OCTA-Based Identification of Different Vascular Patterns in Stargardt Disease

基于OCTA的Stargardt病不同血管模式的识别

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Abstract

PURPOSE: The aim of the present study was to analyze quantitative optical coherence tomography (OCT) and OCT angiography (OCTA) parameters to identify clinically relevant cutoff values able to detect clinically different Stargardt's disease (STGD) subgroups. METHODS: Consecutive STGD patients were recruited and underwent complete ophthalmologic examination, including multimodal imaging. Several quantitative parameters were extracted both from structural OCT and OCTA images and were statistically analyzed. A post hoc analysis was performed to identify a quantitative cutoff able to distinguish two clinically different STGD subgroups. Main outcome measures were total retinal thickness, central macular thickness (CMT), retinal layers thickness, retinal and choroidal hyperreflective foci (HF) number, vessel density (VD), vessel tortuosity (VT), vessel dispersion (Vdisp), and vessel rarefaction (VR) of macular and optic nerve head plexa. RESULTS: Overall, 54 eyes of 54 STGD patients (18 males) and 54 eyes of 54 healthy age- and sex-matched controls were included in the analysis. All quantitative parameters resulted significantly worse in STGD than controls (P < 0.01). Moreover, a VT cutoff of 5 allowed to distinguish the following two categories: a functionally and anatomically better STGD group and a worse group. BCVA resulted 0.42 ± 0.28 logMAR in the best group versus 1.09 ± 0.36 logMAR in the worst (P < 0.01). Structural OCT and OCTA parameters significantly differed between the two STGD groups. CONCLUSIONS: Quantitative OCTA was able to detect different morphofunctional STGD phenotypes. TRANSLATIONAL RELEVANCE: OCTA-based classification of STGD patients detected different patients' subgroups, differing in terms of morphologic and functional features, with a potential impact on clinical and research settings.

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