Peripapillary Choroidal Vascularity Index for Differentiating Papilledema from Pseudopapilledema: A Deep Learning–Based Approach

Purpose: To compare the peripapillary choroidal vascularity index (PPCVI) in eyes with papilledema secondary to idiopathic intracranial hypertension (IIH) and pseudopapilledema due to optic disc drusen (ODD) using a novel deep learning algorithm. Design: A retrospective observational cohort study. Subjects: The study included 30 eyes of 15 patients with papilledema secondary to IIH, 30 eyes of 15 patients with ODD, and 78 eyes of 39 age- and sex-matched healthy controls. All cases of IIH and ODD were confirmed with lumbar puncture and B-scan ultrasonography, respectively. Methods: OCT was performed using a 3.4 mm diameter 360° peripapillary circle scan. Choroidal segmentation was automatically performed with a deep learning ResUNet model and a volumetric smoothing algorithm. The choroidal vascularity index was quantified in each peripapillary scan. Statistical comparisons were made between groups and in IIH patients before and after resolution of papilledema. Linear mixed models were used for analysis. Main Outcome Measures: Mean PPCVI, expressed as a percentage, across study groups and longitudinally in IIH eyes. Conclusions: Reduced PPCVI could be a potential biomarker for differentiating papilledema from pseudopapilledema. An increase in PPCVI after resolution of papilledema supports its utility as a potential parameter for monitoring disease activity. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.