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European Journal of Nuclear Medicine and Molecular Imaging

Erschienen in:

13.11.2023 | Editorial

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

verfasst von: Leandra Piscopo, Emilia Zampella, Michele Klain

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 3/2024

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Gliomas are the most frequent malignant tumors of the central nervous system (CNS), with an incidence of six cases per 100,000 people every year [1]. Generally, the low-grade gliomas are more frequent in younger patients, while high-grade malignant lesions may occur later [1‐3]. The gold standard of treatment in patients with gliomas consists of surgical resection followed by stereotactic radiotherapy [1‐4]. However, recent advances in genetic engineering led to the identification of transduction pathways implicated in tumor proliferation and differentiation [1‐4]. Therefore, targeted molecular therapies have been introduced as promising therapeutic options in patients with glioma [5, 6]. According to WHO classification, both histology and immunohistochemistry are well-established approaches to tumor characterization [1]. However, the 2021 WHO classification introduced several changes in the classification of CNS tumors, focusing on the role of molecular diagnostics [1]. …

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Titel: [18F]FET PET/MR and machine learning in the evaluation of glioma
verfasst von: Leandra Piscopo
Emilia Zampella
Michele Klain
Publikationsdatum: 13.11.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 3/2024
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-023-06505-9

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