin, Elastica van Gieson staining images of skin section were evaluated using Kligman criteria. However, this diagnosis entails some shortcomings. For example, it is invasive and has no metabolic function. Moreover, its mechanism has not been fully clarified. For this study, photoacoustic imaging was used for evaluating skin photoaging mechanisms with acoustic resolution photoacoustic microscopy (AR-PAM). An ultrasonically focused transducer (50 MHz, 6.7 mm focal length) attached to the imaging head detected photoacoustic waves. Photoacoustic signal distributions of various skin aging sections that were a 25-μm-thick human cheek and buttock skin sections of six types were measured at 20 μm intervals using AR-PAM. This study was conducted to ascertain whether elastin parts are distinguishable from collagen parts in photoacoustic images. A difference was found between the photoacoustic spectrum of elastin and that of the collagen at 420–520 nm wavelengths. To examine the distinguishability between elastin and collagen, the signal intensity ratio of 420/450 nm wavelengths was calculated. The signal intensity ratio of the collagen part is higher than that of the elastin part. These results verified the possibility of discriminating elastin from collagen using multi-wavelength analysis of photoacoustic images.

Rectal adenocarcinoma is a common cancer in the United States. Current standard of care techniques (colonoscopy and MRI) have notable drawbacks and surgeons have aggressively put most patients into surgical intervention. Here we have developed a new handheld co-registered ultrasound and acoustic-resolution photoacoustic endoscope (AR-PAE) to evaluate rectal cancer in vivo. The PAE - convolutional neuron network (PAE-CNN) models were trained, validated, and tested. Hyperparameters of PAE-CNN including convolutional kernel size, max pooling kernel size, convolution layers and fully connected layers which connect to amount of imaging information preserved were carefully tuned to optimize classification performance.

Similar to the parking-assist sensors on modern automobiles, which alert drivers of impending impact to an object, we are developing an auditory photoacoustic-based guidance system to assist with avoidance of impending injuries to ureters during hysterectomy procedures. The contribution described in this paper considers international standards for medical alarms. The system was demonstrated during both open and laparoscopic hysterectomy procedures on two human cadavers. Using methylene blue to enhance ureter contrast, the proximity of a surgical tool tip to the ureter was measured using the visual information provided in photoacoustic images. Distance measurements were then successfully mapped to auditory signals, which increased in auditory frequency as the tool-to-ureter distance decreased to convey surgical tool proximity to the ureter. Fundamental frequencies increased from 150 Hz to 866 Hz for tool-to-ureter distances of 2.47 mm to 5 mm. These results are promising to assist with the avoidance of accidental ureteral injuries during hysterectomy and other procedures that suffer from similar challenges with regard to iatrogenic ureteral injuries.

Currently, post-therapy evaluation of colorectal cancer relies on functional MRI, which does not possess resolution and sensitivity well-suited for the task. Endorectal photoacoustic microscopy offers blood contrast and much higher resolution in imaging residual tumor vasculature. Correlational acoustic resolution photoacoustic doppler flowmetry with amplitude dependent masking was implemented, validated with simulations and phantom experiments, and put into use on colorectal patient scanning data. Doppler velocity map demonstrated potential in highlighting flow in the photoacoustic signal region while removing stationary absorber signals, showing vascular density and distribution in agreement with current understanding of colorectal cancer pathology.

As a newly invented technology, ionizing radiation acoustic imaging (iRAI) provides a potential solution for in vivo dosimetry and real-time online monitoring of radiation beam position during external beam radiotherapy, including both conventional and FLASH radiotherapy. In this study, the dose resolution as low as 1% from a single pulse was achieved, demonstrating a clinically acceptable sensitivity of iRAI in mapping the dose deposition. The relative displacement of the radiation beam with respect to the target tissue can be visualized in real time by our clinically ready iRAI and ultrasound (US) dual-modality imaging system.

This study examines the performance of an all-optical and disposable photoacoustic needle probe for characterizing the aggressiveness of prostate cancer in human samples ex vivo. The needle probe consists of a 800um diameter fiber diffuser and a 200um diameter fiber optics hydrophone. The signals acquired by the needle probes were quantified by photoacoustic spectral analysis and envelop statistic methods. Both methods have differentiated between normal tissues and cancerous tissues (n=30 p<0.005), as well as between indolent and aggressiveness cancer tissues (n=16, p<0.01) with statistical significance.

Assessment of morphology and composition of plaques is paramount to characterize their vulnerability. Spectroscopic photoacoustic imaging (sPAI) can image different components, but unmixing accuracy is subject to a proper wavelength selection. In this study, we analyzed the spectral response of plaque tissue in a broad spectral range and proposed a new wavelength selection method based on endmember determination. The method was validated in human plaque samples and phantoms. Results show that our method improves spectral unmixing, and it is possible to characterize plaque composition using at least as many wavelengths as constituents of interest.

We developed a photoacoustic imaging (PAI) and finite element analysis (FEA) approach for characterizing the biomechanical behaviors of the aqueous veins and perilimbal sclera, and their roles in the regulation of intraocular pressure (IOP). In this study, an optical resolution PAI system captures the 3D architectures of the sclera and the aqueous veins perfused with indocyanine green. FEA computes tissue and vein strain fields. The performance of the PAI-FEA has been validated by tensile test in scleral tissue. The methods have also shown the capability of resolving the strain gradients at the vein-sclera interface during the manipulation of IOP.

In spinal fusion surgeries, it is critical to maintain correct trajectories during the process of creating pedicle holes for screw insertion, in order to avoid accidental bone breaches and screw misplacement, which are characterized by screws placed within surrounding cortical bone rather than the cancellous core of the pedicle. One key difference between these two bone types is the greater porosity of the cancellous bone when compared to the more dense, more compact cortical bone. This work investigates the feasibility of using photoacoustic imaging to differentiate cortical from cancellous bone in the lumbar vertebrae of an intact human cadaver, with the ultimate goal of developing a novel photoacoustic surgical system to prevent breaches. Eleven pedicle cannulations were performed in the lumbar vertebrae of a human cadaver, including six holes in the cancellous core and five partial or complete breaches of surrounding cortical bone. Amplitude-based delay-and-sum (DAS), coherence-based short-lag spatial coherence (SLSC), and locally weighted SLSC (LW-SLSC) beamforming were used to characterize differences in the morphology of photoacoustic signals originating from cancellous and cortical bone. Statistically significant differences between the median of measured areas from cortical and cancellous bone measured 6.61 mm² for -6 dB contours obtained with DAS beamforming and ranged from 2.89 mm² to 42.13 mm² for -10 dB and -15 dB contours obtained with DAS, SLSC, and LW-SLSC beamforming (p<0.001). In addition, coherence-based photoacoustic imaging enabled localization of the tip of the optical fiber that was inserted into each prepared pedicle hole. Therefore, both DAS and SLSC beamforming has the potential to synergystically detect the tip of surgical tools and differentiate between signals originating from cortical and cancellous bone. These results are promising for surgical guidance within the desired cancellous core of the pedicle and away from the surrounding cortical bone, in order to avoid costly and painful bone breaches during surgery.

A new concept to achieve ultrasound-mediated hyperthermia (USHT) with the guidance of X-ray-induced radiation acoustic imaging (xRAI) is proposed. During radiation therapy of cancer patients, the received acoustic signals for xRAI can be used to correct the aberration caused by inhomogeneous acoustic property of human skull and provide guidance for focused ultrasound to achieve USHT with the same ultrasound array at the X-ray dose deposition area. To prove this concept, simulations with a human head model were made for both point targets and a tumor volume. The focused acoustic patterns with and without xRAI-based aberration correction were compared. The feasibility of this xRAI-guided USHT concept was further demonstrated by experimental studies using a human skull.

We report a handheld multi-parametric photoacoustic microscopy system for functional and oxygen-metabolic imaging of the human skin microvasculature. With the high spatiotemporal resolution (3 μm and 10-Hz frame rate), the traverse of single red blood cells through the capillary can be visualized, from which the flow speed can be quantified. Furthermore, the multi-parametric measurement enables comprehensive quantification of the oxygen saturation and release in individual microvessels. The utility of this new technique has been demonstrated by studying the microvascular reactivity in humans.

Full-ring ultrasonic transducer array is widely used in photoacoustic computed tomography (PACT) due to its high inplane resolution and full-view fidelity. Image in PACT is often contaminated by spatial aliasing, which has not been studied in detail for full-ring geometry. In this research, using spatiotemporal analysis, we clarified the sources of spatial aliasing. Based this clarification, we demonstrated that the combination of spatial interpolation and temporal filtering can effectively mitigate artifacts caused by aliasing in image reconstruction and spatial sampling. We validated our theory using numerical simulations and in vivo experiments.

The limited view of a planar detector array results in artefacts in the reconstructed images. To address this, iterative image reconstruction methods have been proposed. However, there remains a need for a rigorous assessment of their performance in terms of artefact reduction, small structure detection, spatial resolution and robustness to noise. Additionally, an understanding of the impact of regularisation parameters on image fidelity and SNR as a function of the target geometry and instrument noise is required. The aim of this study is to explore these factors and advance the practical application of iterative reconstruction methods for in vivo images acquired using a planar detection geometry.

Photoacoustic tomography (PAT) reconstruction with linear transducer arrays suffers from limited view artifacts, which impairs the reconstruction accuracy. Here, we introduce a modified Tikhonov regularization method to include vascular map obtained by Ultrasound localized microscopy (ULM) as a spatial prior in PAT reconstruction. We suggest an approach based on L-curve and Pearson correlation map to guide the selection of optimal regularization parameters. Simulation results suggest that spatial prior-based Tikhonov regularization can effectively address the limited view artifacts of PAT reconstruction with linear transducer arrays, paving the way of integrating PAT with ULM to enhance reconstruction accuracy in limited-view PAT.

Among clinical photoacoustic and ultrasound beamforming (BF) techniques, a nonlinear p-th root delay and sum (NL-p-DAS) exhibits better contrast and resolution than conventional delay-and-sum. However, despite its advantages, signal loss and grainy speckles often degrade image quality by signal deformation. Thus, we proposed a new nonlinear BF algorithm called nonlinear p-th root spectral magnitude scaling (NL-p-SMS), which scales the signal in the spectral domain instead of the temporal domain. As a result, we achieved the enhanced contrast, contrast noise ratio, spatial resolution, and less grainy texture without significant signal or feature loss in both in vivo photoacoustic and ultrasound images.

Previous work on 3D freehand photoacoustic imaging has focused on the development of specialized hardware or the use of tracking devices. In this work, we present a novel approach towards 3D volume compounding using an optical pattern attached to the skin. By design, the pattern allows context-aware calculation of the PA image pose in a pattern reference frame, enabling 3D reconstruction while also making the method robust against patient motion. Due to its easy handling optical pattern-enabled context-aware PA imaging could be a promising approach for 3D PA in a clinical environment.

To eliminate the limited angle effect of photoacoustic imaging based on ultrasound linear array, spatially distributed ultrasound sensor array is applied. The accurate sensor array position determines the quality of the imaging results. We proposed two methods based on photoacoustic and ultrasound signals to enhance the imaging quality using a full-ring array. Photoacoustic signals are used to regress the position of each element sensor. In phantom study and mouse brain study, imaging results can yield details clearly with average error rate of less than 50 μm. The proposed methods can contribute to precise biomedical imaging in future application scenarios.

Photoacoustic imaging is historically limited to soft-tissues and cannot image the bone interior. However we have recently demonstrated accurate photoacoustic and ultrasonic imaging in a cortical bone model by accounting for both refraction and elastic anisotropy. In this presentation, we will present photoacoustic imaging results in a bone-mimicking replica and ex vivo bovine long bone. We will demonstrate the accuracy of our imaging approach compared to conventional imaging techniques. Further, we will discuss the results of a parametric spectroscopic study of the source laser wavelength and ultrasonic probe to optimise imaging depth and resolution.

Dynamic reconstruction of three-dimensional (3D) photoacoustic tomography (PAT) recovers a sequence of 3D optical contrast distributions and enables to monitor time-varying changes of the chromophore concentrations in biological tissues. To achieve a high frame rate, only a limited-angle few-view (even a single-view) acoustic measurements can be collected at each time frame. These sparse incomplete data represent a formidable challenge to obtain sequences of reconstructed images with both high spatial and temporal resolution. Furthermore, dynamic PAT reconstruction is extremely computationally and memory expensive. High-resolution spatiotemporal reconstruction of 3D objects is, in fact, computationally unfeasible using naïve extensions of classical PAT reconstruction methods for static images. In this study, we present a fast and accurate randomized algorithm for dynamic PAT reconstruction from few tomographic views. Our method is based on the fact that, for many applications of clinical interest, dynamic PAT images are semi-separable in space and time. That is the sequence of PAT images can be expanded using a relatively small number r of basis functions in space and time. Under this assumption, the dynamic PAT reconstruction problem is reformulated as a penalized least squares model, where the nuclear norm of the space-time image is used for the regularization term. By use of a randomized truncated singular value thresholding method, our approach can be implemented in a memory-efficient (only need to store the r spatial and temporal basis functions) and computationally-scalable (only r PAT reconstructions per iteration) manner. The effectiveness of the proposed method is demonstrated using numerical simulation and experimental data of a 3D phantom.

Photoacoustic Remote Sensing (PARS™), an all-optical, non-contact, reflection-mode, label-free biomedical imaging modality, is sensitive to optical absorption in biological tissues. Images are formed by scanning across tissue, collecting time-domain signals at each point which represent the initial pressures generated through induced thermoelastic expansion. Previously, when obtaining pixel intensity, the rich temporal and spectral content of the time-domain signals has largely been ignored. In this exploratory work, meaningful features are intelligently extracted from the time-domain signals. Based on these extracted features, attributes relevant to pixel intensity can be used to form images of improved contrast and greater detail.

Multiple image quality metrics are currently available to assess target detectability in photoacoustic images. Common metrics include contrast, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR). The generalized contrast-to-noise ratio (gCNR) is a relatively new image quality metric to assess the probability of photoacoustic target detectability. This paper demonstrates the applicability of gCNR to assess photoacoustic image quality using simulated and experimental images created with delay-and-sum (DAS), short-lag spatial coherence (SLSC), generalized coherence factor weighting combined with DAS (GCF+DAS), and minimum variance (MV) beamforming. Images were created from data acquired with a fixed light source with output energy values increasing from 2 mJ to 35 mJ. The gCNR converged to 0.93, 0.98, 0.99, and 0.85 for DAS, SLSC, GCF+DAS, and MV beamforming, respectively, at energies of approximately 20, 10, 10, and 20 mJ, respectively. These results indicate that gCNR has the potential to determine the minimum laser energy needed to maximize the detectability of a photoacoustic target for any given image formation method.

We report a sparse coding-based two-stage image processing technique for noise reduction and contrast enhancement in photoacoustic microscopy (PAM). We have assessed the performance of this denoising technique using multi-parametric PAM images acquired at different optical fluence levels in vivo. Our results show that this technique can significantly improve the contrast-to-noise ratio (~7 times) and visibility of the microvasculature in low-fluence noisy images, enabling us to reduce the optical fluence by a factor of 5 while maintaining a similar image quality. Moreover, this technique improves the accuracy of quantitative measurements of blood oxygenation and flow in low-fluence PAM images.

Optical resolution photoacoustic microscopy (OR-PAM), though possessing high lateral resolution, has been limited by its poor axial resolution. In this study, we adapt the delay-multiply-and-sum (DMAS) beamforming technique to improve axial resolution of OR-PAM without physically increasing the detection bandwidth. Experimental OR-PAM A-line signals from a thin absorbing layer were used to verify the efficacy of the proposed frequency domain DMAS method in axial resolution improvement. The improvement achieved with the proposed method was also further verified by imaging microvasculature of mouse ears in vivo.

We have developed a software package called 3D PHOVIS (3D Photoacoustic Visualization Studio) to support 3D volume data visualization in academia. It was developed with MATLAB-based graphical user interface software that utilizes CPU and GPU parallel computing technology to provide a convenient real-time working environment. 3D PHOVIS includes five modules, which can help volume stitching, scanning distortion removing, depth encoded visualization, and volume rendering with 3D photoacoustic data. It also supports 3D movie generation. In this presentation, we will interpret the algorithms and principles used in software development, and demonstrate its function with several examples.

Among women, ovarian cancer is fifth most common cause of death due to cancer. In clinical ovarian cancer diagnosis via photoacoustic tomography, we face several challenges such as poor image resolution and signal-to-noise ratio (SNR). To address these concerns, we proposed a novel beamformer named lag-based delay multiply and sum combined with coherent factor (DMAS_LAG_CF). The simulations, phantom experiments and ovarian cancer patient data have demonstrated that compared with the delay and sum algorithm (DAS), the new algorithm can achieve better resolution, SNR, and improved hemoglobin contrast of malignant vs. benign ovarian lesions.

Photoacoustic imaging (PAI) is an emerging medical imaging modality that provides high contrast and spatial resolution. A core unsolved problem to effectively support interventional healthcare is the accurate quantification of the optical tissue properties, such as the absorption and scattering coefficients. The contribution of this work is two-fold. We demonstrate the strong dependence of deep learning-based approaches on the chosen training data and we present a novel approach to generating simulated training data. According to initial in silico results, our method could serve as an important first step related to generating adequate training data for PAI applications.

Reflection of photoacoustic (PA) signals from strong acoustic heterogeneities in biological tissue leads to reflection artifacts (RAs) in B-mode PA images. In practice, RAs often clutter clinically obtained PA images, making the interpretation of these images difficult in the presence of hypoechoic or anechoic biological structures. Towards PA artifact removal, several researchers have exploited 1) the frequency/spectrum content of time-series photoacoustic data in order to separate the true signal from artifacts, and 2) the multi-wavelength response of photoacoustic targets, assuming that the spectral nature of RAs correlates well with their corresponding source signals. These approaches are limited to extensive offline processing and sometimes fail to correctly identify artifacts in deep tissue. This study demonstrates the use of a deep neural network with the U-Net architecture to detect and reduce RAs in B-mode PA images. In order to train the proposed deep learning model for the RA reduction task, a program is designed to randomly generate anatomically realistic digital phantoms of human fingers with the capacity to produce RAs when subjected to PA imaging. In-silico PA imaging experiments, modeling photon transport and acoustic wave propagation, on these digital finger phantoms enabled the generation of 1800 training samples. The algorithm was tested on both PA images generated from digital phantoms and in-vivo PA data acquired from human fingers using a hand-held LED-based PA imaging system. Our results suggest that robust reduction of RAs with a deep neural network is possible if the network is trained with sufficiently realistic simulated images.

Spectroscopic photoacoustic (sPA) imaging can be used to map blood oxygen saturation (sO2) within tissue. Its accuracy, however, is degraded deep in tissue by wavelength-dependent optical attenuation. We have developed a convolutional neural network to simultaneously estimate the sO₂ and segment blood vessels from sPA data. The network was trained on Monte Carlo simulated sPA data and predicted sO₂ with 9.31% median pixel error. The network was then retrained on experimental photoacoustic images of cow blood with median prediction error of 4.38%. These results suggest that precise quantitative measurements of sO₂ deep in tissue are attainable using machine learning approaches.

The goal of quantitative optoacoustic tomography (qOAT) is to reconstruct a distribution of absolute chromophore concentrations and/or functional properties from measurements of the optically induced pressure (ultrasound signals) acquired at multiple excitation wavelengths. Estimating the distribution of hemoglobin, an endogenous OAT chromophore, is important because the oxygen saturation distribution of the blood vessels is a well-known indicator of aggressive growth of a cancerous tumor. In a number of studies, a spectral linear unmixing method has been applied to two-dimensional slices of tissue acquired with OAT at multiple wavelengths, leading to promising results at moderate penetration depths of ≤ 2 cm. In the three-dimensional (3D) OAT of the breast, such functional images cannot be accurately reconstructed via the spectral linear unmixing method due to unknown spatial distribution of the optical fluence in a relatively large size of the volume of interest (≥ 4 cm). Optical attenuation in biological tissue depends on the optical wavelength, and the optical fluence is exponentially attenuated with increasing imaging depth. Thus, the accuracy of the estimated distribution decreases with depth. To overcome this challenge, we investigated a spectral linear unmixing method with a simplified optical fluence normalization based on measurements of background absorbed optical energy in the breast. We compare estimates of blood oxygen saturations from two-wavelength clinical OAT breast images and demonstrate acceptable accuracy of ~10% while lack of compensation for the optical fluence distribution can lead to values outside the physiological range. We also quantitatively compare the accuracy of oxygen saturation estimates using numerical simulation of photon transport in realistic 3D OAT breast phantoms at dual wavelengths of 757 and 850 nm with inverse ratio of the optical absorption by deoxy- (Hb) and oxy-hemoglobin (HbO2) and three wavelengths of 757, 800, and 850 nm with inclusion of isosbestic point of the optical absorption in Hb/HbO₂.

In photoacoustic tomography (PAT), measurement errors arise from optical fluence spatial and temporal variations caused by tissue optical absorption and scattering heterogeneities, system noise, and motion. These errors influence the estimation accuracy of blood oxygenation saturation (sO2). In this study, we introduce a sliding multi-pixel approach to mitigate the effect of measurement errors before computing sO2 maps. As a result, the sO2 estimation is both more accurate, as evaluated by residual fitting errors, as well as smoother. We conclude by presenting diagnostic results from PAT of 33 patients with ovarian masses imaged by our coregistered PAT and ultrasound system.

Optical-resolution photoacoustic microscopy (OR-PAM) can image the blood oxygen saturation (sO₂) in vivo without labeling. OR-PAM assumes a linear relationship between the photoacoustic amplitude and the optical absorption coefficient and ignores the wavelength-dependent optical fluence attenuation in tissue. However, strong scattering in biological tissues may significantly change the optical energy deposition, leading to inaccurate sO₂ measurement. Here, we report fluence-compensated OR-PAM to correct the sO₂ imaging. In a narrow optical spectrum, we assume the scattered fluence is linearly related to the optical wavelength. Using three optical wavelengths, we can compensate for the scattering-induced photoacoustic signal change and thus improve the accuracy of sO₂ measurement. We use a Monta Carlo model to validate the linear assumption of the scattered fluence. In in vivo experiments, we demonstrate that the optical fluence compensation can effectively improve the sO₂ accuracy. The compensated arterial sO₂ values are in the range of 0.95 ~ 0.99, which is consistent with normal physiological values. Compared with the uncompensated ones, the accuracy has been improved greatly. Enabled by the accurate sO₂ imaging tool, we can reliably observe the sO₂ gradient in the vascular network. We expect this new technique will further broaden the preclinical and clinical applications of functional OR-PAM.

Photoacoustics Imaging is an emerging imaging modality enabling the recovery of functional tissue parameters such as blood oxygenation. However, quantifying these still remains challenging mainly due to the non-linear influence of the light fluence which makes the underlying inverse problem ill-posed. We tackle this gap with invertible neural networks and present a novel approach to quantifying uncertainties related to reconstructing physiological parameters, such as oxygenation. According to in silico experiments, blood oxygenation prediction with invertible neural networks combined with an interactive visualization could serve as a powerful method to investigate the effect of spectral coloring on blood oxygenation prediction tasks.

Photothermal measurements with an infrared camera enable a fast and contactless part inspection. The main drawback of existing reconstruction methods is the degradation of the spatial resolution with increasing imaging depth, which results in blurred images for deeper lying structures. In this work, we propose an efficient image reconstruction strategy that allows prior information to be included to overcome the diffusion-based information loss. Following the virtual wave concept, in a first step we reconstruct from the measured photothermal signal an acoustic wave field that satisfies the standard wave equation. This wave is called a virtual one, because it is not the measured acoustic wave but mathematically calculated from the temperature signal measured on the sample surface. In the second step, stable and efficient reconstruction methods developed for photoacoustic tomography are used. We compensate for the loss of information in thermal measurements by incorporating the prior information positivity and sparsity. For that purpose we combine circular projections with an iterative regularization scheme. Using experimental data, this work demonstrates that the quality of the reconstruction based on photothermal measurements can be significantly enhanced. The main goal of this work was to illustrate that prior information significantly improves the regularized solution and, hence, the reconstructed field. Using an iterative non-linear regularization method, the prior information positivity and sparsity could be incorporated. The regularization and reconstruction results show that respecting information available about the data significantly increases the quality of the regularized solution.

We introduce a general theoretical framework to study arbitrary light-cavity interactions for planar Fabry-Perot (FP) cavities and explain how optical aberrations reduce optical sensitivity by exciting higher order spatial modes. Moreover we show experimentally that the sensitivity of realistic FP cavities can be improved up to three-fold by a synergistic combination of adaptive optics (AO) and mode filtering. Finally, we discuss the challenges of achieving large sensitivity improvements under photoacoustic imaging conditions and present first results towards implementation of AO-corrected systems, as well as complementing AO with synergistic strategies for improving FP sensitivity.

One of the main challenges in intravascular photoacoustic (IVPA) imaging is the limited sensitivity and bandwidth of miniaturized piezoelectric probes. Optical detectors of ultrasound can drastically improve both these features, but often lack acoustic focusing. In this work, we developed a focused ultrasound detector by integrating a miniaturized acoustic lens, made out of glass, with a silicon-photonics-based detector. A detection bandwidth of up to 80 MHz and lateral resolution beyond 50 µm was demonstrated with a lens diameter of 0.8 mm. Our device is transparent in the near-infrared window, simplifying its integration in a miniaturized IVPA probe.

Optoacoustic (OA) tomography has recently demonstrated ultrafast imaging rates, owing to its unique ability to capture volumetric image data with a single nanosecond-duration flash of light. The achievable spatial resolution of volumetric tomography is however limited by the narrow bandwidth and lack of scalability of the piezo-composite arrays currently employed for OA signal detection. Here we report on the first implementation of high-density spherical matrix array technology based on flexible polyvinylidene difluoride films featuring ultrawideband (38 MHz) sub-millimeter sized elements thus enabling volumetric imaging with ~35 μm resolution, superior image fidelity and excellent signal to noise performance permitting real-time imaging of deep tissues without employing signal averaging. We demonstrate real-time volumetric in vivo imaging capabilities of the new approach by performing cerebral angiography in mice. The new technology leverages the true potential of OA for high spatio-temporal resolution visualization of rapid biodynamics.

In photoacoustic microscopy (PAM), the ultrasound transducer plays a critical role in detecting the PA signals. However, conventional ultrasound transducers are optically opaque, which could hinder the effective delivery of the excitation laser onto the target. Recently, optically-transparent ultrasound transducers have been investigated to address this issue. Nevertheless, the transparent transducers demonstrated so far have either a small numerical aperture (NA) or narrow bandwidth, which limits their acoustic focal spot sizes and therefore achievable spatial resolutions. In this paper, we report a new focused transparent polyvinylidene fluoride (PVDF) transducer with a high NA of 0.64 and a wide acoustic pulseecho bandwidth of 120%. Experiment characterization shows that it has an acoustic center frequency and bandwidth of 36 MHz and 44 MHz, respectively. The acoustic focal diameter and zone are 37.8 μm and 210 μm, respectively. With the new transparent transducer, dual-modal acoustic-resolution PAM (AR-PAM) and pulse-echo ultrasound microscopy (PEUSM) have been demonstrated with a target consisting of black-ink-filled polyimide tubing buried in chicken breast at different depths. The imaging results show that both the (acoustic) lateral and axial resolutions can be maintained even at a penetration depth of larger than 3 mm.

Deep tissue applications (>1 cm) for photoacoustic imaging are currently limited for traditional Fabry-Pérot ultrasound transducers interrogated by tightly focused Gaussian beams due to beam walk-off. We investigate the optical confinement of the beam using plano-concave microresonators with a model based on the ABCD formalism and the use of high-sensitive and high-density multi-element arrays. The results show an improvement in the sensitivity enabling an increase of the penetration depth in tomographic photoacoustic imaging.

We introduce transparent TOBE CMUT arrays for multimodal optical camera imaging, ultrasound imaging and photoacoustic imaging. We used an adhesive wafer bonding process technique to fabricate the 128-element lambda-pitch transducers and achieve high transparency ranging from visible to near-infrared with ultrasound center frequencies of 7.5-9 MHz. The arrays are anticipated to have utility for endoscopic, intravascular, and intra-operative probes for multimodal interventional guidance.

Photoacoustic imaging (PAI) is a hybrid imaging modality that uses ultrasound waves generated from light absorbing tissue chromophores to provide high spatial resolution and depth-resolved molecular information. However, conventional PAI setups involve complicated arrangement of optical components surrounding opaque ultrasound transducers to achieve a co-aligned optical illumination and ultrasound receiving field. This opacity of traditional ultrasound transducers impedes the miniaturization of the imaging head, besides precluding integration with other imaging modalities. To overcome these limitations, we recently fabricated a single element transparent ultrasound transducer (TUT) window using indium tin oxide (ITO) coated lithium niobate (LiNbO₃) piezoelectric material and demonstrated its application for endoscopy and microscopy PAI applications. Extending on this work, we report new developments of TUTs to improve their detection bandwidth, sensitivity, and signal to noise ratio (SNR) while maintaining sufficient transparency. This includes investigating LiNbO₃ and PMN-PT as transparent piezoelectric materials with different matching layer designs. Fabricated TUTs were characterized using pulse echo and electrical impedance analysis. The PAI performance of the fabricated TUTs were characterized using photoacoustic A-line signals from light absorbing targets. The proposed TUTs are low cost, easy to fabricate, and can be scaled and easily integrated into different PAI geometries such as: endoscopy, microscopy, and computed tomography systems for high-throughput imaging applications.

We detail the design for a better photonic-crystal slab (PCS) based sensor for ultrasound sensing. The sensing mechanism relies upon the sensitivity S of the optical resonance of the PCS to the index of the surrounding medium, the quality factor Q of the resonance, as well as the surrounding medium’s photoelastic coefficient. Traditionally, the interplay between S and Q in PCS devices means that increasing one will cause a decrease in the other. Here, we show that the use of so-called bound states in the continuum (BIC)-based resonance allow for a high Q (> 1e5) while maintaining a nominal S (~ 350 nm/RIU). We anticipate using BIC-based PCS sensors to have a 100x improvement in the ultrasound sensitivity over previous PCS devices.

Fabry-Pérot (FP) polymer film sensors are used as ultrasound sensors for Photoacoustic (PA) imaging. Optical models predict that FP sensors should have higher sensitivity than observed experimentally. The models assume FP sensors to be optically flat whereas in practice the polymer film spacer exhibits a degree of surface roughness. To understand the impact of the roughness, an optical model of rough FP sensors was developed. Theoretical results show that roughness can reduce the optical sensitivity by a factor of two. The model will help to guide the design of FP sensors to optimize their sensitivity and, therefore, the imaging depth.

Future applications of photo-acoustic imaging require a matrix of small (wavelength/2) and sensitive ultrasound sensors with read-out through a flexible cable. Integrated optical sensors have good prospects: small and sensitive sensors, wafer-scale fabrication, and matrix read-out via single optical fiber using on-chip optical multiplexing. We propose a new type of opto-mechanical ultrasound sensor (OMUS) in silicon photonic chip technology. By using an acoustically resonant membrane in combination with an innovative split rib-type photonic waveguide, we achieve extremely high sensitivity. We present our experimental results in the frequency range up to 30 MHz.

In this paper, we report a high-frequency photoacoustic sensing (PAS) probe design consisting of an optical fiber for light delivery and two silicon acoustic delay lines (SADLs) for detecting/relaying the PA signals. A beveled tip is formed at the distal end of the optical fiber to overlap the illumination region with the detection zone of the SADLs. Detected PA signals are transmitted through the SADLs with low loss at frequencies up to 17 MHz. For demonstration, a prototype PAS probe using SADLs is designed, fabricated, and tested. Testing results show that the PAS probe provides superior sensitivity with considerable high-frequency improvement.

Distinguishing between acute and chronic intestinal obstruction is essential for the treatment of Crohn's disease (CD). We have demonstrated the capability of spectroscopy photoacoustic (PA) imaging in quantifying hemoglobin and collagen changes. We also developed strain-PA imaging as a novel method for quantifying the intestinal stiffness, which is a mechanical marker of CD. In this study, we combined the spectroscopy and stiffness measurements using a catheter probe and examined the proposed approach in a rabbit model of CD in vivo. The quantitative accuracy of the imaging was validated by histology and micro-elastometry.

Homogeneous laser illumination is critical for side view photoacoustic tomography. In this paper, two homogeneous fiber side illumination methods are proposed by utilizing diffuser coating made of ultraviolet adhesive mixed with silica microspheres. One method is the gradient side diffuser, manufactured by dip coating fiber core with consecutive diffuser sections of different silica microsphere concentrations. The other method is the partially peeled-off diffuser, generated by peeling off part of the diffuser coating section on a single concentration fiber diffuser. Both methods show homogeneous laser side illumination according to simulation and experiment, with adjustable illumination length by design.

Abnormal microcirculatory changes in arterioles, venules and capillaries are key functional indicators of important diseases such as cancer, diabetes or cardiovascular disorders, as well as several neurodegenerative ailments. In vivo visualization of these structures has traditionally been restricted to the shallow depths <1-2 mm reachable with highresolution optical imaging methods. Optoacoustic (photoacoustic) tomography has enabled breaking through this light diffusion barrier to map functional hemodynamic parameters such as oxygen saturation in deep-seated vessels, but frequency-dependent attenuation of ultrasound waves limits the achievable resolution and prevents reaching the capillary level. Imaging of individual capillaries has been achieved via localization of microbubbles flowing in blood with pulseecho ultrasound. Optoacoustic localization of light-absorbing particles in mammalian tissues is however hampered by the strong background absorption of blood. Herein, we demonstrate the feasibility of in vivo localization optoacoustic tomography (LOT) with intravenously injected 5 m microdroplets having optical absorption 10000 higher than red blood cells for near-infrared wavelengths. Three-dimensional imaging of the mouse brain microvasculature through the intact scalp and skull was facilitated by the unidirectional propagation of ultrasound waves, yielding 20 μm resolution at 3 mm depth in turbid mouse brain tissues in vivo.

Accidental injury to underlying blood vessels and nerves during minimally invasive neurosurgery can have severe surgical complications (e.g., blindness, paralysis, and death). Transcranial photoacoustic imaging is a promising technique for real-time visualization of these structures, but it is challenged by acoustic-bone interactions which degrade image quality. We are developing patient-specific simulation methods that identify viable transcranial acoustic windows for intraoperative photoacoustic visualization of these underlying structures. Photoacoustic k-Wave simulations were performed based on a CT volume of an intact human cadaver head, which was later used to create experimental images of the internal carotid arteries. Acoustic receivers distributed across the eyelids measured pressure from intracranial photoacoustic sources. Differences in photoacoustic signal quality between the left and right eyelid receiver locations were investigated. Simulated sensors placed on the right eyelid received a 6.4 dB greater median acoustic energy than simulated sensors placed on the left eyelid, which was confirmed experimentally with a 14.5 dB greater DAS photoacoustic image amplitude with the ultrasound probe placed on the right eyelid rather than the left eyelid. Therefore, the ocular cavity is a viable acoustic window for photoacoustic-guided neurosurgeries with the potential to identify intrapatient, left-right asymmetries, supporting a new paradigm for performing patient-specific simulations prior to surgical guidance.

Photo-mediated ultrasound therapy (PUT) is a novel, non-invasive, and agent-free therapeutic technique that uses a combination of relatively low-intensity ultrasound bursts and nanosecond laser pulses to selectively and precisely remove highly optically absorptive targets. In this work, we developed an integrated ultrasound photoacoustic theranostic system (UPTS) by combining a ultrasound system (V1, Verasonics) with a pulsed laser system. The results from the ex vivo experiments in rabbit tissues demonstrated that UPTS, by working with appropriate laser wavelengths, can selectively remove tissues such as knee tendon and liver via the cavitation synergistically created by the ultrasound bursts and the laser pulses. Such a theranostic system can deliver effective PUT treatment to biological samples along with real-time monitoring by the integrated ultrasound and photoacoustic imaging.

The detection sensitivity of optoacoustic spectroscopy at the short-wavelength infrared (SWIR) region is reduced by water absorption in aqueous solutions. Our work reports marked improvements in the sensitivity of optoacoustic spectroscopic measurements of proteins, lipids, and glucose when performed at 4 °C, compared to conventional optoacoustic or IR spectroscopy. Studying the effect of water temperature on optoacoustic signals revealed a polarity change at temperatures below 4 °C (muting temperature). The dependence of the optoacoustic signal and the muting temperature on sample concentration were further investigated, demonstrating that changes in these dependencies enable accurate quantification of the solute concentration.

We propose a microscale photoacoustic hardware architecture using silicon photonics. The system builds on a platform that monolithically integrates on-chip light excitation and ultrasound detection of photoacoustic signal. The device uses a waveguide terminating with a meta grating structure to engineer an excitation beam profile. The ultrasound receiver is based on a photonic ring resonator that sits on top of mechanical membrane. The pressure wave impinging on the membrane deflects the ring resonator resulting in change in optical readout. We believe the method is scalable to develop low-cost ultra-highly sensitive photoacoustic sensors for applications such as PA imaging, spectroscopy, and microscopy.

A new approach to photoacoustic tomography is presented in which a number of spatially overlapping photoacoustic time series measurements are aligned and registered to extend the effective imaging aperture. This approach not only improves the lateral resolution and imaging depth in tissues but also enables imaging of targets that are much larger than the physical size of the detector array.

Photoacoustic tomography (PAT) is an emerging technology for biomedical imaging that combines the superiorities of high optical contrast and acoustic penetration. In the PAT system, more photoacoustic (PA) signals are preferred to be detected to reconstruct PA image with higher fidelity. However, more PA signals’ detection leads to more time consumption for single-channel scanning based PAT system, or higher cost of data acquisition (DAQ) module for array-based PAT system. To address this issue, we proposed a real-time PAT system only using single DAQ channel, and a deep learning method for PA signal recover and image reconstruction. We superimpose 30 channels’ signals together, shrinking to 4 channels (120/30=4). Furthermore, a four-to-one delay-line module is designed to combine this 4 channels’ data into one channel DAQ. In order to reconstruct the image from four superimposed 30-channels’ PA signals, we train a dedicated deep learning model to reconstruct final PA image.

In the kidney and liver, fibrosis is a powerful predictor of outcomes. Unfortunately, accurate fibrosis quantification cannot be done non-invasively. Photoacoustic (PA) imaging offers the potential for measuring collagen, the principal component of the fibrotic matrix. Here, we demonstrate the potential of PA imaging for fibrosis quantification in preclinical kidney and liver fibrosis models. To induce kidney fibrosis, the left ureter was obstructed for 0 (n = 5), 7 (n = 5) or 14 days (n =5). The right kidneys at each day (n = 15) served as controls. To induce liver fibrosis, carbon tetrachloride (CCl4) injections were given to mice (n = 31). Control mice (n = 12) received corn oil vehicle injections. A PA unmixing algorithm based on the use of the variance inflation coefficient for detecting the multicollinearity of collagen/oxy/deoxyhemoglobin was developed and validated against gold standard histology measurements. The VevoLAZR-X system was used in the 680-930 nm illumination range at 15 MHz. PA imaging revealed 4x more collagen by day 14 post ureteral obstruction compared to sham kidneys. Similarly, PA imaging suggested that fibrotic livers 6 weeks post-CCl4 injection contained about 125% more collagen than control livers. Comparisons with histological gold standards revealed a strong linear correlation (r = 0.89 – 0.99). This work demonstrates the potential of PA imaging to accurately and non-invasively assess fibrotic burden in livers and kidneys. We postulate that this technology will accelerate the preclinical assessment of antifibrotic drugs.

In this study, we evaluated the capability of an LED-based photoacoustic imaging system (AcousticX, 7MHz ultrasound probe, 850 nm LED arrays) in imaging heterogenous vasculature of subcutaneous tumors in mice. For evaluating the functional imaging capability, we used AcousticX with dual-wavelength LED arrays (750/850 nm) and monitored oxygen saturation of the tumor volume. We also compared the tumor images acquired by AcousticX and a commercial laser-based photoacoustic imaging system. Our results show that LED-based photoacoustic imaging can obtain similar imaging performance as a laser-based system and thus holds good promise in preclinical cancer research in an affordable setting.

The heart undergoes complex remodeling processes post myocardial infarction (MI), which are yet to be fully understood. Advanced preclinical in vivo imaging tools are key to a better understanding of the processes underlying ischemic damage and cardiac remodeling. Herein, volumetric optoacoustic tomography (VOT) was used to study remodeling patterns at different stages post MI by measuring the pulmonary transit time, ICG perfusion and cardiac cycle irregularities. The real-time, non-invasive, volumetric capabilities of VOT detected differences in remodeling patterns across different MI models, highlighting the feasibility of VOT as a preclinical cardiac imaging tool to study complex murine heart dynamics.

Histopathological analysis remains a gold standard in preclinical research, which can only be performed as an end-stage analysis. In small animal studies, in order to improve the outcome, it is important to study the disease progression and treatment response over time without sacrificing animals at different time points thereby reducing the number of animals. Photoacoustic imaging with its ability to probe endogenous chromophores in the tissue and being non-invasive has great potential in this aspect. In this work, we aim to use ultrasound and photoacoustic imaging for assessment of liver fibrosis, in particular, to monitor the disease progression. We have used ultrasound and LED-based photoacoustic (US/LED-PA) imaging system, both in its handheld and tomographic mode. In the tomographic mode, the transducer and LED arrays were scanned around the animal for imaging. The imaging was performed on healthy (control) mice and mice with carbon tetrachloride (CCl4) induced liver fibrosis. The control and fibrotic mice were followed over a duration of eight weeks using US/LEDPA imaging. The animals were euthanized, imaged and histopathological analysis were performed at the end of 8-weeks. An increase in photoacoustic contrast and ultrasound echogenicity were observed progressively in the fibrotic livers compared to the control livers. The histological analysis also validated the severity of the fibrosis in the mice. The proposed approach using longitudinal monitoring of disease progression using US/LEDPA imaging can improve the outcome of the study. Since the LED-based system is compact, eye-safe, and easy-to-use, it can be of great benefit in small animal research.

Recently we proposed to use optoacoustic therapy/Nano-Pulse Laser Therapy-NPLT and tested it in rats with traumatic brain injury (TBI). In this study we used an optoacoustic system operating at 808 nm and demonstrated that NPLT prevented TBI-induced upregulation of specific microRNAs (miRNAs) in NSC and significantly decreased TBI-induced impaired maturation and abnormal migration of neural progenitors. Moreover, NPLT-treated injured rats performed significantly better in hippocampus-dependent cognitive tests than did sham rats. Our results strongly suggest that NPLT has the potential to be an effective tool for the treatment of TBI-induced cognitive dysfunction and dysregulation of neurogenesis.

Laser ablation (LA) is gaining acceptance for the treatment of tumors as a viable alternative to surgical resection. In parallel, optoacoustic tomography (OAT) has enabled defining new regimes for diagnosis and characterization of malignant neoplastic lesions with high sensitivity and specificity. Even though pulsed nanosecond lasers are commonly used for both imaging and therapeutic purposes, real-time thermal treatment monitoring with a single laser source has not been previously attempted. Herein, we demonstrate the feasibility of combined OAT and LA by percutaneous irradiation of subcutaneous tumors with a 100 mJ short-pulsed (~5 ns) laser operating at 1064 nm and 100 Hz pulse repetition frequency. The OAT images rendered with a spherical ultrasound transducer array enabled real-time monitoring of the LA lesion progression, which is essential for determining the optimal treatment end-point. Local changes in the optoacoustic signal intensity associated with the induced temperature changes as well as structural alterations in the tumor vasculature could clearly be observed. The optoacoustic volumetric projections further correlated with crosssections extracted from the excised tumors. This newly enabled capability anticipates new theranostic approaches in cancer research and treatment with potential applicability in a clinical setting.

Ultrasound (US) and optoacoustic (OA) imaging provide complementary information for quantitative analysis of the tumor microenvironment. Herein, we demonstrate the unique capabilities of transmission-reflection optoacoustic ultrasound (TROPUS) for characterizing breast cancer in tumor-bearing mice. For this, 4 different mice featuring orthotopic tumor of different sizes were scanned with a full-ring ultrasound transducer array to simultaneously render pulse-echo US images, speed of sound (SoS) maps and OA images. The tumor size, vascular density and its elastic parameters were further quantified in the images. Our results pave the way toward clinical translation of the hybrid TROPUS imaging for tumor detection and characterization.

Gas-filled nanobubbles (NBs) have been used for contrast enhanced ultrasound (US) molecular imaging similar to their microbubble (MB) counterparts. In this work we explore the use of NBs as cancer therapeutic vehicles to enhance radiation therapy and examine the role of photoacoustic (PA) imaging for quantifying the tissue response. Experiments were conducted in 58 mice bearing prostate cancer tumors. The treatment groups consisted of untreated controls (n=14), 8Gy radiation (n=14), US+MB (n=8), US+NB (n=5), US+MB+8Gy (n=12) and US+NB+8Gy (n=5). PA imaging was conducted using the VevoLAZR 21 MHz probe at pre-treatment, 2h and 24h post-treatment. To examine the changes in the tumor microenvironment post-treatment, we measured the tumor oxygen saturation (sO2), total hemoglobin (HbT) and the spectral slope (SS) as a surrogate measurement of vessel size. Histology measures of tumor vascularity/vessel size (CD31) and cellular death (TUNEL) allowed us to interpret the PA biomarker changes. The PA biomarkers revealed the following changes for the US+NB+8Gy group: (a) a 20% decrease in tumor sO2, (b) a 30% increase in tHb and (c) 20% decrease SS. These results suggest that NBs induce vessel damage from US-induced cavitation. Histology elucidates these findings: CD31 staining measuring vascularity decreases by 80% at 24h–this causes the drop in sO2 and increase in HbT; the size of vessels decreases by 10%–this is captured by the SS change. This work shows that PA imaging biomarkers can quantify these vascular changes which in turn enhance the radiation-induced cell death (up to 40%, as measured by TUNEL staining).

Cerebrovascular imaging of rodents is one of the trending applications of optoacoustics aimed at studying brain activity and pathology. Imaging of deep brain structures is often hindered by sub-optimal arrangement of the light delivery and acoustic detection systems. In our work we revisit the physics behind opto-acoustic signal generation and perform theoretical evaluation of optimal laser wavelengths with an aim of enabling whole brain cerebrovascular optoacoustic angiography in small rodents. A comprehensive model based on diffusion approximation was developed to simulate optoacoustic signal generation using optical and acoustic parameters closely mimicking a typical murine brain and surrounding tissues. The model revealed three characteristic wavelength ranges in the visible and near-infrared spectra optimally suited for imaging cerebral vasculature of different size and depth. The theoretical conclusions are confirmed by numerical simulations while in vivo imaging experiments further validated the capacity for accurately resolving brain vasculature at depths ranging between 0.7 and 7 mm.

Understanding brain function mechanisms relies on tools capable of simultaneous structural and functional imaging at the whole brain scale, with high spatio-temporal resolution, often not attainable in a single imaging modality. Here, we employ spherical matrix array geometry to combine optoacoustic tomography (OAT) and ultrasound localisation microscopy (ULM), and obtain dual-mode volumetric images of the whole mouse brain. Together, OAT allows functional readouts of hemodynamics and oxygen metabolism, while ULM provides structural images of the brain vasculature with a resolution of 20 μm, and flow velocity information up to 10 mm/sec, for a comprehensive characterization of microvascular architecture and function.

We report photoacoustic (PA) lifetime (PALT) based oxygen imaging powered by polyacrylamide (PAA) nanoparticles (NPs). The phosphorescenc indicator, oxyphor G2, was conjugated within the matrix of the NPs, giving G2-PAA NPs, followed by PEGylation for biocompatibility and F3 surface modification for tumor targeting. Two laser pulses (630 nm pumping, 920 nm probing) excite the G2-PAA NPs. By varying the delay time between the pump and the probe pulses, the exponential decay of the phosphorescence, which correlates linearly with the ambient oxygen concentration, can be measured. PALT imaging was performed, to quantitatively map the oxygen concentration in biological tissues in vivo, including both cancerous tumors and normal thigh muscles. The successful imaging experiment accomplished on animal models renders a new method for in vivo non-invasive imaging and assessment of hypoxic tumor microenvironments, which is critical for assessing cancer progression, metastasis, and treatment.

Toward non-genetic non-invasive neural modulation with a submillimeter precision, we report the development and application of photoacoustic nanotransducers (PAN) to neural stimulation in cultured primary neurons and in live brain. Our PAN, based on synthesized semiconducting polymer nanoparticles, efficiently generate localized ultrasound by a photoacoustic process upon absorption of nanosecond pulsed light in the NIR-II window. We showed that PAN binding on the neuron membrane through non-specific interaction and specific targeting of mechanosensitive ion channels both successfully activate primary neurons in culture. We also demonstrated in live mouse brain motor cortex activation and invoked subsequent motor responses through PAN.

Regenerative therapies such as stem cell therapies are an area of active investigation that will likely play an important role in the future to improve vision loss from retinal diseases including macular degeneration and retinitis pigmentosa. It is important to visualize these cells after administration to determine their fate and effect. In this study, an advanced non-invasive photoacoustic microscopy (PAM) and optical coherence tomography (OCT) imaging system was developed to monitor cells in vivo. To boost the sensitivity of PAM and OCT, novel ultrapure functionalized chain-like gold nanoparticle (CGNP) clusters were synthesized and cultured into a precursor human retinal pigment epithelial cell line with differentiated properties (ARPE-19) cells. The fabricated CGNP clusters have redshifted plasmonic peak absorption from 520nm to 650nm, resulting in reduced background signal from hemoglobin. The position of cells following subretinal injection into the rabbit retina having laser injury is selectively tracked longitudinally in vivo using integrated photoacoustic microscopy (PAM) and OCT over 3 months in 3 rabbits. PAM images obtained at two different optical wavelengths of 578 nm and 650 nm were overlaid on the same image plane and on the OCT image allowed to distinguish transplanted cells from the adjacent native choroidal vessels and track the migration of the cells over time. Quantification of PAM and OCT signals illustrated that the PAM signal increased by 30-fold, and OCT signal increased by 180 %. Histological analysis confirmed that ARPE-19 cells migrated to the injured sites and correlated with the location noted on the PAM/OCT imaging. This work provides a comprehensive imaging and nanoparticle system that could be used for labeling and tracking of cell-based regenerative therapies.

We report the use of frequency decomposition with ultraviolet photoacoustic remote sensing (UV-PARS) microscopy that enables contact-free and label-free virtual H and E staining. Along with principal component analysis of frequency information, this image reconstruction technique allows for the incorporation of scale-specific information encoded in the frequency spectrum of generated PARS signals. The performance of this image reconstruction technique as demonstrated on histological samples achieves contrast-to-noise ratios of over 55-dB between nuclei and nearby cytoplasmic structures. This technique allows for the rapid and facile production of virtual H and E stained images without the need for additional excitation wavelengths.

We report wide-field polygon-scanning optical-resolution photoacoustic microscopy (OR-PAM) that achieves 1-MHz A-line rate of oxygen saturation in vivo. We develop a polygon-scanning imaging probe. Using stimulated Raman scattering and optical delay in fiber, we develop a dual-wavelength pulsed laser that has proper wavelengths, sufficient pulse energy, high pulse repetition rate, and sub-microseconds wavelength switching time for fast imaging of oxygen saturation. The OR-PAM system offers a 478-Hz B-scan rate and a 1-Hz volumetric imaging rate over a 12×5 mm² scanning area. We demonstrate dynamic imaging of oxygen saturation of fast response to epinephrine injection in the mouse ear. Results show fast hemodynamic and functional changes in centimeter-sized areas.

Here we report a high performance fiber-based photoacoustic microscope for brain sO₂ imaging. The critical element is a fiber-optic ultrasound sensor, which translates the megahertz acoustic waves into detectable lasing frequency variations. Its working bandwidth has been extended to 40 MHz, by reducing the fiber diameter to 58 μm via chemical etching, this sensor should good result in brain sO₂ imaging. The fiber-based PAM offers a new strategy to implement a head-mounted microscope to continuously monitor the brain activities of an awake, free-moving small animal.

Rapid, accurate intraoperative assessment of excised specimens and in vivo resection sites is a critical need in tissue-conserving cancer surgeries. We develop a multimodal imaging system integrating ultraviolet photoacoustic remote sensing (UV-PARS) microscopy with spectral-domain optical coherence tomography (SD-OCT) to provide comprehensive, co-registered information for identifying atypical tissue features. 1050-nm SD-OCT generates a widefield, depth-resolved view of subsurface tissue morphology, with 9-μm axial resolution. UV-PARS produces virtual histological C-scan images of cell nuclei, at 390-nm lateral resolution. Dual-contrast in vivo mouse imaging, and ex vivo imaging of breast and prostate specimens is demonstrated, and correlated with conventional H and E staining.

Histopathology remains the gold standard for assessing tissue microanatomy. Presently, specimens are examined with bright-field microscopes that require thin stained sections of tissue specimens. However, this requires extensive tissue processing and long turnaround times. Frozen sectioning is commonly used during surgery to assess margin status. However, this method can be unreliable as the slides can be difficult to interpret. Employing photoacoustic remote sensing (PARS), we emulate H and E micrographs by visualizing nuclear and cytoplasm contrast directly. These contrasts are visualized in a variety of human tissue samples and fresh thick unprocessed tissue specimens.

We present a fast, multispectral acoustic resolution optoacoustic microscope using a new burst-mode triggering scheme. Three pulsed laser sources are combined to retrieve spectral images across large field-of-views extending over 25mm by 25mm at 28μm lateral and 14μm axial resolution with an overfly scan of a few minutes. Highly sensitive PVDF transducer allows detection of structures 3.8mm below the human skin surface with per pulse energies of only 25μJ. The newly developed system overcomes limitations of previously reported scanning optoacoustic microscopy and mesoscopy implementations, offering a major leap forward in terms of clinical usability, laser safety, effective penetration depth and spectral unmixing capabilities.

Acoustic-resolution optoacoustic microscopy (AR-OAM) visualizes internal tissue structures at millimeter to centimeter scale depths with high spatial resolution. The imaging performance mainly depends on the geometry and detection characteristics of the ultrasound transducer. Reconstruction methods incorporating transducer effects are essential to optimize achievable resolution, contrast and overall image quality. Model-based (MB) reconstruction has been shown to provide excellent imaging performance in several optoacoustic embodiments, due to its capacity to accurately model the transducer. However, the applicability of MB reconstruction methods in AR-OAM has been hampered by the high computational cost. Here, we propose an efficient MB reconstruction framework for largescale AR-OAM by considering scanning symmetries, which enabled capitalizing the computational power of a graphics processing unit. The suggested MB reconstruction method is shown to significantly improve the imaging performance of AR-OAM compared to synthetic aperture focusing technique, as validated in in vivo mouse skin experiment.

Hematoxylin and Eosin (H and E) staining is the gold standard for the majority of histopathological diagnostics but requires lengthy processing times not suitable for point-of-care diagnosis. Here we demonstrate a 266-nm excitation Ultraviolet Photoacoustic Remote Sensing (UV-PARS) and Scattering Microscopy system capable of virtual H and E 3D imaging of tissues in conjunction with with confocal fluorescence microscopy (CFM) for validation in thick tissues. We demonstrate the capabilities of this dual-contrast system for en-face planar and volumetric imaging of human tissue samples exhibiting high concordance with the gold standard of H and E staining procedures as well as confocal fluorescence microscopy. To our knowledge, this is the first near real-time microscopy approach capable of volumetric imaging unstained thick tissues with virtual H and E contrast.

A dual-modal optical imaging system combining photoacoustic remote sensing (PARS) and swept-source optical coherence tomography (SS-OCT) is presented. The PARS subsystem utilized a pulsed excitation beam at 532 nm confocal with a low-coherence interrogation beam centered at 830 nm to detect photoacoustic signals. The OCT subsystem employs a 1060 nm VCSEL swept source with a 60 kHz A-scan rate and 8 μm axial resolution in tissue. Volumetric images were acquired from carbon fibers and in-vivo biological tissues. To our knowledge, this is the first study demonstrating a combination of SS-OCT with optical-resolution photoacoustic microscopy for in-vivo, non-contact imaging of tissues.

Photoacoustic remote sensing (PARS) microscopy with multi-wavelength excitation and spectral unmixing was recently reported for non-contact imaging of hemoglobin oxygen saturation. In this work, we aim to extend this technique to provide additional functional information on oxygen metabolic activity. Stimulated Raman scattering provides multi-wavelength PARS excitation for SO2 estimation, and is integrated with Doppler OCT for quantitative blood flow rate determination. Structural imaging is demonstrated in phantoms and in vivo angiography. To evaluate system performance, tube phantoms containing blood of varied oxygenation and flow rates were imaged. This represents progress towards deploying the technique for in vivo oxygen consumption monitoring.

We developed a handheld photoacoustic signal detector for sentinel lymph node (SLN) localization. The detector consists of a solid-state dye laser and a transparent ultrasound transducer (TUT). The TUT was designed as a focused-type. The TUT had an 8 MHz center frequency with a 30% bandwidth. Using the detector, we confirmed photoacoustic signals in a tube filled with methylene blue (MB) below 10-mm thick chicken tissues. We successfully performed in vivo photoacoustic detection for MB injected SLN localization and subcutaneously injected melanoma assessments. We believe that our detector will play an effective role in SLN localization and biopsy.

Ultrasound transducers used in photoacoustic imaging are bandlimited and have a limited detection angle, which degrades the reconstructed image quality. One way to address this problem is to have transducers with multiple frequency bands with acquisition around the sample. This approach is expensive and it is not feasible for systems with a handheld probe using a linear transducer array. In this work, we aim to develop a deep learning method for photoacoustic reconstruction from bandlimited and limited-view data. We have developed a Generative Adversarial Networks (GANs)-based framework conditioned with a photoacoustic measurement for image reconstruction. In this way, the transducer used in the measurement can be incorporated and the generator trying to compensate for the limited data problem. We have developed the model for a handheld photoacoustic system using a linear transducer array with 128 elements having a center frequency of 7MHz and -6dB bandwidth from 4-10 MHz. We trained the network using simulated blood vessel images and tested it on in vivo measurements from the human forearm. We have compared the reconstructed images using the proposed method with the time-reversal on simulated data for detection using a bandlimited and directional transducer and compared it using the ground truth. Further, we compare our results to the in vivo images from the system which uses a delay and sum algorithm. The results from both simulations and experiments show that the proposed approach can remove bandlimited and limited view artifacts and can achieve a better image quality.

The recovery of the initial pressure rise distribution tends to be an ill-posed problem in the presence of noise and when limited independent data is available, necessitating regularization. The standard regularization schemes include Tikhonov, l1 -norm, and total-variation. These regularization schemes weigh the singular values equally irrespective of the noise level present in the data. This work introduces a fractional framework to weigh the singular values with respect to a fractional power. This fractional framework was implemented for Tikhonov, l1-norm, and total-variation regularization schemes. The fractional framework outperformed the standard regularization schemes by 54% in terms of observed contrast/signal-to-noise-ratio.

Delay-and-sum (DAS) beamforming is the most common non-adaptive beamforming algorithm in photoacoustic (PA) and ultrasound (US) imaging due to its simple implementation. However, it suffers from various drawbacks such as low image resolution, low contrast, and higher sidelobes. Several beamforming algorithms and weighting method was developed in last few years to resolve this problems. Herein, we introduce a new weighting factor named p th root coherence factor (PRCF) to enhance the DAS image quality in terms of various aspects. The proposed method provides better resolution and signal-to-noise ratio (SNR) than the conventional DAS and DAS+CF. We quantitatively compared the image quality metrics of the proposed algorithm with the conventional algorithms. It is observed that our proposed algorithm shows better spatial resolution, SNR, and lower sidelobes for both simulated as well as experimental data. The quantitative results of the experiment (using wire targets) shows that PRCF leads about 55% and 17% improvement in FWHM in comparision with DAS and DAS+CF respectively.

In this paper, a novel Delay and Glow (DAG), back projection-based photoacoustic reconstruction, for point source recovery is presented. The projections of the absorber coefficients are delayed and weighed based on the transducer directivity sensitivity and matched with the other projections from other transducer elements leading to glow the point source at the exact location. The DAG was tested with 2-D experimental and simulation studies and compared with conventional delay and sum (DAS) reconstruction method. The proposed algorithm outperforms the DAS in terms of contrast to noise ratio (CNR) and RMS errors.

In this work, we present the open source “Simulation and Image Processing for Photoacoustic Imaging (SIMPA)” toolkit that facilitates simulation of multispectral photoacoustic images by streamlining the use of state-of-the-art frameworks that numerically approximate the respective forward models. SIMPA provides modules for all the relevant steps for photoacoustic forward simulation: tissue modelling, optical forward modelling, acoustic modelling, noise modelling, as well as image reconstruction. We demonstrate the capabilities of SIMPA by performing image simulation using MCX and k-Wave for the optical and acoustic forward modelling, as well as an experimentally determined noise model and a custom tissue model.

Delay and Sum (DAS) is one of the most prevalent and common beamforming algorithms used in ultrasound and photoacoustic image (PAI) reconstruction. This beamforming algorithm is mostly used due to its simple implementation and real time capability. However, it has several drawbacks such as high level side lobes, low image resolution and poor contrast. To address these issues, a new adaptive weighting factor has been proposed in this paper, named delay-multiply-sum-to-standard-deviation-factor (DMSSF). It improves all kinds of drawback like, lateral resolution, signal to noise ratio (SNR), and reduces side lobes of the reconstructed image compare to the other conventional methods like DAS, DAS+CF. The proposed weighting technique leads to get narrower main lobe and make the target much more detectable with respect to background. This novel method contributes significantly to the improvement of linear array based clinical photoacoustic imaging and expands the horizon of DAS image reconstruction and its potentiality.

In circular scanning geometry based Photoacoustic tomographic (PAT) imaging systems, the axial resolution is spatially invariant and is limited by the bandwidth of the detector. However, the tangential resolution is spatially varying and is dependent on the aperture size of the detector. Conventionally, large aperture size detectors are the preferred choice for detection element in circular view PAT imaging systems but it hampers the tangential resolution. Although several techniques have been proposed to improve the tangential resolution, they are also hindered by their inherent limitations. Herein, we propose a deep learning architecture to counter the spatially variant tangential resolution in circular scanning PAT.We used a (U-Net) based CNN architecture to improve the tangential resolution of the acquired PAT images. Our results suggest the proposed deep learning architecture improves the tangential resolution of the acquired by five folds, without compromising the image quality.

Photoacoustic imaging (PAI) has the potential to revolutionize healthcare due to the valuable information on tissue physiology that is contained in multispectral signals. Clinical translation of the technology requires conversion of the high-dimensional acquired data into clinically relevant and interpretable information. In this work, we present a deep learning-based approach to semantic segmentation of multispectral PA images to facilitate interpretability of recorded images. Based on a validation study with experimentally acquired data of healthy human volunteers, we show that a combination of tissue segmentation, sO2 estimation, and uncertainty quantification can create powerful analyses and visualizations of multispectral photoacoustic images.

Tissue heterogeneities and the presence of strong optical absorbers hinder the applications of quantitative photoacoustic imaging (PA). Having an accurate description of optical fluence distribution in heterogeneous media is essential to obtain absorption estimates. While Monte Carlo simulations and diffusion models are frequently used to approximate fluence distribution, they ignore the unique heterogeneities across imaged samples or individuals. This paper presents a method to estimate the optical fluence distributions in two-dimensional PA images applying image-based iterated corrections of the fluence map. The method was validated using a virtual tissue phantom and consecutive light transport simulations. PA images were generated synthetically, based on the true light distribution, and were subsequently used to correct the estimated fluence distribution. The correlation between the original phantom and each corrected image was measured to quantify the accuracy of the method. We found that each iteration resulted in an increase in the correlation and a qualitative improvement between the original phantom and the corrected image. This method is expected to improve the accuracy of PA imaging, especially in multi-wavelength applications and those affected by strong absorbers such as contrast agents.

Usage of low energy alternatives, such as light emitting diode (LED) and pulsed laser diode (PLD), to solid state lasers as a source of illumination in photoacoustic tomography (PAT) is being actively investigated for several preclinical and clinical applications due to its inherent advantages such as portability, low cost and high pulse repetition frequency (PRF). However, the photoacoustic signal acquired from such low energy sources particularly LED, have weak light absorption-to-ultrasound conversion efficiency. Due to the weak nature of the generated PA signals, noises from external sources, such as, electronic noise, jitter, etc. have a more pronounced detrimental effect on the quality of the reconstructed LED-PAT images resulting in low Signal-to-Ratio (SNR) values. The high PRF of LED-PAT systems is usually exploited to improve the SNR by performing averaging of several hundreds of frames. However, this is a time-consuming procedure and decreases the frame rate achievable using the imaging system. In this work, we demonstrate that by employing signal recovery strategy at sub-λ array locations along with a denoising filter, it is feasible to improve image quality and reduce noise from LED-PAT images acquired using commercially available LED-PAUS imaging system (AcousticX, Cyberdyne Inc., Ibaraki, Japan). This method was tested on phantom and in-vivo data acquired using the above-mentioned system and was found to yield reduction in background noise of up to 12 dB compared to mere averaging Also, by applying the proposed method, we achieved two-fold improvement in lateral resolution.

Photoacoustic imaging is a new imaging technology in recent years, which combines the advantages of high resolution and rich contrast of optical imaging with the advantages of high penetration depth of acoustic imaging. Photoacoustic imaging has been widely used in biomedical fields, such as brain imaging, tumor detection and so on. The signal-tonoise ratio (SNR) of image signals in photoacoustic imaging is generally low due to the limitation of laser pulse energy, electromagnetic interference in the external environment and system noise. In order to solve the problem of low SNR of photoacoustic images, we use feedforward denoising convolutional neural network to further process the obtained images, so as to obtain higher SNR images and improve image quality. We use Python language to manage the referenced Python external library through Anaconda, and build a feedforward noise-reducing convolutional neural network on Pycharm platform. We first processed and segmated a training set containing 400 images, and then used it for network training. Finally, we tested it with a series of cerebrovascular photoacoustic microscopy images. The results show that the peak signal-to-noise ratio (PSNR) of the image increases significantly before and after denoising. The experimental results verify that the feed-forward noise reduction convolutional neural network can effectively improve the quality of photoacoustic microscopic images, which provides a good foundation for the subsequent biomedical research.

Photoacoustic Tomography (PAT) is a novel biomedical imaging modality, whose reconstructed image is based on the target responds of the instantaneous pulse laser excitation. The target emits photoacoustic (PA) signal upon the laser impulse excitation, which contains the information of light absorption of the target. To reconstruct a high quality image of PAT, recovering the full bandwidth of the PA signal is necessary. While practical transducers cannot cover the full bandwidth of the PA signal, and has low sensitivity for ultralow frequency PA signal that induce the PA image distortion. In this study, a broadband PA signal enhancement method with morphological frequency convolution is proposed to recover PA signal. From the original reconstructed PA image frequency analyses, we get the convolution kernels and process the PA signal. The recovered full-bandwidth signal reconstructed the PA image more realistic and with less distortion.

Capacitive micromachined ultrasound transducers (CMUTs) are gaining more interest for photoacoustic imaging due to its low-cost, high bandwidth and flexibility in size and shape. However, the beampattern of CMUTs usually exhibits wide mainlobes and high sidelobes, degrading the imaging resolution and contrast. We propose to improve the beampattern with optimization of apodization by imposing conditions on the angular distribution of the signal energy received from a PA point source to minimize the sidelobes magnitude and maintain the mainlobe energy. Both simulations and experiments results demonstrate that the proposed apodization suppress the sidelobes up to 30dB when compared with Uniform weights.

Multispectral Photoacoustic Tomography (MSPAT) is capable of visualizing the concentration distribution of various chromophores in biological tissues, where the unmixing process is usually performed with the spectral fitting method that requires the absorption spectral signatures of all chromophores in the tissue to be known. However, due to the changes of spectral signatures of some exogenous contrast agents in vitro and in vivo, the conventional fitting method will be hindered. Although the blind unmixing algorithms do not require the exact absorption spectrum of each chromophore in advance, it is often sensitive to noise, which may lead to low quantitative results. Considering that the non-negativity of concentration distribution and absorption spectra of the chromophores as well as the sparsity of concentration image of exogenous contrast agent in the gradient domain, we herein propose a modified MSPAT implementation that utilizes a non-negative matrix factorization iterative reconstruction framework with the support of a priori information of spectral signature of oxy-/deoxy-hemoglobin and valid sparsity regularization during the iteration. Consequently, the spectral signature of the exogenous contrast agent and the concentration distribution of each chromophore can be recovered simultaneously. The proposed approach has been validated by simulation and in vivo experiments, exhibiting promising performances in image fidelity even when the multi-wavelength photoacoustic tomographic images used for spectral unmixing are affected by noise or reconstruction artifacts.

Photoacoustic (PA) computed tomography (PACT) combines the superiorities of both optical imaging and ultrasound imaging, which is based on the generation of acoustic signal (PA wave) by short pulsed laser light. However, in many applications, the sensor array can only partially enclose the target, resulting in limited-view setup and image reconstruction with severe artifacts. Standard reconstruction always induces artifacts using limited-view signals, which are influenced by limited angle coverage of transducers, finite bandwidth, and uncertain heterogeneous biological tissue. To address these issues, in this paper, a deep learning based approach is proposed to compensate the missing data due to limited view (e.g. only 90 degrees coverage). To acquire the missing data from the other 270 degrees’ view, we trained an end-to-end network to recover the limited-view PA data, which have been delayed to form a pressure map in region of interest.

Temperature dependence of photoacoustic (PA) signal is a crucial factor in PA temperature sensing, imaging, and monitoring of thermal therapies. In this study, we report theoretical and simulation studies to describe the temperature dependence of PA-signal and hence the Gruneisen parameter. A light-absorbing organic dye (Methylene blue) is taken as the sample, and the variation of PA-signal against change in temperature is plotted from the simulated data. Experiments were conducted, employing a home-built photoacoustic microscopy imaging system to measure PA signal, for the validation study. A CW-laser beam (of wavelength, 642nm) is used to vary the temperature of the organic dye during the experiment, and the average PA-signal is measured from the acquired PA image. The change in temperature of the sample due to the laser irradiation is noted separately. PA-signal strength and its amplification against temperature change is plotted from the experimental data. It is observed that the experimental results are well-matched with the theory and simulated data.

One of the key limitations for the clinical translation of photoacoustic imaging is its penetration depth, which is linked to the tissue maximum permissible exposures (MPE) recommended by the American National Standards Institute (ANSI). Here, we propose a method based on deep learning in order to enhance the signal-to-noise ratio of deep structures in the brain tissue. The proposed method is evaluated in an in vivo sheep brain imaging experiment. We believe this method can facilitate clinical translation of photoacoustic technique in brain imaging, especially in neonates via transfontanelle imaging.

Photoacoustic imaging technology is a new functional imaging method in biomedical application field. It is based on photoacoustic effect. It combines the advantages of high resolution and rich contrast of optical imaging with the advantages of high penetration depth of acoustic imaging. It can be used for noninvasive detection of structural, functional and molecular abnormalities in biological tissues, Multi scale information of micro and macro world is detected. Photoacoustic microscope is a micro imaging device based on photoacoustic effect. It can measure the amplitude and phase of photoacoustic signals generated at different positions on the solid surface, so as to determine the optical properties, thermal properties, elasticity or geometric structure of samples. However, the traditional optical resolution photoacoustic microscopy imaging system usually uses strong focused Gaussian beam, which has long imaging time and weak penetrating ability, so it is difficult to achieve fast imaging of solid inner surface. The vortex beam has the characteristics of spiral wavefront structure, circular distribution of light intensity, definite orbital angular momentum and phase singularity. Based on the above characteristics, vortex light has high directivity, wide frequency band and wide bandwidth, which can be used for deep and efficient penetrating imaging of inner surface. In this paper, Matlab is used to generate the ideal and transmitted vortex light phase diagram and spot, and then k-wave simulation software is used to build the virtual simulation platform of vortex photoacoustic microscopy imaging system. In the MATLAB simulation, the vortex light beam irradiates on the vascular cells to image the vascular tissue. The results show that vorticity light has better penetrating ability and faster imaging speed than Gaussian light. This study is helpful to detect the deep structure and properties of vascular cells by using vortex light, and put forward a new idea for the deep fast imaging of solid surface.

The study of the relationship between the spectral characteristics of the photoacoustic signal and the size, density and shape of the absorber is of great significance to image reconstruction and is of great practical significance to the better application of photoacoustic imaging in the medical field. This paper uses the simulation software COMSOL Multiphysics to design a two-dimensional simulation model based on finite element to study the relationship between the spectral characteristics of the photoacoustic signal and the properties of the absorber. In this study, the model consists of three parts: 1) water layer; 2) short pulse laser source (wavelength of 840nm); 3) gastric tumor tissue. The laser point source is located in the middle of the upper water layer. By solving the diffusion equation and the biological heat equation, respectively, the propagation of light in the water layer and the temperature change in biological tissues are simulated. When the absorber is irradiated by a Gaussian pulsed laser, due to the extremely short time, the absorber can be regarded as adiabatic expansion after absorbing energy, thereby generating ultrasonic waves. Using the finite element analysis method, the complex situation of photoacoustic imaging is transformed into the coupling of multiple physical fields, and the photoacoustic signal is obtained by numerical calculation of partial differential equations. Analyzing the simulation results, it is found that the spectral characteristics of the photoacoustic signal are closely related to the size of the absorber. The relationship obtained in this simulation experiment is: the spectral intercept and the size of the absorber have a power function relationship, the larger the size, the larger the spectral intercept , And the growth rate increases with the increase of the size; the spectral slope and the size of the absorber also have a power function relationship, the larger the size, the smaller the spectral slope, and the rate of change of the slope decreases with the increase of the size. For the relationship between the spectral characteristics and density of the photoacoustic signal, the intercept and slope characteristics are opposite. As the density of the photoacoustic absorber increases, the spectral slope of the photoacoustic signal increases, and the spectral intercept of the photoacoustic signal decreases. The photoacoustic signals and spectrograms of different shapes of absorbers have their own characteristics. The research results in this paper can promote the research of photoacoustic imaging and can better apply photoacoustic imaging in the medical field.

X-ray induced acoustic (XA) imaging is a promising imaging technique that can identify X-ray absorption contrast with much reduced ionizing radiation. In this study, we developed the X-ray induced acoustic imaging system that uses a synchrotron and a single-element focused ultrasound transducer. The synchrotron has an energy of 4-20 keV, a pulse width of 30 ps, a pulse-repetition period of 2 ns, and a bunch-repetition period of 940 ns. Due to the short pulse repetition, we obtained the XA amplitude in the frequency domain. Then, we successfully obtained 2D phantom imaging with a lead rectangular target.

We developed a photoacoustic imaging (PAI) system based on a solid-state dye laser. Using the system, PA images of a tube filled with methylene blue (MB) below 3.9 cm chicken tissue were successfully obtained. After injecting MB into a rat, MB dyed sentinel lymph node (SLN) under chicken tissue was well described. In addition, it was confirmed the change in PA amplitude of the SLN over time in the PA images. Additionally, lymph vessels, SLN, and blood vessels were also successfully identified in multispectral PA images. These results demonstrate the clinical potential of the system in SLN detection.

Photoacoustic imaging is a hybrid technique which offers high contrast and specificity of optical imaging techniques and excellent spatial resolution of ultrasound imaging. In recent years, there has been tremendous developments in this field and photoacoustic imaging is now facing an exciting challenge of clinical translation. We developed a multispectral LED-based photoacoustic and ultrasound imaging system (AcousticX), which has been already proven to be useful in multiple preclinical and clinical superficial imaging applications. In the first version of AcousticX, acoustic detection was performed using linear array ultrasound probes with center frequencies of 5, 7 and 10 MHz. With these probes, we were able to achieve an imaging depth of 1 cm in tissue in vivo with spatial resolution of around 150-250 μm. However, it is important to improve the imaging depth for exploring wide range of deep-tissue applications. In this work, we developed a new broadband 2.5 MHz ultrasound probe to improve the imaging depth. Using this ultrasound probe and 850 nm LED arrays, we performed phantom, ex vivo and in vivo human volunteer studies and achieved an imaging depth of 2.5^-3 cm. We compared the imaging performance of the newly developed probe with the already available US probes and conformed that the 2.5 MHz probe is 3-4 times more sensitive with spatial resolution suitable for deep-tissue applications. When imaging the brachial artery of a human volunteer, we achieved an imaging depth of 2.6 cm at a frame rate of 6 Hz, which is the highest reported in vivo imaging depth in LED-based photoacoustic imaging. We believe that this is the first step towards real-time deep tissue LED-based photoacoustic imaging with potential in multiple clinical applications.

The study of the interaction between laser and brain tissue has important theoretical and practical significance for brain imaging. A two-dimensional simulation model that studies the propagation of light and heat transfer in brain tissue based on finite element has been developed by using the commercial finite element simulation software COMSOL Multiphysics. In this study, the model consists of three parts of 1) a layer of water on the surface of the brain, 2) brain tissue and 3) short pulsed laser source (the wavelength is 840nm). The laser point source is located in the middle of the layer of water above the brain tissue and irradiates the brain tissue. The propagation of light in brain tissue was simulated by solving the diffusion equation. And the temperature changes of gray matter and blood vessels were achieved by solving the biological heat transfer equation. The simulation results show that the light energy in the brain tissue decreases exponentially with the increase of penetration depth. Since the cerebral blood vessels have a stronger absorption on light compared with the surrounding tissues, the remaining light energy of the blood vessels in the cerebral cortex is ~ 85.8% of the remaining light energy in the surrounding gray matter. In the process of biological heat transfer, due to more light deposition in blood vessels, the temperature of blood vessels is 0.15 K higher than that of gray matter, and the temperature of gray matter hardly changes. This research is helpful to understand the propagation of light in the brain and the interaction between them, and has certain theoretical guiding for the optical imaging of the brain.

Tissue trauma often causes hematoma formation. Recently, we proposed to use the optoacoustic technique for hematoma detection and performed studies on hematoma monitoring and imaging in the brain and skin. It is well known that methemoglobin is produced during hematoma aging. In this work we propose to use the optoacoustic technique for staging, monitoring, and imaging of hematomas during their formation and aging. We measured optoacoustic spectra of methemoglobin in the 800-950 nm spectral range in which it has strong absorption and demonstrated that this spectral range can be used for of hematoma staging, monitoring, and imaging.

In this work, we demonstrate the use of parylene C to reduce the ring down time and enhance the fractional bandwidth of a piezoelectric micromachined ultrasound transducer (PMUT). We further study the effect of increase in thickness of parylene C on the vibration response of a PMUT such as the fundamental resonant frequency and the maximum static deflection. It is found that the increase in the thickness of the deposited parylene C film, decreases the quality factor of a PMUT, following a linear trend, with negligible effect on its fundamental resonant frequency. This can be considered to be an important finding as far as the field of ultrasound imaging is concerned, since this technique paves the way to control the axial resolution of the B-mode ultrasound scan by simply tuning a PMUT’s quality factor.

Aortic atherosclerotic plaque rupture can cause cerebral and cardiac infarction. Detecting lipid-rich vulnerable plaque early is important to prevent plaque rupture. However, using conventional modalities to evaluate such plaques is difficult. Photoacoustic imaging can elucidate tissue characteristics. Some lipid-rich plaque evaluations have used intravascular photoacoustic imaging systems. A handheld photoacoustic imaging system was developed to reduce invasiveness and to ease handling. Lipid-rich plaque detection capability was evaluated using phantom experiments. Mimic plaques (comprising oleic acid cholesterol and linoleic acid cholesterol) are embedded into a silicone tube. The silicone tube is filled with ovine blood. These objects were fixed in a water with black ink and biological tissue (chicken breast). For observation, laser light is guided to the model phantom surface by an optical fiber bundle close to the linear ultrasound probe. The photoacoustic signal distributions are then recorded as photoacoustic images. The photoacoustic images, obtained for which wavelengths where lipid light absorbance is high, show strong photoacoustic signals from the mimic plaque at a depth of human carotid artery. At wavelengths of 1150–1300 nm, similarity between photoacoustic spectra and the absorption spectrum of lipid was evaluated by calculating the correlation coefficient in photoacoustic images. Results show high correlation at the mimic plaque. Results demonstrate that the detection of lipid-rich plaque can be done, even optical properties (e.g. scattering coefficient and absorption coefficient) of the surrounding tissue were inhomogeneous. Future studies must conduct in vivo experiments and examine optimization to improve SNR.

A non-destructive elastic properties detection method based on 3×3 fiber-optic coupler based interferometer is proposed. The relationship of speed versus frequency components of surface acoustic wave (SAW) propagating through the surface of an object gives clues of its physical properties such as elasticity, density, and thickness, etc. In order to reliably observe the SAW signals of objects where physical contact is not allowed, we constructed an interferometer based on the fiber-optic coupler and measured the SAW signal. The performance of the system was verified with well-defined layer phantoms which were made in various structures and analyzed the elasticity and structure of the samples.

We discuss the characterization and analysis of ultrasonically sculpted virtual optical waveguides in scattering media using a novel physics-based renderer. Our renderer is physically accurate, unbiased, and fast. Unlike other simulators, our renderer can handle heterogeneous refractive index profiles in scattering media. Using the renderer, we characterized the effect of different parameters of virtual optical waveguides to enhance the overall light throughput in transparent and scattering media. The simulator can potentially be used for analysis-by-synthesis and design of innovative acousto-optics systems, capable of generating complex virtual elements in scattering media.

Low cost and high-power LED’s are replacing highly expensive and bulky Lasers in photoacoustic imaging (PAI) technology. LEDs bring the opportunity to image samples at a higher repetition rate (in kHz) compared to the conventional Q switched lasers (typically upto 20 Hz) and thus offer high frame rate and averaging power while maintain real-time imaging capability. In order to make a complete switch from Laser to LEDs, a proper understanding of this newly emerging class of LED arrays is important, for e.g., beam divergence, beam focus, coherence, time-dependent power and wavelength stability, penetration depth and sensitivity, etc. We performed characterization and optimization experiments on different tissue mimicking phantoms with various optical scattering and absorbing properties using a commercially available AcousticX PAI system with customized 3D printed holders for the LED array. The axial and lateral positions of LED arrays with respect to the acoustic probe to image deep lesions upto 1.5 cm were optimized. We also report the sensitivity of the system and Signal-to-noise-ratio (SNR) dependency of the LED arrays’ axial and lateral positions. Finally, we also demonstrate the adaptability of our custom designed, 3D printed variable angle and distance holder to perform deep tissue ultrasound and photoacoustic imaging probe on phantoms of with absorbers at different depth and in subcutaneous tumors and compare it with traditional laser based photoacoustic imaging systems.

Photoacoustic microscopy (PAM), an emerging biomedical imaging technology, has provided the label-free imaging of biomolecules with the aid of superior optical contrast in them. A pulsed laser with wavelength of 532 nm is widely used to visualize the microvascular structures of small animal or human in vivo. Employing a customized 1-axis high-speed scanning device and ring-shaped ultrasound transducer (RUT), we developed a high-speed PAM system which enables wide field-of-view (FOV) imaging with high sensitivity. The optical and ultrasonic beam can be automatically aligned without opto-ultrasound beam combiner (OUC) by transmitting the laser through the hole in the transducer. Especially the transducer used in our system was designed to have a long focal length and a large sensing area to achieve wide-field imaging with high sensitivity. To verify the high sensitivity of the developed system, we performed ultrasonic pulse-echo experiments on quartz and PA in vitro imaging on leaf skeletons. Compared to the conventional beam alignment method which adopts OUC, the enhancement of signal-to-noise ratio (SNR) was 15 dB and 12 dB in those experiments, respectively. In addition, the high-speed scanner was designed to scan up to 12 mm long at resonant frequency of 80 Hz and to cover the wide sensing area of the transducer. By utilizing these specifications, the microvascular structures in a whole mouse ear could be imaged within 30 seconds without any additional image registration. The developed system could be a practical imaging platform for future studies in microvasculatures such as hemodynamic changes, oxygen saturation, and metabolism.

Photoacoustic microscopy (PAM) has demonstrated a wide range of medical and biomedical applications by providing vascular information. Since the size of PAM images is usually extremely large, an efficient compression method can help in the storage and transportation of these images. We have implemented multiple signal compression methods in LabVIEW with a high compression ratio, and an execution time below the repetition rate of the pulsed laser. The qualitative and quantitative results of ex vivo vasculature imaging with and without compression showed nearidentical images with significantly smaller size.

Acoustic resolution photoacoustic microscopy (AR-PAM) provides high imaging resolution at an imaging depth beyond the optical diffusion limit. In these systems, the lateral resolution can be improved by using an ultrasound transducer (UST) with high numerical aperture (NA). However, increasing the NA of UST leads to a decreased depth of focus (DOF), resulting in deterioration of resolution in the out-of-focus regions. Image processing algorithms are commonly employed to improve the resolution outside the focal region. In this work, we propose a deep learning method to enhance the images obtained using AR-PAM. AR-PAM images were first simulated using k-wave toolbox in MATLAB. Convolutional neural network (CNN) based architecture was trained using these simulated images. The resulting model was then tested on experimentally collected AR-PAM images. Our results demonstrated that this method can significantly improve the outof-focus resolution of AR-PAM, thereby enhancing the image quality.

As an emerging nondestructive imaging technology recently, photoacoustic imaging (PAI), which is based on photoacoustic effect, combines the advantages: the high resolution and contrast of optical imaging and the high penetration depth of acoustic imaging. Thereinto, as a branch of photoacoustic imaging, photoacoustic microimaging inherited the advantages of photoacoustic imaging. The unique focusing mode of photoacoustic microimaging can meet the requirements of higher resolution in biological imaging, thus, it gained extensive applications in medical science field. However, on account of using high numerical aperture objective lens strongly focus on Gaussian beam, traditional photoacoustic microimaging system has shallow depth of imaging field, and its transverse resolution and signal-to-noise ratio deteriorate rapidly outside the focal point, limiting the velocity of large volume imaging. Owing to solve these problems, in this paper, we build a simulation platform for Airy beam photoacoustic microscopy based on K-Wave simulation toolbox. This platform uses Airy beam to inspire initial Photoacoustic signal in large volume and K-Wave simulation toolbox to simulate the propagation, recording and reconstruction process of Photoacoustic signal. As nondiffraction beam, Airy beam features the capacity of large depth of field, thus, its application could reach the requirement of large depth of field imaging of Photoacoustic microscopy system. Measuring the performances of the constructed Photoacoustic microscopy system, we constructed three-dimensional imaging of the blood vessel. By simulating A-Scan, B-Scan and C-Scan, we measured the performances of this system, such as axial resolution, transverse resolution and depth of field. Meanwhile, the three-dimensional imaging of the vertically tilted fiber also verified the three-dimensional imaging capability of the Airy beam photoacoustic microscopy simulation platform. The establishment of the simulation platform has a significance for the theoretical research of photoacoustic microscopy and its application in biomedicine.

Photoacoustic tomography is a new medical imaging technology with the advantages of high resolution, high contrast and high penetration depth. There are three common photoacoustic imaging methods in practical applications: photoacoustic microscopic imaging (PAM), photoacoustic computed tomography (PACT), photoacoustic tomography (PAE). As an important branch of photoacoustic imaging, photoacoustic microscopy combines high contrast of optical imaging with high resolution of ultrasonic imaging. In photoacoustic microscopy, acousto-optic coupling prism is a very important component, which is usually composed of irregular prism and spherical concave acoustic lens at the bottom. Its function is to carry out optical transmission and ultrasonic detection. The ultrasonic depth of field of spherical concave acoustic lens is limited. In order to overcome this defect, researchers propose to use conical concave acoustic lens to produce Bessel sound beam to realize large depth of field ultrasonic detection. But the conical concave acoustic lens affects laser focusing and imaging. In order to solve this problem, we propose an optimization method to eliminate the influence of conical concave acoustic lens on beam transmission. A calibration mirror is added to the acousto-optic coupling prism with conical concave acoustic lens at the bottom, and the deterioration of the cone concave acoustic lens to the beam transmission is eliminated by optimizing the surface shape and thickness of the calibration mirror by Zemax. The optimization effect is evaluated by analyzing the spot. The simulation results show that the optimization method can eliminate the influence of the conical concave acoustic lens on the beam transmission, make the focal point and the focal point keep the coaxial focus, and improve the detection efficiency of the photoacoustic signal. This work is of theoretical significance for the systematic study of large depth of field photoacoustic microscopy.

In recent years, photoacoustic imaging, an emerging nondestructive biomedical imaging technology, has shown great potential for early diagnosis of diseases with its advantages of highly sensitive optical contrast and high resolution. It is a hard project to collect a large number of pathological medical images by using photoacoustic imaging. How to compress large amounts of data, rapid transmission and storage of important value information has become an urgent problem to be solved. In this paper, build a virtual simulation platform for compressed sensing photoacoustic tomography by combining compressed sensing reconstruction algorithms with photoacoustic imaging based on the k-wave simulation toolbox. On the one hand, compressed sensing can reduce sample rates, accelerated the speed of imaging. On the other hand, it can modify the demands for hardware devices and facilitate to transmit and store of data. The k-wave simulation toolbox is used to build simulation models for simulating the propagation of photoacoustic fields, recording of photoacoustic signals, and image reconstruction. We validated the performance of the simulation platform by imaging the vascular network. The results show that the virtual simulation platform compressed sensing photoacoustic tomography can achieve high-quality photoacoustic imaging with less data. The virtual platform can provide theoretical guidance for the application of compressed sensing in photoacoustic imaging.

We have developed a fast, wide field-of-view, simple-to-implement laser scanning photoacoustic microscopy (PAM) system that is capable of imaging of the whole rat brain in < 1s. The system utilizes galvo scanners and a novel scanning scheme, that can counter the trade off between imaging speed and scanning area. We performed in-vivo imaging of rat brain to demonstrate the imaging capability of the system.

Photoacoustic imaging technology is a new imaging technology has emerged in recent years, which combines the advantages of optical imaging and acoustic imaging, optical imaging and acoustic imaging have their own advantages, optical imaging has rich contrast , acoustic imaging has high resolution and high penetration. Photoacoustic imaging has been widely used in biomedical fields, such as brain imaging, tumor detection. As an important branch of photoacoustic imaging technology, optical-resolution photoacoustic microscopy can be applied from cells to tissues. However, the traditional optical-resolution photoacoustic microscopy usually uses a tight focused gaussian beam, the depth-of-field is small, and it is difficult to achieve rapid large volumetric imaging. In order to overcome this issue, researchers have proposed many solutions, one of which is to replace gaussian beams with non-diffracted beams. Bessel beam, as a nondiffracted beam, has a large depth of field. We applied it to optical -resolution photoacoustic microscopy. In reality, the cost of building such a Bessel-beam photoacoustic microscopy is relatively high and the system is complicated. Therefore, a virtual simulation technology is urgently needed for simulation research. Here, we proposed a virtual simulation platform of Bessel-beam photoacoustic microscopy based on k-Wave. The platform generates Bessel beam in the focus area of the objective lens by the circular slit, and the Bessel beam irradiates on the sample to generate the initial photoacoustic pressure field in a wide depth range. The k-Wave is used to simulate the propagation of photoacoustic fields, record photoacoustic signals and image reconstruction. The three-dimensional imaging of vascular network further verifies the large depth of field of Bessel-beam photoacoustic microscopy simulation platform. The establishment of the simulation platform is of great significance to the theoretical research of Bessel-beam photoacoustic microscopy and its application in biomedicine.

Photodynamic therapy (PDT) is a photochemistry based cytotoxic technique that imparts cellular damage via excitation of a photosensitizer with drug-specific wavelength of light. Previously we and other groups have shown the efficacy of photoacoustic imaging in predicting treatment response of vascular targeted photodynamic therapy. In this work we evaluate the efficacy of photoacoustic imaging to monitor cellular targeted photodynamic therapy and its role in predicting recurrence. The dose at the treatment site for I PDT is determined by three factors: photosensitizer (PS) concentration, oxygenation status and delivered light irradiance. Most of the FDA approved photosensitizers in their triplet-excited state generate cytotoxic species by reacting with the ground state oxygen that is available in the surrounding environment. Given the inter- and intra-subject variability in the uptake of the photosensitizer and the distribution of oxygen in the tumor, understanding the interplay between these dose parameters could aid in determining photodynamic therapy efficacy. Using various subcutaneous and orthotopic mouse models we demonstrate both oxygenation status of the tumor prior to the treatment and the change in oxygen saturation 48 hrs post treatment can predict efficacy of Aminolevulinic acid (ALA) based cellular PDT with <92% sensitivity and specificity. We further compare the predictive capability of photoacoustic imaging with the more predominantly used fluorescence imaging and immunohistochemistry techniques.