Purpose: Differentiation between tumor progression (TP) and treatment related abnormalities (TRA) in post-treatment high-grade glioma patients remains a diagnostic challenge. This study investigates if ADC in regions of hyperperfusion and hypoperfusion, based on DSC-PWI data, combined with the volume of these regions can provide accurate differentiation between TP from TRA in post-treatment glioma patients. Methods: Post-treatment high-grade astrocytoma patients were retrospectively included. The patient endpoint (TP or TRA) was determined by clinical/radiological follow-up or histopathological confirmation. DSC-PWI sequences were processed into fractional tumor burden (FTB) maps, resulting in voxel classes: FTBlow (hypoperfusion) and FTBhigh (hyperperfusion). These were superimposed on ADC-maps, allowing regional ADC determination. This data was analyzed using logistic regression. The accuracy of this model in predicting TP was determined using a ROC-analysis and compared to ROC analyses of the individual metrics. Results: Ninety-eight patients were included (TP n=68). Regional ADC differed significantly between FTBlow and FTBhigh (p < 0.01). The logistic model indicated that the volume FTBhigh had an odds ratio of 1.16 (p = 0.03), the other predictors were non-significant (volume FTBlow, ADC in FTBlow, ADC in FTBhigh). The ROC analysis showed an area under the ROC (AUROC) curve of 0.72. This was not significantly higher than the AUROC of FTBhigh or whole lesion rCBV (p = 0.38, p = 0.30). Conclusion: ADC measured inside of DSC-PWI classes combined with the volume of hypo- and hyperperfusion can differentiate between TP and TRA with fair diagnostic accuracy. It does not provide improvement over whole lesion rCBV or FTBhigh alone.