Journal of Ophthalmic and Optometric Sciences

Background: The human body's microbiome having a powerful impact on many diseases, it was necessary to study the relationship between DED and the ocular microbiome, and the purpose of this study is to examine the existence of this connection.

Material and Methods: Two datasets of the ocular surface microbiome in dry eye patients were used for this research, one with data of patients before and after treatment with intense pulsed light (IPL), while the other only holds information on cases suffering from a dry eye condition. 

Results: The first dataset of both eyes of 20 patients with dry eye symptoms before and after IPL therapy was analyzed entirely. Bacteroidales (in 61 percent of the patients), Actinomycetales (in 60 percent of patients), Lactobacillales (in 61 percent of patients), and Erysipelotrichales (in 61 percent of patients) declined after the treatment. Still, the total difference between patient populations and treatment was not statistically proven (P value > 0.05). The second dataset contained data from 87 patients with dry eye disease, and it demonstrated that Burkholderiales, Actinomycetales, Pseudomonadales, and Clostridiales are among the most abundant bacteria in this group, in contrast to the first dataset, which was occupied by Clostridiales, Burkholderiales, Actinomycetales, Bacteroidales, Bacillales, and Lactobacillales.

Conclusion: This study showed there are multiple bacterial orders that have increased or decreased after the patients received their treatment with IPL, stating a potential connection between the mentioned orders and DED. More research is necessary to indicate a solid relationship between these two.

Background: Coats is a retinal disorder causing dilation of blood vessels in the human retina. The present study aims to measure electroretinography (ERG) in patients suffering from Coats disease.

Material and Methods: 11 (20 eyes) male patients suffering from Coats were selected for the present study. Electroretinography was measured in the patient group using the Mangoni machine. The result was compared with the 11 (22 eyes) normal population following the ERG test. SPSS version 22 was used for this purpose.

Results: The case and control groups were not significantly different in age, while a significant difference was observed in Best corrected visual acuity. BCVA between the two groups. Furthermore ( 110.9±8.63 and 93.09 ± 8.04 in control and case respectively ) , the difference between the mean amplitude of ERG, b wave was statistically significant as far as patient and normal groups were concerned.   

Conclusion: Coats disease damages the retina, which can be measured by the amplitude of ERG, b wave.

Background: To investigate the Risk factors for AGV ( Ahmed glaucoma valve) failure.

Material and Methods: A retrospective review was conducted on the medical records of patients with varying causes of glaucoma who had undergone AGV implantation. The primary measure of success was the cumulative achievement of an intraocular pressure (IOP) between 5 and 21 mmHg, with a 20 % reduction from baseline, with or without medication to lower IOP. The secondary measures of success were the IOP levels and the number of medications used for glaucoma treatment.

Results: The study enrolled a total of 120 participants, with an average age of 48.9 ± 19.6 years and an average follow-up period of 4.5 ± 1.4 years. The mean survival duration was 5.3 ± 0.5 years in patients with high pressure (HP), which was significantly shorter than the 6.4 ± 0.2 years in those without HP. The likelihood of surgical failure increased with higher baseline IOP, with an odds ratio of 1.07 (95 % confidence interval: 1.02-1.12). In a logistic regression model, neovascular glaucoma was the only factor significantly associated with the occurrence of HP, with an odds ratio of 3.14 (95 % confidence interval: 1.2-8.1).

Conclusion :Neovascular glaucoma and a Higher Baseline IOP are risk factors for AGV failure.

Background: The cataract is the most prevalent cause of blindness worldwide and is responsible for more than 51 % of blindness cases. As the treatment process is becoming smart and the burden of ophthalmologists is reducing, many existing systems have adopted machine-learning-based cataract classification methods with manual extraction of data features. However, the manual extraction of retinal features is generally time-consuming and exhausting and requires skilled ophthalmologists.

Material and Methods: Convolutional neural network (CNN) is a highly common automatic feature extraction model which, compared to machine learning approaches, requires much larger datasets to avoid overfitting issues. This article designs a deep convolutional network for automatic cataract recognition in healthy eyes. The algorithm consists of four convolution layers and a fully connected layer for hierarchical feature learning and training.

Results: The proposed approach was tested on collected images and indicated an 90.88 % accuracy on testing data. The keras model provides a function that evaluates the model, which is equal to the value of 84.14 %, the model can be further developed and improved to be applied for the automatic recognition and treatment of ocular diseases.

Conclusion: This study presented a deep learning algorithm for the automatic recognition of healthy eyes from cataractous ones. The results suggest that the proposed scheme outperforms other conventional methods and can be regarded as a reference for other retinal disorders.

Background:To report a false negative 18F-Fluorodeoxyglucose (FDG) positron emission tomography/ computed tomography (PET/CT) of liver metastasis in a patient with malignant uveal melanoma.

Material and Methods:A 74-year-old man with left eye uveal melanoma and liver metastasis that was found seven months after the enucleation surgery.

Results:Seven months post-enucleation surgery, ultrasonography revealed a suspicious hepatic lesion. Further investigation using magnetic resonance imaging (MRI) and PET scan was recommended. MRI with and without contrast reported mild post-contrast enhancement in the right lobe of the liver, suggestive of metastasis from the known tumor of the patient. 18F-FDG PET/CT surprisingly showed no metabolic evidence of malignancy throughout the body. Finally, the patient was scheduled for an ultrasound-guided biopsy. Pathology reported metastatic malignant melanoma.

Conclusion:It is important to remember not to rely solely on PET/CT since it may report false negative results in liver metastasis.

Dizziness and nausea are among the symptoms of multiple sclerosis (MS). The present manuscript reports a case suspected of MS who experienced severe dizziness and nausea while recording pattern reversal checkerboard (PRC) visual evoked potential (VEP), whereas she felt comfortable during the flash type of VEP (FVEP). Therefore, we suggest recording FVEP in patients with any problem produced due to PRC VEP.

Background: To summarize the neuro-ophthalmologic disorders that mimic glaucoma.

Material and Methods: All studies from PubMed, Scopus, and Google Scholar were found using these keywords: optic atrophy, neuro-ophthalmologic disorders, glaucoma mimicker, glaucoma masquerader, and mimic glaucoma.

Results: The main neuro-ophthalmologic disorders that mimic glaucoma are large physiologic cupping, optic disc cup asymmetry, hereditary optic neuropathy, tilted disc syndrome, morning glory anomaly, superior segmental optic nerve hypoplasia, optic disc coloboma, optic disc pits, optic disc drusen, high myopia, inflammatory conditions (optic neuritis), toxic-nutritional optic neuropathy, nutritional deficiency, toxins, traumatic optic neuropathy, compressive optic neuropathy, periventricular leukomalacia, hydrocephalus, perinatal asphyxia, ischemic optic neuropathy, and radiation optic neuropathy.

Conclusion: Repeated evaluations of visual functions such as visual acuity, visual field, and color vision are necessary for diagnosing glaucoma mimickers. Furthermore, a precise examination of the optic disc and retina is crucial. Notably, it is necessary to consider normal-tension glaucoma as an exclusionary diagnosis.