Diffusion tensor imaging and optimized fiber tracking in glioma patients: Histopathologic evaluation of tumor-invaded white matter structures

Neuroimage. 2007 Feb 1;34(3):949-56. doi: 10.1016/j.neuroimage.2006.08.051. Epub 2006 Dec 12.


Fiber tracking is increasingly used to plan and guide neurosurgical procedures of intracranial tumors in the vicinity of functionally important areas of the brain. However, valid data concerning the reliability of tracking with respect to the actual pathoanatomical situation are lacking. We retrospectively correlated fiber tracking based on magnetic resonance (MR) DT imaging with the histopathological data of 25 patients with WHO grade II and III gliomas. Fiber tracking using the Fiber Assignment by Continuous Tracking (FACT) method was performed to investigate the integrity of white matter tracts in the surrounding border zone of the lesions. The tracking procedure was stopped when fractional anisotropy (FA) thresholds = 0.1, 0.15, 0.2, 0.25, and 0.3, or a tract turning angle >60 degrees were encountered. In 9 patients we were able to reconstruct brain fiber tracts at biopsy loci (2-32% tumor infiltration) using an FA threshold of 0.15 and 0.2, but not for a threshold of 0.25 or 0.3. The neurological outcome demonstrated potential tumor cell infiltration of functionally intact brain fiber tracts in the range of 2-8%. These findings may be useful in planning therapeutic approaches to gliomas in the vicinity of eloquent brain regions.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Artificial Intelligence
  • Brain Neoplasms / pathology*
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Glioma / pathology*
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Male
  • Middle Aged
  • Neoplasm Invasiveness
  • Nerve Fibers, Myelinated / pathology*
  • Neural Pathways / pathology
  • Pattern Recognition, Automated / methods
  • Reproducibility of Results
  • Sensitivity and Specificity