Arterial-Input-Function(AIF) is a pre-requisite in fitting generalized-tracer-kinetic-model(GTKM) to dynamic-contrast-enhanced(DCE) MRI data for computing tracer-kinetic-parameters(TKP). TKP are highly sensitive to peak and shape of AIF, and this results in variation in computed parameter values across studies. These variations can reduce accuracy of TKP in glioma grading. We hypothesize that propagation of these AIF related errors to TKP can be mitigated using normalization w.r.t. corresponding average TKP values of healthy tissue and normalized TKP might improve glioma grading. The proposed normalization w.r.t. healthy gray-matter tissue has significantly reduced variations of TKP and improved accuracy of glioma grading particularly using Ktrans.