Department of Bioengineering, University of Washington, Seattle, Washington.
Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida.
Ophthalmol Retina. 2020 Feb;4(2):204-215. doi: 10.1016/j.oret.2019.09.012. Epub 2019 Oct 1.
To determine age-related changes in choroidal thickness and the volume of choroidal vessels and stroma using automated algorithms based on structural swept-source OCT (SS-OCT) scans.
Prospective and observational study.
The study included 144 normal participants with ages ranging from 20 to 88 years.
A previously reported strategy was used to automatically segment the choroid using SS-OCT structural images. Attenuation correction was applied on B-scans to enhance the choroidal contrast and facilitate more accurate automatic segmentation of the 3-dimensional choroidal vessel and stroma. The parameters that we investigated included mean choroidal thickness (MCT), choroidal vessel volume (CVV), choroidal stroma volume (CSV), choroid vascularity index (CVI), and the choroidal stroma-to-vessel volume ratio (CSVR). Correlations between MCT and choroidal vessel metrics of CVV, CSV, CVI, and CSVR were studied. Regional distributions of MCT and CVI were analyzed using a grid centered on the fovea. Age-related changes in MCT, CVV, CSV, and CVI were studied in the entire scanning region, as well as in the subregions of the grids.
Age-related changes in MCT, CVV, CSV, and CVI using 6×6-mm and 12×12-mm SS-OCT scans.
The automated choroid segmentations were validated against manual segmentations, and MCT measurements were shown to be in good agreement (P < 0.0001). Choroidal vessel volume and CSV showed significant correlations with MCT (all P < 0.0001). Interestingly, CVI and CSVR were constant, with little variation among all participants regardless of age and MCT (61.1±1.8% and 0.64±0.05, respectively). Measurements on 12×12-mm and 6×6-mm scans showed excellent agreement in all scan regions (all P < 0.0001). While choroidal thickness and choroidal volume, which includes both choroidal vessels and stroma, decrease with age (all P < 0.0001), the CVI and CSVR vary little among all ages in all regions.
Whereas MCT, CVV, and CSV decrease with age, the CVI and CSVR remain constant in all regions with age. Ongoing studies are using these automated algorithms on SS-OCT structural datasets to investigate the diagnostic usefulness of these choroidal parameters in a myriad of ocular and systemic diseases.
使用基于结构扫频源光学相干断层扫描（SS-OCT）的自动算法来确定脉络膜厚度和脉络膜血管及基质体积随年龄的变化。
前瞻性和观察性研究。
本研究纳入了年龄在 20 岁至 88 岁之间的 144 名正常参与者。
使用先前报道的策略，使用 SS-OCT 结构图像自动分割脉络膜。对 B 扫描进行衰减校正，以增强脉络膜对比度，从而更准确地自动分割三维脉络膜血管和基质。我们研究的参数包括平均脉络膜厚度（MCT）、脉络膜血管容积（CVV）、脉络膜基质容积（CSV）、脉络膜血管密度指数（CVI）和脉络膜基质-血管容积比（CSVR）。研究了 MCT 与 CVV、CSV、CVI 和 CSVR 的脉络膜血管指标之间的相关性。使用以黄斑为中心的网格分析 MCT 和 CVI 的区域分布。研究了整个扫描区域以及网格子区域中 MCT 和 CVI 的年龄相关性变化。
使用 6×6mm 和 12×12mm SS-OCT 扫描测量 MCT、CVV、CSV 和 CVI 的年龄相关性变化。
自动脉络膜分割与手动分割进行了验证，MCT 测量结果一致性良好（P<0.0001）。脉络膜血管容积和 CSV 与 MCT 呈显著相关性（均 P<0.0001）。有趣的是，CVI 和 CSVR 几乎不变，所有参与者无论年龄和 MCT 如何，差异均较小（分别为 61.1±1.8%和 0.64±0.05）。在所有扫描区域，12×12mm 和 6×6mm 扫描的测量结果具有很好的一致性（均 P<0.0001）。虽然脉络膜厚度和包含脉络膜血管和基质的脉络膜容积随年龄增长而降低（均 P<0.0001），但在所有年龄和所有区域，CVI 和 CSVR 变化很小。
尽管 MCT、CVV 和 CSV 随年龄增长而降低，但 CVI 和 CSVR 在所有年龄和所有区域均保持不变。正在进行的研究正在 SS-OCT 结构数据集上使用这些自动算法，以研究这些脉络膜参数在各种眼部和系统性疾病中的诊断价值。
