Twa Michael D, Schulle Krystal L, Chiu Stephanie J, Farsiu Sina, Berntsen David A
*OD, PhD, FAAO †OD, FAAO ‡PhD School of Optometry (MDT), Department of Biomedical Engineering (MDT), University of Alabama at Birmingham, Birmingham, Alabama; College of Optometry, University of Houston, Houston, Texas (KLS, DAB); Department of Biomedical Engineering, Duke University, Durham, North Carolina (SJC, SF); and Department of Ophthalmology, Duke University Medical Center, Durham, North Carolina (SF).
Optom Vis Sci. 2016 Nov;93(11):1387-1398. doi: 10.1097/OPX.0000000000000985.
Spectral domain optical coherence tomography (SD-OCT) imaging permits in vivo visualization of the choroid with micron-level resolution over wide areas and is of interest for studies of ocular growth and myopia control. We evaluated the speed, repeatability, and accuracy of a new image segmentation method to quantify choroid thickness compared to manual segmentation.
Two macular volumetric scans (25 × 30°) were taken from 30 eyes of 30 young adult subjects in two sessions, 1 hour apart. A single rater manually delineated choroid thickness as the distance between Bruch's membrane and sclera across three B-scans (foveal, inferior, and superior-most scan locations). Manual segmentation was compared to an automated method based on graph theory, dynamic programming, and wavelet-based texture analysis. Segmentation performance comparisons included processing speed, choroid thickness measurements across the foveal horizontal midline, and measurement repeatability (95% limits of agreement (LoA)).
Subjects were healthy young adults (n = 30; 24 ± 2 years; mean ± SD; 63% female) with spherical equivalent refractive error of -3.46 ± 2.69D (range: +2.62 to -8.50D). Manual segmentation took 200 times longer than automated segmentation (780 vs. 4 seconds). Mean choroid thickness at the foveal center was 263 ± 24 μm (manual) and 259 ± 23 μm (automated), and this difference was not significant (p = 0.10). Regional segmentation errors across the foveal horizontal midline (±15°) were ≤9 μm (median) except for nasal-most regions closest to the nasal peripapillary margin-15 degrees (19 μm) and 12 degrees (16 μm) from the foveal center. Repeatability of choroidal thickness measurements had similar repeatability between segmentation methods (manual LoA: ±15 μm; automated LoA: ±14 μm).
Automated segmentation of SD-OCT data by graph theory and dynamic programming is a fast, accurate, and reliable method to delineate the choroid. This approach will facilitate longitudinal studies evaluating changes in choroid thickness in response to novel optical corrections and in ocular disease.
光谱域光学相干断层扫描(SD-OCT)成像能够在体内以微米级分辨率对大面积脉络膜进行可视化,这对于眼部生长和近视控制的研究具有重要意义。我们评估了一种新的图像分割方法在量化脉络膜厚度方面的速度、可重复性和准确性,并与手动分割进行了比较。
对30名年轻成年受试者的30只眼睛进行了两次黄斑区容积扫描(25×30°),两次扫描间隔1小时。由一名评估者手动划定脉络膜厚度,即跨越三次B扫描(中央凹、下方和最上方扫描位置)测量Bruch膜与巩膜之间的距离。将手动分割与基于图论、动态规划和基于小波的纹理分析的自动分割方法进行比较。分割性能比较包括处理速度、中央凹水平中线处的脉络膜厚度测量以及测量的可重复性(95%一致性界限(LoA))。
受试者为健康年轻成年人(n = 30;24±2岁;平均值±标准差;63%为女性),等效球镜屈光不正为-3.46±2.69D(范围:+2.62至-8.50D)。手动分割比自动分割耗时长200倍(780秒对4秒)。中央凹中心处的平均脉络膜厚度,手动测量为263±24μm,自动测量为259±23μm,差异无统计学意义(p = 0.10)。除了最靠近鼻侧视乳头周围边缘且距中央凹中心15度(19μm)和12度(16μm)的鼻侧最远端区域外,中央凹水平中线(±15°)处的区域分割误差≤9μm(中位数)。脉络膜厚度测量的可重复性在两种分割方法之间相似(手动LoA:±15μm;自动LoA:±14μm)。
通过图论和动态规划对SD-OCT数据进行自动分割是一种快速、准确且可靠的脉络膜描绘方法。这种方法将有助于进行纵向研究,以评估脉络膜厚度在新型光学矫正和眼部疾病影响下的变化。