To evaluate and compare subbasal corneal nerve parameters of the inferior whorl in patients with dry eye disease (DED), neuropathic corneal pain (NCP), and controls using a novel deep-learning-based algorithm to analyze in-vivo confocal microscopy (IVCM) images. Subbasal nerve plexus (SNP) images of the inferior whorl of patients with DED (n = 49, 77 eyes), NCP (n = 14, 24 eyes), and controls (n = 41, 59 eyes) were taken with IVCM and further analyzed using an open-source artificial intelligence (AI)-based algorithm previously developed by our group. This algorithm automatically segments nerves, immune cells, and neuromas in the SNP. The following parameters were compared between groups: nerve area density, average nerve thickness, average nerve segment tortuosity, junction point density, neuroma density, and immune cell density. 160 eyes of 104 patients (63 % females), aged 56.8 ± 15.4 years, were included. The mean nerve area density was significantly lower in the DED ( = 0.012) and NCP ( < 0.001) groups compared to the control group. The junction point density was lower in the NCP group compared with control ( = 0.001) and DED ( = 0.004) groups. The immune cell density was higher in the DED group compared with controls ( < 0.001). Deep-learning-based analysis of IVCM images of the corneal SNP inferior whorl distinguished a decreased mean nerve area density in patients with DED and NCP compared with controls and an increased immune cell density in patients with oGVHD- and SS-associated DED. These findings suggest that the inferior whorl could be used as landmark to distinguish between patients with DED and NCP.

中文翻译：

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神经性角膜疼痛和干眼症患者基底下神经丛下轮的体内共聚焦显微镜图像深度学习分析


评估和比较干眼症 （DED）、神经性角膜疼痛 （NCP） 患者和对照组下轮的基底下角膜神经参数，使用基于深度学习的新型算法分析体内共聚焦显微镜 （IVCM） 图像。用 IVCM 拍摄 DED （n = 49， 77 眼）、NCP （n = 14， 24 眼） 和对照组 （n = 41， 59 眼） 患者下轮盘的基底下神经丛 （SNP） 图像，并使用我们小组之前开发的基于开源人工智能 （AI） 的算法进一步分析。该算法会自动分割 SNP 中的神经、免疫细胞和神经瘤。比较组间参数： 神经区密度、平均神经厚度、平均神经节段迂曲度、连接点密度、神经瘤密度和免疫细胞密度。包括 104 名患者 （63% 为女性） 的 160 只眼睛，年龄 56.8 ± 15.4 岁。与对照组相比，DED （ = 0.012） 和 NCP （ < 0.001） 组的平均神经面积密度显著降低。与对照组 （ = 0.001） 和 DED （ = 0.004） 组相比，NCP 组的交界点密度较低。与对照组相比，DED 组的免疫细胞密度较高 （ < 0.001）。对角膜 SNP 下轮纹的 IVCM 图像进行基于深度学习的分析发现，与对照组相比，DED 和 NCP 患者的平均神经区域密度降低，而 oGVHD 和 SS 相关 DED 患者的免疫细胞密度增加。这些发现表明，下轮纹可以作为区分 DED 和 NCP 患者的标志。