Background: Differentiating Pseudoprogression (PSP) from True Progression (TP) in High-Grade Gliomas (HGGs) is challenging. Integrating parameters from advanced Magnetic Resonance Imaging (MRI) techniques may improve diagnostic performance.
Objective: Integrating multiparametric MRI (mp-MRI) with a Multiparametric Scoring System (MSS) may improve PSP-TP differentiation.
Material and Methods: In this prospective study, thirty HGG patients with post-standard treatment underwent mp-MRI on a 3T system, including Dynamic Susceptibly Contrast (DSC) MRI, Intravoxel Incoherent Motion (IVIM) MRI, Magnetic Resonance Spectroscopy (MRS), and anatomical imaging. Parametric maps were extracted, registered to anatomical images, and analyzed within a Volume of Interest (VOI) on the enhancing lesion in post-contrast T1-weighted images. Mean VOI values were compared between PSP and TP groups. Statistical analysis identified significant parameters, their Area Under the Curve’s (AUC), and optimal cutoffs, used to assign binary scores (0 or 1) and calculate a sum score for each patient. The diagnostic performance of the sum score was assessed using Receiver Operating Characteristic (ROC) curve analysis against a reference standard determined by follow-up MRI or histopathology when available.
Results: nCBV, nCBF, and nMTT   from DSC MRI, normalized-D* from IVIM-MRI, and normalized-Cho/Cr from MRS exhibited significantly higher values in the TP group. Normalized-D and -ADC   from IVIM-MRI were significantly elevated in the PSP group. The MSS approach, integrating these parameters into a sum score, demonstrated high diagnostic performance with 0.958 AUC, 87.5% sensitivity, and 92.9% specificity for distinguishing PSP from TP. 
Conclusion: Addressing the limitations of single-parameter MRI approaches, the MSS method effectively integrates mp-MRI parameters to distinguish PSP from TP in HGG patients, enhancing diagnostic performance.