Toward tract-specific fractional anisotropy (TSFA) at crossing-fiber regions with clinical diffusion MRI

Magn Reson Med. 2015 Dec;74(6):1768-79. doi: 10.1002/mrm.25548. Epub 2014 Dec 1.

Abstract

Purpose: White matter fractional anisotropy (FA), a measure suggesting microstructure, is significantly underestimated with single diffusion tensor model at crossing-fiber regions (CFR). We propose a tract-specific FA (TSFA), corrected for the effects of crossing-fiber geometry and free water at CFR, and adapted for tract analysis with diffusion MRI (dMRI) in clinical research.

Methods: At CFR voxels, the proposed technique estimates free water fraction (fiso ) as a linear function of mean apparent diffusion coefficient (mADC), fits the dual tensors and estimates TSFA. Digital phantoms were designed for testing the accuracy of fiso and fitted dual-anisotropies at CFR. The technique was applied to clinical dMRI of normal subjects and hereditary spastic paraplegia (HSP) patients to test the effectiveness of TSFA.

Results: Phantom simulation showed unbiased estimates of dual-tensor anisotropies at CFR and high accuracy of fiso as a linear function of mADC. TSFA at CFR was highly consistent to the single tensor FA at non-CFR within the same tract with normal human dMRI. Additional HSP imaging biomarkers with significant correlation to clinical motor function scores could be identified with TSFA.

Conclusion: Results suggest the potential of the proposed technique in estimating unbiased TSFA at CFR and conducting tract analysis in clinical research.

Keywords: Gaussian mixture model; TSFA; diffusion MRI; dual-tensor; free water elimination; tract analysis; tract-specific fractional anisotropy.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Anisotropy
  • Brain / anatomy & histology*
  • Child
  • Computer Simulation
  • Diffusion Tensor Imaging / methods*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Male
  • Models, Statistical
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • White Matter / anatomy & histology*
  • Young Adult