角膜基底下神经弯曲度客观分析及其在干眼和糖尿病患者中的改变

摘要

Objective To construct an objective analysis system of corneal nerve tortuosity and detect the changes of corneal subbasal nerve tortuosity in patients with dry eye and diabetes. Methods GradeⅠtoⅣnerve tortuosity were evaluated and 80 photos of each grade were randomly chosen from the in vivo confocal microscopy library. Nerve fibers were extracted,segmented and then analyzed by 6 tortuosity related parameters including L C, Seg L C mean,Cur mean,Specific p,ICM and SCC mean. After verifying the validaty of parameters above,a cross-sectional study was conducted. Subjects were collected from June,2018 to February,2019 in Peking University Third Hospital,and were divided into healthy control group (28 persons 56 eyes),dry eye without diabetes group (28 patients 56 eyes),diabetes without dry eye group(24 patients 48 eyes),diabetes with dry eye group (23 patients 46 eyes) . Basic and dry eye information includes sex,age,ocular surface disease index ( OSDI) ,tear film break-up time (TBUT),Schirmer Ⅰ test (SⅠt) and corneal fluorescence staining (CFS) score. Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) were detected in diabetic patients. Cochet-Bonnet examination (C-BE) was detected to evaluate corneal sensation and 2 corneal subbasal nerve photos of each eye were selected for effective tortuosity and density related parameters analysis. Data was analyzed by SPSS and diagnostic test were perfomed by MedCalc. This study followed the Declaration of Helsinki. This study protocol was approved by Ethic Committee of Peking University Third Hospital ( No. IRB00006761-M2017354 ) . Written informed consent was obtained from each subject prior to entering study cohort. Results L C,Seg L C mean,Cur mean,Specific p,ICM and SCC mean increased as the nerve tortuosity increased from Grade Ⅰ to Grade Ⅳ,with an overall significance among 4 groups (F=39. 100, 36. 367,57. 743,4. 043,6. 818,33. 493;all at P<0. 01). Among the above 6 parameters,Cur mean and L C of any two groups were of significant difference (all at P<0. 01). Twenty three to twenty eight persons were enrolled in each group of the cross-sectional study. Sex and age were comparable among 4 groups. Diagnostic criteria were met in dry eye and diabetes. Corneal sensation parameter C-BE decreased in diabetes without dry eye group and diabetes with dry eye group compared with healthy control group ( all at Adj P<0. 05 ) , other than in dry eye without diabetes group (AdjP≥0. 05). Nerve density of diabetes without dry eye group and diabetes with dry eye group was lower compared with healthy control group(all at P<0. 001),while no significant difference between dry eye without diabetes group and healthy control group(P≥0. 05). Among the effective parameters of tortuosity,L C,Cur mean,Seg L C mean and SCC mean of dry eye without diabetes group,diabetes without dry eye group,diabetes with dry eye group were higher compared with healthy control group ( all at P<0. 05 ) . Diagnostic tests of tortuosity related parameters all showed an area under curve (AUC) from 0. 5 to 0. 7. Conclusions L C and Cur mean can be used to analyze corneal nerve curvature more reliably. Compared with normal volunteers,patients of dry eye or diabetes show higher corneal subbasal nerve tortuosity.%目的 建立评价角膜神经弯曲度的客观标准并分析干眼及糖尿病患者角膜基底下神经弯曲度的改变.方法 根据主观分级方法任意选取Ⅰ～Ⅳ级弯曲度的角膜神经图像各80幅,将神经提取分割后对6个角膜神经弯曲度相关参数(L C、Seg L C mean、Cur mean、Specific p、ICM和SCC mean)进行分析.确认参数有效性后,进行横断面研究,收集2018年6月至2019年2月在北京大学第三医院就诊的干眼非糖尿病患者28例56眼,糖尿病非干眼患者24例48眼,糖尿病干眼患者23例46眼,招募健康志愿者28人56眼作为正常对照组.收集受检者基本资料及干眼和糖尿病相关信息后,每眼选取2幅角膜基底下神经图像进行弯曲度及密度相关参数分析.结果 Ⅰ～Ⅳ级弯曲度神经图像L C、Seg L C mean、Cur mean、Specific p、ICM和SCC mean随弯曲度级别增高而增大,总体比较差异均有统计学意义(F=39.100、36.367、57.743、4.043、6.818、33.493,均P<0.01),其中L C及Cur mean两两比较差异均有统计学意义(均P<0.01).角膜知觉方面,糖尿病非干眼组和糖尿病干眼组角膜知觉测量(C-BE)较正常对照组均降低,差异均有统计学意义(均AdjP<0.05),而干眼非糖尿病组与正常对照组之间C-BE差异均无统计学意义(AdjP≥0.05).糖尿病非干眼组和糖尿病干眼组神经密度较正常对照组降低,差异均有统计学意义(均P<0.001);干眼非糖尿病组神经密度较正常对照组有降低趋势,但差异无统计学意义(P≥0.05).干眼非糖尿病组、糖尿病非干眼组和糖尿病干眼组L C、Cur mean、Seg L C mean和SCC mean较正常对照组均增大,差异均有统计学意义(均P<0.05);ICM与正常对照组相比差异均无统计学意义(均P≥0.05).角膜基底下神经弯曲度相关参数用于诊断干眼的曲线下面积(AUC)均在0.5～0.7.结论 L C和Cur mean用于分析角膜神经弯曲度较为可靠.与正常人相比,干眼及糖尿病患者角膜基底下神经弯曲度增高.