Assessment of injured spinal cord using diffusion tensor tractography

Kanehiro Fujiyoshi, Tsunehiko Konomi, Osahiko Tsuji, Masayuki Yamada, Keigo Hikishima, Suketaka Momoshima, Hideyuki Okano, Yoshiaki Toyama, Masaya Nakamura

Research output: Chapter in Book/Report/Conference proceedingChapter


In spinal cord injury (SCI), the evaluation of axonal fibers is important to assess the severity of injury and efficacy of any treatment protocol, but conventional methods such as tracer injection in the brain parenchyma are highly invasive and require histological evaluation, precluding clinical applications. Magnetic resonance imaging (MRI) is essential for predicting prognosis and planning treatment of patients with SCI noninvasively. However, the information provided by conventional T1- and T2-weighted MRI of the spinal cord is essentially limited to the differentiation of the white matter from the gray matter. By contrast, diffusion-weighted magnetic resonance imaging (DWI) provides much information about biological structures. In particular, diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) are powerful tools for evaluating white matter fibers in the central nervous system. We previously established a reproducible SCI model in adult common marmosets and demonstrated that DTT could be used to trace the neural tracts in the intact and injured spinal cord of these animals in vivo. Recently, many reports using DTT to analyze the spinal cord area have been published. Based on the findings from our experimental studies, we are now routinely performing DTT of the human spinal cord clinically. In this chapter, we outline the basic principles of DTT and describe the characteristics, limitations, and clinical application of DTT in the spinal cord.

Original languageEnglish
Title of host publicationNeuroprotection and Regeneration of the Spinal Cord
PublisherSpringer Japan
Number of pages21
ISBN (Electronic)9784431545026
ISBN (Print)4431545018, 9784431545019
Publication statusPublished - 01-11-2014

All Science Journal Classification (ASJC) codes

  • General Medicine


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