Artificial intelligence-based assessment of imaging biomarkers in epiretinal membrane surgery

Purpose: This study investigated the applicability of a validated AI-algorithm for analyzing different retinal biomarkers in eyes affected by epiretinal membranes (ERMs) before and after surgery. Methods: A retrospective study included 40 patients surgically treated for ERMs removal between November 2022 and January 2024. Pars plana vitrectomy with ERM/ILM peeling was performed by a single experienced surgeon. A validated AI algorithm was used to analyze OCT scans, focusing on intraretinal fluid (IRF) and subretinal fluid (SRF) volumes, external limiting membrane (ELM) and ellipsoid zone (EZ) interruption percentages and hyper-reflective foci (HRF) counts. Results: Postoperative best corrected visual acuity (BCVA) significantly improved (p < 0.01), and central macular thickness (CMT) decreased from 483.61 ± 96.32 to 386.82 ± 94.86 µm (p = 0.001). IRF volume reduced from 0.283 ± 0.39 mm3 to 0.142 ± 0.27 mm3 (p = 0.036) particularly in the central 1 mm-circle. SRF, HRF and EZ/ELM interru...