Artificial intelligence (AI) is an emerging field which could make an intelligent healthcare model a reality and has been garnering traction in the field of medicine, with promising results. There have been recent developments in machine learning and/or deep learning algorithms for applications in ophthalmology-primarily for diabetic retinopathy, and age-related macular degeneration. However, AI research in the field of cornea diseases is relatively new. Algorithms have been described to assist clinicians in diagnosis or detection of cornea conditions such as keratoconus, infectious keratitis and dry eye disease. AI may also be used for segmentation and analysis of cornea imaging or tomography as an adjunctive tool. Despite the potential advantages that these new technologies offer, there are challenges that need to be addressed before they can be integrated into clinical practice. In this review, we aim to summarize current literature and provide an update regarding recent advances in AI technologies pertaining to corneal diseases, and its potential future application, in particular pertaining to image analysis.

Since its introduction, optical coherence tomography (OCT) has revolutionized the field of ophthalmology and has now become an indispensable, noninvasive tool in daily practice. Most ophthalmologists are familiar with its use in the assessment and monitoring of retinal and optic nerve diseases. However, it also has important applications in the assessment of anterior segment structures, including the cornea, conjunctiva, sclera, anterior chamber, and iris, and has the potential to transform the clinical examination of these structures. In this review, we aim to provide a comprehensive overview of the potential clinical utility of anterior segment OCT (AS-OCT) for a wide range of anterior segment pathologies, such as conjunctival neoplasia, pterygium, scleritis, keratoconus, corneal dystrophies, and infectious/noninfectious keratitis. In addition, the clinical applications of AS-OCT (including epithelial mapping) in preoperative planning and postoperative monitoring for corneal and refractive surgeries are discussed.

Teleophthalmology is a widely recognised way to provide health care to patients living in rural and remote regions by leveraging limited clinician availability and resources. This is most important in low socioeconomic areas, where the disparity between prevalence of preventable blindness and practicing ophthalmologists is greatest. The ubiquity and accessibility of smartphones allow them to be utilised in a clinical setting and facilitate teleophthalmology. While the current market of smartphone adapters capable of imaging ocular pathology is expanding, few focus on the anterior segment and operate independently of the slit-lamp microscope. This article reviews the available smartphone adapters capable of imaging anterior segment pathology.

Artificial intelligence (AI) technology is promising in the field of healthcare. With the developments of big data and image-based analysis, AI shows potential value in ophthalmology applications. Recently, machine learning and deep learning algorithms have made significant progress. Emerging evidence has demonstrated the capability of AI in the diagnosis and management of anterior segment diseases. In this review, we provide an overview of AI applications and potential future applications in anterior segment diseases, focusing on cornea, refractive surgery, cataract, anterior chamber angle detection, and refractive error prediction.

Optical coherence tomography (OCT) is a revolutionary in vivo imaging technology that presents real-time information on ocular structures. Angiography based on OCT, known as optical coherence tomography angiography (OCTA), is a noninvasive and time-saving technique originally utilized for visualizing retinal vasculature. As devices and built-in systems have evolved, high-resolution images with depth-resolved analysis have assisted ophthalmologists in accurately localizing pathology and monitoring disease progression. With the aforementioned advantages, application of OCTA has extended from the posterior to anterior segment. This nascent adaptation showed good delineation of the vasculature in the cornea, conjunctiva, sclera, and iris. Thus, neovascularization of the avascular cornea and hyperemia or ischemic changes involving the conjunctiva, sclera, and iris has become prospective applications for AS-OCTA. Although traditional dye-based angiography is regarded as the gold standard in demonstrating vasculature in the anterior segment, AS-OCTA is expected to be a comparable but more patient-friendly alternative. In its initial stage, AS-OCTA has exhibited great potential in pathology diagnosis, therapeutic evaluation, presurgical planning, and prognosis assessments in anterior segment disorders. In this review of AS-OCTA, we aim to summarize scanning protocols, relevant parameters, and clinical applications as well as limitations and future directions. We are sanguine about its wide application in the future with the development of technology and refinement in built-in systems.

Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implications on every subspecialty within medicine. This review highlights the applications of AI in ophthalmology: a specialty that lends itself well to the integration of computer algorithms due to the high volume of digital imaging, data, and objective metrics such as central retinal thickness. The focus of this review is the use of AI in retina, cornea, anterior segment, and pediatrics.

OBJECTIVE: To assess the long-term refractive status, visual outcome, astigmatism, and the change in biometric optic components in older adolescents up to age 17 years with threshold retinopathy of prematurity (ROP) treated with diode laser.
METHODS: A retrospective, longitudinal study in which cycloplegic refraction, keratometry, and the biometric measurement of optic components were performed on 28 consecutive preterm eyes with laser-treated threshold ROP at age 17 years. The study results were statistically analysed and compared with age-matched full-term control.
RESULTS: All patients with ROP had myopia (average spherical equivalent of - 6.35 D, ranges from - 1.25 to - 12.38 D), and 12 eyes (43%) were highly myopic (spherical equivalent <  - 6.0 D). Threshold ROP eyes exhibited a significantly poorer visual acuity (P < 0.001), greater cylinder refractive error (P < 0.001), higher corneal astigmatism (P < 0.001), and flatter horizontal corneal curvature (P = 0.01) compared with age-matched controls. Biometric optic components analysis revealed a significant shallower anterior chamber depth (P < 0.001), thicker lens (P < 0.001), and shorter axial length (P = 0.021) in laser-treated ROP eyes compared with age-matched controls.
CONCLUSIONS: In this 17-year longitudinal study, a higher prevalence of myopia and astigmatism was observed in laser-treated threshold ROP eyes compared with age-matched control eyes. Myopia and astigmatism in laser-treated ROP eyes typically progress through adolescence after school age. Therefore, we recommend that preterm patients with laser-treated threshold ROP should attend regular follow-up not only for refractive status but also for structural change of anterior segment until their adolescence.

Anterior segment optical coherence tomography (AS-OCT) constitutes an important imaging modality to examine the anterior eye, which is commonly used in research and clinical practice. Since its introduction, a range of image analysis methods have been developed to quantify these images using different analysis techniques for various applications. This systematic review aims to provide an in-depth summary and to classify image analysis techniques found in the literature applied to AS-OCT images.
Scopus and Engineering Village databases were searched to retrieve relevant studies up to and including January 2022. Customized search statements were used along with cross reference and hand search techniques to ensure a complete coverage. Performance metrics were extracted, analyzed, and compared (when possible).
Three main application categories were identified: glaucoma assessment, corneal segmentation, and anterior segment biometry. These three categories constitute 66% of the total studies reported in this review. Studies were also analyzed by year of publication, and since 2019 deep learning methods were favored over traditional programming or machine learning methodologies. Overall, the AS-OCT image analysis field is less developed compared to posterior segment OCT imaging.
This review presents the state of the art in the field of AS-OCT image analysis. It highlights the opportunities for future areas of research, such as the expansion of DL methods and the extension to specific clinical areas that have received limited attention including surgical monitoring, contact lenses, and specific clinical conditions such as keratoconus and corneal lesions.

OBJECTIVE: Primary congenital glaucoma (PCG) is a form of childhood glaucoma caused by maldevelopment of the anterior chamber. Disease severity differs greatly amongst patients. Ultrasound biomicroscopy (UBM) is a non-invasive technique that can visualize the anterior segment in infants in vivo. The purpose of this narrative review is to make an overview of the UBM data in PCG and study the applicability of UBM in characterizing the disease.
METHODS: An online search was performed on PubMed in December 2020. After a critical appraisal of the included articles, study and patient characteristics were summarized. The UBM measurements of the anterior segment in PCG of the different studies were analysed.
RESULTS: Six studies were included in this review. All were cross-sectional prospective studies. A total of 221 PCG eyes were examined. PCG eyes showed a larger trabecular iris angle, decreased iris thickness, narrower or absent Schlemm\'s canal and an increased zonular length compared to controls. Abnormal tissue membrane covering the trabecular meshwork and abnormal insertion of the iris and ciliary process were frequently found. The success rate of glaucoma surgery depended on the severity of anterior segment malformations found with UBM.
CONCLUSIONS: Malformations of the anterior segment in PCG can be demonstrated by UBM in vivo. This imaging can help to characterize disease severity and might support surgical treatment decisions.

The aim of this study is to describe the involvement of Epstein-Barr Virus (EBV) in the diseases of the ocular anterior segment. This is a narrative review designed using the PUBMED, SCOPE and Web of Science databases, searching for reported literature on findings in the anterior ocular segment related to EBV between 1990 and 2020. Epstein-Barr Virus (EBV) is implicated in the development of salmon-coloured conjunctival masses in the context of acute mononucleosis and lymphoproliferative disorders. Moreover, EBV can cause haemorrhagic conjunctivitis and its corneal implications appear as different types of keratitis patterns. The involvement of EBV in the pathogenesis of anterior segment inflammation is not well-defined. Current evidence regarding anterior segment disease caused by EBV infection has been proved by positive viral detection through polymerase chain reaction test in eyes with lymphoproliferative disorders known to be caused by EBV, as B- and NK/T-cell lymphoid tumours. Antiviral treatment (oral Aciclovir or Valaciclovir) in anterior segment disease caused by EBV remains controversial.