Gibbs point field model quantifies disorder in microvasculature of U87-glioblastoma. (7th June 2020)

• Record Type: Journal Article
• Authors: Hahn, Artur; Bode, Julia; Krüwel, Thomas; Kampf, Thomas; Buschle, Lukas R.; Sturm, Volker J.F.; Zhang, Ke; Tews, Björn; Schlemmer, Heinz-Peter; Heiland, Sabine; Bendszus, Martin; Ziener, Christian H.; Breckwoldt, Michael O.; Kurz, Felix T.
• Is Part Of: Journal of theoretical biology. Volume 494(2020)
• Publication Date: 2020-06-07
• Subjects: Cerebral vasculature -- Glioblastoma -- Entropy -- SPIM; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2020.110230
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: Glioblastoma decreases the regularity of microvascular architecture in brain tissue. Statistical physics model can quantify disorder of capillaries with single variable. The order parameter of the One Component Plasma model can characterize vasculature. The order parameter can be linked to relaxation rates in magnetic resonance imaging. Non-invasive vessel disorder estimates on MRI-voxels has been shown to be feasible. Graphical abstract: Abstract: Microvascular proliferation in glioblastoma multiforme is a biological key mechanism to facilitate tumor growth and infiltration and a main target for treatment interventions. The vascular architecture can be obtained by Single Plane Illumination Microscopy (SPIM) to evaluate vascular heterogeneity in tumorous tissue. We make use of the Gibbs point field model to quantify the order of regularity in capillary distributions found in the U87 glioblastoma model in a murine model and to compare tumorous and healthy brain tissue. A single model parameter Γ was assigned that is linked to tissue-specific vascular topology through Monte-Carlo simulations. Distributions of the model parameter Γ differ significantly between glioblastoma tissue with mean 〈 Γ G 〉 = 2.1 ± 0.4, as compared to healthy brain tissue with mean 〈 Γ H 〉 = 4.9 ± 0.4, suggesting that the average Γ-value allows for tissue differentiation. These results may be used for diagnostic magnetic resonance imaging, where it has been shown recently that Γ is linked to tissue-inherent relaxation parameters.