Performance Comparison of Feature Generation Algorithms for Mosaic Photoacoustic Microscopy

Choroidal neovascularization (CNV) is a hallmark of advanced age-related macular degeneration and is a leading cause of irreversible vision loss and blindness in the world. There is a lack of imaging modalities that can detect CNV early. Photoacoustic microscopy (PAM) combines acoustic and optical imaging to create high-resolution images that can delineate microvasculature non-invasively and permit for visualization of CNV. However, to distinguish CNV from native microvasculature, molecular contrast agents can be applied to increase the sensitivity of PAM imaging. In this study, functionalized indocyanine green (ICG) with RGD ligands (ICG-RGD) was synthesized and applied to in vivo imaging of CNV in the rabbit retina using a custom-built high-resolution PAM imaging system. RGD ligands selective binds to integrins present in neovascularization. The CNV model was created in three New Zealand White rabbits via subretinal injection of human vascular endothelial grow factor (VEGF-165). Three-dimensional in vivo PAM images of CNV were acquired before and after intravenous injection of 400 µL ICG-RGD at a concentration of 2.5 mg/mL over a period of 14 days. In addition, color fundus photography and fluorescence imaging were also acquired. This enables visualization of the newly developed CNV as well as monitoring the changes in CNV over time. With the administration of ICG-RGD, PAM signal amplitudes enhanced up to 15.7-fold at day 1 post-injection and persisted up to 5 days. The PAM results were also confirmed by fluorescence imaging. Biosafety studies show no systemic toxicity of the ICG-RGD. These studies demonstrate the potential of molecular PAM imaging for the characterization of microvasculature pathologies.

Retinal safety evaluation of photoacoustic microscopy

Visualizing ocular vasculature is important in clinical ophthalmology because ocular circulation abnormalities are early signs of ocular diseases. Photoacoustic microscopy (PAM) images the ocular vasculature without using exogenous contrast agents, avoiding associated side effects. Moreover, 3D PAM images can be useful in understanding vessel-related eye disease. However, the complex structure of the multi-layered vessels still present challenges in evaluating ocular vasculature. In this study, we demonstrate a new method to evaluate blood circulation in the eye by combining in vivo PAM imaging and an ocular surface estimation method based on a machine learning algorithm: a random sample consensus algorithm. By using the developed estimation method, we were able to visualize the PA ocular vascular image intuitively and demonstrate layer-by-layer analysis of injured ocular vasculature. We believe that our method can provide more accurate evaluations of the eye circulation in ophthalmic applications.

Non-human primates (NHPs) are crucial models for studies of neuronal activity. Emerging photoacoustic imaging modalities offer excellent tools for studying NHP brains with high sensitivity and high spatial resolution. In this research, a photoacoustic microscopy (PAM) device was used to provide a label-free quantitative characterization of cerebral hemodynamic changes due to peripheral mechanical stimulation. A 5 × 5 mm area within the somatosensory cortex region of an adult squirrel monkey was imaged. A deep, fully connected neural network was characterized and applied to the PAM images of the cortex to enhance the vessel structures after mechanical stimulation on the forelimb digits. The quality of the PAM images was improved significantly with a neural network while preserving the hemodynamic responses. The functional responses to the mechanical stimulation were characterized based on the improved PAM images. This study demonstrates capability of PAM combined with machine learning for functional imaging of the NHP brain.

Photoacoustic microscopy (PAM) enables structural and functional imaging at a microscopic level, playing a vital role in biomedical imaging. However, due to the limitations imposed by its scanning mechanism, PAM faces a trade‐off between spatial resolution and imaging speed. While deep learning has improved PAM imaging speed, the image reconstruction performance of existing methods under high downsampling ratios still needs improvement. To address these limitations, we propose UPAM‐KAN for undersampled PAM image reconstruction. This model is based on U‐Net and integrates dedicated Kolmogorov–Arnold Network layers into the tokenized intermediate representations to construct its backbone network. Furthermore, three feature fusion extraction modules are proposed to enhance details, extract multi‐scale features, and fuse shallow and deep features, respectively. Compared with the leading methods in undersampled PAM image reconstruction, UPAM‐KAN achieves significant SSIM improvements of 8.322% and 2.692% on the Leaf Vein and Mouse Cerebrovascular datasets with only 1.4% of fully sampled pixels, respectively. Moreover, for functional reconstruction, the model pre‐trained on public datasets achieves a 3.275% SSIM improvement in oxygen saturation at the 1/4 undersampling ratio. These results demonstrate that UPAM‐KAN efficiently reconstructs both structural and functional information, offering insights for high‐speed PAM imaging, dynamic vascular imaging and tissue functional monitoring.

OBJECTIVERoughly 6.5 million diabetic patients in the United States suffer from chronic wounds that exhibit impaired healing response1. These wounds often do not respond to standard treatment due to insufficient oxygenation in the wound bed2. Given the heterogeneity of oxygen levels in wounds and the importance of oxygen in tissue repair, it is compelling to develop a reliable way to non‐invasively monitor oxygen levels within chronic wounds over time. Previously, we demonstrated the ability of topically‐delivered BF2nbm(I)PLA boron dye nanoparticles (BNPs) that phosphoresce differentially at varying oxygen levels, to provide a spatial map of oxygen levels throughout the wound bed of a murine full‐thickness cutaneous wound3. The objective of this work is to validate the ability of BNP imaging to detect impaired tissue oxygenation during wound healing in diabetic individuals compared to healthy individuals.METHODSWe have developed a novel model of wound healing in the murine ear which allows measurements of oxygen levels in both tissue and blood vessels using BNP imaging and photoacoustic microscopy (PAM), respectively. PAM non‐invasively measures structural and hemodynamic changes, including vessel diameter, hemoglobin concentration, blood flow speed, and hemoglobin oxygen saturation levels in individual blood vessels down to the capillary level during microvascular remodeling within wound beds4. In this ear wound model, the epidermis and a portion of the dermis, including the center feeder arteriole and its main branches, are excised from the center of the ear lobe. The wound is covered with Tegaderm bandage to prevent drying, and the mouse is fitted with an Elizabethan collar to prevent it from removing the bandage. At regular intervals until the wound heals, BNPs are topically applied to the wound and excited by UV light for two minutes during which the fluorescence (F) and phosphorescence (P) emission signals are recorded using a camera. A custom Matlab program calculates the ratio of F:P emission intensities at each pixel in the wound bed image, which provides a relative mapping of oxygen levels throughout the wound. Following BNP imaging, PAM imaging is performed in order to calculate the percent sO2 in each blood vessel in/around the wound bed. BNP and PAM measurements are compared to one another for wounds in both healthy and diabetic mice.RESULTSDiabetic db/db mice exhibit muted wound oxygenation increases over time compared to non‐diabetic control mice. BNP fluorescence:phosphorescence emission ratios from wound beds emulate sO2 trends generated via PAM, confirming the ability of BNPs to assess tissue oxygenation over time in both diabetic and healthy wounds.CONCLUSIONSBNPs can be used to monitor tissue oxygenation over time in diabetic and healthy wounds. Given their low cost and potential for clinical monitoring of these wounds in humans, BNPs warrant further study for non‐invasively monitoring wound healing over time.Support or Funding InformationUVA School of Medicine Pinn Scholars ProgramThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Angiogenesis induced by growth factor administration, which can augment the blood supply in regenerative applications, has drawn wide attention in medical research. Longitudinal monitoring of vascular structure and development in vivo is important for understanding and evaluating the dynamics of involved biological processes. In this work, a dual-modality imaging system consisting of photoacoustic microscopy (PAM) and optical coherence tomography (OCT) was applied for noninvasive in vivo imaging of angiogenesis in a murine model. Fibrin scaffolds, with and without basic fibroblast growth factor (bFGF), were implanted in a flexible imaging window and longitudinally observed over 9 days. Imaging was conducted at 3, 5, 7, and 9 days after implantation to monitor vascularization in and around the scaffold. Several morphometric parameters were derived from the PAM images, including vessel area density (VAD), total vessel length (TVL), and vessel mean diameter (VMD). On days 7 and 9, mice receiving bFGF-laden fibrin gels exhibited significantly larger VAD and TVL compared to mice with fibrin-only gels. In addition, VMD significantly decreased in +bFGF mice versus fibrin-only mice on days 7 and 9. Blood vessel density, evaluated using immunohistochemical staining of explanted gels and underlying tissue on day 9, corroborated the findings from the PAM images. Overall, the experimental results highlight the utility of a dual-modality imaging system in longitudinally monitoring of vasculature in vivo with high resolution and sensitivity, thereby providing an effective tool to study angiogenesis.

This study aims to investigate the feasibility of using photoacoustic microscopy for the diagnosis of prostatitis. We induced inflammation in rats to establish a model of prostatitis using Freund’s Complete Adjuvant (FCA). Prostate tissues from both the model and control groups were extracted and processed into histological sections. We explored the photoacoustic microscopy imaging results of unstained sections, consistent with the histological detection results using HE staining. Inflammation was found to enhance the photoacoustic signals. Subsequently, we conducted photoacoustic microscopy imaging on all samples, and the detection results were nearly consistent with the diagnoses made by medical professionals. Finally, we quantified the collected photoacoustic signals to classify the severity of prostatitis.

UPAMNet: A unified network with deep knowledge priors for photoacoustic microscopy

In this study, the nondestructive testing (NDT) of tilted subsurface defects with a concave cross section was performed using a photoacoustic microscope (PAM). The tilted subsurface defects were formed in a metal plane specimen by mechanical processing. The obtained signal distribution was affected by the tilt angle of the subsurface defects, and the relationship between the gradient ratio and the tilt angle value exhibited a good correlation.

Identifying complete response (CR) after rectal cancer preoperative treatment is critical to deciding subsequent management. Imaging techniques, including endorectal ultrasound and MRI, have been investigated but have low negative predictive values. By imaging post-treatment vascular normalization using photoacoustic microscopy, we hypothesize that co-registered ultrasound and photoacoustic imaging will better identify complete responders. In this study, we used in vivo data from 21 patients to develop a robust deep learning model (US-PAM DenseNet) based on co-registered dual-modality ultrasound (US) and photoacoustic microscopy (PAM) images and individualized normal reference images. We tested the model's accuracy in differentiating malignant from non-cancer tissue. Compared to models based on US alone (classification accuracy 82.9 ± 1.3%, AUC 0.917(95%CI: 0.897-0.937)), the addition of PAM and normal reference images improved the model performance significantly (accuracy 92.4 ± 0.6%, AUC 0.968(95%CI: 0.960-0.976)) without increasing model complexity. Additionally, while US models could not reliably differentiate images of cancer from those of normalized tissue with complete treatment response, US-PAM DenseNet made accurate predictions from these images. For use in the clinical settings, US-PAM DenseNet was extended to classify entire US-PAM B-scans through sequential ROI classification. Finally, to help focus surgical evaluation in real time, we computed attention heat maps from the model predictions to highlight suspicious cancer regions. We conclude that US-PAM DenseNet could improve the clinical care of rectal cancer patients by identifying complete responders with higher accuracy than current imaging techniques.

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 present a dual modality ultra-thin imaging system based on a optical multimode fiber and a optical fiber hydrophone that combines optical resolution photoacoustic and fluorescence microscopy.

Imaging of the cells and microvasculature simultaneously is beneficial to the study of tumor angiogenesis and microenvironments. We designed and built a fiber-optic based photoacoustic microscopy (PAM) and confocal fluorescence microscopy (CFM) dual-modality imaging system. To explore the feasibility of this all-optical device for future endoscopic applications, a microelectromechanical systems (MEMS) scanner, a miniature objective lens, and a small size optical microring resonator as an acoustic detector were employed trying to meet the requirements of miniaturization. Both the lateral resolutions of PAM and CFM were quantified to be 8.8μm. Axial resolutions of PAM and CFM were experimentally measured to be 19μm and 53μm, respectively. The experiments on ex vivo animal bladder tissues demonstrate the good performance of this system in imaging not only microvasculature but also cellular structure, suggesting that this novel imaging technique holds potential for improved diagnosis and guided treatment of bladder cancer.

Viewing individual cells and ambient microvasculature simultaneously is crucial for understanding tumor angiogenesis and microenvironments. We developed a confocal fluorescence microscopy (CFM) and photoacoustic microscopy (PAM) dual-modality imaging system that can assess fluorescent contrast and optical absorption contrast in biologic samples simultaneously. After staining tissues with fluorescent dye at an appropriate concentration, each laser pulse can generate not only sufficient fluorescent signals from cells for CFM but also sufficient photoacoustic signals from microvessels for PAM. To explore the potential of this system for diagnosis of bladder cancer, experiments were conducted on a rat bladder model. The CFM image depicts the morphology of individual cells, showing not only large polygonal umbrella cells but also intracellular components. The PAM image acquired at the same time provides complementary information on the microvascular distribution in the bladder wall, ranging from large vessels to capillaries. This device provides an opportunity to realize both histologic assay and microvascular characterization simultaneously. The combination of the information of individual cells and local microvasculature in the bladder offers the capability of envisioning the viability and activeness of these cells and holds promise for more comprehensive study of bladder cancer in vivo.