Distinguishing true progression from treatment effects in glioblastoma: a practical, evidence-graded imaging framework for the multidisciplinary team.

BACKGROUND

Distinguishing true progression (TP) from treatment effects-pseudoprogression (PsP) and radiation necrosis (RN)-after chemoradiation for glioblastoma (GBM) is a consequential, unresolved decision that conventional MRI cannot reliably make in 30-40% of cases, and that is rarely made by any single specialty alone.

METHODS

We synthesized and graded evidence from RANO 2.0, advanced MRI (perfusion, diffusion, and spectroscopy), amino acid PET (per PET RANO 1.0), and radiomics, based on a literature search of PubMed/MEDLINE, Embase, and Cochrane (2010-2025).

RESULTS

In selected cohorts, combined MRI plus amino acid PET reports areas under the curve of 0.90-0.95 versus 0.65-0.72 for conventional MRI alone; however, these figures come from cohorts spanning the full range of post-treatment enhancement-including easily classified cases-rather than the ambiguous subset in which advanced imaging is actually used, and therefore likely overstate real-world accuracy. We organize the evidence around clinical modifiers of pretest probability-MGMT methylation, interval since chemoradiation, neurologic trajectory, antiangiogenic or immunotherapy exposure, reirradiation, and lesion location-that determine how heavily each imaging tier should be weighted. For amino acid PET, we address U.S. access, including recently published prospective and multicenter diagnostic-accuracy data for 18F-fluciclovine.

CONCLUSIONS

We propose a tiered imaging framework-RANO 2.0 MRI → perfusion MRI → amino acid PET → tissue sampling or empirical therapy-explicitly as a structure for prospective evaluation, not a validated clinical decision tool. The principal unresolved gap is amino acid PET performance conditional on an equivocal perfusion MRI, which ongoing trials should address.