Dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging for glioma grading: Preliminary comparison of vessel compartment and permeability parameters using hotspot and histogram analysis

Introduction: Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings. This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant K-trans. Methods: Twenty-six newly diagnosed glioma patients underwent 3T -MR DCE and DSC imaging. Parametric maps of CBV, Vp and K-trans were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and K-trans values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis. Results: rCBV, Vp and K-trans measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. /Cans hotspots co -localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBV(max), and 1.000 for Vp(max) and K-max(trans). Combination of DCE-derived Vp and K-trans parameters improved the diagnostic performance of the histogram method. Conclusion: This initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well -established DSC-derived rCBV for glioma grading. DCE-derived K-trans is equally useful for grading, providing different informations with respect to Vp. (C) 2016 Published by Elsevier Ireland Ltd.