研究目的
To propose an OCTA frame-averaging method and investigate the effects of the number of frames acquired and averaged on metrics quantifying the foveal avascular zone (FAZ), vessel morphology, and parafoveal intercapillary area (PICA).
研究成果
Averaging multiple OCTA frames reduces error in automated FAZ segmentation and improves robustness of vessel morphology and perfusion metrics, with significant benefits observed when averaging more than two frames but limited additional benefit beyond five frames. This enhances the utility of OCTA biomarkers for clinical applications.
研究不足
Small number of subjects (n=19), limited to subjects without retinal disease, narrow age range (23-49 years), specific to one OCTA device (Optovue), and reliance on a custom FAZ segmentation algorithm not validated with commercial or deep learning methods.
1:Experimental Design and Method Selection:
The study involved acquiring multiple OCTA frames, ranking them by an image quality metric (mean gradient magnitude), registering frames using rigid registration, and averaging a subset. Two studies were conducted: one varying the number of averaged frames (N) with fixed acquired frames (M=10), and another varying both M and N.
2:Sample Selection and Data Sources:
19 subjects without known retinal disease, ages 23-49, imaged using the AngioVue OCTA system.
3:List of Experimental Equipment and Materials:
AngioVue OCTA system (Optovue Inc.), MATLAB software, ImageJ with StackReg plugin, Fiji AnalyzeSkeleton plugin.
4:Experimental Procedures and Operational Workflow:
Acquire 10 OCTA volume scans per subject, export en face images, calculate gradient magnitude for quality ranking, register and average frames, apply automated FAZ segmentation algorithm, and analyze metrics (FAZ area, perimeter, centroid, PICA, vessel endpoints, vessel length).
5:Data Analysis Methods:
Statistical analysis using Wilcoxon signed-rank test, Dice coefficient for segmentation accuracy, coefficient of variation for precision, and exponential fitting for vessel metrics.
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