MAGNETIC RESONANCE IMAGING ASSESSMENT OF TUMOUR MICROSTRUCTURE IN GLIOBLASTOMA: A CROSS-SECTIONAL STUDY (THE MIMOSA STUDY)
Abstract AIMS Key to improving understanding of Glioblastoma Multiforme (GBM) tumour growth and treatment response, and in developing new treatments, lies in improving understanding of tumour interaction with host cells in the tumour micro-environment (TME). To do this we will utilise the Cardiff University Brain Research Imaging Centre’s (CUBRIC’s) capacity for advanced diffusion-weighted magnetic resonance imaging (DW-MRI) by using the CONNECTOM microstructure MRI scanner. This scanner comprises the UK National Microstructure Imaging Facility and is one of only 4 such systems in the world. This system will allow a novel approach to characterising tissue microstructure and the TME in patients with GBM. METHODS From March 2025, with IRAS approval, we will recruit 40 patients with newly diagnosed GBM through the South Wales neuro-oncology service. We will record demographic, clinicopathological and molecular genetic information and perform DW-MRI scans using the 3T microstructure scanner in patients prior to their surgical procedure and at 3 and 6 months. After surgery, patients will receive radiotherapy treatment with concurrent and adjuvant Temozolomide. RESULTS For DW-MRI analysis we will apply models to obtain estimates of the intracellular signal fraction, cell radius, extracellular and extravascular signal fraction, extracellular diffusivities and vascular signal fraction and apply radiomic textural feature analysis. We will also correlate imaging findings with clinicopathological information. CONCLUSION We aim to demonstrate feasibility of performing microstructure MRI scans at CUBRIC in patients with GBM and provide non-invasive, quantitative DW-MRI measures of both the composition (such as different cell types, extracellular matrix and vasculature) and microstructure (such as cell size, density and morphology) of the TME in patients with GBM. We propose that conducting these measures and demonstrating how these may evolve in a temporal fashion following treatment will provide novel characterisation of the TME and provide mechanistic insight to enable improved assessment and prediction of treatment response in patients with GBM.
Authors
- Florian A. Siebzehnrübl (ORCID: https://orcid.org/0000-0001-8411-8775)
- Leandro Beltrachini (ORCID: https://orcid.org/0000-0003-4602-1416)
- Harpreet Hyare (ORCID: https://orcid.org/0000-0002-4672-3349)
- Derek Kenton Jones (ORCID: https://orcid.org/0000-0003-4409-8049)
- Najmus Sahar Iqbal
- Elisenda Bonet-Carné (ORCID: https://orcid.org/0000-0003-0567-6141)
- Emiliano Spezi (ORCID: https://orcid.org/0000-0002-1452-8813)
- Hannah Khirwadkar
- Daniel C. Alexander (ORCID: https://orcid.org/0000-0003-2439-350X)
- Georgy Joy Eralil (ORCID: https://orcid.org/0000-0001-6261-7979)
- Marco Palombo (ORCID: https://orcid.org/0000-0003-4892-7967)
- J. Powell (ORCID: https://orcid.org/0000-0002-9247-7302)
- Laura Panagiotaki
- Jenny Golten
- Kathy Seddon
Institutions
- Swansea Bay University Health Board (GB)
- Cardiff and Vale University Health Board (GB)
- Hospital Sant Joan de Déu Barcelona (ES)
- University College London Hospitals NHS Foundation Trust (GB)
- Velindre NHS Trust (GB)
- Morriston Hospital (GB)
- Cancer Care Northwest (US)
- Laboratoire d’Imagerie Biomédicale (FR)
- Stem Cell Institute (PA)
- National Hospital for Neurology and Neurosurgery (GB)
- University College London (GB)
- Cardiff University (GB)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Neuro-Oncology
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1093/neuonc/noaf185.045
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00