Purpose To compare visualization of choroidal neovascularization (CNV) secondary to age-related macular degeneration (AMD) using an ultra-high speed swept-source (SS)-optical coherence tomography angiography (OCTA) prototype versus a spectral-domain (SD)-OCTA device. Design Comparative analysis of diagnostic instruments. Methods Patients were prospectively recruited to be imaged on SD-OCT and SS-OCT devices on the same day. The SD-OCT device employed is the RTVue Avanti that operates at ~840nm wavelength and 70,000 A-scans/second. The SS-OCT device used is an ultra-high speed long-wavelength prototype that operates at ~1050nm wavelength and 400,000 A-scans/second. Two observers independently measured the CNV area on OCTA en face images from the two devices using ImageJ. The non-parametric Wilcoxon signed-rank test was used to compare area measurements and p-values of <0.05 were considered statistically significant. Results Fourteen eyes from 13 patients were enrolled. The CNV in 11 eyes (78.6%) were classified as type-1, 2 eyes (14.3%) as type-2, and 1 eye (7.1%) as mixed type. Total CNV area measured using SS-OCT and SD-OCT 3mm × 3mm OCTA were 0.949 ± 1.168mm2 and 0.340 ± 0.301mm2, respectively (p=0.001). For the 6mm × 6mm OCTA the total CNV area using SS-OCT and SD-OCT were 1.218 ± 1.284mm2 and 0.604 ± 0.597mm2, respectively (p=0.0019). The field of view did not significantly affect the measured CNV area (p=0.19 and p=0.18 for SS-OCT and SD-OCT respectively). Conclusion SS-OCTA yielded significantly larger CNV areas than SD-OCTA. It is possible that SS-OCTA is better able to demarcate the full extent of CNV vasculature.

Structured Abstract PURPOSE To develop a robust, sensitive, and fully automatic algorithm to quantify diabetes related capillary dropout using optical coherence tomography (OCT) angiography (OCTA). METHODS A 1050 nm wavelength, 400 kHz A-scan rate swept-source OCT prototype was used to perform volumetric OCTA imaging over 3 mm × 3 mm fields in normal controls (n = 5), patients with diabetes without diabetic retinopathy (DR) (n = 7), patients with non-proliferative diabetic retinopathy (NPDR) (n = 9), and patients with proliferative diabetic retinopathy (PDR) (n = 5); for each patient, one eye was imaged. A fully automatic algorithm to quantify intercapillary areas was developed. RESULTS Of the 26 evaluated eyes, the segmentation was successful in 22 eyes (85%). The mean values of the 10 and 20 largest intercapillary areas, either including or excluding the foveal avascular zone, showed a consistent trend of increasing size from normal control eyes, to eyes with diabetic retinopathy but without DR, to NPDR eyes, and finally, to PDR eyes. CONCLUSIONS OCTA based screening and monitoring of DR patients is critically dependent on automated vessel analysis. The presented algorithm was able to automatically extract an intercapillary area based metric in patients having various stages of DR. Intercapillary area based approaches are likely more sensitive to early stage capillary dropout than vascular density based methods.