In vivo structural analysis of articular cartilage using diffusion tensor magnetic resonance imaging

  • Azuma T
  • Nakai R
  • Takizawa O
 et al. 
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Abstract

Purpose: The articular cartilage is a small tissue with a matrix structure of three layers between which the orientation of collagen fiber differs. A diffusion-weighted twice-refocused spin-echo echo-planar imaging (SE-EPI) sequence was optimized for the articular cartilage, and the structure of the three layers of human articular cartilage was imaged in vivo from diffusion tensor images. Materials and Methods: The subjects imaged were five specimens of swine femur head after removal of the flesh around the knee joint, five specimens of swine articular cartilage with flesh present and the knee cartilage of five adult male volunteers. Based on diffusion-weighted images in six directions, the mean diffusivity (MD) and the fractional anisotropy (FA) values were calculated. Results: Diffusion tensor images of the articular cartilage were obtained by sequence optimization. The MD and FA value of the specimens (each of five examples) under different conditions were estimated. Although the articular cartilage is a small tissue, the matrix structure of each layer in the articular cartilage was obtained by SE-EPI sequence with GRAPPA. The MD and FA values of swine articular cartilage are different between the synovial fluid and saline. In human articular cartilage, the load of the body weight on the knee had an effect on the FA value of the surface layer of the articular cartilage. Conclusion: This method can be used to create images of the articular cartilage structure, not only in vitro but also in vivo. Therefore, it is suggested that this method should support the elucidation of the in vivo structure and function of the knee joint and might be applied to clinical practice. © 2009 Elsevier Inc. All rights reserved.

Author-supplied keywords

  • Articular cartilage
  • Diffusion tensor MRI
  • In vivo analysis
  • Matrix structure

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Authors

  • Takashi Azuma

  • Ryusuke Nakai

  • Osamu Takizawa

  • Sadami Tsutsumi

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