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Noninvasive Imaging of Conjunctival Goblet Cells as a Method for Diagnosing Dry Eye Disease in an Experimental Mouse Model

体内 医学 病理 眼科 接收机工作特性 杯状细胞 临床前影像学 组织学 生理盐水 内科学 生物 上皮 生物技术
作者
Jeong‐Ho Kim,Jungbin Lee,Seonghan Kim,Sook Hyun Yoon,Yeong Chae Jo,Ki Hean Kim,Hong Kyun Kim
出处
期刊:Translational Vision Science & Technology [Association for Research in Vision and Ophthalmology (ARVO)]
卷期号:12 (12): 22-22
标识
DOI:10.1167/tvst.12.12.22
摘要

Purpose: The purpose of this study was to evaluate a noninvasive conjunctival goblet cell (GC) imaging method for assessing dry eye disease (DED) in an experimental mouse model. Methods: Moxifloxacin-based fluorescence microscopy (MBFM) was used to examine GCs noninvasively in 56 mice. Forty-two (42) DED-induced mice were divided into 2 groups and treated topically for 14 days with cyclosporine (CsA) or normal saline (NS). In vivo MBFM imaging and clinical DED evaluations were performed and goblet cell density (GCD) and goblet cell area (GCA) were obtained and compared with histological GCD using periodic acid-Schiff (PAS) staining. Correlation and receiver operating characteristic (ROC) analyses showed MBFM's high diagnostic value. Results: The GCD and GCA of the DED mice obtained from in vivo MBFM imaging were highly correlated with clinical DED parameters and GCD obtained from PAS histology. The therapeutic effect of CsA, as observed by in vivo MBFM, was significant with respect to that of NS treatment. The ROC curves derived from in vivo MBFM showed high diagnostic value in assessing DED. Conclusions: The proposed noninvasive method has high diagnostic value in assessing the severity of DED and the effect of treatment for this disease. Translational Relevance: A noninvasive imaging method using moxifloxacin-based fluorescence microscopy was evaluated for assessing DED in an experimental mouse model. The method showed high diagnostic value in assessing the severity of DED and the effect of treatment, bridging the gap between basic research and clinical treatment. The study provides a promising tool for diagnosing and monitoring DED.
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