[18F]FET PET/MR and machine learning in the evaluation of glioma-Reference-Cited by-同舟云学术

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[18F]FET PET/MR and machine learning in the evaluation of glioma

Published:2023-11-13 Issue:3 Volume:51 Page:797-799
ISSN:1619-7070
Container-title:European Journal of Nuclear Medicine and Molecular Imaging
language:en
Short-container-title:Eur J Nucl Med Mol Imaging

Author:

Piscopo Leandra,Zampella Emilia,Klain Michele

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine,Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00259-023-06505-9.pdf

Reference26 articles.

1. Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. 2021;23(8):1231–51. https://doi.org/10.1093/neuonc/noab106.

2. Weller M, van den Bent M, Preusser M, Le Rhun E, Tonn JC, Minniti G, et al. EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat Rev Clin Oncol. 2021;18(3):170–86. https://doi.org/10.1038/s41571-020-00447-z. (Erratum.In:NatRevClinOncol. 2022May;19(5):357-358).

3. Ludwig K, Kornblum HI. Molecular markers in glioma. J Neurooncol. 2017;134(3):505–12. https://doi.org/10.1007/s11060-017-2379-y.

4. Nicholson JG, Fine HA. Diffuse glioma heterogeneity and its therapeutic implications. Cancer Discov. 2021;11(3):575–90. https://doi.org/10.1158/2159-8290.CD-20-1474.

5. Norden AD, Wen PY. Glioma therapy in adults. Neurologist. 2006;12(6):279–92. https://doi.org/10.1097/01.nrl.0000250928.26044.47.

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