Morgan Jessica I W, Vergilio Grace K, Hsu Jessica, Dubra Alfredo, Cooper Robert F
Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Center for Advanced Retinal and Ocular Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Transl Vis Sci Technol. 2018 Jun 22;7(3):21. doi: 10.1167/tvst.7.3.21. eCollection 2018 Jun.
Recent advances in adaptive optics scanning light ophthalmoscopy (AOSLO) have enabled visualization of cone inner segments through nonconfocal split-detection, in addition to rod and cone outer segments revealed by confocal reflectance. Here, we examined the interobserver reliability of cone density measurements in both AOSLO imaging modalities.
Five normal subjects (nine eyes) were imaged along the horizontal and vertical meridians using a custom AOSLO with confocal and nonconfocal split-detection modalities. The resulting images were montaged using a previously described semiautomatic algorithm. Regions of interest (ROIs) were selected from the confocal montage at 190 μm, and from split-detection and confocal montages at 900 and 1800 μm from the fovea. Four observers (three experts, one naïve) manually identified cone locations in each ROI, and these locations were used to calculate bound densities. Intraclass correlation coefficients and Dice's coefficients were calculated to assess interobserver agreement.
Interobserver agreement was high in cone-only images (confocal 190 μm: 0.85; split-detection 900 μm: 0.91; split-detection 1800 μm: 0.89), moderate in confocal images at 900 μm (0.68), and poor in confocal images at 1800 μm (0.24). Excluding the naïve observer data substantially increased agreement within confocal images (190 μm: 0.99; 900 μm: 0.80; 1800 μm: 0.68).
Interobserver measurements of cone density are more reliable in rod-free retinal images. Moreover, when using manual cell identification, it is essential that observers are trained, particularly for confocal AOSLO images.
This study underscores the need for additional reliability studies in eyes containing pathology where identifying cones can be substantially more difficult.
自适应光学扫描光检眼镜(AOSLO)的最新进展使得除了通过共焦反射成像显示的视杆和视锥细胞外节外,还能够通过非共焦分裂检测对视锥细胞内节进行可视化。在此,我们研究了两种AOSLO成像模式下视锥细胞密度测量的观察者间可靠性。
使用具有共焦和非共焦分裂检测模式的定制AOSLO对5名正常受试者(9只眼)的水平和垂直子午线进行成像。使用先前描述的半自动算法对所得图像进行拼接。从距中央凹190μm的共焦拼接图像以及距中央凹900μm和1800μm的分裂检测和共焦拼接图像中选择感兴趣区域(ROI)。四名观察者(三名专家,一名新手)手动识别每个ROI中的视锥细胞位置,并使用这些位置计算边界密度。计算组内相关系数和戴斯系数以评估观察者间的一致性。
仅视锥细胞图像的观察者间一致性较高(共焦190μm:0.85;分裂检测900μm:0.91;分裂检测1800μm:0.89),900μm共焦图像的一致性中等(0.68),1800μm共焦图像的一致性较差(0.24)。排除新手观察者的数据显著提高了共焦图像内的一致性(190μm:0.99;900μm:0.80;1800μm:0.68)。
在无视杆细胞的视网膜图像中,观察者对视锥细胞密度的测量更可靠。此外,在使用手动细胞识别时,观察者必须接受培训,特别是对于共焦AOSLO图像。
本研究强调了在含有病理学的眼睛中进行额外可靠性研究的必要性,在这些眼睛中识别视锥细胞可能会困难得多。