Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging

Abstract Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to esti...

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Autores principales:	Hamed Akbari, Anahita Fathi Kazerooni, Jeffrey B. Ware, Elizabeth Mamourian, Hannah Anderson, Samantha Guiry, Chiharu Sako, Catalina Raymond, Jingwen Yao, Steven Brem, Donald M. O’Rourke, Arati S. Desai, Stephen J. Bagley, Benjamin M. Ellingson, Christos Davatzikos, Ali Nabavizadeh
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f3997d4247b045488e4da9cb506d56e2
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Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging

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