Department of Bioengineering, University of Washington, Seattle, Washington, USA.
Department of Ophthalmology, University of Washington, Seattle, Washington, USA.
Sci Rep. 2018 Nov 14;8(1):16826. doi: 10.1038/s41598-018-34826-5.
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.
脉络膜毛细血管(CC)的可视化和量化仍然具有挑战性。我们提出了一种创新的三步配准和平均方法,使用重复的扫频源光学相干断层扫描血管造影(SS-OCTA)扫描,对 CC 进行自动定量评估。纳入 6 名受试者,使用 3mm×3mm 扫描模式,从黄斑区到赤道区对 SS-OCTA 进行多次扫描,对每个受试者的多个位置进行成像。每个受试者采集了 5 个重复体积。复杂的光学微血管造影(OMAG)算法被应用于识别 CC 板中的血流。对 CC 的 SS-OCTA 图像应用自动三步平移、仿射和 B 样条配准,然后进行平均。使用模糊聚类方法从平均图像中分割血管和血流缺损。评估了 CC 可视化的改善情况,并通过计算平均毛细血管腔间距来估计毛细血管的平均间距。设计并验证了一系列血流缺损密度、数量、大小、复杂度指数和纵横比指数(FDD、FDN、FDS、FDCI 和 FDARI)的定量指数,随着重复扫描次数的增加进行平均。对黄斑区和赤道区的 CC 进行了定量评估和比较。观察到在黄斑区毛细血管的间距约为 24µm,并向赤道区增加。所有五个定量指数(FDD、FDN、FDS、FDCI 和 FDARI)都随着多次平均而发生显著变化,并且随着重复次数达到 4 次时趋于稳定。我们提出的配准和平均算法显著提高了 SS-OCTA 对 CC 的可视化。为 CC 设计的五个指数为 CC 的定量评估提供了更多选择,并在辅助理解疾病病理、早期诊断和治疗监测方面具有很大潜力。