100 resultados para subcompositional coherence


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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.

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PURPOSE: To evaluate the quantitative and topographic relationship between reticular pseudodrusen (RPD) on infrared reflectance (IR) and subretinal drusenoid deposits (SDD) on en face volumetric spectral domain optical coherence tomography. METHODS: Reticular pseudodrusen were marked on IR images by a masked observer. Subretinal drusenoid deposits were visualized on en face sections of spectral domain optical coherence tomography below the external limiting membrane and identified by a semiautomated technique. Control RPD lesions were generated in a random distribution for each IR image. Binary maps of control and experimental RPD and SDD were merged and analyzed in terms of topographic localization and quantitative drusen load comparison. RESULTS: A total of 54 eyes of 41 patients diagnosed with RPD were included in this study. The average number of RPD lesions on IR images was 320 ± 44.62 compared with 127 ± 26.02 SDD lesions on en face (P < 0.001). The majority of RPD lesions did not overlap with SDD lesions and were located >30 μm away (92%). The percentage of total SDD lesions overlapping RPD was 2.91 ± 0.87% compared with 1.73 ± 0.68% overlapping control RPD lesions (P < 0.05). The percentage of total SDD lesions between 1 and 3 pixels of the nearest RPD lesion was 5.08 ± 1.40% compared with 3.33 ± 1.07% between 1 and 3 pixels of the nearest control RPD lesion (P < 0.05). CONCLUSION: This study identified significantly more RPD lesions on IR compared with SDD lesions on en face spectral domain optical coherence tomography and found that a large majority of SDD (>90% of lesions) were >30 μm away from the nearest RPD. Together, our findings indicate that RPD and SDD are two entities that are only occasionally topographically associated, suggesting that at some stage in their development, they may be pathologically related.

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PURPOSE The purpose of this study was to classify and detect intraretinal hemorrhage (IRH) in spectral domain optical coherence tomography (SD-OCT). METHODS Initially the presentation of IRH in BRVO-patients in SD-OCT was described by one reader comparing color-fundus (CF) and SD-OCT using dedicated software. Based on these established characteristics, the presence and the severity of IRH in SD-OCT and CF were assessed by two other masked readers and the inter-device and the inter-observer agreement were evaluated. Further the area of IRH was compared. RESULTS About 895 single B-scans of 24 eyes were analyzed. About 61% of SD-OCT scans and 46% of the CF-images were graded for the presence of IRH (concordance: 73%, inter-device agreement: k = 0.5). However, subdivided into previously established severity levels of dense (CF: 21.3% versus SD-OCT: 34.7%, k = 0.2), flame-like (CF: 15.5% versus SD-OCT: 45.5%, k = 0.3), and dot-like (CF: 32% versus SD-OCT: 24.4%, k = 0.2) IRH, the inter-device agreement was weak. The inter-observer agreement was strong with k = 0.9 for SD-OCT and k = 0.8 for CF. The mean area of IRH detected on SD-OCT was significantly greater than on CF (SD-OCT: 11.5 ± 4.3 mm(2) versus CF: 8.1 ± 5.5 mm(2), p = 0.008). CONCLUSIONS IRH seems to be detectable on SD-OCT; however, the previously established severity grading agreed weakly with that assessed by CF.

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AIM To report the finding of extension of the 4th hyper-reflective band and retinal tissue into the optic disc in patients with cavitary optic disc anomalies (CODAs). METHODS In this observational study, 10 patients (18 eyes) with sporadic or autosomal dominant CODA were evaluated with enhanced depth imaging optical coherence tomography (EDI-OCT) and colour fundus images for the presence of 4th hyper-reflective band extension into the optic disc. RESULTS Of 10 CODA patients (18 eyes), five patients (8 eyes) showed a definite 4th hyper-reflective band (presumed retinal pigment epithelium (RPE)) extension into the optic disc. In these five patients (seven eyes), the inner retinal layers also extended with the 4th hyper-reflective band into the optic disc. Best corrected visual acuity ranged from 20/20 to 20/200. In three patients (four eyes), retinal splitting/schisis was present and in two patients (two eyes), the macula was involved. In all cases, the 4th hyper-reflective band extended far beyond the termination of the choroid into the optic disc. The RPE extension was found either temporally or nasally in areas of optic nerve head excavation, most often adjacent to peripapillary pigment. Compared with eyes without RPE extension, eyes with RPE extension were more myopic (mean dioptres -0.9±2.6 vs -8.8±5, p=0.043). CONCLUSIONS The RPE usually stops near the optic nerve border separated by a border tissue. With CODA, extension of this hyper-reflective band and retinal tissue into the disc is possible and best evaluable using EDI-OCT or analogous image modalities. Whether this is a finding specific for CODA, linked to specific gene loci or is also seen in patients with other optic disc abnormalities needs further evaluation.

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The comprehensive structure of cooperation at domestic level reflects on bilateral, regional and global level.

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The complexity of migration issues is clearly reflected by states diverging national migration policy interests that exists within one state. In line with the Swiss Report on International Cooperation on Migration of the Swiss Federal Council , this complexity requires close coordination and cooperation between the governmental institutions and all offices. Only through a close and coherent cooperation between all governmental actors involved in migration issues the migration-development nexus can be strength. The present paper will suggest how intergovernmental cooperation can lead to better policy coherence in migration by interlinking all actors involved.

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PURPOSE To evaluate image contrast and color setting on assessment of retinal structures and morphology in spectral-domain optical coherence tomography. METHODS Two hundred and forty-eight Spectralis spectral-domain optical coherence tomography B-scans of 62 patients were analyzed by 4 readers. B-scans were extracted in 4 settings: W + N = white background with black image at normal contrast 9; W + H = white background with black image at maximum contrast 16; B + N = black background with white image at normal contrast 12; B + H = black background with white image at maximum contrast 16. Readers analyzed the images to identify morphologic features. Interreader correlation was calculated. Differences between Fleiss-kappa correlation coefficients were examined using bootstrap method. Any setting with significantly higher correlation coefficient was deemed superior for evaluating specific features. RESULTS Correlation coefficients differed among settings. No single setting was superior for all respective spectral-domain optical coherence tomography parameters (P = 0.3773). Some variables showed no differences among settings. Hard exudates and subretinal fluid were best seen with B + H (κ = 0.46, P = 0.0237 and κ = 0.78, P = 0.002). Microaneurysms were best seen with W + N (κ = 0.56, P = 0.025). Vitreomacular interface, enhanced transmission signal, and epiretinal membrane were best identified using all color/contrast settings together (κ = 0.44, P = 0.042, κ = 0.57, P = 0.01, and κ = 0.62, P ≤ 0.0001). CONCLUSION Contrast and background affect the evaluation of retinal structures on spectral-domain optical coherence tomography images. No single setting was superior for all features, though certain changes were best seen with specific settings.