Abstract
Background: Anti-Vascular Endothelial Growth Factor (VEGF) therapy is an effective therapy for improving and stabilizing the vision of patients with neovascular age-related macular degeneration (nAMD). However, the treatment requirements, particularly the number of intraocular injections, can vary significantly among patients. This study aimed to analyze the vascular characteristics of macular neovascularizations (MNVs) to identify potential biomarkers that could predict the required injection frequency throughout the disease course. Methods: In all patients, the initial diagnosis of nAMD was confirmed using optic coherence tomography (OCT), fluorescein angiography, and OCT angiography (OCTA). MNVs detected using OCTA were subjected to quantitative vascular analysis of their area, total vascular length (sumL), fractal dimension (FD), and flow density. These results were then correlated with the number of intravitreal anti-VEGF treatments administered during the first 3 years of treatment. Additionally, the relationship between the parameters and visual acuity progression was analyzed. Results: A total of 68 treatment-naïve eyes were included in the study, comprising 31 eyes with type 1 MNV, 19 eyes with type 2 MNV, and 18 eyes with type 3 MNV. The average MNV area at baseline was 1.11 mm(2) ± 1.18 mm(2), the mean total vascular length was 12.95 mm ± 14.24 mm, the mean fractal dimension was 1.26 ± 0.14, and the mean flow density was 41.19 ± 5.87. On average, patients in our cohort received 19.8 ± 8.5 intravitreal injections (IVIs). A significant correlation was found between the number of administered IVIs in the first 3 treatment years and the MNV area (p < 0.005), sumL (p < 0.005), and FD (p < 0.05), while no correlation was found with flow density. Additionally, there was no significant association between MNV type and treatment requirements, nor between MNV vascular architecture and visual acuity progression. Conclusions: The results suggest that the specific vascular structure of untreated MNV may serve as a predictor of long-term treatment demand. With the emergence of new drug classes and advancements in imaging techniques, these parameters could offer valuable insights for forecasting treatment requirements.