Published online Nov 28, 2015. doi: 10.4329/wjr.v7.i11.405
Peer-review started: April 21, 2015
First decision: June 9, 2015
Revised: August 31, 2015
Accepted: October 12, 2015
Article in press: October 13, 2015
Published online: November 28, 2015
AIM: To determine existing correlates among diffusion tensor imaging (DTI)-derived metrics in healthy brains and brains with glioblastoma multiforme (GBM).
METHODS: Case-control study using DTI data from brain magnetic resonance imaging of 34 controls (mean, 41.47; SD, ± 21.94 years; range, 21-80 years) and 27 patients with GBM (mean, SD; 48.41 ± 15.18 years; range, 18-78 years). Image postprocessing using FSL software calculated eleven tensor metrics: fractional (FA) and relative anisotropy; pure isotropic (p) and anisotropic diffusions (q), total magnitude of diffusion (L); linear (Cl), planar (Cp) and spherical tensors (Cs); mean (MD), axial (AD) and radial diffusivities (RD). Partial correlation analyses (controlling the effect of age and gender) and multivariate Mancova were performed.
RESULTS: There was a normal distribution for all metrics. Comparing healthy brains vs brains with GBM, there were significant very strong bivariate correlations only depicted in GBM: [FA↔Cl (+)], [FA↔q (+)], [p↔AD (+)], [AD↔MD (+)], and [MD↔RD (+)]. Among 56 pairs of bivariate correlations, only seven were significantly different. The diagnosis variable depicted a main effect [F-value (11, 23) = 11.842, P≤ 0.001], with partial eta squared = 0.850, meaning a large effect size; age showed a similar result. The age also had a significant influence as a covariate [F (11, 23) = 10.523, P < 0.001], with a large effect size (partial eta squared = 0.834).
CONCLUSION: DTI-derived metrics depict significant differences between healthy brains and brains with GBM, with specific magnitudes and correlations. This study provides reference data and makes a contribution to decrease the underlying empiricism in the use of DTI parameters in brain imaging.
Core tip: Diffusion tensor imaging (DTI)-derived metrics depict specific magnitudes and correlations; and significant differences between healthy brains and brains with glioblastoma multiforme (GBM). For example, only 5 bivariate correlations in GBM depicted significant very strong association: [FA↔Cl (+)], [FA↔q (+)], [p↔AD (+)], [D↔MD (+)], and [MD↔RD (+)]. Among 56 pairs of correlations, only seven were significantly different. Diagnosis showed a main effect [F-value (11, 23) = 11.842, P≤ 0.001], with a large effect size (partial eta squared = 0.850); a similar result was observed for age. This study makes a contribution to decrease the empiricism in the use of DTI parameters in brain imaging.