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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Neuro-Oncology and Neurosurgical Oncology
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1447010

Post-operative glioblastoma cancer cell distribution in the peritumoural oedema

Provisionally accepted
Andrei C. Macarie Andrei C. Macarie 1Szabolcs B. Suveges Szabolcs B. Suveges 2Mohamed Okasha Mohamed Okasha 3Kismet Hossain-Ibrahim Kismet Hossain-Ibrahim 3J D. Steele J D. Steele 2Dumitru Trucu Dumitru Trucu 4*
  • 1 Mathematics & Medicine, University of Dundee, Dundee, United Kingdom
  • 2 School of Medicine, University of Dundee, Dundee, Scotland, United Kingdom
  • 3 NHS Tayside, Dundee, Scotland, United Kingdom
  • 4 Mathematics, University of Dundee, Dundee, United Kingdom

The final, formatted version of the article will be published soon.

    Glioblastoma multiforme (GBM), the most aggressive primary brain tumour, exhibits low survival rates due to its rapid growth, infiltrates surrounding brain tissue, and is highly resistant to treatment.One major challenge is oedema infiltration, a fluid build-up that provides a path for cancer cells to invade other areas. MRI resolution is insufficient to detect these infiltrating cells, leading to relapses despite chemotherapy and radiotherapy. In this work, we propose a new multiscale mathematical modelling method, to explore the oedema infiltration and predict tumour relapses.To address tumour relapses, we investigated several possible scenarios for the distribution of remaining GBM cells within the oedema after surgery. Furthermore, in this computational modelling investigation on tumour relapse scenarios were investigated assuming the presence of clinically relevant chemo-radio therapy, numerical results suggest that a higher concentration of GBM cells near the surgical cavity edge led to limited spread and slower progression of tumour relapse. Finally, we explore mathematical and computational avenues for reconstructing relevant shapes for the initial distributions of GBM cells within the oedema from available MRI scans. The results obtained show good overlap between our simulation and the patient's serial MRI scans taken 881 days into the treatment. While still under analytical investigation, this work paves the way for robust reconstruction of tumour relapses from available clinical data.

    Keywords: Multiscale modelling, cancer invasion, Glioblastoma, chemotherapy, Radiotherapy, Surgery, 3D computational modelling, MRI scans

    Received: 10 Jun 2024; Accepted: 20 Sep 2024.

    Copyright: © 2024 Macarie, Suveges, Okasha, Hossain-Ibrahim, Steele and Trucu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Dumitru Trucu, Mathematics, University of Dundee, Dundee, United Kingdom

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