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. We evaluated the medical treatment course for LSCD in patients with glaucoma. We retrospectively reviewed the electronic medical records of patients diagnosed with LSCD and investigated their background, course of treatment, and classification stages of LSCD before and after treatment. The global consensus classification system (stages IA-C, IIA-B, and III) proposed by Deng et al. (Cornea 2020) was used. Seven patients (two males) and eight eyes were studied. The median age of the patients was 82 years, and the mean duration of glaucoma treatment was 8 years. The patients had open-angle glaucoma (four eyes), exfoliation glaucoma (one eye), neovascular glaucoma (one eye), normal tension glaucoma (one eye), and uveitic glaucoma (one eye). Stage classifications at diagnosis were stage IA in four eyes and stages IC, IIA, IIB, and III in one eye each. All treatments were carried out with dry eye drops, steroid eye drops, and antibiotics. The mean duration of treatment was 1.4 years. The classifications at the time of the final visit were normal corneal epithelium (three eyes), stage IA (two eyes), IIA (one eye), and III (two eyes). Three eyes (37%) improved by more than one stage and one eye deteriorated by more than one stage. LSCD is long-lasting and difficult to treat in a short period; thus, it requires careful medical attention.

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. However, the findings gradually worsened and the right upper palpebral conjunctiva remained exposed. Exposed tissue was resected and histopathological examinations revealed the presence of IgG4 positive cells (10>/400HPF). Anti-IL-5 receptor alpha chain antibody treatment was stopped and changed to prednisolone. The findings improved and anti-IL-4 receptor alpha chain antibody was added to control eosinophilic sinusitis and eosinophilic severe bronchial asthma. The lesions worsened when the prednisolone was reduced under treatment with anti-IL-4 receptor alpha-chain antibody. Conclusions and importance: In this case, the proliferative changes could not be suppressed by treatment targeting IL-5R receptor alpha-chain and IL-4R receptor alpha-chain, suggesting that the patient had VKC-like severe allergic conjunctivitis as a manifestation of IgG4-related disease. Additionally, it should be noted that if the severe conjunctivitis cannot be suppressed by treatment with immunosuppressive eye drops or various systemic biological agents, the conjunctivitis may be a manifestation of IgG4 related disease.

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. Here, we report our experience regarding deep anterior lamellar keratoplasty treatment of patients with post-LASIK granular corneal dystrophy type 2. METHODS: We describe two Japanese women who underwent deep anterior lamellar keratoplasty to treat corneal opacities that worsened after LASIK. RESULTS: One patient had a family history of corneal dystrophies. During the initial visit to our clinic, numerous fine opacities were found at the LASIK flap interface in both patients. The clinical findings were compatible with post-LASIK granular corneal dystrophy type 2. Both patients underwent deep anterior lamellar keratoplasty by one of the authors (T.C.). In both procedures, the surgeon used a visco-dissection technique and successfully removed the whole corneal stroma. Histopathological examination of the excised corneal button from each eye revealed amyloid and hyaline deposits at the LASIK flap interface. Neither patient experienced recurrent corneal opacity during the follow-up visit at 8 years (patient 1) and 6 years (patient 2). CONCLUSION: Deep anterior lamellar keratoplasty can be used for the treatment of post-LASIK granular corneal dystrophy type 2. Removal of the entire host stroma may be important for the prevention of recurrent corneal opacity.

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 ± 13.6 years) from 101 LDO patients and 113 ASOCT images (29 men and 84 women; mean age, 38.3 ± 19.9 years) from 71 normal subjects. We trained to construct 9 single and 502 ensemble DL models with 9 different network structures, and calculated the area under the curve (AUC), sensitivity, and specificity to compare the distinguishing abilities of these single and ensemble DL models. RESULTS: For the highest single DL model (DenseNet169), the AUC, sensitivity, and specificity for distinguishing LDO were 0.778, 64.6%, and 72.1%, respectively. For the highest ensemble DL model (VGG16, ResNet50, DenseNet121, DenseNet169, InceptionResNetV2, InceptionV3, and Xception), the AUC, sensitivity, and specificity for distinguishing LDO were 0.824, 84.8%, and 58.8%, respectively. The heat maps indicated that these DL models placed their focus on the tear meniscus region of the ASOCT images. CONCLUSION: The combination of DL and ASOCT images could distinguish between tear meniscus of LDO patients and normal subjects with a high level of accuracy. These results suggest that DL might be useful for automatic screening of patients for LDO.

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 ± 17.7 years; 44 men and 93 women) and 84 images from 84 individuals with normal meibomian glands (mean age, 53.3 ± 19.6 years; 29 men and 55 women). We constructed and trained 9 different network structures and used single and ensemble DL models and calculated the area under the curve, sensitivity, and specificity to compare the diagnostic abilities of the DL. RESULTS: For the single DL model (the highest model; DenseNet-201), the area under the curve, sensitivity, and specificity for diagnosing obstructive MGD were 0.966%, 94.2%, and 82.1%, respectively, and for the ensemble DL model (the highest ensemble model; VGG16, DenseNet-169, DenseNet-201, and InceptionV3), 0.981%, 92.1%, and 98.8%, respectively. CONCLUSIONS: Our network combining DL and in vivo laser confocal microscopy learned to differentiate between images of healthy meibomian glands and images of obstructive MGD with a high level of accuracy that may allow for automatic obstructive MGD diagnoses in patients in the future.

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. CME-530 and SP-6000 images were compared to assess the consistency of the fully automated method. The SP-6000 images from the two methods were compared. Intraclass correlation coefficients (ICCs) for the three measurements were calculated, and parametric multiple comparisons tests and Bland-Altman analysis were performed. RESULTS: The ECD mean value was 2425 ± 883 (range 516-3707) cells/mm2. ICC values were > 0.9 for all three microscopes for ECD, but the coefficients of variation (CVs) were 0.3-0.6. For ECD measurements, Bland-Altman analysis revealed that the mean difference was 42 cells/mm2 between the SP-2000P and SP-6000 for the center-dot method; 57 cells/mm2 between the SP-6000 measurements from both methods; and -5 cells/mm2 between the SP-6000 and CME-530 for the fully automated method (95% limits of agreement: - 201 to 284 cell/mm2, - 410 to 522 cells/mm2, and - 327 to 318 cells/mm2, respectively). For CV measurements, the mean differences were - 3, - 12, and 13% (95% limits of agreement - 18 to 11, - 26 to 2, and - 5 to 32%, respectively). CONCLUSIONS: Despite using three replicate measurements, the precision of the center-dot method with the SP-2000P and SP-6000 software was only ± 10% for ECD data and was even worse for the fully automated method. CLINICAL TRIAL REGISTRATION: Japan Clinical Trials Register ( http://www.umin.ac.jp/ctr/index/htm9 ) number UMIN 000015236.