Safety and Efficacy of Ranibizumab in Diabetic Macular Edema (RESOLVE Study): A 12-month, randomized, controlled, double-masked, multicenter phase II study

The expression of vascular endothelial growth factor (VEGF) is elevated in diabetic macular edema (DME). Ranibizumab binds to and inhibits multiple VEGF variants. We investigated the safety and efficacy of ranibizumab in DME involving the foveal center.

Behavior of SD-OCT-detected hyperreflective foci in the retina of anti-VEGF-treated patients with diabetic macular edema

Hyperreflective foci (HFs) are observable within the neurosensory retina in diabetic macular edema (DME) using spectral domain optical coherence tomography (SD-OCT). HFs have also been seen in wet age-related macular degeneration (AMD), although the origin is still unknown; however, they reduced significantly during anti-VEGF (vascular endothelial growth factor) therapy, and their baseline amount seemed to correlate with treatment success. In this study the behavior of HFs was evaluated during anti-VEGF therapy for DME.

Differential optical densities of intraretinal spaces

PURPOSE: To test the hypothesis that hyporeflective spaces in the neuroretina found on optical coherence tomography (OCT) examination have different optical reflectivities according to whether they are associated with exudation or degeneration. METHODS: Retrospective analysis of eyes with idiopathic perifoveal telangiectasia (IPT), diabetic macular edema (DME), idiopathic central serous chorioretinopathy (CSC), retinitis pigmentosa (RP), or cone dystrophy (CD) and eyes of healthy control subjects. OCT scans were performed. Raw scan data were exported and used to calculate light reflectivity profiles. Reflectivity data were acquired by projecting three rectangular boxes, each 50 pixels long and 5 pixels wide, into the intraretinal cystoid spaces, centrally onto unaffected peripheral RPE, and onto the prefoveolar vitreous. Light reflectivity in the retinal pigment epithelium (RPE), vitreous, and intraretinal spaces for the different retinal conditions and control subjects were compared. RESULTS: Reflectivities of the vitreous and the RPE were similar among the groups. Hyporeflective spaces in eyes with exudation (DME, RP, and CSC) had higher reflectivity compared with the mean reflectivity of the vitreous, whereas the cystoid spaces in the maculae of the eyes without exudation (CD and IPT) had a lower reflectivity than did the normal vitreous. CONCLUSIONS: Analysis of the light reflectivity profiles may be a tool to determine whether the density of hyporeflective spaces in the macula is greater or less than that of the vitreous, and may be a way to differentiate degenerative from exudative macular disease.

Differentiation of Diabetic Macular Edema From Pseudophakic Cystoid Macular Edema by Spectral-Domain Optical Coherence Tomography.

PURPOSE: To differentiate diabetic macular edema (DME) from pseudophakic cystoid macular edema (PCME) based solely on spectral-domain optical coherence tomography (SD-OCT). METHODS: This cross-sectional study included 134 participants: 49 with PCME, 60 with DME, and 25 with diabetic retinopathy (DR) and ME after cataract surgery. First, two unmasked experts classified the 25 DR patients after cataract surgery as either DME, PCME, or mixed-pattern based on SD-OCT and color-fundus photography. Then all 134 patients were divided into two datasets and graded by two masked readers according to a standardized reading-protocol. Accuracy of the masked readers to differentiate the diseases based on SD-OCT parameters was tested. Parallel to the masked readers, a computer-based algorithm was established using support vector machine (SVM) classifiers to automatically differentiate disease entities. RESULTS: The masked readers assigned 92.5% SD-OCT images to the correct clinical diagnose. The classifier-accuracy trained and tested on dataset 1 was 95.8%. The classifier-accuracy trained on dataset 1 and tested on dataset 2 to differentiate PCME from DME was 90.2%. The classifier-accuracy trained and tested on dataset 2 to differentiate all three diseases was 85.5%. In particular, higher central-retinal thickness/retinal-volume ratio, absence of an epiretinal-membrane, and solely inner nuclear layer (INL)-cysts indicated PCME, whereas higher outer nuclear layer (ONL)/INL ratio, the absence of subretinal fluid, presence of hard exudates, microaneurysms, and ganglion cell layer and/or retinal nerve fiber layer cysts strongly favored DME in this model. CONCLUSIONS: Based on the evaluation of SD-OCT, PCME can be differentiated from DME by masked reader evaluation, and by automated analysis, even in DR patients with ME after cataract surgery. The automated classifier may help to independently differentiate these two disease entities and is made publicly available.