Automated Quantitative Assessment of Retinal Fluid Volumes as Important Biomarkers in Neovascular Age-Related Macular Degeneration.

Purpose: To evaluate retinal fluid volume data extracted from optical coherence tomography (OCT) scans by artificial intelligence algorithms in the treatment of neovascular age-related macular degeneration (NV-AMD).

Design: Perspective.

Methods: A review was performed of retinal image repository datasets from diverse clinical settings.

Settings: Clinical trial (HARBOR) and trial follow-on (Age-Related Eye Disease Study 2 10-year Follow-On); real-world (Belfast and Tel-Aviv tertiary centers).

Patients: 24,362 scans of 1,095 eyes (HARBOR); 4,673 of 880 (Belfast); 1,470 of 132 (Tel-Aviv); 511 of 511 (Age-Related Eye Disease Study 2 10-year Follow-On). ObservationProcedures: Vienna Fluid Monitor or Notal OCT Analyzer applied to macular cube scans. OutcomeMeasures: Intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED) volumes.

Results: The fluid volumes measured in neovascular AMD were expressed efficiently in nanoliters. Large ranges that differed by population were observed at the treatment-naïve stage: 0-3,435 nL (IRF), 0-5,018 nL (SRF), and 0-10,022 nL (PED). Mean volumes decreased rapidly and consistently with anti-vascular endothelial growth factor therapy. During maintenance therapy, mean IRF volumes were highest in Tel-Aviv (100 nL), lower in Belfast and HARBOR-Pro Re Nata, and lowest in HARBOR-monthly (21 nL). Mean SRF volumes were low in all: 30 nL (HARBOR-monthly) and 48-49 nL (others).

Conclusions: Quantitative measures of IRF, SRF, and PED are important biomarkers in NV-AMD. Accurate volumes can be extracted efficiently from OCT scans by artificial intelligence algorithms to guide the treatment of exudative macular diseases. Automated fluid monitoring identifies fluid characteristics in different NV-AMD populations at baseline and during follow-up. For consistency between studies, we propose the nanoliter as a convenient unit. We explore the advantages of using these quantitative metrics in clinical practice and research.