Here we aim to characterize human glioblastoma with FFC-NMR using cerebral tissue of normal pig as a reference. Power-law models and Fries-Belorisky model (quadrupolar 14N-1H coupling peaks (QPs)) were used to analyse the T1-dispersion. Linear Discriminant Analysis and statistical tests of derived fit parameters were used for classification. T1 values at low field were found significantly different between cerebral tissues and glioblastoma, a result which is well admitted by the NMR community. However our most relevant finding is the role of the molecular dynamics related parameters to discriminate glioblastoma from cerebral tissues. QPs parameters also appear as a possible biomarkers but require higher signal sensitivity.