Tractional Retinal Detachment Related to Hemoglobin C Trait Retinopathy: A Case Report.

Hemoglobin C (HbC) disease is an uncommon disease that is generally considered benign, causing only occasionally painless hematuria, osteomyelitis, and dental abnormalities. Ocular manifestations have rarely been described in these patients. Here we report a novel ophthalmological manifestation of the disease. A 20-year-old woman presented with progressive visual loss in her right eye due to tractional retinal detachment. The left eye was apparently normal, but wide-field fluorescence angiography showed mild peripheral ischemia with multiple vascular abnormalities. Vitrectomy was performed and the systemic workup revealed the presence of hemoglobinopathy C in heterozygous form. HbC disease can be sight-threating due to retinal proliferation, similar to sickle cell retinopathy. Patients affected with this disease should undergo regular surveillance. Ultra-wide angiography is a helpful examination to detect peripheral ischemia in the earlier stages.

Prevalence and implications of the presence of intraocular silicone oil droplets in patients treated with intravitreal injections of anti-VEGF.

BACKGROUND: To determine the percentage of patients who have silicone droplets in the vitreous after treatment with different anti-Vascular Endothelial Growth Factor (anti-VEGF) intravitreal injections (IVI) and how symptomatic they are. METHODS: One hundred fifty-two eyes of 140 patients who had at least received an IVI were recruited for this study. Data collection included the number and type of IVI (aflibercept, ranibizumab and bevacizumab) and the follow-up time. A complete ophthalmologic examination was carried out and patients were classified in four groups according to the amount of silicone droplets found in dilated fundoscopy (nonexistent, scarce, moderate and abundant). Measurement of intraocular pressure (IOP) was also carried out. An interview was conducted to report the presence and intensity of the symptomatology. RESULTS: Silicone oil droplets were reported in 109 eyes (71.7%). A positive correlation was found between the number of IVIs received and the quantity of droplets found, especially when aflibercept was used. Posterior vitreous detachment (PVD) was present in 65.8% of the patients, showing a positive correlation with the number of bubbles. Regarding the symptomatology, 60 eyes (39.5%) had floaters and the disturbance was reported to be 4 out of 10. The group with a moderate amount of silicone droplets had the highest percentage of floaters (60%). No statistical differences in the IOP were found between groups, although the group with abundant droplets had a higher mean IOP. CONCLUSION: A high prevalence of silicone droplets in vitreous of patients who undergo IVI treatment was found. It appears to have little impact on symptomatology and rise of IOP.

Validation of an autonomous artificial intelligence-based diagnostic system for holistic maculopathy screening in a routine occupational health checkup context.

PURPOSE: This study aims to evaluate the ability of an autonomous artificial intelligence (AI) system for detection of the most common central retinal pathologies in fundus photography. METHODS: Retrospective diagnostic test evaluation on a raw dataset of 5918 images (2839 individuals) evaluated with non-mydriatic cameras during routine occupational health checkups. Three camera models were employed: Optomed Aurora (field of view - FOV 50º, 88% of the dataset), ZEISS VISUSCOUT 100 (FOV 40º, 9%), and Optomed SmartScope M5 (FOV 40º, 3%). Image acquisition took 2 min per patient. Ground truth for each image of the dataset was determined by 2 masked retina specialists, and disagreements were resolved by a 3rd retina specialist. The specific pathologies considered for evaluation were "diabetic retinopathy" (DR), "Age-related macular degeneration" (AMD), "glaucomatous optic neuropathy" (GON), and "Nevus." Images with maculopathy signs that did not match the described taxonomy were classified as "Other." RESULTS: The combination of algorithms to detect any abnormalities had an area under the curve (AUC) of 0.963 with a sensitivity of 92.9% and a specificity of 86.8%. The algorithms individually obtained are as follows: AMD AUC 0.980 (sensitivity 93.8%; specificity 95.7%), DR AUC 0.950 (sensitivity 81.1%; specificity 94.8%), GON AUC 0.889 (sensitivity 53.6% specificity 95.7%), Nevus AUC 0.931 (sensitivity 86.7%; specificity 90.7%). CONCLUSION: Our holistic AI approach reaches high diagnostic accuracy at simultaneous detection of DR, AMD, and Nevus. The integration of pathology-specific algorithms permits higher sensitivities with minimal impact on its specificity. It also reduces the risk of missing incidental findings. Deep learning may facilitate wider screenings of eye diseases.