Automated Quantitative Assessment of Retinal Fluid Volumes as Important Biomarkers in 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 (NVAMD). DESIGN: Perspective. METHODS: A review was performed of retinal image repository datasets from diverse clinical settings. SETTINGS: Clinical trial (HARBOR) and trial follow-on (AgeRelated Eye Disease Study 2 10-year Follow-On); realworld (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 (AgeRelated Eye Disease Study 2 10-year Follow-On). OBSERVATION PROCEDURES: Vienna Fluid Monitor or Notal OCT Analyzer applied to macular cube scans. OUTCOME MEASURES: 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-naive 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 NVAMD 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.

Automated summary

The study evaluated the use of artificial intelligence algorithms to extract retinal fluid volume data from OCT scans for treatment of NVAMD. The results showed rapid decrease in fluid volumes with anti-VEGF therapy, and the importance of quantitative measures of IRF, SRF, and PED as biomarkers in NV-AMD. Using nanoliters as a convenient unit for consistency between studies is proposed.