Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation

The purpose of this study was to establish a high-performing radiomics strategy with machine learning from conventional and diffusion MRI to differentiate recurrent glioblastoma (GBM) from radiation necrosis (RN) after concurrent chemoradiotherapy (CCRT) or radiotherapy. Eighty-six patients with GBM...

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Detalles Bibliográficos
Autores principales: Park, Yae Won, Choi, Dongmin, Park, Ji Eun, Ahn, Sung Soo, Kim, Hwiyoung, Chang, Jong Hee, Kim, Se Hoon, Kim, Ho Sung, Lee, Seung-Koo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858615/
https://www.ncbi.nlm.nih.gov/pubmed/33536499
http://dx.doi.org/10.1038/s41598-021-82467-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858615/
https://www.ncbi.nlm.nih.gov/pubmed/33536499
http://dx.doi.org/10.1038/s41598-021-82467-y

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