Contribution of PET imaging to radiotherapy planning and monitoring in glioma patients - a report of the PET/RANO group

• Published in: Neuro-oncology (Charlottesville, Va.) Vol. 23; no. 6; pp. 881 - 893
• Main Authors: Galldiks, Norbert, Niyazi, Maximilian, Grosu, Anca L, Kocher, Martin, Langen, Karl-Josef, Law, Ian, Minniti, Giuseppe, Kim, Michelle M, Tsien, Christina, Dhermain, Frederic, Soffietti, Riccardo, Mehta, Minesh P, Weller, Michael, Tonn, Jörg-Christian
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 01-06-2021
• Subjects: Brain Neoplasms - diagnostic imaging; Brain Neoplasms - radiotherapy; Glioma - diagnostic imaging; Glioma - radiotherapy; Humans; Positron-Emission Tomography; Radiopharmaceuticals; Radiotherapy Planning, Computer-Assisted; Review; FDG; glioblastoma; target volume; radiation injury; amino acid PET
• ISSN: 1522-8517; 1523-5866
• DOI: 10.1093/neuonc/noab013

Abstract
The management of patients with glioma usually requires multimodality treatment including surgery, radiotherapy, and systemic therapy. Accurate neuroimaging plays a central role for radiotherapy planning and follow-up after radiotherapy completion. In order to maximize the radiation dose to the tumor and to minimize toxic effects on the surrounding brain parenchyma, reliable identification of tumor extent and target volume delineation is crucial. The use of positron emission tomography (PET) for radiotherapy planning and monitoring in gliomas has gained considerable interest over the last several years, but Class I data are not yet available. Furthermore, PET has been used after radiotherapy for response assessment and to distinguish tumor progression from pseudoprogression or radiation necrosis. Here, the Response Assessment in Neuro-Oncology (RANO) working group provides a summary of the literature and recommendations for the use of PET imaging for radiotherapy of patients with glioma based on published studies, constituting levels 1-3 evidence according to the Oxford Centre for Evidence-based Medicine.