Dataset Information

Hyperreflectivity of Inner Retinal Layers as a Quantitative Parameter of Ischemic Damage in Acute Retinal Vein Occlusion (RVO): An Optical Coherence Tomography Study.

ABSTRACT: Purpose:To investigate the reflectivity changes of inner retinal layers in acute retinal vein occlusion (RVO) on spectral-domain optical coherence tomography (SD-OCT) and to correlate these values with other known parameters of acute ischemic damage. Patients and Methods:In this retrospective and observational case series, 230 eyes from 115 patients with acute RVO (central or branch) were categorized as ischemic or non-ischemic depending on fluorescein angiography (FA) images at baseline. Thickness and reflectivity of selected retinal layers were measured from SD-OCT images at baseline. Reflectivity values were correlated with other parameters of acute ischemic damage (best-corrected visual acuity (BCVA), retinal thickness, extent of macular edema, ischemic area on fluorescein angiography). The data were compared with contralateral eyes (controls). Prominent middle limiting membrane sign (p-MLM) was also registered. Results:RVO reflectivity values differed significantly in all retinal layers compared to controls (P<0.001). Ischemic RVO eyes had higher optical intensity values for the innermost retinal layer (IMRL; P=0.008) and inner retinal layer (P=0.019) compared to non-ischemic cases. For all RVO eyes as well as central RVO, severity parameters like BCVA, central and total retinal thickness showed a strong correlation with the IMRL reflectivity. In branch RVO, BCVA remained significantly correlated with the IMRL reflectivity, while the thickness values showed significant correlation only for central foveal thickness in non-ischemic branch RVO type. The p-MLM was seen on OCT in 94% of the ischemic and in 66% of the non-ischemic RVO cases. Conclusion:Acute RVO leads to increased reflectivity of inner retinal layers with significantly higher values in the ischemic vs non-ischemic type. Increased inner retinal layers' reflectivity correlated significantly with BCVA, retinal thickness of separate retinal layers, as well as ischemic area on FA. Quantitative non-invasive measurement of inner retinal layers' reflectivity might be used to determine the extent of acute ischemic retinal damage in RVO.

SUBMITTER: Furashova O

PROVIDER: S-EPMC7457850 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Hyperreflectivity of Inner Retinal Layers as a Quantitative Parameter of Ischemic Damage in Acute Retinal Vein Occlusion (RVO): An Optical Coherence Tomography Study.

Furashova Olga O Matthè Egbert E

Clinical ophthalmology (Auckland, N.Z.) 20200824

<h4>Purpose</h4>To investigate the reflectivity changes of inner retinal layers in acute retinal vein occlusion (RVO) on spectral-domain optical coherence tomography (SD-OCT) and to correlate these values with other known parameters of acute ischemic damage.<h4>Patients and methods</h4>In this retrospective and observational case series, 230 eyes from 115 patients with acute RVO (central or branch) were categorized as ischemic or non-ischemic depending on fluorescein angiography (FA) images at b ...[more]

PMID: 32921978

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Project description:PurposeTo report an asymmetry analysis of macular inner retinal layers using swept-source optical coherence tomography (OCT) and to evaluate the utility for glaucoma diagnosis.DesignObservational, cross-sectional study.ParticipantsSeventy normal healthy subjects and 62 glaucoma patients.MethodsThree-dimensional scans were acquired from 70 normal subjects and 62 open angle glaucoma patients by swept-source OCT. The thickness of the retinal nerve fiber layer, ganglion cell-inner plexiform layer (GCIPL), ganglion cell complex, and total retina were calculated within a 6.2×6.2 mm macular area divided into a 31×31 grid of 200×200 ?m superpixels. For each of the corresponding superpixels, the thickness differences between the subject eyes and contra-lateral eyes and between the upper and lower macula halves of the subject eyes were determined. The negative differences were displayed on a gray-scale asymmetry map. Black superpixels were defined as thickness decreases over the cut-off values.ResultsThe negative inter-ocular and inter-hemisphere differences in GCIPL thickness (mean ± standard deviation) were -2.78 ± 0.97 ?m and -3.43 ± 0.71 ?m in the normal group and -4.26 ± 2.23 ?m and -4.88 ± 1.46 ?m in the glaucoma group. The overall extent of the four layers' thickness decrease was larger in the glaucoma group than in the normal group (all Ps<0.05). The numbers of black superpixels on all of the asymmetry maps were larger in the glaucoma group than in the normal group (all Ps<0.05). The area under receiver operating characteristic curves of average negative thickness differences in macular inner layers for glaucoma diagnosis ranged from 0.748 to 0.894.ConclusionsThe asymmetry analysis of macular inner retinal layers showed significant differences between the normal and glaucoma groups. The diagnostic performance of the asymmetry analysis was comparable to that of previous methods. These findings suggest that the asymmetry analysis can be a potential ancillary diagnostic tool.

Project description:PurposeTo examine whether deep-learning denoised optical coherence tomography angiography (OCTA) images could enhance automated macular ischemia quantification in branch retinal vein occlusion (BRVO).MethodsThis retrospective, single-center, cross-sectional study enrolled 74 patients with BRVO and 46 age-matched healthy subjects. The severity of macular ischemia was graded as mild, moderate, or severe. Denoised OCTA images were produced using a neural network model. Quantitative parameters derived from denoised images, including vessel density and nonperfusion area, were compared with those derived from the OCTA machine. The main outcome measures were correlations between quantitative parameters, and areas under receiver operating characteristic curves (AUCs) in classifying the severity of the macular ischemia.ResultsThe vessel density and nonperfusion area from denoised images were correlated strongly with the corresponding parameters from machine-derived images in control eyes and BRVO eyes with mild or moderate macular ischemia (all P < 0.001). However, no such correlation was found in eyes with severe macular ischemia. The vessel density and nonperfusion area from denoised images had significantly larger area under receiver operating characteristic curve than those derived from the original images in classifying moderate versus severe macular ischemia (0.927 vs 0.802 [P = 0.042] and 0.946 vs 0.797, [P = 0.022], respectively). There were no significant differences in the areas under receiver operating characteristic curve between the denoised images and the machine-derived parameters in classifying control versus BRVO, and mild versus moderate macular ischemia.ConclusionsA neural network model is useful for removing speckle noise on OCTA images and facilitating the automated grading of macular ischemia in eyes with BRVO.Translational relevanceDeep-learning denoised optical coherence tomography angiography images could enhance automated macular ischemia quantification.

Project description:PurposeTo determine the impact of segmentation error correction and precision of standardized grading of time domain optical coherence tomography (OCT) scans obtained during an interventional study for macular edema secondary to central retinal vein occlusion (CRVO).MethodsA reading center team of two readers and a senior reader evaluated 1199 OCT scans. Manual segmentation error correction (SEC) was performed. The frequency of SEC, resulting change in central retinal thickness after SEC, and reproducibility of SEC were quantified. Optical coherence tomography characteristics associated with the need for SECs were determined. Reading center teams graded all scans, and the reproducibility of this evaluation for scan quality at the fovea and cystoid macular edema was determined on 97 scans.ResultsSegmentation errors were observed in 360 (30.0%) scans, of which 312 were interpretable. On these 312 scans, the mean machine-generated central subfield thickness (CST) was 507.4 ± 208.5 μm compared to 583.0 ± 266.2 μm after SEC. Segmentation error correction resulted in a mean absolute CST correction of 81.3 ± 162.0 μm from baseline uncorrected CST. Segmentation error correction was highly reproducible (intraclass correlation coefficient [ICC] = 0.99-1.00). Epiretinal membrane (odds ratio [OR] = 2.3, P < 0.0001), subretinal fluid (OR = 2.1, P = 0.0005), and increasing CST (OR = 1.6 per 100-μm increase, P < 0.001) were associated with need for SEC. Reading center teams reproducibly graded scan quality at the fovea (87% agreement, kappa = 0.64, 95% confidence interval [CI] 0.45-0.82) and cystoid macular edema (92% agreement, kappa = 0.84, 95% CI 0.74-0.94).ConclusionsOptical coherence tomography images obtained during an interventional CRVO treatment trial can be reproducibly graded. Segmentation errors can cause clinically meaningful deviation in central retinal thickness measurements; however, these errors can be corrected reproducibly in a reading center setting.Translational relevanceSegmentation errors are common on these images, can cause clinically meaningful errors in central retinal thickness measurement, and can be corrected reproducibly in a reading center setting.

Project description:BackgroundRetinal vein occlusion (RVO) is the second most common vision-threatening retinal vascular disease. Intravitreal dexamethasone implant has been applied to treat macular edema secondary to RVO (RVO-ME). However, the alteration of morphologic features detected with optical coherence tomography angiography (OCTA) has not been fully studied in RVO-ME patients before and after the treatment.ObjectiveThis study is aimed at identifying potential therapeutic targets in RVO with integrative bioinformatic analysis and compares the OCTA characteristics alterations in patients with RVO-ME receiving injection of dexamethasone intravitreal implant.MethodsBioinformatic analysis was analyzed in GSE101398 dataset from the Gene Expression Omnibus database. Multiple functional enrichment analyses were performed, and protein-protein interaction network was constructed to visualize the key node genes. Eleven eyes with RVO-ME were examined with OCTA before and after intravitreal dexamethasone implant. The OCTA parameters, including macular thickness, vessel density, foveal avascular zone parameters, the number of hyperreflective foci (HRF), area of cystoid edema, and subretinal fluid (SRF), were compared. The correlation was analyzed between best-corrected visual acuity (BCVA) and OCTA parameters.ResultsA total of 79 differentially expressed genes were identified. Functional enrichment analyses revealed the enriched inflammatory events in RVO. In RVO-ME, Pearson correlation revealed that baseline BCVA was positively correlated with the area of SRF and central macular thickness, while no correlation was detected between baseline BCVA and HRF number or the area of cystoid edema. The visual acuity improved, and the central macular thickness was decreased after intravitreal dexamethasone implant injection. Besides, the number of HRF, the area of cystoid edema, and SRF were significantly alleviated after dexamethasone intravitreal injection.ConclusionRetinal inflammation plays a crucial role in RVO pathogenesis. The imaging biomarkers of RVO including Müller glial intracellular edema, and retinal pigment epithelium dysfunction, could be assessed in OCTA and attenuated by intravitreal dexamethasone implant effectively.

Dataset Information

Hyperreflectivity of Inner Retinal Layers as a Quantitative Parameter of Ischemic Damage in Acute Retinal Vein Occlusion (RVO): An Optical Coherence Tomography Study.

Publications

Hyperreflectivity of Inner Retinal Layers as a Quantitative Parameter of Ischemic Damage in Acute Retinal Vein Occlusion (RVO): An Optical Coherence Tomography Study.

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