BACKGROUND AND PURPOSE: MR imaging can measure tissue perfusion and the integrity of the blood-brain barrier. We hypothesize that a combined measure of cerebral blood volume and vascular permeability using vascular-space occupancy (VASO) MR imaging, a recently developed imaging technique, is of diagnostic value for predicting tumor grade. MATERIALS AND METHODS: Thirty-nine patients (9 World Health Organization [WHO] grade II, 20 grade III, and 10 grade IV as determined by histopathologic assessment) were examined using VASO MR imaging, and regions-of-interest analysis was performed in tumoral regions, as well as in regions contralateral to the tumor. A Mann-Whitney test was conducted on the resulting VASO indices for a pairwise comparison across tumor grades. Nominal logistic regression was used to evaluate the use of VASO parameters for predicting group membership (by the percentage of correct classifications). RESULTS: The ratio between tumor side and contralateral side, VASO(Ratio), showed significant differences in all 3 of the pairwise comparisons (P <.01). VASO values in the tumoral regions, VASO(Tumor), showed significant difference between grade II and III and between II and IV but not between III and IV. Both VASO(Tumor) and VASO(Ratio) were found to be significant predictors of tumor grade, giving diagnostic accuracies of 66.7% and 71.8%, respectively. When testing to discriminate grade II tumors from higher grade tumors, the areas under the receiver operating characteristic curve were found to be 0.974 and 0.985 for VASO(Tumor) and VASO(Ratio), respectively. CONCLUSION: VASO MR imaging can be used for noninvasive tumor grade prediction based on cerebral blood volume and vascular permeability. VASO is more effective in separating WHO grade II from higher grades than in separating grade III from grade IV.
- Blood Volume
- blood supply
- Brain Neoplasms
- pathology Humans Image Interpretation
- methods Magnetic Resonance Imaging
- methods Male Middle Aged Neovascularization
- pathology Reproducibility of Results Sensitivity and Specificity