MRI-Based Radiomics Combined with Deep Learning for Distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas

MRI-Based Radiomics Combined with Deep Learning for Distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas

This study aimed to investigate the potential of quantitative radiomic data extracted from conventional MR images in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type glioblastomas (GBMs). A cohort of 57 treatment-naïve patients with IDH-mutant grade 4 astrocytomas (<i>n</i&...

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Bibliographic Details
Main Authors: Seyyed Ali Hosseini, Elahe Hosseini, Ghasem Hajianfar, Isaac Shiri, Stijn Servaes, Pedro Rosa-Neto, Laiz Godoy, MacLean P. Nasrallah, Donald M. O’Rourke, Suyash Mohan, Sanjeev Chawla
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Cancers
Subjects:
grade 4 astrocytoma
glioblastoma
isocitrate dehydrogenase mutation
conventional magnetic resonance imaging
radiomics
machine learning
Online Access:https://www.mdpi.com/2072-6694/15/3/951

Internet

https://www.mdpi.com/2072-6694/15/3/951

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