Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI

Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI

The globally accepted surgical strategy in glioblastomas is removing the enhancing tumor. However, the peritumoral region harbors infiltration areas responsible for future tumor recurrence. This study aimed to evaluate a predictive model that identifies areas of future recurrence using a voxel-based...

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Bibliographic Details
Main Authors: Santiago Cepeda, Luigi Tommaso Luppino, Angel Pérez-Núñez, Ole Solheim, Sergio García-García, María Velasco-Casares, Anna Karlberg, Live Eikenes, Rosario Sarabia, Ignacio Arrese, Tomás Zamora, Pedro Gonzalez, Luis Jiménez-Roldán, Samuel Kuttner
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Cancers
Subjects:
glioblastoma
artificial intelligence
MRI
recurrence
radiomics
machine learning
Online Access:https://www.mdpi.com/2072-6694/15/6/1894

Internet

https://www.mdpi.com/2072-6694/15/6/1894

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