基于角膜共聚焦显微镜的神经纤维人工智能分析方法

Artificial Intelligence Analysis of Nerve Fibers Based on Corneal Confocal Microscopy

  • 摘要: 糖尿病周围神经病变(diabetic peripheral neuropathy, DPN)是糖尿病最常见的慢性并发症之一。基于临床症状体征以及电生理检查的传统DPN诊断方法主要用于检测大神经纤维病变,而DPN最早出现损伤的部位是小神经纤维。角膜共聚焦显微镜(corneal confocal microscopy, CCM)能够在高倍镜下分析角膜神经纤维的变化,是一种快速、可重复、定量测量小神经纤维病变的无创技术,可早期诊断DPN并前瞻性评估神经形态学改变,具有良好的应用前景。本文就CCM评估糖尿病神经病变的临床应用研究以及CCM相关人工智能分析方法进行综述,以期为临床诊疗提供借鉴。

     

    Abstract: Diabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes. Traditional DPN diagnostic methods are based on clinical symptoms and signs as well as electrophysiological examination, which are mainly used to detect the lesions of large nerve fibers. However, the small nerve fibers are the earliest ones damaged in DPN. Corneal confocal microscopy (CCM) can analyze the changes of corneal nerve fibers under a high power microscope. It is a rapid, repeatable and quantitative noninvasive technique to measure small nerve fibers. It can diagnose DPN early and evaluate neuromorphological changes prospectively. It has a good application expectation. During this article, we summarized the role and limitations of DPN's most reliable parameters of corneal nerve in evaluating diabetic autonomic neuropathy and diabetic micro-vascular complications. Further, we reviewed the clinical application of CCM in evaluating diabetic neuropathy and analysis methods of CCM related artificial intelligence, in order to provide references for clinical diagnosis and treatment.

     

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