Magnetic resonance imaging features differentiate histologic and molecular subtypes of glioblastoma IDH-Wild type CNS WHO grade 4

Date
2026-01-21
Language
American English
Embargo Lift Date
Committee Members
Degree
Degree Year
Department
Grantor
Journal Title
Journal ISSN
Volume Title
Found At
Springer
Can't use the file because of accessibility barriers? Contact us with the title of the item, permanent link, and specifics of your accommodation need.
Abstract

Purpose: Glioblastoma IDH-wild type, CNS WHO grade 4 (GBM) can be diagnosed on the basis of histologic features (histological-GBM) or molecular features (molecular-GBM). Only few studies report neuroimaging features of GBM in its modern classification, and none have controlled for surgical status or used multiple logistic regression analysis to determine unique predictors. Our study aimed to validate MRI features that distinguish histological-GBM and molecular-GBM.

Methods: We analyzed a training cohort (n = 255) and validation cohort (n = 44) of GBM cases, classified according to the 2021 WHO Classification of Tumors of the CNS. For the training cohort, univariate and multiple logistic regression analyses determined if MRI metrics (contrast enhancement, ring-enhancement, vasogenic edema, multifocal tumor, lesion diameter, hemorrhage, number of lobes, and normalized ADC) and surgery type (biopsy vs. resection) predicted GBM-type (histological vs. molecular). A reduced multiple logistic regression model was constructed and applied to the validation dataset.

Results: There were 231 histological-GBMs and 24 molecular-GBMs in the training cohort. Multiple logistic regression analysis including both MRI metrics and surgery type showed that contrast enhancement (OR 7.83 [95%CI: 1.23–49.68], p = 0.029), ring enhancement (OR 5.98 [95%CI: 1.09–32.93, p = 0.040), and normalized ADC (OR 0.78 [95%CI: 0.62–0.99], p = 0.039) differed between histological and molecular-GBM. Analysis of the validation dataset using the unique training dataset-derived predictor variables (contrast-enhancement, ring-enhancement, and normalized ADC) found correct classification of each histological and molecular-GBM.

Conclusion: Molecular and histological-GBM exhibit distinct MRI phenotypes independent of surgical status.

Supplementary Information: The online version contains supplementary material available at 10.1007/s11060-026-05431-8.

Description
item.page.description.tableofcontents
item.page.relation.haspart
Cite As
Patel SH, Mayorov S, Kim W, et al. Magnetic resonance imaging features differentiate histologic and molecular subtypes of glioblastoma IDH-Wild type CNS WHO grade 4. J Neurooncol. 2026;176(3):177. Published 2026 Jan 21. doi:10.1007/s11060-026-05431-8
ISSN
Publisher
Series/Report
Sponsorship
Major
Extent
Identifier
Relation
Journal
Journal of Neuro-Oncology
Source
PMC
Alternative Title
Type
Article
Number
Volume
Conference Dates
Conference Host
Conference Location
Conference Name
Conference Panel
Conference Secretariat Location
Version
Final published version
Full Text Available at
This item is under embargo {{howLong}}