中国神经再生研究(英文版) ›› 2013, Vol. 8 ›› Issue (23): 2155-2164.doi: 10.3969/j.issn.1673-5374.2013.23.005

• 原著:脑损伤修复保护与再生 • 上一篇    下一篇

基于三线性插值的脑白质纤维成像

  

  • 收稿日期:2013-04-25 修回日期:2013-06-15 出版日期:2013-08-15 发布日期:2013-08-15

Tri-linear interpolation-based cerebral white matter fiber imaging

Shan Jiang1, Pengfei Zhang1, Tong Han2, Weihua Liu1, Meixia Liu1   

  1. 1 School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
    2 Medical Image Evaluation Center, Tianjin Huanhu Hospital, Tianjin 300060, China
  • Received:2013-04-25 Revised:2013-06-15 Online:2013-08-15 Published:2013-08-15
  • Contact: Shan Jiang, Ph.D., Associate professor, School of Mechanical Engineering, Tianjin University, Tianjin 300072, China, shanjiang@tju.edu.cn
  • Supported by:

    国家自然科学基金 No.60703045

摘要:

扩散张量成像是目前活体、三维、无创显示脑白质纤维束的惟一方法,同时也是观察和研究神经再生的一个重要工具。目前研究者提出了多种基于扩散张量的纤维追踪方法,但如何使计算快速,追踪纤维更长、更光滑、细节显示更清晰,一直是纤维追踪在临床应用上需要不断改进的问题。文章提出了三线性插值的纤维追踪方法,以一右侧基底节区急性梗死灶患者为例,设计了基于能量最小和极限原理的三线性插值算法以及张量线算法实验,分别对同一感兴趣区域(胼胝体膝部)进行纤维追踪,将2种方法追踪结果进行对比,并结合患者实际病情以及大脑真实解剖加以验证。数据统计结果显示三线性插值法所追踪出的白质神经纤维的最大长度和平均长度明显更长。追踪图像结果显示三线性插值算法所追踪纤维更光滑、走向更加明显,细节显示更加清晰。追踪纤维的异常情况与患者实际病情较好吻合,经胼胝体部位的纤维追踪显示与大脑解剖结构基本一致。表明三线性插值算法可以达到较好的追踪效果,追踪结果真实可靠。

关键词: 神经再生, 神经影像学, 扩散张量成像, 三线性插值, 张量线算法, 白质纤维, 纤维追踪, 核磁共振成像

Abstract:

Diffusion tensor imaging is a unique method to visualize white matter fibers three-dimensionally, non-invasively and in vivo, and therefore it is an important tool for observing and researching neural regeneration. Different diffusion tensor imaging-based fiber tracking methods have been already investigated, but making the computing faster, fiber tracking longer and smoother and the details shown clearer are needed to be improved for clinical applications. This study proposed a new fiber tracking strategy based on tri-linear interpolation. We selected a patient with acute infarction of the right basal ganglia and designed experiments based on either the tri-linear interpolation algorithm or tensorline algorithm. Fiber tracking in the same regions of interest (genu of the corpus callosum) was performed separately. The validity of the tri-linear interpolation algorithm was verified by quan-titative analysis, and its feasibility in clinical diagnosis was confirmed by the contrast between tracking results and the disease condition of the patient as well as the actual brain anatomy. Statis-tical results showed that the maximum length and average length of the white matter fibers tracked by the tri-linear interpolation algorithm were significantly longer. The tracking images of the fibers indicated that this method can obtain smoother tracked fibers, more obvious orientation and clearer details. Tracking fiber abnormalities are in good agreement with the actual condition of patients, and tracking displayed fibers that passed though the corpus callosum, which was consistent with the anatomical structures of the brain. Therefore, the tri-linear interpolation algorithm can achieve a clear, anatomically correct and reliable tracking result.

Key words: neural regeneration, neuroimaging, diffusion tensor imaging, tri-linear interpolation, tensor algorithm, white matter fiber, fiber tracking, magnetic resonance imaging, grants-supported paper, neuroregeneration