Case report: Medical treatment for limbal epithelial stem cell deficiency in patients treated for glaucoma.

Limbal epithelial stem cell deficiency (LSCD) is an abnormal corneal epithelial lesion with several causes. The patient was diagnosed using fluorescein staining. Bullous keratopathy, multiple surgeries, and drug-related damage can cause LSCD in glaucoma patients.

A case of IgG4-related conjunctival tumor with severe systemic allergy treated with antibodies against cytokine receptors.

Purpose: To present a case of IgG4-related conjunctival tumor in which anti-IL-5 receptor alpha-chain and anti-IL-4 receptor alpha-chain antibodies were administered for eosinophil sinusitis and severe bronchial asthma, but conjunctivitis could not be controlled.

Observations: A 53-year-old male patient started to receive anti-IL-5 receptor alpha chain antibody to treat eosinophilic sinusitis and eosinophilic severe bronchial asthma. Several months later, proliferative changes of the right palpebral conjunctiva appeared and were treated with tacrolimus and betamethasone eye drops.

Long-Term Observation of Deep Anterior Lamellar Keratoplasty in Patients with Post-LASIK Granular Corneal Dystrophy Type 2: Two Case Reports.

Introduction: Laser-assisted in situ keratomileusis (LASIK) exacerbates granular corneal dystrophy type 2. Post-LASIK granular corneal dystrophy type 2 is treated by several surgical techniques. To the best of our knowledge, no report has addressed the results of deep anterior lamellar keratoplasty in affected patients.

Automatic screening of tear meniscus from lacrimal duct obstructions using anterior segment optical coherence tomography images by deep learning.

Purpose: We assessed the ability of deep learning (DL) models to distinguish between tear meniscus of lacrimal duct obstruction (LDO) patients and normal subjects using anterior segment optical coherence tomography (ASOCT) images.

Methods: The study included 117 ASOCT images (19 men and 98 women; mean age, 66.6 ± 13.

Deep Neural Network-Based Method for Detecting Obstructive Meibomian Gland Dysfunction With in Vivo Laser Confocal Microscopy.

Purpose: To evaluate the ability of deep learning (DL) models to detect obstructive meibomian gland dysfunction (MGD) using in vivo laser confocal microscopy images.

Methods: For this study, we included 137 images from 137 individuals with obstructive MGD (mean age, 49.9 ± 17.

Comparison of semi-automated center-dot and fully automated endothelial cell analyses from specular microscopy images.

Purpose: To evaluate two specular microscopy analysis methods across different endothelial cell densities (ECDs).

Methods: Endothelial images of one eye from each of 45 patients were taken by using three different specular microscopes (three replicates each). To determine the consistency of the center-dot method, we compared SP-6000 and SP-2000P images.