Wu Zhichao, Weng Denis S D, Thenappan Abinaya, Ritch Robert, Hood Donald C
Department of Psychology, Columbia University, New York, NY, USA.
Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.
Transl Vis Sci Technol. 2018 Mar 29;7(2):14. doi: 10.1167/tvst.7.2.14. eCollection 2018 Apr.
To evaluate a manual region-of-interest (ROI) approach for detecting progressive macular ganglion cell complex (GCC) changes on optical coherence tomography (OCT) imaging.
One hundred forty-six eyes with a clinical diagnosis of glaucoma or suspected glaucoma with macular OCT scans obtained at least 1 year apart were evaluated. Changes in the GCC thickness were identified using a manual ROI approach (ROI), whereby region(s) of observed or suspected glaucomatous damage were manually identified when using key features from the macular OCT scan on the second visit. Progression was also evaluated using the global GCC thickness and an automatic ROI approach (ROI), where contiguous region(s) that fell below the 1% lower normative limit and exceeded 288 μm in size were evaluated. Longitudinal signal-to-noise ratios (SNRs) were calculated for progressive changes detected by each of these methods using individualized estimates of test-retest variability and age-related changes, obtained from 303 glaucoma and 394 healthy eyes, respectively.
On average, the longitudinal SNR for the global thickness, ROI and ROI methods were -0.90 y, -0.91 y, and -1.03 y, respectively, and was significantly more negative for the ROI compared with the global thickness ( = 0.003) and ROI methods ( = 0.021).
Progressive glaucomatous macular GCC changes were optimally detected with a manual ROI approach.
These findings suggests that an approach based on a qualitative evaluation of OCT imaging information and consideration of known patterns of damage can improve the detection of progressive glaucomatous macular damage.
评估一种手动感兴趣区域（ROI）方法，用于在光学相干断层扫描（OCT）成像上检测黄斑神经节细胞复合体（GCC）的进展性变化。
对146只临床诊断为青光眼或疑似青光眼且黄斑OCT扫描间隔至少1年的眼睛进行评估。使用手动ROI方法识别GCC厚度的变化，即在第二次就诊时使用黄斑OCT扫描的关键特征手动识别观察到或疑似青光眼损伤的区域。还使用整体GCC厚度和自动ROI方法评估进展情况，其中评估低于1%较低正常下限且大小超过288μm的连续区域。使用分别从303只青光眼和394只健康眼睛获得的重测变异性和年龄相关变化的个体化估计值，计算通过这些方法中的每一种检测到的进展性变化的纵向信噪比（SNR）。
平均而言，整体厚度、ROI和ROI方法的纵向SNR分别为-0.90y、-0.91y和-1.03y，与整体厚度（P = 0.003）和ROI方法（P = 0.021）相比，ROI的纵向SNR显著更负。
采用手动ROI方法能最佳地检测青光眼性黄斑GCC的进展性变化。
这些发现表明，基于对OCT成像信息的定性评估和对已知损伤模式的考虑的方法，可以改善对青光眼性黄斑进展性损伤的检测。
