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Choriocapillaris (CC) visualization and quantification remains challenging. We propose an innovative three-step registration and averaging approach using repeated swept source optical coherence tomography angiography (SS-OCTA) scans to conduct automatic quantitative assessment on CC. Six subjects were enrolled, each imaged at several locations with SS-OCTA from macular to equatorial regions using 3 mm × 3 mm scanning pattern. Five repeated volumes were collected for each subject. The complex optical microangiography (OMAG) algorithm was applied to identify blood flow in CC slab. An automatic three-step registration of translation, affine and B-Spline was applied to  en face  OCTA images of CC, followed with averaging. A fuzzy clustering approach was used to segment vasculature and flow deficits from the averaged images. The improvement in visualization of CC was evaluated and the average intercapillary distance was estimated by calculating the averaged capillary lumen spacing. A series of quantitative indices of flow deficit density, number, size, complexity index and aspect ratio index (FDD, FDN, FDS, FDCI and FDARI) were designed and validated with the increase of repeated scan numbers for averaging. Quantitative assessment was applied and compared on CC in macular and equatorial regions. The intercapillary distance was observed to be around 24 µm at macula and increased toward equatorial regions. All five quantitative indices (FDD, FDN, FDS, FDCI and FDARI) showed significant changes with multiple averaging and tend to become stable with repeated number of 4. Our proposed registration and averaging algorithm significantly improved the visualization of CC with SS-OCTA. The designed five indices for CC provide more options in the quantitative assessment of CC and are of great potentials in assisting the understanding of disease pathology, early diagnosis and treatment monitoring.

scientific reports

Improving visualization and quantitative assessment of choriocapillaris with swept source OCTA through registration and averaging applicable to clinical systems