Identification of prognostically relevant residual tumor burden in glioblastoma after surgery: A comparative analysis of MR-based RANO resect classes vs [ <sup>18</sup> F]FET PET.

J Jens Blobner (Department of Neurosurgery LMU, Munich, Germany) K Katharina Müller (Department of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany) M Michael Muether (Department of Neurosurgery, University Hospital Münster, Münster, Germany) W Wolfgang Roll J Jonas Reis (Institute for Neuroradiology, LMU University Hospital, LMU Munich, Munich, Germany) M Maximilian Mair (Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria) N Niklas Thon (Department of Neurosurgery, Knappschaft University Hospital Bochum, Bochum, Germany) S Stephan Schoenecker (Department of Radiation Oncology, LMU University Hospital, Munich, Germany) P Patrick Harter (Center of Neuropathology and Prion Research, Faculty of Medicine, LMU Munich, Munich, Germany) D Darius Kalasauskas (Department of Neurosurgery, LMU University Hospita, Munich, Germany) L Louisa von Baumgarten (12Department of Neurosurgery, Ludwig Maximilian University, Munich, Germany) F Florian Ringel J Joerg Tonn (Department of Neurosurgery, LMU University Hospital, Munich, Germany) P Philipp Karschnia N Nathalie Lisa Albert (Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany)

Abstract

2068 Background: Accurate assessment of postoperative residual tumor burden is critical in IDH -wildtype glioblastoma. The MRI-based RANO resect classification stratifies patients according to postoperative contrast-enhancing and non-contrast enhancing tumor volume but may underestimate metabolically active residual disease. The additional prognostic value of postoperative [¹⁸F]FET PET beyond MRI is yet unclear. Methods: This retrospective bicentric study included 140 patients with newly diagnosed IDH -wildtype glioblastoma and evaluable postoperative MRI and [¹⁸F]FET PET. Residual tumor volumes were segmented on MRI and classified according to the RANO resect system. PET-derived residual metabolic tumor volumes were defined using PET RANO 1.0 criteria. Spatial agreement between MRI- and PET-based volumes was quantified using Dice coefficients. Associations with overall survival were analyzed using Cox regression. Incremental prognostic value of PET was assessed using an imaging-only model (contrast-enhanced T1 (T1CE) vs. T1CE + PET) and a fully adjusted model including clinical covariates. Results: PET-derived residual tumor volumes exceeded MRI-defined volumes and showed low spatial concordance with MRI (Dice coefficient: 0.01–0.25) across all RANO resect classes. Postoperative PET-, T1CE-, and T2/FLAIR-derived tumor volumes were each associated with overall survival. Increasing PET-derived residual tumor burden was associated with a continuous increase in mortality risk. In multivariable Cox regression, PET-derived residual tumor volume remained independently associated with overall survival (adjusted hazard ratio 1.021 per cm³, 95% CI 1.008–1.033; ** p = 0.0024). In the imaging-only model, addition of PET improved time-dependent discrimination between 6 and 24 months (ΔAUC(t) 0.03–0.07) and increased Harrell’s C (ΔC ≈ 0.03). In the fully adjusted model, PET provided significant non-redundant prognostic information (likelihood ratio test, * p = 0.0049). Conclusions: Postoperative [¹⁸F]FET PET identifies metabolically active residual tumor not adequately captured by MRI and provides additional prognostic information beyond MRI-based assessment. Integration of PET into postoperative evaluation may refine prognostic stratification in IDH-wildtype glioblastoma.

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 2068-2068
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (15)

J

Jens Blobner

Department of Neurosurgery LMU, Munich, Germany

K

Katharina Müller

Department of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

M

Michael Muether

Department of Neurosurgery, University Hospital Münster, Münster, Germany

W

Wolfgang Roll

J

Jonas Reis

Institute for Neuroradiology, LMU University Hospital, LMU Munich, Munich, Germany

M

Maximilian Mair

Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria

N

Niklas Thon

Department of Neurosurgery, Knappschaft University Hospital Bochum, Bochum, Germany

S

Stephan Schoenecker

Department of Radiation Oncology, LMU University Hospital, Munich, Germany

P

Patrick Harter

Center of Neuropathology and Prion Research, Faculty of Medicine, LMU Munich, Munich, Germany

D

Darius Kalasauskas

Department of Neurosurgery, LMU University Hospita, Munich, Germany

L

Louisa von Baumgarten

12Department of Neurosurgery, Ludwig Maximilian University, Munich, Germany

F

Florian Ringel

J

Joerg Tonn

Department of Neurosurgery, LMU University Hospital, Munich, Germany

P

Philipp Karschnia

N

Nathalie Lisa Albert

Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany