Radiomic profiling of orthotopic mouse models of glioblastoma reveals histopathological correlations associated with tumour response to ionising radiation
File(s)
Published version
Author(s)
Baxan, Nicoleta
Perryman, Richard
Chatziathanasiadou, M
Syed, Nelofer
Type
Journal Article
Abstract
Background: Glioblastoma (GB) is a particularly malignant brain tumour which carries a poor prognosis and presents limited treatment options. MRI is standard practice for differential diagnosis at initial presentation of GB and can assist in both treatment planning and response assessment. MRI radiomics allows for discerning GB features of clinical importance that are not evident by visual analysis, augmenting the morphological and functional tumour characterisation beyond traditional imaging techniques. Given that radiotherapy is part of the standard of care for GB patients, establishing a platform for phenotyping radiation treatment responses using non-invasive methods is of high relevance. Methods: In this study, we modelled the responses to ionising radiation across four orthotopic mouse models of GB using diffusion and perfusion radiomics. We have identified the optimal set of radiomic features that reflect tumour cellularity, microvascularity, and blood flow changes brought about by radiation treatment in these murine orthotopic models of GB, and directly compared them with endpoint histopathological analysis. Results: We showed that the selected radiomic features can quantify textural information and pixel interrelationships of tumour response to radiation therapy, revealing subtle image patterns that may reflect intra-tumoural spatial heterogeneity. When compared to GB patients, similarities in selected radiomic features were noted between orthotopic murine tumours and non-enhancing central tumour areas in patients, along with several discrepancies in tumour cellularity and vascularization, denoted by distinct grey level intensities and nonuniformity metrics. Conclusion: As the field evolves, radiomic profiling of GB may enhance the evaluation of targeted therapeutic strategies, accelerate the development of new therapies, and act as a potential virtual biopsy tool.
Date Issued
2025-04-02
Date Acceptance
2025-04-04
Citation
Cancers, 2025, 17 (8)
ISSN
2072-6694
Publisher
MDPI AG
Journal / Book Title
Cancers
Volume
17
Issue
8
Copyright Statement
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).
License URL
Identifier
10.3390/cancers17081258
Subjects
Baxan, N.
Perryman, R.
Chatziathanasiadou, M.V.
Syed, N glioblastoma
radiomics
histopathology
MRI
Publication Status
Published
Article Number
1258
Date Publish Online
2025-04-08