Radiomic Profiling of Orthotopic Mouse Models of Glioblastoma Reveals Histopathological Correlations Associated with Tumour Response to Ionising Radiation.
Simple Summary: Glioblastoma (GB) is an aggressive form of brain cancer that is usually rapidly fatal. MRI plays an important role in the evaluation of GB, both at initial diagnosis and follow up after radiotherapy. Radiomics is an advanced technique that uses computer algorithms to extract and anal...
| Publicado en: | Cancers Vol. 17; no. 8; pp. 1258 - 1280 |
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| Autores principales: | , , , |
| Formato: | diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
MDPI
Apr2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=184758884&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 184758884 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 20726694 B74B jtl: Cancers issn: 20726694 maglogo: N pubinfo: dt: Apr2025 vid: 17 iid: 8 pid: 97109 pub: MDPI artinfo: ui: 184758884 184758884 184758884 10.3390/cancers17081258 184758884 ppf: 1258 ppct: 22 formats: tig: atl: Radiomic Profiling of Orthotopic Mouse Models of Glioblastoma Reveals Histopathological Correlations Associated with Tumour Response to Ionising Radiation. aug: au: Baxan, Nicoleta Perryman, Richard Chatziathanasiadou, Maria V. Syed, Nelofer affil: John Fulcher Neuro-Oncology Laboratory, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK sug: subj: Glioma Physiopathology Glioma Radiography Glioma Pathology Radiomics Histological Techniques Tumor Markers, Biological Analysis Animal Studies Mice Magnetic Resonance Imaging Methods Algorithms Radiation, Ionizing Blood Capillary Permeability Funding Source ab: Simple Summary: Glioblastoma (GB) is an aggressive form of brain cancer that is usually rapidly fatal. MRI plays an important role in the evaluation of GB, both at initial diagnosis and follow up after radiotherapy. Radiomics is an advanced technique that uses computer algorithms to extract and analyse a wealth of detailed information from radiological scans, going beyond what the human eye can perceive. Radiomic profiling of GB using MRI can yield characteristics related to the tumour's morphological and functional responses post treatment, turning standard medical images into a rich source of quantitative data. In this study, we propose a radiomic framework based on MRI diffusion and perfusion metrics to model responses to ionising radiation across several orthotopic mouse models of GB. Our findings provided valuable and translatable insights into radiation treatment responses and evaluated the suitability of orthotopic mouse models of GB as representatives of human GB. This may improve the pre-clinical evaluation of targeted therapeutic strategies, accelerate the development of new treatments, and serve as a potential non-invasive biopsy alternative. 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. pubtype: Academic Journal doctype: diagnostic images pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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