Introduction of Deep Learning-Based Infrared Image Analysis to Marginal Reflex Distance1 Measurement Method to Simultaneously Capture Images and Compute Results: Clinical Validation Study.

Marginal reflex distance1 (MRD1) is a crucial clinical tool used to evaluate the position of the eyelid margin in relation to the cornea. Traditionally, this assessment has been conducted manually by plastic surgeons, ophthalmologists, or trained technicians. However, with the advancements in artificial intelligence (AI) technology, there is a growing interest in the development of automated systems capable of accurately measuring MRD1. In this context, we introduce novel MRD1 measurement methods based on deep learning algorithms that can simultaneously capture images and compute the results. This prospective observational study involved 154 eyes of 77 patients aged over 18 years who visited Chungnam National University Hospital between 1 January 2023 and 29 July 2023. We collected four different MRD1 datasets from patients using three distinct measurement methods, each tailored to the individual patient. The mean MRD1 values, measured through the manual method using a penlight, the deep learning method, ImageJ analysis from RGB eye images, and ImageJ analysis from IR eye images in 56 eyes of 28 patients, were 2.64 ± 1.04 mm, 2.85 ± 1.07 mm, 2.78 ± 1.08 mm, and 3.07 ± 0.95 mm, respectively. Notably, the strongest agreement was observed between MRD1_deep learning (DL) and MRD1_IR (0.822, p < 0.01). In a Bland-Altman plot, the smallest difference was observed between MRD1_DL and MRD1_IR ImageJ, with a mean difference of 0.0611 and ΔLOA (limits of agreement) of 2.5162, which was the smallest among all of the groups. In conclusion, this novel MRD1 measurement method, based on an IR camera and deep learning, demonstrates statistical significance and can be readily applied in clinical settings.

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement.

The accurate assessment of wound size is a critical step in advanced wound care management. This study aims to introduce and validate a Light Detection and Ranging (LiDAR) technique for measuring wound size. Twenty-eight wounds treated from December 2022 to April 2023 at the Chungnam National University Hospital were analyzed. All the wounds were measured using three techniques: conventional ruler methods, the LiDAR technique, and ImageJ analysis. Correlation analysis, linear regression, and Bland-Altman plot analysis were performed to validate the accuracy of the novel method. The measurement results (mean ± standard deviation) obtained using the ruler method, LiDAR technique, and ImageJ analysis were 112.99 ± 110.07 cm2, 73.59 ± 72.97 cm2, and 74.29 ± 72.15 cm2, respectively. The Pearson correlation coefficient was higher for the LiDAR application (0.995) than for the conventional ruler methods (mean difference, -5.0000 cm2), as was the degree of agreement (mean difference, 38.6933 cm2). Wound size measurement using LiDAR is a simple and reliable method that will enable practitioners to conveniently assess wounds with a flattened and irregular shape with higher accuracy. However, non-flattened wounds cannot be assessed owing to the technical limitations of LiDAR.

Localised structuring of metal-semiconductor cores in silica clad fibres using laser-driven thermal gradients.

The molten core drawing method allows scalable fabrication of novel core fibres with kilometre lengths. With metal and semiconducting components combined in a glass-clad fibre, CO2 laser irradiation was used to write localised structures in the core materials. Thermal gradients in axial and transverse directions allowed the controlled introduction, segregation and chemical reaction of metal components within an initially pure silicon core, and restructuring of heterogeneous material. Gold and tin longitudinal electrode fabrication, segregation of GaSb and Si into parallel layers, and Al doping of a GaSb core were demonstrated. Gold was introduced into Si fibres to purify the core or weld an exposed fibre core to a Si wafer. Ga and Sb introduced from opposite ends of a silicon fibre reacted to form III-V GaSb within the Group IV Si host, as confirmed by structural and chemical analysis and room temperature photoluminescence.

Comparison of Postoperative Outcomes Between Monitored Anesthesia Care and General Anesthesia in Closed Reduction of Nasal Fracture.

Fracture of nasal bone is among the most common facial bone fractures. Reduction of nasal bone fracture is able to be performed under local or general anesthesia. The aim of this study is to compare monitored anesthetic care (MAC) and general anesthesia (GA) based on intraoperative vital signs, and the adverse effects after closed reduction of nasal bone fractures.The authors performed a retrospective study of 45 patients who underwent a closed reduction of nasal bone fracture between January 1, 2016 and December 31, 2016. Patients are divided into an MAC group (n = 17) or GA group (n = 28). A sore throat, postoperative pain scores, nausea, vomiting, hospital stay, operation time, and the result of surgery are compared between the groups. All the patients have interviewed their satisfaction of aesthetic and functional outcome.The operation time and hospital stay were lower in the MAC group. There is no difference in a sore throat, postoperative pain score, and the result of surgery significantly. In the MAC and GA groups, there was no statistically significant difference in the postoperative cosmetic and functional satisfaction scores.Closed reduction of nasal bone fracture using MAC is as safe and efficient as GA. However, MAC anesthesia may not be feasible if airway discomfort due to bleeding is expected, or fracture is severe and multiple manipulations are required. Therefore, MAC is considered to be a good alternative when patients undergoing short-term or small operations do not prefer general anesthesia.