目的:使用体内共聚焦显微镜(IVCM)研究干眼症(DED)伴眼痛患者角膜基底下神经丛(SNP)的半自动和全自动定量分析结果之间的相关性和一致性。
方法:共有50名自愿参与者参加了这项研究,即,25名患有眼部疼痛的DED患者和25名健康对照。每位患者都接受了眼部症状的评估,使用:眼表疾病指数(OSDI),眼痛评估调查(OPAS),泪膜破裂时间(TBUT)试验,Schirmer测试,角膜染色,IVCM。选择每只眼睛角膜的五个SNP图像,并使用半自动分析软件(NeuronJ)和全自动方法(ACCMetrics)进行分析,以量化角膜神经纤维密度(CNFD),角膜神经分支密度(CNBD),角膜神经纤维长度(CNFL)。
结果:CNFD的组内相关系数(ICC)(0.460[0.382-0.532],p<0.001),CNBD(0.608[0.545-0.665],p<0.001),和CNFL(0.851[0.822-0.875],p<0.001)表示NeuronJ和ACCMetrics软件测量的重复性和一致性。两种方法得到的CNFL值(r=0.881,p<0.001)具有极高的相关性,同样,CNFD值(r=0.669,p<0.001)和CNBD值(r=0.703,p<0.001)高度相关。CNFL的曲线下面积最大(AUC;0.747[0.700-0.793],p<0.001)使用ACCMetrics时。在患有眼痛的DED患者中,半自动和全自动量化的平均CNFD值分别为23.5±8.1和23.8±8.6n/mm2;平均CNBD值分别为46.0±21.3,35.7±23.3n/mm2;平均CNFL值分别为19.3±4.3和15.2±3.8mm/mm2,均显著低于健康受试者(p<0.001).
结论:通过ACCMetrics和NeuronJ获得的测量值之间存在显着相关性,特别是对于CNFL,可作为诊断DED眼痛的主要指标。该疾病的SNP明显低于健康受试者。
OBJECTIVE: Investigate the correlation and agreement between the results of semiautomated and fully automated quantitative analysis of the corneal sub-basal nerve plexus (SNP) in patients with dry eye disease (DED) with ocular pain using in vivo confocal microscopy (IVCM).
METHODS: A total of 50 voluntary participants were enrolled in this study, i.e., 25 DED patients with ocular pain and 25 healthy controls. Each patient underwent an evaluation of ocular symptoms that utilized: the Ocular Surface Disease Index (OSDI), the Ocular Pain Assessment Survey (OPAS), the tear film breakup time (TBUT) test, the Schirmer test, corneal staining, and IVCM. Five SNP images of the cornea of each eye were selected and analyzed using a semiautomated analysis software (NeuronJ) and a fully automated method (ACCMetrics) to quantify corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fiber length (CNFL).
RESULTS: The intraclass correlation coefficient (ICC) of the CNFD (0.460 [0.382-0.532], p < 0.001), CNBD (0.608 [0.545-0.665], p < 0.001), and CNFL (0.851 [0.822-0.875], p < 0.001) represents the repeatability and consistency of measurements by the NeuronJ and ACCMetrics software. The CNFL values (r = 0.881, p < 0.001) obtained using the two methods have extremely high correlation, and similarly, the CNFD values (r = 0.669, p < 0.001) and CNBD values (r = 0.703, p < 0.001) are highly correlated. The CNFL had the biggest area under the curve (AUC; 0.747 [0.700-0.793], p < 0.001) when using ACCMetrics. In DED patients with ocular pain, the mean CNFD values for semiautomated and fully automated quantization were 23.5 ± 8.1 and 23.8 ± 8.6 n/mm2; the mean CNBD values were 46.0 ± 21.3, 35.7 ± 23.3 n/mm2; and the mean CNFL values were 19.3 ± 4.3 and 15.2 ± 3.8 mm/mm2, which were significantly lower than healthy subjects (p < 0.001).
CONCLUSIONS: There is a significant correlation between the measurements obtained via ACCMetrics and NeuronJ, especially for CNFL, which can be considered as the primary indicator in the diagnosis of DED with ocular pain. The SNP of the disease was significantly lower than that of healthy subjects.