A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma

SIMPLE SUMMARY: Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques,...

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Detalles Bibliográficos
Autores principales: Kebir, Sied, Schmidt, Teresa, Weber, Matthias, Lazaridis, Lazaros, Galldiks, Norbert, Langen, Karl-Josef, Kleinschnitz, Christoph, Hattingen, Elke, Herrlinger, Ulrich, Lohmann, Philipp, Glas, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690380/
https://www.ncbi.nlm.nih.gov/pubmed/33105661
http://dx.doi.org/10.3390/cancers12113080

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690380/
https://www.ncbi.nlm.nih.gov/pubmed/33105661
http://dx.doi.org/10.3390/cancers12113080

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