Retinal optical coherence tomography manifestations of intraocular lymphoma

PURPOSE: Primary central nervous system lymphoma (PCNSL) is a rare disease. The index report describes a patient with intraocular lymphoma secondary to recurrent PCNSL and corresponding retinal findings on spectral domain optical coherence tomography (SD-OCT). METHODS: Case report. RESULTS: OCT changes were documented and correlated with the clinical course of intraocular lymphoma progression in the index patient. The OCT changes, manifested as hyperreflective material accumulation in the intraretinal and subretinal pigment epithelial spaces, were caused by lymphomatous infiltration. CONCLUSION: SD-OCT can be useful in diagnosing and monitoring the progression or regression of intraocular lymphoma with retinal involvement

Retinal optical coherence tomography manifestations of intraocular lymphoma.

PURPOSE: Primary central nervous system lymphoma (PCNSL) is a rare disease. The index report describes a patient with intraocular lymphoma secondary to recurrent PCNSL and corresponding retinal findings on spectral domain optical coherence tomography (SD-OCT). METHODS: Case report. RESULTS: OCT changes were documented and correlated with the clinical course of intraocular lymphoma progression in the index patient. The OCT changes, manifested as hyperreflective material accumulation in the intraretinal and subretinal pigment epithelial spaces, were caused by lymphomatous infiltration. CONCLUSION: SD-OCT can be useful in diagnosing and monitoring the progression or regression of intraocular lymphoma with retinal involvement

Application of Deep Learning to Retinal-Image-Based Oculomics for Evaluation of Systemic Health: A Review

The retina is a window to the human body. Oculomics is the study of the correlations between ophthalmic biomarkers and systemic health or disease states. Deep learning (DL) is currently the cutting-edge machine learning technique for medical image analysis, and in recent years, DL techniques have been applied to analyze retinal images in oculomics studies. In this review, we summarized oculomics studies that used DL models to analyze retinal images—most of the published studies to date involved color fundus photographs, while others focused on optical coherence tomography images. These studies showed that some systemic variables, such as age, sex and cardiovascular disease events, could be consistently robustly predicted, while other variables, such as thyroid function and blood cell count, could not be. DL-based oculomics has demonstrated fascinating, “super-human” predictive capabilities in certain contexts, but it remains to be seen how these models will be incorporated into clinical care and whether management decisions influenced by these models will lead to improved clinical outcomes

Peripheral Retinal Neovascularization with Vitreous Hemorrhage in HIV Retinopathy

We report a case of peripheral retinal neovascularization and vitreous hemorrhage in the setting of HIV retinopathy that can serve to extend the clinical spectrum of this condition. A 53-year-old African-American woman with AIDS was referred for decreased vision in the left eye and was found to have peripheral retinal neovascularization and vitreous hemorrhage. She had a workup that was negative for etiologies of retinal ischemia. Peripheral laser photocoagulation was used to treat areas of nonperfusion. To our knowledge, this is the first reported case of peripheral retinal neovascularization and vitreous hemorrhage in the setting of HIV retinopathy, and it can serve to extend the clinical spectrum of this condition

Prediction of visual impairment in retinitis pigmentosa using deep learning and multimodal fundus images

Background: The efficiency of clinical trials for retinitis pigmentosa (RP) treatment is limited by the screening burden and lack of reliable surrogate markers for functional end points. Automated methods to determine visual acuity (VA) may help address these challenges. We aimed to determine if VA could be estimated using confocal scanning laser ophthalmoscopy (cSLO) imaging and deep learning (DL). Methods: Snellen corrected VA and cSLO imaging were obtained retrospectively. The Johns Hopkins University (JHU) dataset was used for 10-fold cross-validations and internal testing. The Amsterdam University Medical Centers (AUMC) dataset was used for external independent testing. Both datasets had the same exclusion criteria: visually significant media opacities and images not centred on the central macula. The JHU dataset included patients with RP with and without molecular confirmation. The AUMC dataset only included molecularly confirmed patients with RP. Using transfer learning, three versions of the ResNet-152 neural network were trained: infrared (IR), optical coherence tomography (OCT) and combined image (CI). Results: In internal testing (JHU dataset, 2569 images, 462 eyes, 231 patients), the area under the curve (AUC) for the binary classification task of distinguishing between Snellen VA 20/40 or better and worse than Snellen VA 20/40 was 0.83, 0.87 and 0.85 for IR, OCT and CI, respectively. In external testing (AUMC dataset, 349 images, 166 eyes, 83 patients), the AUC was 0.78, 0.87 and 0.85 for IR, OCT and CI, respectively. Conclusions: Our algorithm showed robust performance in predicting visual impairment in patients with RP, thus providing proof-of-concept for predicting structure-function correlation based solely on cSLO imaging in patients with RP

Global Current Practice Patterns for the Management of Open Globe Injuries

To determine global current practice patterns for the management of open globe injuries and identify areas of variation. Cross-sectional survey. An online survey assessed global management paradigms for open globe injuries from August 2020 to January 2021. Responses were collected from experts at eye trauma centers and emergency departments worldwide who manage ≥1 open globe injury per month. The survey assessed the use/selection of antibiotics and steroids, procedural and imaging decisions, and admission practices for open globe injuries. Responses were received from representatives of 36 of 42 institutions (85.7%), of which 33 (78.6%) had sufficient trauma volume to be included. Included responses were distributed across North America (n=12, 36.4%), Asia (n=12, 36.4%), South America (n=4, 12.1%), Africa (n=3, 9.1%), Europe (n=1, 3.0%), and Australia (n=1, 3.0%). Preoperative systemic antibiotics for open globe injuries were administered by 75.8% (n = 25/33) of institutions, while 30.3% (n = 10/33) administered preoperative topical antibiotics. Intraoperative ophthalmic antibiotics for open globe injuries were used by 54.5% (n = 18/33) of experts. Most institutions also administered postoperative systemic antibiotics (n = 23 [69.7%]) and topical steroids (n = 29 [87.9%]), although specific medication choices diverged. At 19 responding centers (61.3% of the 31 that had trainees), residents participated in surgical repairs. Many institutions discharged patients after repair, but 54.5% (n = 18/33) of locations routinely admitted them for observation. Preferred management practices for open globe injuries vary widely. To ensure the highest standard of care for all patients, evidence-based international guidelines for the treatment of these injuries are needed

Global Current Practice Patterns for the Management of Central Retinal Artery Occlusion.

Global practice paradigms for central retinal artery occlusion (CRAO) were summarized. Responses were collected from specialists via survey. Management patterns for CRAO rely on physician and center-level preferences given the lack of evidence-based international guidelines