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    Visualising spatial heterogeneity in glioblastoma using imaging habitats

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    Authors
    Waqar, M.
    Van Houdt, P. J.
    Hessen, E.
    Li, K. L.
    Zhu, X.
    Jackson, A.
    Iqbal, M.
    O'Connor, James P B
    Djoukhadar, I.
    van der Heide, U. A.
    Coope, D. J.
    Borst, Gerben R
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    Affiliation
    Department of Neurosurgery, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester
    Issue Date
    2022
    
    Metadata
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    Abstract
    Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.
    Citation
    Waqar M, Van Houdt PJ, Hessen E, Li KL, Zhu X, Jackson A, et al. Visualising spatial heterogeneity in glioblastoma using imaging habitats. Frontiers in oncology. 2022;12:1037896. PubMed PMID: 36505856. Pubmed Central PMCID: PMC9731157. Epub 2022/12/13. eng.
    Journal
    Frontiers in Oncology
    URI
    http://hdl.handle.net/10541/625893
    DOI
    10.3389/fonc.2022.1037896
    PubMed ID
    36505856
    Additional Links
    https://dx.doi.org/10.3389/fonc.2022.1037896
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.3389/fonc.2022.1037896
    Scopus Count
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