Gunvant Pinakin, Zheng Yufeng, Essock Edward A, Parikh Rajul S, Prabakaran Selvaraj, Babu Jonnadula Ganesh, Shekar Chandra G, Thomas Ravi
Department of Research, Southern College of Optometry, TN 38104-2222, USA.
J Glaucoma. 2009 Aug;18(6):464-71. doi: 10.1097/IJG.0b013e31818c6f2b.
To directly compare in 1 population: (1) the performance of Optical Coherence Tomograph (OCT) and GDx-Variable Corneal Compensator (VCC) when using Wavelet-Fourier Analysis (WFA) and Fast-Fourier Analysis (FFA), (2) the performance of these shape-based and standard metrics, and (3) the shape of the retinal nerve fiber layer (RNFL) temporal, superior, nasal, inferior, temporal (TSNIT) curves obtained by the 2 different devices.
RNFL estimates were obtained from 136 eyes of 136 individuals (73 healthy and 63 mild glaucoma). WFA and FFA with and without asymmetry measures were performed on the TSNIT RNFL estimates to identify glaucoma from healthy eyes. Performance of WFA, FFA, and the standard metrics of OCT (Inferior Average) and GDX-VCC (Nerve Fiber Indicator) was evaluated by calculating receiver operating characteristic area. Measurements were obtained at a custom radius (33 to 41 pixels) for GDx-VCC to match the OCT radius (1.73 mm).
WFA and FFA shape analysis significantly improved performance of both OCT (0.937) and GDx-VCC (0.913) compared with Inferior Average and Nerve Fiber Indicator (0.852 and 0.833, respectively). With either shape-based or standard metrics, OCT performance was slightly, but not significantly, better than GDx-VCC performance. Comparison of RNFL curves revealed that the GDx-VCC curves were more jagged and the peaks shifted more nasally when compared with the OCT RNFL curves.
Performance of both OCT and GDx-VCC devices are improved by shape-based analysis methods. Classification performance was greater when using WFA for the OCT, and greater with FFA for the GDx-VCC. Significant differences between the machines exist in the measured TSNIT thicknesses, possibly because of GDx-VCC's measurements being affected by polarization magnitude varying with angle.
在同一人群中直接比较：（1）光学相干断层扫描（OCT）和GDx可变角膜补偿器（VCC）在使用小波傅里叶分析（WFA）和快速傅里叶分析（FFA）时的性能；（2）这些基于形状的指标和标准指标的性能；（3）通过两种不同设备获得的视网膜神经纤维层（RNFL）颞侧、上方、鼻侧、下方、颞侧（TSNIT）曲线的形状。
从136名个体的136只眼中获得RNFL估计值（73名健康者和63名轻度青光眼患者）。对TSNIT RNFL估计值进行有无不对称测量的WFA和FFA，以从健康眼中识别青光眼。通过计算受试者操作特征面积来评估WFA、FFA以及OCT（下方平均值）和GDx-VCC（神经纤维指标）的标准指标的性能。对于GDx-VCC，在自定义半径（33至41像素）处进行测量，以匹配OCT半径（1.73毫米）。
与下方平均值和神经纤维指标（分别为0.852和0.833）相比，WFA和FFA形状分析显著提高了OCT（0.937）和GDx-VCC（0.913）的性能。无论是基于形状的指标还是标准指标，OCT的性能略优于GDx-VCC，但差异不显著。RNFL曲线的比较显示，与OCT RNFL曲线相比，GDx-VCC曲线更参差不齐，峰值向鼻侧偏移更多。
基于形状的分析方法可提高OCT和GDx-VCC设备的性能。使用WFA时OCT的分类性能更佳，使用FFA时GDx-VCC的分类性能更佳。两台机器测量的TSNIT厚度存在显著差异，可能是因为GDx-VCC的测量受偏振幅度随角度变化的影响。
