Novel Semi-Automated System for Multi-Dimensional Analysis of Macular Neovascularization: A Comparative Study of Quantitative Biomarkers and Morphological-Pathophysiological Classification

Purpose: To introduce and validate a novel semi-automated ImageJ-based macro for comprehensive analysis of macular neovascularization (MNV) in OCTA images. The system is benchmarked against quantitative parameters from recent literature and provides novel biomarkers plus an automated morphological–pathophysiological classification that objectively distinguishes active, mature quiescent, transitional, and arteriolarized states. Methods: We developed an advanced image-processing pipeline incorporating hybrid multiscale vessel enhancement (Laplacian of Gaussian and tubeness filters), dynamic region-of-interest refinement, and boundary-branch exclusion. The system generates a Vascular Complexity Score and Vascular Stability Score (0–100), as well as automated classification into Medusa, Seafan, Glomerular, Tree-in-bud, and Dead-tree patterns mapped to pathophysiological states using quantitative thresholds and published clinical criteria. A total of 112 MNV lesions imaged on three OCTA platforms (Zeiss PlexElite 6×6 mm, Zeiss HD 3×3 mm, Optovue Solix 6×6 mm) were analyzed. Results: Raw topological metrics differed substantially by device, precluding direct numerical comparison. Device-specific principal component analysis and piecewise-linear normalization yielded convergent Standardized Complexity, Caliber Uniformity, and Maturity scores (all medians ≈50, Kruskal–Wallis p≥0.276), indicating effective removal of device- and field-of-view–dependent scaling while preserving biological information. Automated morphological classification identified the full spectrum of MNV subtypes across all platforms, supporting cross-device robustness. Conclusion: This system provides a robust platform for standardized, device-independent quantification of MNV architecture. By integrating morphological patterns with quantitative biomarkers and automated pathophysiological classification, it enables objective differentiation of active angiogenesis from mature remodeling and may improve clinical decision-making and patient stratification in neovascular AMD.