Automated Retinal Vascular Analysis Reveals Response to Acetazolamide in Idiopathic Intracranial Hypertension

To assess whether automated analysis of retinal arterioles and venules can identify treatment response in papilledema secondary to idiopathic intracranial hypertension (IIH).

This retrospective analysis used data from a multicenter, randomized, double-blind, placebo-controlled IIH treatment trial. Participants (n = 165) with mild visual loss were assigned to a dietary/lifestyle modification plus acetazolamide (ACZ) or placebo for 6 months. Color fundus photographs, optical coherence tomography (OCT), and clinical metrics were collected at baseline and at multiple follow-up visits. AutoMorph, a deep learning-based pipeline, quantified venule and arteriole diameters, fractal dimensionality, tortuosity, and vessel density. Venular widths were standardized to arteriolar widths to form a venule-to-arteriole (V:A) ratio, which was correlated with Frisén grade, OCT optic nerve head (ONH) parameters, and cerebrospinal fluid (CSF) opening pressure.

Baseline vascular OCT metrics and Frisén grades were similar between groups. At month 1, ACZ significantly reduced venule diameters (-4.59 µm; P = 0.02), and placebo showed no change (+1.21 µm; P = 0.54). The V:A ratio was consistently lower in the ACZ group than placebo from month 1 (1.20 vs. 1.24, respectively; P = 0.03) to month 6 (1.16 vs. 1.23, P = 0.02). Higher Frisén grades correlated strongly with increased mean V:A values (R2 = 0.91, P = 0.011). The V:A ratio was significantly associated with CSF opening pressure at month 6 (R2 = 0.47, P < 0.001).

Automated retinal vessel analysis provides a promising, non-invasive method for monitoring treatment response in IIH and may complement traditional imaging and clinical assessments.

Deep learning-based retinal vessel metrics may provide an accessible biomarker for monitoring treatment response in papilledema.