NIMG-37. “SYNTHETIC” PERFUSION MRI WITH ADJUSTABLE ACQUISITION PARAMETERS IN BRAIN TUMORS USING DYNAMIC SPIN-AND-GRADIENT-ECHO ECHOPLANAR IMAGING

Abstract INTRODUCTION Dynamic susceptibility contrast (DSC) perfusion MRI can assess normalized relative cerebral blood volume (nrCBV) and percentage of signal recovery (PSR) in brain tumors, which can aid in differential diagnosis, molecular profiling, and identification of disease progression. However, CBV-optimized and PSR-optimized protocols differ in terms of acquisition parameters. Additionally, DSC dependency on acquisition parameters limits the universalizability of diagnostic cutoffs for nrCBV and PSR across institutions and scanners. This study aims to generate “synthetic” DSC datasets with adjustable synthetic acquisition parameters using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) to: 1) simultaneously generate nrCBV and PSR with optimal acquisition parameters, 2) compare DSC datasets with heterogeneous external cohorts. METHODS Thirty-eight patients with contrast-enhancing brain tumors were prospectively imaged with dynamic SAGE-EPI during a non-preloaded single-dose contrast injection. Multiple synthetic DSC datasets with desired pulse sequence parameters were generated using the Bloch equations applied to the dual-echo gradient-echo (GE) data extracted from dynamic SAGE-EPI datasets, with or without optional preload simulation. For each patient, synthetic protocols were set to match guideline-compliant CBV-optimized protocols, PSR-optimized protocols, and protocols used in external cohorts from the literature, for comparison. RESULTS Dynamic SAGE-EPI allowed for simultaneous generation of CBV-optimized and PSR-optimized DSC datasets with a single contrast injection. Conversely, suboptimal PSR computation from guideline-compliant CBV-optimized protocols resulted in rank variations within the cohort (Spearman’s ρ=0.83-0.89, i.e. 31%-21% rank variation). Treatment-naïve glioblastoma exhibited lower parameter-matched PSR compared to the external cohorts of treatment-naïve primary CNS lymphomas (PCNSL) (p<0.0001), supporting a role of synthetic DSC for multicenter comparisons. CONCLUSIONS Dynamic SAGE-EPI allows for simultaneous generation of CBV-optimized and PSR-optimized DSC data with a single injection, facilitating use of a single perfusion protocol for all DSC applications. This approach may also be useful for comparisons of perfusion parameters across heterogeneous multicenter datasets.