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Abstract Corneal transplantation is the primary treatment for irreversible corneal diseases, but due to limited donor availability, bioengineered corneal equivalents are being developed as a solution, with biocompatibility, structural integrity, and physical function considered key factors. Since conventional evaluation methods may not fully capture the complex properties of the cornea, there is a need for advanced imaging and assessment techniques. In this study, we proposed a deep learning-based automatic segmentation method for transplanted bioengineered corneal equivalents using optical coherence tomography to achieve a highly accurate evaluation of graft integrity and biocompatibility. Our method provides quantitative individual thickness values, detailed maps, and volume measurements of the bioengineered corneal equivalents, and has been validated through 14 days of monitoring. Based on the results, it is expected to have high clinical utility as a quantitative assessment method for human keratoplasties, including automatic opacity area segmentation and implanted graft part extraction, beyond animal studies.

Spatial sampling density and data size are important determinants of the imaging speed of photoacoustic microscopy (PAM). Therefore, undersampling methods that reduce the number of scanning points are typically adopted to enhance the imaging speed of PAM by increasing the scanning step size. Since undersampling methods sacrifice spatial sampling density, by considering the number of data points, data size, and the characteristics of PAM that provides three-dimensional (3D) volume data, in this study, we newly reported deep learning-based fully reconstructing the undersampled 3D PAM data. The results of quantitative analyses demonstrate that the proposed method exhibits robustness and outperforms interpolation-based reconstruction methods at various undersampling ratios, enhancing the PAM system performance with 80-times faster-imaging speed and 800-times lower data size. The proposed method is demonstrated to be the closest model that can be used under experimental conditions, effectively shortening the imaging time with significantly reduced data size for processing.

Optical fiber is widely used in optical coherence tomography (OCT) to propagate light precisely with low attenuation and low dispersion. However, the total optical path length within the optical fiber varies in accordance with changes of the temperature. This leads changes in the total optical travel path of the interfering signals and results in shifting of OCT image position to an unintended depth pixel value. In this paper, we presented the temperature-based automatic path length compensating method in OCT to limit the external temperature effect and control the image position in micro-scale without manual movement of optical components. By utilizing developed hardware and software of automatic temperature control system, the external temperature of optical fiber is precisely regulated that evokes thermal expansion and finally changes the physical length of fiber, which is main mechanism of temperature-based path length compensating method. The effectiveness of the presented method was verified by two-dimensional OCT images of mirror and in vivo retina. The obtained results confirmed the path length variance due to temperature change is computable and can be regulated in real-time for whole pixel range of OCT image. Therefore, the proposed temperature-based path length compensating method can be used as an alternative method to precisely control the position of OCT image, while eliminating the effect of external temperature and apply to effectively configuring compact optical systems.

Pores are the microscopic openings in the skin that emit oils and sweat. Pores can appear larger due to acne, sun damage, or increased sebum production, a waxy and oily substance that causes oily skin. Investigating and extracting sebum from facial pores is essential for treating skin issues as the enlargement of the pores causes higher susceptibility of the skin to microbe aggressions and inflammatory reactions. In this study, we assessed the volumetric size of pores before and after the sebum extraction using spectral domain optical coherence tomography (SD-OCT). To properly estimate the volume of the sebum before and after extraction, multiple cross-sectional OCT images were selected. The area of a single pixel was calculated from the OCT images using the scanning range. Furthermore, an algorithm was developed to use the pixel area to calculate the full volumetric size of the skin pore. This research illustrates the use of a high-resolution microscopic analysis using SD-OCT in dermatological research and can operate as a guideline for future research investigations in evaluating non-destructively wounded tissue analysis, underlying skin biochemistry, and facial statistical approaches in skin parameters for moisturizer treatment.

Photoacoustic imaging (PAI) is a hybrid non-invasive imaging technique used to merge high optical contrast and high acoustic resolution in deep tissue. PAI has been extensively developed by utilizing its advantages that include deep imaging depth, high resolution, and label-free imaging. As a representative implementation of PAI, photoacoustic microscopy (PAM) has been used in preclinical and clinical studies for its micron-scale spatial resolution capability with high optical absorption contrast. Several handheld and portable PAM systems have been developed that improve its applicability to several fields, making it versatile. In this study, we developed a laboratory-customized, two-axis, waterproof, galvanometer scanner-based handheld PAM (WP-GVS-HH-PAM), which provides an extended field of view (14.5 × 9 mm2) for wide-range imaging. The fully waterproof handheld probe enables free movement for imaging regardless of sample shape, and volume rate and scanning region are adjustable per experimental conditions. Results of WP-GVS-HH-PAM-based phantom and in vivo imaging of mouse tissues (ear, iris, and brain) confirm the feasibility and applicability of our system as an imaging modality for various biomedical applications.

The aim of this study was to quantitatively assess the residual adhesive on orthodontic ceramic bracket-removed dental surface. In orthodontic process, ceramic bracket was repeated debonding physically, then the adhesive remained on the dental surface. The residual adhesive caused a lack of adhesive strength between dental and ceramic bracket. Since commonly used adhesive in orthodontics is translucent, residual adhesive is hard to be detected with conventional microscopes. Therefore, 1310 nm center wavelength swept-source OCT system based on laboratory customized image processing algorithm was used for the precise detection of residual adhesive on tooth surface. The algorithm separates residual adhesive from dental surface by comparing the height of adjacent B-scan images, while providing color-scaled images emphasizing the thickness information of residual adhesive. Finally, the acquired results were compared with microscopic and adhesive remnant index scoring gold standards, while the comparison confirmed the potential merits and the improvements of the proposed method over gold standards.

Abstract Totally implantable venous devices are used in medical care for parenteral nutrition, vascular access, administrating chemotherapeutic agents and so on. Although the large variety of catheter complications, catheter fracture is a rare but serious complication. The pinch off syndrome is caused by the compression of the catheter between the clavicle and first rib, and may lead to fracture and possible dislocation of the catheter. We report here the case history of a patient with metastatic breast cancer who developed a rare complication of subclavian catheter fracture as a consequence of pinch off syndrome.