Towards Model-Based Characterization of Biomechanical Tumor Growth Phenotypes

Abler, Daniel; Büchler, Philippe; Rockne, Russell C. (2019). Towards Model-Based Characterization of Biomechanical Tumor Growth Phenotypes. In: International Symposium on Mathematical and Computational Oncology. Lecture Notes in Computer Science: Vol. 11826 (pp. 75-86). Cham: Springer International Publishing 10.1007/978-3-030-35210-3_6

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Gliomas are the most common malignant brain tumors in adults, with Glioblastoma (GBM) being the most agressive subtype. GBM is clinically evaluated with magnetic resonance imaging (MRI) and presents with different growth phenotypes, involving varying degrees of healthy tissue invasion and tumor induced herniation, also known as mass effect. GBM growth in the brain is frequently modeled as a reaction-diffusion process in which varying ratios of diffusion and proliferation coefficients mimic the observed spectrum of growth phenotypes ranging from nodal to diffuse. However, reaction-diffusion models alone are insufficient to explain tumor-induced mass effect on normal peripheral tissues, which is a critical clinical issue.

We propose an analysis method and framework for estimating GBM growth properties (proliferation, invasiveness, displacive potential) from MRI data routinely collected in the clinical management of GBM. This framework accounts for the mass-effect of the growing tumor by assuming a coupling between local tumor-cell density and volumetric expansion of the tissue.

We evaluate the reconstruction workflow on synthetic data that represents a range of realistic growth situations and levels of uncertainty. For most parameter combinations (90%) that correspond to tumors detectable by T1-weighted MRI, target parameters are recovered with a relative error of less than 15%.

Item Type:

Book Section (Book Chapter)


10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Musculoskeletal Biomechanics
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]

UniBE Contributor:

Abler, Daniel, Büchler, Philippe


500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
500 Science > 510 Mathematics
600 Technology > 620 Engineering




Lecture Notes in Computer Science


Springer International Publishing


[124] H2020-MSCA-IF-2016 Project ID 753878




Daniel Jakob Silvester Abler

Date Deposited:

17 Dec 2019 15:17

Last Modified:

05 Dec 2022 15:32

Publisher DOI:





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