A major source of complexity in the mathematical modelling of an angiogenic process derives from the strong coupling of the kinetic parameters of the relevant stochastic branching-and-growth of the capillary network with a family of interacting underlying fields. The aim of this paper is to propose a novel mathematical approach for reducing complexity by (locally) averaging the stochastic cell, or vessel densities in the evolution equations of the underlying fields, at the mesoscale, while keeping stochasticity at lower scales, possibly at the level of individual cells or vessels. This method leads to models which are known as hybrid models. In this paper, as a working example, we apply our method to a simplified stochastic geometric model, inspired by the relevant literature, for a spatially distributed angiogenic process. The branching mechanism of blood vessels is modelled as a stochastic marked counting process describing the branching of new tips, while the network of vessels is modelled as the union of the trajectories developed by tips, according to a system of stochastic differential equations `a la Langevin.

Stochastic modelling of tumour-induced angiogenesis / V. Capasso, D. Morale. - In: JOURNAL OF MATHEMATICAL BIOLOGY. - ISSN 0303-6812. - 58:1-2(2009), pp. 219-233. [10.1007/s00285-008-0193-z]

Stochastic modelling of tumour-induced angiogenesis

V. Capasso
Primo
;
D. Morale
Ultimo
2009

Abstract

A major source of complexity in the mathematical modelling of an angiogenic process derives from the strong coupling of the kinetic parameters of the relevant stochastic branching-and-growth of the capillary network with a family of interacting underlying fields. The aim of this paper is to propose a novel mathematical approach for reducing complexity by (locally) averaging the stochastic cell, or vessel densities in the evolution equations of the underlying fields, at the mesoscale, while keeping stochasticity at lower scales, possibly at the level of individual cells or vessels. This method leads to models which are known as hybrid models. In this paper, as a working example, we apply our method to a simplified stochastic geometric model, inspired by the relevant literature, for a spatially distributed angiogenic process. The branching mechanism of blood vessels is modelled as a stochastic marked counting process describing the branching of new tips, while the network of vessels is modelled as the union of the trajectories developed by tips, according to a system of stochastic differential equations `a la Langevin.
Angiogenesis; Birth and growth processes; Hybrid models; Stochastic differential equations
Settore MAT/06 - Probabilita' e Statistica Matematica
2009
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/40190
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