Sungkyunkwan University · 医学
Professor Su Jeong Song's research lab focuses on ophthalmic diseases, particularly age-related macular degeneration (AMD) and diabetic retinopathy, with an emphasis on epidemiological trends, risk factor identification, and advanced diagnostic and therapeutic approaches in the Korean population. The lab investigates the role of systemic factors such as hypertension and diabetes in retinal diseases, while also exploring innovative drug delivery systems using enzyme-responsive peptide nanostructures for targeted ocular therapy. Their work bridges clinical ophthalmology with nanomedicine, aiming to improve early detection, treatment efficacy, and patient outcomes in retinal disorders.
Figures are computed from collected data and may differ slightly.
In this study, the prevalence of early AMD was similar to other studies though the prevalence of late AMD was low. High blood pressure as well as age was a risk factor of early AMD. South Koreans may have a higher prevalence of PCV than white populations. These findings provide preliminary information for further investigation of AMD in South Koreans.
Although there was a rapid increase in the prevalence of diabetes in the Korean population in the past decade, the prevalence of diabetic retinopathy remained stable during the study period. However, just three out of 10 patients with diabetes underwent regular annual dilated fundus examinations. Thus, an improvement in the continuity of diabetic retinopathy screening among patients with diabetes is necessary to reduce the risk of visual impairment as a result of diabetic retinopathy.
For the past several decades, tremendous efforts have been made to decrease the complications of diabetes, including diabetic retinopathy. New diagnostic modalities like ultrawide field fundus fluorescein angiography and spectral domain optical coherence tomography has allowed more accurate diagnosis of early diabetic retinopathy and diabetic macular edema. Antivascular endothelial growth factors are now extensively used to treat diabetic retinopathy and macular edema with promising results. The
Purpose: To identify the prevalence, risk factors, and subtypes of age-related macular degeneration (AMD) in a screened South Korean population. Methods: A total of 10,890 participants (aged 50–92) who underwent a health check-up at Kangbuk Samsung Hospital from January to December 2006 were included. Fundus photographs and systemic risk factors were assessed. Subtype frequencies of neovascular AMD were recorded according to angiograms. AMD was defined in accord with the international classifica
The lower frequency of moderate BCVA improvement for those with good preoperative BCVA and phakic lens status might influence visual improvement, and therefore, a recommendation for surgery.
Self-assembled peptide nanostructures recently have gained much attention as drug delivery systems. As biomolecules, peptides have enhanced biocompatibility and biodegradability compared to polymer-based carriers. We introduce a peptide nanoparticle system containing arginine, histidine, and an enzyme-responsive core of repeating GLFG oligopeptides. GLFG oligopeptides exhibit specific sensitivity towards the enzyme cathepsin B that helps effective controlled release of cargo molecules in the cyt
In addition to traditional risk factors, insulin resistance was associated with an increased risk of DR in Koreans with type 2 diabetes.
Ultra-wide-field fundus imaging (UFI) provides comprehensive visualization of crucial eye components, including the optic disk, fovea, and macula. This in-depth view facilitates doctors in accurately diagnosing diseases and recommending suitable treatments. This study investigated the application of various deep learning models for detecting eye diseases using UFI. We developed an automated system that processes and enhances a dataset of 4697 images. Our approach involves brightness and contrast
Drusen are the main aspect of detecting age-related macular degeneration (AMD). Ophthalmologists can evaluate the condition of AMD based on drusen in fundus images. However, in the early stage of AMD, the drusen areas are usually small and vague. This leads to challenges in the drusen segmentation task. Moreover, due to the high-resolution fundus images, it is hard to accurately predict the drusen areas with deep learning models. In this paper, we propose a multi-scale deep learning model for dr
Peptide nanostructure has been widely explored for drug-delivery systems in recent studies. Peptides possess comparatively lower cytotoxicity and are more efficient than polymeric carriers. Here, we propose a peptide nanorod system, composed of an amphiphilic oligo-peptide RH<sub>3</sub>F<sub>8</sub> (Arg-His<sub>3</sub>-Phe<sub>8</sub>), as a drug-delivery carrier. Arginine is an essential amino acid in typical cell-penetration peptides, and histidine induces endo- and lysosomal escape because
Our enhancement process improves LQ fundus images that suffer from complex degradation significantly. Moreover our customized CNN achieved improved performance over the existing state-of-the-art methods. Overall, our framework can have a clinical impact on reducing re-examinations and improving the accuracy of diagnosis.
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