Estimation of current and post-treatment retinal function in chronic central serous chorioretinopathy using artificial intelligence.

ABSTRACT: Refined understanding of the association of retinal microstructure with current and future (post-treatment) function in chronic central serous chorioretinopathy (cCSC) may help to identify patients that would benefit most from treatment. In this post-hoc analysis of data from the prospective, randomized PLACE trial (NCT01797861), we aimed to determine the accuracy of AI-based inference of retinal function from retinal morphology in cCSC. Longitudinal spectral-domain optical coherence tomography (SD-OCT) data from 57 eyes of 57 patients from baseline, week 6-8 and month 7-8 post-treatment were segmented using deep-learning software. Fundus-controlled perimetry data were aligned to the SD-OCT data to extract layer thickness and reflectivity values for each test point. Point-wise retinal sens

SUBMITTER: Pfau M 

PROVIDER: S-EPMC8516921 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature