8 research outputs found
Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma
PURPOSE: To determine whether differences in modeling implementation will impact the correction of leakage effects (from blood brain barrier disruption) and relative cerebral blood volume (rCBV) calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced (DSC)-MRI at 3T field strength. MATERIALS AND METHODS: This HIPAA-compliant study included 52 glioma patients undergoing DSC-MRI. Thirty-six patients underwent both non Preload Dose (PLD) and PLD-corrected DSC acquisitions, with sixteen patients undergoing PLD-corrected acquisitions only. For each acquisition, we generated two sets of rCBV metrics using two separate, widely published, FDA-approved commercial software packages: IB Neuro (IBN) and NordicICE (NICE). We calculated 4 rCBV metrics within tumor volumes: mean rCBV, mode rCBV, percentage of voxels with rCBV > 1.75 (%>1.75), and percentage of voxels with rCBV > 1.0 (Fractional Tumor Burden or FTB). We determined Pearson (r) and Spearman (Ï) correlations between non-PLD- and PLD-corrected metrics. In a subset of recurrent glioblastoma patients (n=25), we determined Receiver Operator Characteristic (ROC) Areas-Under-Curve (AUC) for FTB accuracy to predict the tissue diagnosis of tumor recurrence versus post-treatment effect (PTRE). We also determined correlations between rCBV and microvessel area (MVA) from stereotactic biopsies (n=29) in twelve patients. RESULTS: Using IBN, rCBV metrics correlated highly between non-PLD- and PLD-corrected conditions for FTB (r=0.96, Ï=0.94), %>1.75 (r=0.93, Ï=0.91), mean (r=0.87, Ï=0.86) and mode (r=0.78, Ï=0.76). These correlations dropped substantially with NICE. Using FTB, IBN was more accurate than NICE in diagnosing tumor vs PTRE (AUC=0.85 vs 0.67) (p<0.01). The highest rCBV-MVA correlations required PLD and IBN (r=0.64, Ï=0.58, p=0.001). CONCLUSIONS: Different implementations of perfusion MRI software modeling can impact the accuracy of leakage correction, rCBV calculation, and correlations with histologic benchmarks