研究目的
To evaluate microvascular changes and quantitative parameters in patients with central retinal vein occlusion (CRVO) using optical coherence tomography angiography (OCTA) and to find differences between ischemic and non-ischemic CRVO types.
研究成果
OCTA can accurately evaluate microvascular structures in CRVO patients, with deep capillary plexus being more severely affected. It helps in distinguishing ischemic from non-ischemic CRVO and may have prognostic value for visual outcome. A reduced model formula (3.9 × F1S + 0.8 × F3S) with a threshold of 12.6 provides good diagnostic accuracy.
研究不足
OCTA cannot be used in patients with significant opacity and poor fixation, leading to exclusion of some patients. Limited sample size. Difficulty in assessing accurate ischemic area in retinal periphery due to hemorrhage in acute CRVO. Severe macular edema may interfere with OCTA interpretation due to signal attenuation and disorganization. Automated segmentation may cause artifacts. Results are generalized only to selected patients without severe macular edema.
1:Experimental Design and Method Selection:
Observational case-control study using OCTA to assess microvascular parameters in CRVO patients and healthy controls. Statistical analysis included generalized estimating equation (GEE), ROC curve analysis, and logistic regression.
2:Sample Selection and Data Sources:
31 patients with new-onset treatment-na?ve CRVO (≤1 month) and 20 age/gender-matched healthy controls. Exclusion criteria included significant media opacity, low image quality (signal strength index <50), severe cystoid macular edema, history of intraocular injection, and other ophthalmologic conditions.
3:List of Experimental Equipment and Materials:
OCTA device (Optovue, Inc, Fremont CA, USA) operating at 840 nm wavelength with 70,000 A-scans per second, using split-spectrum amplitude decorrelation angiography algorithm. Images were taken at 3×3 mm and 8×8 mm scan sizes.
4:Experimental Procedures and Operational Workflow:
OCTA was performed on all participants. Images were analyzed at three capillary layers: superficial capillary network, deep capillary network, and choriocapillaris. Blood flow and vascular density were calculated in specified areas.
5:Data Analysis Methods:
Data analyzed using R software. Statistical tests included Kolmogorov-Smirnov test, GEE, ROC analysis, Pearson correlation, repeated measures ANOVA, and logistic regression with AIC and BIC criteria.
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