Amino acid PET vs. RANO MRI for prediction of overall survival in patients with recurrent high grade glioma under bevacizumab therapy.

Avastin Glioblastoma Magnetic resonance imaging Positron emission tomography Pseudoresponse Therapy monitoring

Journal

European journal of nuclear medicine and molecular imaging
ISSN: 1619-7089
Titre abrégé: Eur J Nucl Med Mol Imaging
Pays: Germany
ID NLM: 101140988

Informations de publication

Date de publication:
17 Jan 2024
Historique:
received: 20 09 2023
accepted: 01 01 2024
medline: 17 1 2024
pubmed: 17 1 2024
entrez: 16 1 2024
Statut: aheadofprint

Résumé

To summarize evidence on the comparative value of amino acid (AA) PET and conventional MRI for prediction of overall survival (OS) in patients with recurrent high grade glioma (rHGG) under bevacizumab therapy. Medical databases were screened for studies with individual data on OS, follow-up MRI, and PET findings in the same patient. MRI images were assessed according to the RANO criteria. A receiver operating characteristic curve analysis was used to predict OS at 9 months. Five studies with a total of 72 patients were included. Median OS was significantly lower in the PET-positive than in the PET-negative group. PET findings predicted OS with a pooled sensitivity and specificity of 76% and 71%, respectively. Corresponding values for MRI were 32% and 82%. Area under the curve and sensitivity were significantly higher for PET than for MRI. For monitoring of patients with rHGG under bevacizumab therapy, AA-PET should be preferred over RANO MRI.

Identifiants

pubmed: 38228970
doi: 10.1007/s00259-024-06601-4
pii: 10.1007/s00259-024-06601-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

Références

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Auteurs

Artem Chaban (A)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Birgit Waschulzik (B)

Institute of AI and Informatics in Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Denise Bernhardt (D)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Department of Radiation Oncology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Claire Delbridge (C)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Department of Pathology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Friederike Schmidt-Graf (F)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Department of Neurology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Arthur Wagner (A)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Department of Neurosurgery, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Benedikt Wiestler (B)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Department of Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Wolfgang Weber (W)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Igor Yakushev (I)

Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany. igor.yakushev@tum.de.

Classifications MeSH