DOI 10.3390/diagnostics16010126
Imaging Approaches for the Diagnosis of Dry Eye: A Review.
Аннотация
Dry eye disease (DED) is a multifactorial disorder of the ocular surface, characterised by tear film instability, hyperosmolarity, inflammation, and neurosensory abnormalities. Its clinical heterogeneity and the weak correlation between symptoms and signs complicate both diagnosis and management. Conventional assessments, such as patient-reported symptom questionnaires and basic clinical tests like the Schirmer test, are useful; however, their variability and limited sensitivity highlight the need for more reliable and objective diagnostic tools. This narrative review summarises and analyses current imaging approaches used for the diagnosis of DED. A comprehensive literature search was performed in the PubMed and Google Scholar databases to identify relevant studies published up to October 2025. In recent years, imaging technologies have revolutionised the approach to DED. Modalities such as in vivo confocal microscopy (IVCM), meibography, anterior segment optical coherence tomography (AS-OCT), interferometry, thermography, tear fluorescein clearance, impression cytology, and multifunctional imaging systems allow for non-invasive, high-resolution, and reproducible assessment of ocular surface structures and tear film dynamics. The integration of these techniques into clinical practice supports a more personalised management of DED. Future directions include further technological refinements and the application of artificial intelligence (AI) to imaging analysis, with the potential to enhance diagnostic precision and facilitate earlier intervention. While imaging cannot replace a thorough clinical examination, it has become an essential adjunct that significantly enriches the evaluation and management of patients with DED.
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.