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基于角膜共聚焦显微镜的神经纤维人工智能分析方法

吴俊,  费思佳,  沈博,  张瀚文,  黄剑锋,  潘琦,  赵建春,  丁大勇

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文章导航 > 协和医学杂志  > 2021 >  12(5): 736-741
吴俊, 费思佳, 沈博, 张瀚文, 黄剑锋, 潘琦, 赵建春, 丁大勇. 基于角膜共聚焦显微镜的神经纤维人工智能分析方法[J]. 协和医学杂志, 2021, 12(5): 736-741. doi: 10.12290/xhyxzz.2021-0510
引用本文: 吴俊, 费思佳, 沈博, 张瀚文, 黄剑锋, 潘琦, 赵建春, 丁大勇. 基于角膜共聚焦显微镜的神经纤维人工智能分析方法[J]. 协和医学杂志, 2021, 12(5): 736-741. doi: 10.12290/xhyxzz.2021-0510
shu
WU Jun, FEI Sijia, SHEN Bo, ZHANG Hanwen, HUANG Jianfeng, PAN Qi, ZHAO Jianchun, DING Dayong. Artificial Intelligence Analysis of Nerve Fibers Based on Corneal Confocal Microscopy[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 736-741. doi: 10.12290/xhyxzz.2021-0510
Citation: WU Jun, FEI Sijia, SHEN Bo, ZHANG Hanwen, HUANG Jianfeng, PAN Qi, ZHAO Jianchun, DING Dayong. Artificial Intelligence Analysis of Nerve Fibers Based on Corneal Confocal Microscopy[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 736-741. doi: 10.12290/xhyxzz.2021-0510
shu

基于角膜共聚焦显微镜的神经纤维人工智能分析方法

doi: 10.12290/xhyxzz.2021-0510
  • 1.

    西北工业大学电子信息学院，西安 710072

  • 2.

    中国医学科学院 北京协和医学院研究生院，北京 100730

  • 3.

    国家老年医学中心 中国医学科学院老年医学研究院 北京医院 眼科，北京 100730

  • 4.

    国家老年医学中心 中国医学科学院老年医学研究院 北京医院 内分泌科，北京 100730

  • 5.

    北京致远慧图科技有限公司人工智能实验室，北京 100872

基金项目: 

国家重点研发计划 2020YFC2009006

国家重点研发计划 2020YFC2009000

陕西省自然科学基础研究计划 2020JM-129

西北工业大学硕士研究生创意创新种子基金 CX2020162

西北工业大学国家级大学生创新创业训练计划 S202010699207

西北工业大学国家级大学生创新创业训练计划 S202010699630

详细信息
    通讯作者:

    潘琦  电话：010-85138663，E-mail: panqi621@126.com

    吴俊、费思佳为共同第一作者

    吴俊、费思佳为共同第一作者

  • 中图分类号: R-1; R770.4; R587.1

Artificial Intelligence Analysis of Nerve Fibers Based on Corneal Confocal Microscopy

  • 1.

    School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China

  • 2.

    Graduate School, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

  • 3.

    Department of Ophthalmology, Beijing hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China

  • 4.

    Department of Endocrinology, Beijing hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China

  • 5.

    Vistel AI Lab, Visionary Intelligent Ltd., Beijing 100872, China

Funds: 

China National Key R & D Program 2020YFC2009006

China National Key R & D Program 2020YFC2009000

Natural Science Basic Research Plan in Shaanxi Province of China 2020JM-129

Seed Foundation of Innovation and Creation for Postgraduate Students in Northwestern Polytechnical University CX2020162

National Innovation and Entrepreneurship Training Program for College Students S202010699207

National Innovation and Entrepreneurship Training Program for College Students S202010699630

More Information
    Corresponding author: PAN Qi   Tel: 86-10-85138663, E-mail: panqi621@126.com

    摘要
  • 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.
    作者贡献：吴俊、费思佳共同查阅文献，撰写初稿并修订论文；沈博、张瀚文、黄剑锋、赵建春、丁大勇提出修改建议；潘琦负责终审校对。
    利益冲突：无
    吴俊、费思佳为共同第一作者
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    • 参考文献(37)
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出版历程
  • 收稿日期:  2021-07-02
  • 录用日期:  2021-07-29
  • 网络出版日期:  2021-09-22
  • 刊出日期:  2021-09-30

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