Edoardo Midena, Marco Lupidi, Luisa Frizziero, Giulia Midena, Elisabetta Pilotto, Lisa Toto, Maria Vittoria Cicinelli, Daniele Veritti, Giuseppe Covello, Rosangela Lattanzio, Michele Figus, Luca Danieli, Enrico Borrelli, Michele Reibaldi, Daniele Tognetto, Leandro Inferrera, Simone Donati, Settimio Rossi, Paolo Melillo, Paolo Lanzetta, Valentina Sarao, Giulia Gregori, Carlo Cagini, Chiara Maria Eandi, Adriano Carnevali, Vincenzo Scorcia, Emilia Maggio, Grazia Pertile, Ciro Costagliola, Gilda Cennamo, Paolo Mora, Roberto Dell'Omo, Marzia Affatato, Marzia Passamonti, Mariacristina Parravano, Nicola Vito Lassandro, Marco Nassisi, Francesco Viola, Niccolò Castellino, Francesco Cappellani, Giuseppe Giannaccare, Francesco Boscia, Maria Oliva Grassi, Donatella Musetti, Valentina Folegani, Alessandro Invernizzi, Luca Rossetti, Tommaso Bacci, Federico Ricci, Marco Lombardo, Mary Romano, Nicola Valsecchi, Michele Coppola, Fabiano Cavarzeran
Quantitative AI-based OCT analysis demonstrated that the ELM and EZ have distinct yet complementary relationships with fluid biomarkers and visual acuity. EZ alterations are more prevalent and associated with I-HRF increases, whereas ELM disruption appears to reflect deeper structural damage and stronger functional impairment. Integrating outer retinal layer integrity with other features of DME may provide a more comprehensive characterization of DME and support a more personalized prognostic assessment and therapeutic strategies.
PURPOSE: To investigate the behavior of the external limiting membrane (ELM) and ellipsoid zone (EZ) in diabetic macular edema (DME) using artificial intelligence (AI)-based optical coherence tomography (OCT) quantification.
METHODS: This was a cross-sectional study. OCT scans of eyes affected by DME were analyzed using a validated AI platform to quantify intraretinal fluid (IRF), subretinal fluid (SRF), inflammatory hyper-reflective retinal foci (I-HRF), and the percentage of interruption of the ELM and EZ. Eyes were classified according to ELM/EZ interruption and grouped into four patterns of integrity: no interruption, EZ interruption >ELM, ELM > EZ, and ELM = EZ. The distribution of the ELM/EZ disruption and associations with other biomarkers, and clinical data, including visual acuity, were analyzed.
RESULTS: We analyzed 2355 eyes from 1688 patients affected by DME. ELM interruption was observed in 21.9% of eyes and EZ interruption in 37.6%. A greater prevalence of EZ disruption was also identified in both previously treated and untreated eyes. Eyes with an interrupted ELM/EZ showed significantly greater IRF and SRF volumes and a more centrally located IRF distribution. I-HRF counts were significantly higher in eyes with predominant EZ damage. ELM disruption showed the strongest correlation with visual acuity and SRF burden.
CONCLUSIONS: Quantitative AI-based OCT analysis demonstrated that the ELM and EZ have distinct yet complementary relationships with fluid biomarkers and visual acuity. EZ alterations are more prevalent and associated with I-HRF increases, whereas ELM disruption appears to reflect deeper structural damage and stronger functional impairment. Integrating outer retinal layer integrity with other features of DME may provide a more comprehensive characterization of DME and support a more personalized prognostic assessment and therapeutic strategies.