Modelling glioma progression, mass effect and intracranial pressure in patient anatomy.

brain deformation glioma intracranial pressure patient-specific modelling tumour mass effect

Journal

Journal of the Royal Society, Interface
ISSN: 1742-5662
Titre abrégé: J R Soc Interface
Pays: England
ID NLM: 101217269

Informations de publication

Date de publication:
03 2022
Historique:
entrez: 23 3 2022
pubmed: 24 3 2022
medline: 31 3 2022
Statut: ppublish

Résumé

Increased intracranial pressure is the source of most critical symptoms in patients with glioma, and often the main cause of death. Clinical interventions could benefit from non-invasive estimates of the pressure distribution in the patient's parenchyma provided by computational models. However, existing glioma models do not simulate the pressure distribution and they rely on a large number of model parameters, which complicates their calibration from available patient data. Here we present a novel model for glioma growth, pressure distribution and corresponding brain deformation. The distinct feature of our approach is that the pressure is directly derived from tumour dynamics and patient-specific anatomy, providing non-invasive insights into the patient's state. The model predictions allow estimation of critical conditions such as intracranial hypertension, brain midline shift or neurological and cognitive impairments. A diffuse-domain formalism is employed to allow for efficient numerical implementation of the model in the patient-specific brain anatomy. The model is tested on synthetic and clinical cases. To facilitate clinical deployment, a high-performance computing implementation of the model has been publicly released.

Identifiants

pubmed: 35317645
doi: 10.1098/rsif.2021.0922
pmc: PMC8941421
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

20210922

Subventions

Organisme : NCI NIH HHS
ID : P30 CA062203
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA217378
Pays : United States

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Auteurs

Jana Lipková (J)

Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Dana-Farber Cancer Institute, Boston, MA, USA.
Broad Institute of Harvard and MIT, Cambridge, MA, USA.

Bjoern Menze (B)

Department of Informatics, Technical University of Munich, Munich, Germany.
Department of Quantitative Biomedicine, University of Zürich, Zürich, Switzerland.
Department of Neuroradiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Benedikt Wiestler (B)

Department of Neuroradiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Petros Koumoutsakos (P)

Computational Science and Engineering Lab, ETH Zürich, Zürich, Switzerland.
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.

John S Lowengrub (JS)

Department of Mathematics, University of California, Irvine, CA, USA.
Department of Biomedical Engineering, University of California, Irvine, CA, USA.
Center for Complex Biological Systems, Chao Family Comprehensive Cancer Center, University of California, Irvine, CA, USA.

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