中国神经再生研究(英文版)

中国神经再生研究(英文版) ›› 2018, Vol. 13 ›› Issue (8): 1465-1470.doi: 10.4103/1673-5374.235307

• 原著:周围神经损伤修复保护与再生 • 上一篇    下一篇

三维可视化新方法重建长段周围神经功能束

  

  • 收稿日期:2018-05-13 出版日期:2018-08-15 发布日期:2018-08-15
  • 基金资助:

    国家自然科学基金(30571913)、广东省科学技术项目(2013B010404019)、广东省自然科学基金(9151008901000006)、广东省医学科研基金会(A2009173)

Three-dimensional visualization of the functional fascicular groups of a long-segment peripheral nerve

Jian Qi1, Wei-Ya Wang2 , Ying-Chun Zhong3, Jia-Ming Zhou4, Peng Luo5, Ping Tang3, Cai-Feng He6, Shuang Zhu7, Xiao-Lin Liu1, Yi Zhang8   

  1. 1 Department of Orthopedics and Microsurgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China;
    2 Department of Plastic Surgery, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, Guangxi Zhuang Autonomous Region, China;
    3 Automation College, Guangdong University of Technology, Guangzhou, Guangdong Province, China;
    4 Scientific Research Department, Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China;
    5 Department of Orthopedics, Shenzhen Nanshan People’s Hospital, Shenzhen, Guangdong Province, China;
    6 Zhongshan University Medical Equipment Co., Ltd., Guangzhou, Guangdong Province, China;
    7 Department of Joint and Orthopedics, Orthopedic Center, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, China;
    8 Department of Plastic Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
  • Received:2018-05-13 Online:2018-08-15 Published:2018-08-15
  • Contact: Yi Zhang, M.D., Ph.D.,doczy2006@126.com
  • Supported by:

    This study was supported by the National Natural Science Foundation of China, No. 30571913; a grant from the Science and Technology Project of Guangdong Province of China, No. 2013B010404019; the Natural Science Foundation of Guangdong Province of China, No.9151008901000006; the Medical Scientific Research Foundation of Guangdong Province of China, No. A2009173.

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摘要：

周围神经干内部各功能束组的三维可视化图像能直观有效地反映功能束与束组的整体三维信息，为周围神经损伤修复方式的选择以及组织工程神经的构建提供有益帮助。但目前带标志点的二维全景图像的获取、配准、识别及周围神经三维重建等步骤还存在关键技术问题还亟待解决，而且人工操作导致合成的可视化三维立体模型精度欠佳，尚不能真实还原神经内部的立体显微解剖结构。鉴于此，我们设计了一种二次成像技术及计算机自动配准的新方法，对周围神经功能束进行三维可视化重建，以期获得更好的成像效果。取新鲜成人尸体右上臂20 cm长尺神经标本行乙酰胆碱酯酶染色，采用二次成像技术，以体视显微镜于AchE 染色前、后分别获取同一切片的2 张全景图像，通过Photoshop软件图层叠加进行图像处理，并利用空间变换方法实现自动配准，结合人工辅助获取功能束轮廓，通过Amira 4.1 医学三维重建软件进行长段尺神经功能束三维重建，评估重建逆向还原效果。结果显示，利用二次成像Photoshop软件处理同一张切片染色前、后的图像轮廓吻合度良好，合成图像获得的标志点定位精确，操作简便快捷。优化最小二乘支持向量机方法识别精度高，误差率为8.25%；构建的三维模型可清晰的观察到尺神经内部不同性质功能束交叉融合的变化，其任意水平切割逆向还原基本吻合。上述数据证实，采用二次成像技术和计算机自动配准的方法，可成功重建出清晰的长段周围神经三维可视化图像，方便快捷，效果较好。

orcid:0000-0001-6463-6970(Yi Zhang)

关键词: 周围神经, 尺神经, 三维重建, 功能束群, 配准, 分割, 定位点, 自动配准, 乙酰胆碱酯酶, 计算机模拟实验, 神经再生

Abstract:

The three-dimensional (3D) visualization of the functional bundles in the peripheral nerve provides direct and detailed intraneural spatial information. It is useful for selecting suitable surgical methods to repair nerve defects and in optimizing the construction of tissue-engineered nerve grafts. However, there remain major technical hurdles in obtaining, registering and interpreting 2D images, as well as in establishing 3D models. Moreover, the 3D models are plagued by poor accuracy and lack of detail and cannot completely reflect the stereoscopic microstructure inside the nerve. To explore and help resolve these key technical problems of 3D reconstruction, in the present study, we designed a novel method based on re-imaging techniques and computer image layer processing technology. A 20-cm ulnar nerve segment from the upper arm of a fresh adult cadaver was used for acetylcholinesterase (AChE) staining. Then, 2D panoramic images were obtained before and after AChE staining under the stereomicroscope. Using layer processing techniques in Photoshop, a space transformation method was used to fulfill automatic registration. The contours were outlined, and the 3D rendering of functional fascicular groups in the long-segment ulnar nerve was performed with Amira 4.1 software. The re-imaging technique based on layer processing in Photoshop produced an image that was detailed and accurate. The merging of images was accurate, and the whole procedure was simple and fast. The least square support vector machine was accurate, with an error rate of only 8.25%. The 3D reconstruction directly revealed changes in the fusion of different nerve functional fascicular groups. In conclusion. The technique is fast with satisfactory visual reconstruction.

Key words: nerve regeneration, peripheral nerve, ulnar nerve, three-dimensional reconstruction, functional fascicular group, registration, segmentation, locating spots, auto-registration, acetylcholinesterase, neural regeneration