Vitreoretinal lymphomas (VRL) are rare diseases. They comprise about 1% to 3% of intraocular tumors and the incidence varies between 0.02 to 0.05 of 100 000 people in the North American population.¹

To estimate the prevalence of nonrefractive visual impairment and blindness in European persons 55 years of age and older. Few visual impairment and blindness prevalence estimates are available for the European population. In addition, many of the data collected in European population-based studies currently are unpublished and have not been included in previous estimates. Fourteen European population-based studies participating in the European Eye Epidemiology Consortium (n = 70 723) were included. Each study provided nonrefractive visual impairment and blindness prevalence estimates stratified by age (10-year strata) and gender. Nonrefractive visual impairment and blindness were defined as best-corrected visual acuity worse than 20/60 and 20/400 in the better eye, respectively. Using random effects meta-analysis, prevalence rates were estimated according to age, gender, geographical area, and period (1991-2006 and 2007-2012). Because no data were available for Central and Eastern Europe, population projections for numbers of affected people were estimated using Eurostat population estimates for European high-income countries in 2000 and 2010. The age-standardized prevalence of nonrefractive visual impairment in people 55 years of age or older decreased from 2.22% (95% confidence interval [CI], 1.34-3.10) from 1991 through 2006 to 0.92% (95% CI, 0.42-1.42) from 2007 through 2012. It strongly increased with age in both periods (up to 15.69% and 4.39% in participants 85 years of age or older from 1991 through 2006 and from 2007 through 2012, respectively). Age-standardized prevalence of visual impairment tended to be higher in women than men from 1991 through 2006 (2.67% vs. 1.88%), but not from 2007 through 2012 (0.87% vs. 0.88%). No differences were observed between northern, western, and southern regions of Europe. The projected numbers of affected older inhabitants in European high-income countries decreased from 2.5 million affected individuals in 2000 to 1.2 million in 2010. Of those, 584 000 were blind in 2000, in comparison with 170 000 who were blind in 2010. Despite the increase in the European older population, our study indicated that the number of visually impaired people has decreased in European high-income countries in the last 20 years. This may be the result of major improvements in eye care and prevention, the decreasing prevalence of eye diseases, or both.

Purpose: To evaluate the reliability of automated fluid detection in identifying retinal fluid activity in OCT scans of patients treated with anti-VEGF therapy for neovascular age-related macular degeneration by correlating human expert and automated measurements with central retinal subfield thickness (CSFT) and fluid volume values. Methods: We utilized an automated deep learning approach to quantify macular fluid in SD-OCT volumes (Cirrus, Spectralis, Topcon) from patients of HAWK and HARRIER Studies. Three-dimensional volumes for IRF and SRF were measured at baseline and under therapy in the central millimeter and compared to fluid gradings, CSFT and foveal centerpoint thickness (CPT) values measured by the Vienna Reading Center. Results: 41.906 SD-OCT volume scans were included into the analysis. Concordance between human expert grading and automated algorithm performance reached AUC values of 0.93/0.85 for IRF and 0.87 for SRF in HARRIER/HAWK in the central millimeter. IRF volumes showed a moderate correlation with CSFT at baseline (HAWK: r = 0.54; HARRIER: r = 0.62) and weaker correlation under therapy (HAWK: r = 0.44; HARRIER: r = 0.34). SRF and CSFT correlations were low at baseline (HAWK: r = 0.29; HARRIER: r = 0.22) and under therapy (HAWK: r = 0.38; HARRIER: r = 0.45). The residual standard error (IRF: 75.90 µm; SRF: 95.26 µm) and marginal residual standard deviations (IRF: 46.35 µm; SRF: 44.19 µm) of fluid volume were high compared to the range of CSFT values. Conclusion: Deep learning-based segmentation of retinal fluid performs reliably on OCT images. CSFT values are weak indicators for fluid activity in nAMD. Automated quantification of fluid types, highlight the potential of deep learning-based approaches to objectively monitor anti-VEGF therapy.

Vitreoretinal lymphoma (VRL) is a rare ocular pathology that is notorious for mimicking chronic uveitis, which is a seemingly benign condition in comparison. The most common form of VRL is the diffuse large B-cell type, and there has been a high mortality rate. This dismal prognosis can be improved significantly if the disease is diagnosed early, but until now there is no consensus on an appropriate diagnostic algorithm. We conducted a retrospective search of PubMed Central^® and analyzed results from thirty-three studies that were published between 2011–2021. The chosen studies incorporated some popular testing tools for VRL, and our analyses focused on comparing the average sensitivity of five diagnostic methods. The methods included cytology including ancillary immunohistochemistry, Myeloid Differentiation Factor 88 (MyD88) mutation analysis, polymerase chain reaction (PCR) for monoclonal rearrangements of immunoglobulin heavy chain (IgH) and T-cell Receptor (TCR) genes, flow cytometry, and IL10 and IL6 analysis. Across the varied diagnostic methods employed in thirty-three studies explored in this analysis, MyD88 mutation assay emerged as a strong contender given its sensitivity and low coefficient of variation. There is an imminent need for the introduction of newer assays that can further improve the sensitivity of identifying MyD88 mutation in cancer cells seen in the vitreous.

Objectives To assess the agreement in evaluating optical coherence tomography (OCT) variables in the leading macular diseases such as neovascular age-related macular degeneration (nAMD), diabetic macular oedema (DMO) and retinal vein occlusion (RVO) among OCT-certified graders. Methods SD-OCT volume scans of 356 eyes were graded by seven graders. The grading included presence of intra- and subretinal fluid (IRF, SRF), pigment epithelial detachment (PED), epiretinal membrane (ERM), conditions of the vitreomacular interface (VMI), central retinal thickness (CRT) at the foveal centre-point (CP) and central millimetre (CMM), as well as height and location of IRF/SRF/PED. Kappa statistics (κ) and intraclass correlation coefficient (ICC) were used to report categorical grading and measurement agreement. Results The overall agreement on the presence of IRF/SRF/PED was κ = 0.82/0.85/0.81; κ of VMI condition was 0.77, that of ERM presence 0.37. ICC for CRT measurements at CP and CMM was excellent with an ICC of 1.00. Height measurements of IRF/SRF/PED showed robust consistency with ICC = 0.85–0.93. There was substantial to almost perfect agreement in locating IRF/SRF/PED with κ = 0.67–0.86. Between diseases, κ of IRF/SRF presence was 0.69/0.80 for nAMD, 0.64/0.83 for DMO and 0.86/0.89 for RVO. Conclusion Even in the optimized setting, featuring certified graders, standardized image acquisition and the use of a professional reading platform, there is a disease dependent variability in biomarker evaluation that is most pronounced for IRF in nAMD as well as DMO. Our findings highlight the variability in the performance of human expert OCT grading and the need for AI-based automated feature analyses.

Background/Aims To explore whether the existence and pattern of distribution of macular haemorrhage or exudate can be valuable diagnostic markers for macular neovascularization type 3 (MNV3) in patients with neovascular age‐related macular degeneration. Methods Eighty‐three eyes of 83 consecutive treatment naïve patients with stage 3 MNV3 were enrolled. The diagnosis was based on fluorescein angiography (FA) and optical coherence tomography (OCT). Subretinal and intraretinal haemorrhage and dense exudates were evaluated on colour fundus photography. Fluorescein angiography (FA) images and OCT scans were used to identify the axial location of the haemorrhage. 83 patients with MNV1 and 83 with MNV2 were included as two control groups. Results In the MNV3 group, 62 (75%) eyes had intraretinal haemorrhage and 52 (63%) had dense exudates. 73 (88%) eyes had intraretinal haemorrhage and/or dense exudates. 41 (49%) had both pathologies. The intraretinal haemorrhage was flame shaped over the lesion and punctate or semi‐punctate further away from it and directed to the fovea. No subretinal haemorrhage was noticed. In the MNV1 and MNV2 groups, 11 (13%) and 24 (29%) eyes had subretinal haemorrhage or dense exudates, respectively. No intraretinal haemorrhage was seen in the two control groups. The prevalence of exudates and haemorrhage (irrespective of its location) was greater in MNV3 than in MNV1 or 2 (p < 0.0001). Conclusion The existence and pattern of distribution of intraretinal haemorrhage is pathognomonic of MNV3. It makes (alone or with dense exudates) the diagnose MNV3 possible using fundoscopy or colour fundus photo and without further diagnostic expenditure.