Abstract Purpose Clinical prognostication and decision-making in IDH-mutant glioma is increasingly complex, especially with new targeted treatment options like IDH-inhibitors. Individual patient risk stratification for better treatment planning is needed; however, standard prognostic models rely on clinical and histologic parameters as well as MRI, which may not fully reflect the tumor’s biological behavior. Positron emission tomography (PET) imaging of the 18 kDa translocator protein (TSPO) is known as surrogate marker of activated microglia and macrophages and enables non-invasive assessment of the tumor microenvironment and peri-/intratumoral inflammation as well as TSPO-positive tumor cells. The aim of this study was to investigate TSPO-PET imaging in IDH-mutant glioma and its association with outcome. Methods In this monocentric, retrospective study, 46 patients with newly diagnosed IDH-mutant glioma who had undergone TSPO-PET imaging with ¹⁸FGE180 prior to any therapeutic intervention were included. Quantitative PET parameters including mean and maximum standardized uptake values (SUV max , SUV mean ) and the respective PET-positive tumor volumes were evaluated for their association with clinical data and time to next intervention (TTNI), and overall survival (OS). Results The cohort consisted of 27 patients (58.7%) with astrocytoma, IDH-mutant (median age 36 years (30–51)) and 19 patients (41.3%) with oligodendroglioma, IDH-mutant and 1p/19q-codeleted (median age 41 years (36–48)). High SUV max on TSPO-PET imaging was associated with shorter TTNI, and OS ( p = 0.0118 and p = 0.0459, respectively). In multivariate analyses adjusting for age, KPS, WHO grade, FET-PET-positive volume, and tumor volume on contrast-enhanced MRI, the TSPO-PET-positive volume was associated with TTNI (hazard ratio (HR) = 1.037, 95% CI: 1.009–1.064, p = 0.0106). Conclusions This study highlights the potential prognostic utility of TSPO-PET imaging in newly diagnosed IDH-mutant glioma. Our findings support the inclusion of PET imaging in future clinical trials to develop imaging-based risk models for better prognostication and individualized treatment guidance.
Müller et al. (Sat,) studied this question.