Cost-Effective 3D Reconstruction of Retinal Vasculature from 2D OCTA B-Scans: A Software-Based Approach with Layer-Specific Insights

Purpose Optical Coherence Tomography Angiography (OCTA) delivers high-resolution 2D images of retinal vasculature, but its 2D projections limit comprehensive assessment of 3D vascular structures in diseases such as diabetic retinopathy. Hardware-based 3D solutions are expensive and inaccessible, prompting the need for cost-effective software alternatives. Methods We developed a software-based pipeline for 3D reconstruction of retinal vasculature from standard 2D OCTA B-scans, involving Hue, Saturation, Value (HSV)-based thresholding for layer and vessel segmentation, 5th-order spline interpolation along the depth axis, standard deviation projection for en face views, and affine registration. The method was applied to 304 B-scans per volume from 16 eyes (9 healthy controls, mean age 32 ± 5 years; 7 with diabetic retinopathy, mean age 48 ± 7 years, mild-to-severe NPDR) acquired using a 70 kHz SD-OCT system (RTVue-XR, Optovue, CA). Reconstruction accuracy was evaluated against device-generated 2D en face projections using Dice scores and vessel density metrics, with layer-specific analysis for superficial, deep, and full retina. Results Post-interpolation, the method achieved mean Dice scores of 0.8321 ± 0.0148 (full retina), 0.7993 ± 0.0309 (superficial), and 0.6871 ± 0.0624 (deep), markedly improving from pre-interpolation values (e.g., full retina: 0.4028 ± 0.0161; p < 0.01). 3D vessel density more than doubled post-interpolation (e.g., full retina: from 0.0778 ± 0.0125 to 0.2095 ± 0.0331), resolving capillary discontinuities. Pathologic eyes showed trends toward reduced 3D vessel density, particularly in the deep layer (healthy: 0.1803 ± 0.0446 vs. pathologic: 0.1584 ± 0.0330; p = 0.0703), consistent with microvascular dropout in diabetic retinopathy. Conclusion This accessible, hardware-independent software method enables detailed layer-specific 3D visualization of retinal vasculature from routine 2D OCTA data, with high fidelity and potential to enhance clinical detection of vascular abnormalities. An interactive tool further supports real-time exploration, facilitating integration into clinical practice. Larger cohort validation is warranted.