A sensitive and automatic white matter fiber tracts model for longitudinal analysis of diffusion tensor images in multiple sclerosis

Claudio Stamile, Gabriel Kocevar, François Cotton, Françoise Durand-Dubief, Salem Hannoun, Carole Frindel, Charles R.G. Guttmann, David Rousseau, Dominique Sappey-Marinier

研究成果: Article査読

13 被引用数 (Scopus)

抄録

Diffusion tensor imaging (DTI) is a sensitive tool for the assessment of microstructural alterations in brain white matter (WM). We propose a new processing technique to detect, local and global longitudinal changes of diffusivity metrics, in homologous regions along WM fiber-bundles. To this end, a reliable and automatic processing pipeline was developed in three steps: 1) co-registration and diffusion metrics computation, 2) tractography, bundle extraction and processing, and 3) longitudinal fiber-bundle analysis. The last step was based on an original Gaussian mixture model providing a fine analysis of fiber-bundle cross-sections, and allowing a sensitive detection of longitudinal changes along fibers. This method was tested on simulated and clinical data. High levels of F-Measure were obtained on simulated data. Experiments on cortico-spinal tract and inferior fronto-occipital fasciculi of five patients with Multiple Sclerosis (MS) included in a weekly follow-up protocol highlighted the greater sensitivity of this fiber scale approach to detect small longitudinal alterations.

本文言語English
論文番号e0156405
ジャーナルPloS one
11
5
DOI
出版ステータスPublished - 2016 5
外部発表はい

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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