Evaluating optical coherence tomography (OCT) findings as potential biomarkers in central nervous system (CNS) lymphoma with or without ocular involvement

Background To evaluate spectral domain optical coherence tomography (SD-OCT) findings as biomarkers in primary central nervous system lymphoma (PCNSL) with or without ocular involvement. Methods This study was a cross-sectional study and patients with a confirmed diagnosis of PCNSL with or without ocular involvement were included. Patient cohort finder tool was used to identify patients with lymphoma using ICD-10 codes (C82–C88), from January 2004 to October 2017. A total of 14,820 patients were identified. Procedure code (92134) for optical coherence tomography (OCT) was then applied to identify patients who had underdone OCT imaging at ophthalmology clinic. Clinic charts of 460 patients with lymphoma and available OCT were reviewed to identify patients with confirmed diagnosis of PCNSL and divided into two groups (Group 1: with and Group 2: without ocular involvement). OCT scans of patients in both study groups were analyzed for the presence of (1) Hyperreflective deposits in choroid, retinal pigment epithelium (RPE), outer and inner retina; (2) RPE thickening; (3) Vitreous debris; (4) Intraretinal fluid; (5) Ellipsoid zone disruption by masked graders. Chi-square was used to analyze the difference between the groups. Results Twenty-two eyes (11 patients) with PCNSL were included this study (Group 1: 6 eyes and Group 2: 16 eyes). Mean age of subjects was 65 years. Five patients (45.45%) were female. There was no statistically significant difference between the groups for the presence of hyperreflective deposits in choroid, RPE, outer and inner retina, and presence of RPE thickening, intraretinal fluid, and ellipsoid zone disruption. Vitreous debris was found more commonly in group 1 subjects (83%) than group 2 (31.25%) (p = 0.029). All subjects in both groups showed hyperreflective deposits in the RPE demonstrating RPE infiltration. However, RPE thickening was noted only in 3 patients (Group1: 1 and Group2: 2). Conclusions OCT finding of hyperreflective deposits present in eyes with lymphoma secondary to PCNSL are also observed in eyes with PCNSL without ocular disease. However, the vitreous deposits are more commonly found in eyes with ocular disease. These hyperreflective deposits can serve as biomarkers for early detection of ocular involvement by PCNSL.

Causes of poor eye contact in infants: a population-based study

Background Establishing eye contact between infants and parents is important for early parent-child bonding and lack of eye contact may be a sign of severe underlying disease. The aim of the study was to evaluate the causes of poor or lacking eye contact in infants. Methods Cross-sectional study reviewing all referrals of infants ≤1 year of age from January 1rst, 2016 to December 31rst, 2018. Medical information was retrieved from patient files covering pregnancy, birth, diagnostic work-up and ocular parameters such as refraction, visual acuity and structural findings. Results We identified 99 infants with poor or lacking eye contact. The relative frequency of causes was neurologic disease 36.4% (36/99), delayed visual maturation 24.2% (24/99), ocular disease 21.2% (21/99) and idiopathic infantile nystagmus 4.0% (4/99). Fourteen infants had a visual function within age-related norms at first examination despite poor eye contact at the time of referral. Of the infants with available data, 18/27 (33.3%) with neurologic cause, 15/23 (65.2%) with delayed visual maturation and 9/21 (42.9%) with ocular cause had visual acuity within the age-related norm at latest follow-up (0-41 months). In 23 infants, a genetic cause was found. Conclusion Poor eye contact in infants may be a sign of severe underlying disease, such as neurological or ocular disease. Close collaboration between pediatric ophthalmologists and neuro-pediatricians are warranted in the management of these infants.

A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection

Glaucoma is a chronic ocular disease characterized by damage to the optic nerve resulting in progressive and irreversible visual loss. Early detection and timely clinical interventions are critical in improving glaucoma-related outcomes. As a typical and complicated ocular disease, glaucoma detection presents a unique challenge due to its insidious onset and high intra- and interpatient variabilities. Recent studies have demonstrated that robust glaucoma detection systems can be realized with deep learning approaches. The optic disc (OD) is the most commonly studied retinal structure for screening and diagnosing glaucoma. This paper proposes a novel context aware deep learning framework called GD-YNet, for OD segmentation and glaucoma detection. It leverages the potential of aggregated transformations and the simplicity of the YNet architecture in context aware OD segmentation and binary classification for glaucoma detection. Trained with the RIGA and RIMOne-V2 datasets, this model achieves glaucoma detection accuracies of 99.72%, 98.02%, 99.50%, and 99.41% with the ACRIMA, Drishti-gs, REFUGE, and RIMOne-V1 datasets. Further, the proposed model can be extended to a multiclass segmentation and classification model for glaucoma staging and severity assessment.

The Hard Facts on GP Contact Lens Care

The article is designed to explain the various steps needed to be undertaken daily to keep gas permeable (GP) contact lenses clean, wettable, and free from pathogens that could cause ocular disease. It explains why the steps need to be performed and what the adverse consequences of failing to perform them might be.Translation of the article: Ruslan Tahaveev (Academy of Medical Optics and Optometry