Opportunities and pitfalls in the quantification of fiber integrity: what can we gain from Q-ball imaging?
The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration.
Fritzsche
Klaus H
KH
Division of Medical and Biological Informatics, German Cancer Research Center, Heidelberg, Germany. k.fritzsche@dkfz-heidelberg.de
Laun
Frederik B
FB
Meinzer
Hans-Peter
HP
Stieltjes
Bram
B
D016880:Anisotropy; D016477:Artifacts; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000295:instrumentation / Q000379:methods; D006801:Humans; D008959:Models, Neurological; D009010:Monte Carlo Method; D009434:Neural Pathways / Q000033:anatomy & histology; D019047:Phantoms, Imaging