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Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique can be successfully translated into clinics. Among these, electromagnetic interference (EMI) noise, in addition to the limited signal-to-noise ratio (SNR), have hindered the rapid development of related technologies. Unlike endoscopic ultrasound, in which the SNR can be increased by simply applying a higher pulsing voltage, there is a fundamental limitation in leveraging the SNR of PAE signals because they are mostly determined by the optical pulse energy applied, which must be within the safety limits. Moreover, a typical PAE hardware situation requires a wide separation between the ultrasonic sensor and the amplifier, meaning that it is not easy to build an ideal PAE system that would be unaffected by EMI noise. With the intention of expediting the progress of related research, in this study, we investigated the feasibility of deep-learning-based EMI noise removal involved in PAE image processing. In particular, we selected four fully convolutional neural network architectures, U-Net, Segnet, FCN-16s, and FCN-8s, and observed that a modified U-Net architecture outperformed the other architectures in the EMI noise removal. Classical filter methods were also compared to confirm the superiority of the deep-learning-based approach. Still, it was by the U-Net architecture that we were able to successfully produce a denoised 3D vasculature map that could even depict the mesh-like capillary networks distributed in the wall of a rat colorectum. As the development of a low-cost laser diode or LED-based photoacoustic tomography (PAT) system is now emerging as one of the important topics in PAT, we expect that the presented AI strategy for the removal of EMI noise could be broadly applicable to many areas of PAT, in which the ability to apply a hardware-based prevention method is limited and thus EMI noise appears more prominently due to poor SNR.

Tissue clearing has gained attention as a pioneering research tool for imaging of large tissue samples. This technique improves light transmission by reducing light scattering within tissues, either by removing lipids or by replacing water with a high refractive index solution. Although various clearing techniques have been developed, quantitative assessments on clearing efficacy depending on tissue properties are rare. In this study, we developed the quantitative mapping of regional clearing efficacy using mean free path in optical coherence tomography (OCT) and proton density in magnetic resonance imaging (MRI), and demonstrated its feasibility in the brain sample with four representative clearing techniques (benzyl alcohol and benzyl benzoate [BABB], Clear T , Scale, and passive CLARITY technique [PACT]). BABB (solvent-based clearing), involving both refractive index matching and lipid removal, exhibited best optical clearing performance with the highest proton density reduction both in gray and white matter. Lipid-removing techniques such as Scale (aqueous hyperhydration) and PACT (hydrogel embedding) showed higher clearing efficiency in white matter than gray matter in accordance with larger proton density increase in white matter. For Clear T (aqueous-based simple immersion), we observed lowest clearing efficiency in the white matter as well as poor lipid removal reflected in low proton density reduction. Our results showed the feasibility of the regional mapping of clearing efficacy and correlating optical transparency and proton density changes using OCT and MRI from existing tissue clearing techniques. This novel quantitative mapping of clearing efficacy depending on tissue types and clearing methods may be helpful in the development of optimized clearing methods for different biological samples.

Otitis media (OM), a middle-ear infection, is the most common childhood illness treated by pediatricians. If inadequately treated, OM can result in long-term chronic problems persisting into adulthood. Children with chronic OM or recurrent OM often have conductive hearing loss and communication difficulties and require surgical treatment. Tympanostomy tube insertion, the placement of a small drainage tube in the tympanic membrane (TM), is the most common surgical procedure performed in children under general anesthesia. Recent clinical studies have shown evidence of a direct correspondence between chronic OM and the presence of a bacterial biofilm within the middle ear. Biofilms are typically very thin and cannot be recognized using a regular otoscope. Here we report the use of optical coherent ranging techniques to noninvasively assess the middle ear to detect and quantify biofilm microstructure. This study involves adults with chronic OM, which is generally accepted as a biofilm-related disease. Based on more than 18,537 optical ranging scans and 742 images from 13 clinically infected patients and 7 normal controls using clinical findings as the gold standard, all middle ears with chronic OM showed evidence of biofilms, and all normal ears did not. Information on the presence of a biofilm, along with its structure and response to antibiotic treatment, will not only provide a better fundamental understanding of biofilm formation, growth, and eradication in the middle ear, but also may provide much-needed quantifiable data to enable early detection and quantitative longitudinal treatment monitoring of middle-ear biofilms responsible for chronic OM.

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents.

Since glaucoma is a progressive and irreversible optic neuropathy, accurate screening and/or early diagnosis is critical in preventing permanent vision loss. Recently, optical coherence tomography (OCT) has become an accurate diagnostic tool to observe and extract the thickness of the retinal nerve fiber layer (RNFL), which closely reflects the nerve damage caused by glaucoma. However, OCT is less accessible than fundus photography due to higher cost and expertise required for operation. Though widely used, fundus photography is effective for early glaucoma detection only when used by experts with extensive training. Here, we introduce a deep learning-based approach to predict the RNFL thickness around optic disc regions in fundus photography for glaucoma screening. The proposed deep learning model is based on a convolutional neural network (CNN) and utilizes images taken with fundus photography and with RNFL thickness measured with OCT for model training and validation. Using a dataset acquired from normal tension glaucoma (NTG) patients, the trained model can estimate RNFL thicknesses in 12 optic disc regions from fundus photos. Using intuitive thickness labels to identify localized damage of the optic nerve head and then estimating regional RNFL thicknesses from fundus images, we determine that screening for glaucoma could achieve 92% sensitivity and 86.9% specificity. Receiver operating characteristic (ROC) analysis results for specificity of 80% demonstrate that use of the localized mean over superior and inferior regions reaches 90.7% sensitivity, whereas 71.2% sensitivity is reached using the global RNFL thicknesses for specificity at 80%. This demonstrates that the new approach of using regional RNFL thicknesses in fundus images holds good promise as a potential screening technique for early stage of glaucoma.

Multi-layered hydrogels consisting of bi- or tri-layers with different swelling ratios are designed to soft hydrogel actuators by self-folding. The successful use of multi-layered hydrogels in this application greatly relies on the precise design and fabrication of the curvature of self-folding. In general, however, the self-folding often results in an undesired mismatch with the expecting value. To address this issue, this study introduces an interfacial layer formed between each layered hydrogel, and this layer is evaluated to enhance the design and fabrication precision. By considering the interfacial layer, which forms through diffusion, as an additional layer in the multi-layered hydrogel, the degree of mismatch in the self-folding is significantly reduced. Experimental results show that as the thickness of the interfacial layer increases, the multi-layered hydrogel exhibits a 3.5-fold increase in its radius of curvature during the self-folding. In addition, the diffusion layer is crucial for creating robust systems by preventing the separation of layers in the muti-layered hydrogel during actuation, thereby ensuring the integrity of the system in operation. This new strategy for designing multi-layered hydrogels including an interfacial layer would greatly serve to fabricate precise and robust soft hydrogel actuators.

This study evaluated the effect of air injection depth in the big-bubble (BB) technique, which is used for corneal tissue preparation in lamellar keratoplasty. The BB technique was performed on ex vivo human corneoscleral buttons using a depth-sensing needle, based on optical coherence tomography (OCT) imaging technology. The needle tip, equipped with a miniaturized OCT depth-sensing probe, was inserted for air injection at a specified depth. Inside the corneal tissue, our needle obtained OCT line profiles, from which residual thickness below the needle tip was measured. Subjects were classified into Groups I, II, III, and IV based on injection depths of 75–80%, 80–85%, 85–90%, and >90% of the full corneal thickness, respectively. Both Type I and II BBs were produced when the mean residual thicknesses of air injection were 109.7 ± 38.0 µm and 52.4 ± 19.2 µm, respectively. Type II BB (4/5) was dominant in group IV. Bubble burst occurred in 1/16 cases of type I BB and 3/16 cases of type II BB, respectively. Injection depth was an important factor in determining the types of BBs produced. Deeper air injection could facilitate formation of Type II BBs, with an increased risk of bubble bursts.

Development of a dual-display handheld optical coherence tomography (OCT) system for retina and optic-nerve-head diagnosis beyond the volunteer motion constraints is reported. The developed system is portable and easily movable, containing the compact portable OCT system that includes the handheld probe and computer. Eye posterior chambers were diagnosed using the handheld probe, and the probe could be fixed to the bench-top cradle depending on the volunteers’ physical condition. The images obtained using this handheld probe were displayed in real time on the computer monitor and on a small secondary built-in monitor; the displayed images were saved using the handheld probe’s built-in button. Large-scale signal-processing procedures such as k-domain linearization, fast Fourier transform (FFT), and log-scaling signal processing can be rapidly applied using graphics-processing-unit (GPU) accelerated processing rather than central-processing-unit (CPU) processing. The Labview-based system resolution is 1,024 × 512 pixels, and the frame rate is 56 frames/s, useful for real-time display. The 3D images of the posterior chambers including the retina, optic-nerve head, blood vessels, and optic nerve were composed using real-time displayed images with 500 × 500 × 500 pixel resolution. A handheld and bench-top hybrid mode with a dual-display handheld OCT was developed to overcome the drawbacks of the conventional method.

Background Wrinkles represent a characteristic symptom of skin aging. In recent years, various studies have focused on their prevention and/or cure. However, clinical tests are still the only method available to directly detect and evaluate the anti‐wrinkle efficacy of various substances. Moreover, no in vitro strategy for such anti‐aging skin analysis has been reported. Therefore, in this study, we aimed to develop a novel technology to overcome these limitations. Materials and methods Full‐thickness (FT) skin wrinkle mimics with various widths and depths were fabricated using a collagen stamping method. These were analyzed and compared using 2D and 3D Swept Source‐Optical Coherence Tomography (SS‐OCT) imaging technologies. Results SS‐OCT demonstrated superficial and cross‐sectional images of the wrinkle mimics, and the size of the wrinkles was validated using image analysis. Retinoic acid treatment significantly decreased both the depth and width of wrinkles formed in the FT skin wrinkle mimics. Conclusions Using 3D tissue engineering and SS‐OCT imaging technologies, we developed a novel in vitro technique that can directly detect skin wrinkles. This significantly efficient method could lead to an alternative strategy for animal experiments and preclinical anti‐aging research on the skin.

The integration of nanoparticles (NPs) into molecular self-assemblies has been extensively studied with the aim of building well-defined, ordered structures which exhibit advanced properties and performances. This study demonstrates a novel strategy for the preparation of a spike-like self-assembly designed to enhance UV blocking. Poly(2-hydroxyethyl aspartamide) (PHEA) substituted with octadecyl chains and menthyl anthranilate (C18-M-PHEA) was successfully synthesized by varying the number of grafted groups to control their morphology and UV absorption. The in situ incorporation of polymerized rod-like TiO2 within the C18-M-PHEA self-aggregates generated spike-like self-assemblies (TiO2@C18-M-PHEA) with a chestnut burr structure in aqueous solution. The results showed that the spike-like self-assemblies integrated with TiO2 NPs exhibited a nine-fold increase in UV protection by simultaneous UV absorption and scattering compared with the pure TiO2 NPs formed via a bulk mixing process. This work provides a novel method for UV protection using self-assembling poly(amino acid)s derivatives integrated with functional nanoparticles to tune their morphology and organization.