BRINZOLAMIDE-INDUCED EYE DISCHARGE: A RARE ENTITY

ABSTRACTA 62-year-old lady diagnosed to have normal tension glaucoma was receiving triple therapy of topical brinzolamide, timolol, and careprost. Postapplication of brinzolamide eye drops patient experienced mucoid eye discharge starting 10 minutes after application of eye drops and persistingfor ½ hr. Slit lamp examination findings did not reveal any signs of infection. She gave a history of mucoid discharge since the day she was started onbrinzolamide eye drops. There are only two case reports describing mucoid discharge following brinzolamide eye drops. Thus, we report a similarscenario in our patient. We report this case so as to avoid unnecessary suspicion of infection in such cases.Keywords: Glaucoma, mucoid, infection

BILATERAL BLINDNESS DUE TO ANTI-TUBERCULAR TREATMENT: A RARE PRESENTATION

ABSTRACTEthambutol and isoniazid (INH) are antimicrobial agents used in the treatment of tuberculosis. Optic neuropathy is a well-recognized toxic effectof these drugs, usually manifesting as a decrease in visual acuity and deficits in color vision. This study presents the case of a 75-year-old malediagnosed of spinal tuberculosis, who developed irreversible bilateral optic neuropathy causing complete blindness induced by ethambutol and INH.Ophthalmologic examination revealed sluggish pupillary reactions and optic disc pallor in both eyes. Visual evoked potential and magnetic resonanceimaging brain complemented the confirmation of the diagnosis.Keywords: Ethambutol, Isoniazid, Optic neuritis, Tuberculosis

OPTIC NEUROPATHY INDUCED BY LOW DOSE OF ETHAMBUTOL: A RARE PRESENTATION

Ethambutol is a bacteriostatic antimicrobial agent used in the treatment of tuberculosis. Optic neuropathy is a potentially severe side effect of ethambutol, which is dose related. Ethambutol-induced optic neuropathy (EON) incidence is 15%, 5% & 1% when taken at 50 mg/kg/day , 25 mg/kg/day & 15 mg/kg/day respectively for 3 months. We report a case of bilateral EON in 20-year-old female after 1 month of exposure to 15 mg/kg/day of ethambutol for tubercular meningitis. Ophthalmologic examination revealed bilateral ill sustained pupillary reactions and optic disc pallor. Deranged color vision test and scotomas on Goldmann perimetry in both eyes, aided in diagnosis.Keywords: Low dose ethambutol, Optic neuropathy, Tuberculosis

Automated retinal health diagnosis using pyramid histogram of visual words and Fisher vector techniques

Untreated age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma may lead to irreversible vision loss. Hence, it is essential to have regular eye screening to detect these eye diseases at an early stage and to offer treatment where appropriate. One of the simplest, non-invasive and cost-effective techniques to screen the eyes is by using fundus photo imaging. But, the manual evaluation of fundus images is tedious and challenging. Further, the diagnosis made by ophthalmologists may be subjective. Therefore, an objective and novel algorithm using the pyramid histogram of visual words (PHOW) and Fisher vectors is proposed for the classification of fundus images into their respective eye conditions (normal, AMD, DR, and glaucoma). The proposed algorithm extracts features which are represented as words. These features are built and encoded into a Fisher vector for classification using random forest classifier. This proposed algorithm is validated with both blindfold and ten-fold cross-validation techniques. An accuracy of 90.06% is achieved with the blindfold method, and highest accuracy of 96.79% is obtained with ten-fold cross-validation. The highest classification performance of our system shows the potential of deploying it in polyclinics to assist healthcare professionals in their initial diagnosis of the eye. Our developed system can reduce the workload of ophthalmologists significantly.Accepted versio

Diabetic retinopathy in patients with diabetic foot syndrome in South India

Purpose: The purpose was to study the retinopathy status in diabetic patients with a risk of diabetic foot (DF) syndrome visiting a tertiary care hospital in South India. Methods: In this cross sectional study all patients with diabetes mellitus (DM) with a risk of DF syndrome, visiting a tertiary care hospital during the study period, underwent an ophthalmological evaluation for documentation of their retinopathy status. Results: One hundred and eighty-two patients diagnosed to have a risk profile for DF syndrome were included in the study. Their mean age was 59.28 years and 75.27% were males. The mean duration of Type 1 and Type 2 variants of DM was 14.9 years and 10.9 years, respectively. Of the 182 patients, 67.58% had retinopathy changes. Proliferative diabetic retinopathy (DR) constituted 17.88% of the total patients with retinopathy. An increased presence of retinopathy in patients with an increased risk grade of DF was found significant by the Chi-square test (P < 0.001). Conclusion: Our study found an increased presence of DR in a South Indian cohort with DF syndrome. The severity of retinopathy was greater in patients with higher grades of risk for DF. The establishment of an association between DR and DF syndrome will help in developing an integrated management strategy for these two debilitating consequences of diabetes

Computer-aided diagnosis of glaucoma using fundus images : a review

Background and objectives: Glaucoma is an eye condition which leads to permanent blindness when the disease progresses to an advanced stage. It occurs due to inappropriate intraocular pressure within the eye, resulting in damage to the optic nerve. Glaucoma does not exhibit any symptoms in its nascent stage and thus, it is important to diagnose early to prevent blindness. Fundus photography is widely used by ophthalmologists to assist in diagnosis of glaucoma and is cost-effective. Methods: The morphological features of the disc that is characteristic of glaucoma are clearly seen in the fundus images. However, manual inspection of the acquired fundus images may be prone to inter-observer variation. Therefore, a computer-aided detection (CAD) system is proposed to make an accurate, reliable and fast diagnosis of glaucoma based on the optic nerve features of fundus imaging. In this paper, we reviewed existing techniques to automatically diagnose glaucoma. Results: The use of CAD is very effective in the diagnosis of glaucoma and can assist the clinicians to alleviate their workload significantly. We have also discussed the advantages of employing state-of-art techniques, including deep learning (DL), when developing the automated system. The DL methods are effective in glaucoma diagnosis. Conclusions:Novel DL algorithms with big data availability are required to develop a reliable CAD system. Such techniques can be employed to diagnose other eye diseases accurately

Automated screening system for retinal health using bi-dimensional empirical mode decomposition and integrated index

Posterior Segment Eye Diseases (PSED) namely Diabetic Retinopathy (DR), glaucoma and Age-related Macular Degeneration (AMD) are the prime causes of vision loss globally. Vision loss can be prevented, if these diseases are detected at an early stage. Structural abnormalities such as changes in cup-to-disc ratio, Hard Exudates (HE), drusen, Microaneurysms (MA), Cotton Wool Spots (CWS), Haemorrhages (HA), Geographic Atrophy (GA) and Choroidal Neovascularization (CNV) in PSED can be identified by manual examination of fundus images by clinicians. However, manual screening is labour-intensive, tiresome and time consuming. Hence, there is a need to automate the eye screening. In this work Bi-dimensional Empirical Mode Decomposition (BEMD) technique is used to decompose fundus images into 2D Intrinsic Mode Functions (IMFs) to capture variations in the pixels due to morphological changes. Further, various entropy namely Renyi, Fuzzy, Shannon, Vajda, Kapur and Yager and energy features are extracted from IMFs. These extracted features are ranked using Chernoff Bound and Bhattacharyya Distance (CBBD), Kullback-Leibler Divergence (KLD), Fuzzy-minimum Redundancy Maximum Relevance (FmRMR), Wilcoxon, Receiver Operating Characteristics Curve (ROC) and t-test methods. Further, these ranked features are fed to Support Vector Machine (SVM) classifier to classify normal and abnormal (DR, AMD and glaucoma) classes. The performance of the proposed eye screening system is evaluated using 800 (Normal=400 and Abnormal=400) digital fundus images and 10-fold cross validation method. Our proposed system automatically identifies normal and abnormal classes with an average accuracy of 88.63%, sensitivity of 86.25% and specificity of 91% using 17 optimal features ranked using CBBD and SVM-Radial Basis Function (RBF) classifier. Moreover, a novel Retinal Risk Index (RRI) is developed using two significant features to distinguish two classes using single number. Such a system helps to reduce eye screening time in polyclinics or community-based mass screening. They will refer the patients to main hospitals only if the diagnosis belong to the abnormal class. Hence, the main hospitals will not be unnecessarily crowded and doctors can devote their time for other urgent cases