Forni Riccardo, Maruotto Ida, Zanuccoli Anna, Nicoletti Riccardo, Trimigno Luca, Corbellino Matteo, Travé-Huarte Sònia, Giannaccare Giuseppe, Gargiulo Paolo
Institute of Biomedical and Neural Engineering, Reykjavik University, 102 Reykjavik, Iceland.
Espansione Group, 40050 Bologna, Italy.
Diagnostics (Basel). 2025 May 9;15(10):1199. doi: 10.3390/diagnostics15101199.
: This study introduces a novel method for the automated detection and quantification of meibomian gland morphology using gray value distribution profiles. The approach addresses limitations in traditional manual and deep learning-based meibography analysis, which are often time-consuming and prone to variability. : This study enrolled 100 volunteers (mean age 40 ± 16 years, range 18-85) who suffered from dry eye and responded to the Ocular Surface Disease Index questionnaire for scoring ocular discomfort symptoms and infrared meibography for capturing imaging of meibomian glands. By leveraging pixel brightness variations, the algorithm provides real-time detection and classification of long, medium, and short meibomian glands, offering a quantitative assessment of gland atrophy. : A novel parameter, namely "atrophy index", a quantitative measure of gland degeneration, is introduced. Atrophy index is the first instrumental measurement to assess single- and multiple-gland morphology. : This tool provides a robust, scalable metric for integrating quantitative meibography into clinical practice, making it suitable for real-time screening and advancing the management of dry eyes owing to meibomian gland dysfunction.
本研究介绍了一种利用灰度值分布曲线自动检测和量化睑板腺形态的新方法。该方法解决了传统手动和基于深度学习的睑板腺造影分析的局限性，这些方法往往耗时且容易出现变异性。本研究招募了100名患有干眼症的志愿者（平均年龄40±16岁，范围18 - 85岁），他们对眼表疾病指数问卷进行评分以评估眼部不适症状，并进行红外睑板腺造影以获取睑板腺图像。通过利用像素亮度变化，该算法可实时检测和分类长、中、短睑板腺，对腺体萎缩进行定量评估。引入了一个新参数，即“萎缩指数”，这是一种评估腺体退化的定量测量方法。萎缩指数是评估单腺体和多腺体形态的首个仪器测量指标。该工具为将定量睑板腺造影纳入临床实践提供了一个强大、可扩展的指标，使其适用于实时筛查，并推动因睑板腺功能障碍导致的干眼症的管理。
