Anomalous Advection-Diffusion Models for Avascular Tumour Growth

TL;DR

This paper introduces two novel fractional advection-diffusion models for avascular tumour growth, providing a more realistic macroscopic understanding of tumour dynamics and their interaction with the microenvironment.

Contribution

The study develops fixed and variable order fractional advection-diffusion models for tumour growth, advancing biological modeling with more accurate and flexible representations.

Findings

Both models offer realistic insights into tumour growth.

The fixed-order model overestimates tumour size compared to clinical data.

The variable-order model shows moderate sensitivity to parameters.

Abstract

In this study, we model avascular tumour growth in epithelial tissue. This can help us to get a macroscopic view of the interaction between the tumour with its surrounding microenvironment and the physical changes within the tumour spheroid. This understanding is likely to assist in the development of better diagnostics, improved therapies and prognostics. In biological systems, most of the diffusive and convective processes are through cellular membranes which are porous in nature. Due to its porous nature, diffusive processes in biological systems are heterogeneous. Fractional advection-diffusion equations are well suited to model heterogeneous biological systems; though most of the early studies did not use this fact. They modelled tumour growth with simple advection-diffusion equation or diffusion equation. We have developed two spherical models based on fractional advection-diffusion equations: one of fixed order and the other of variable order for avascular tumour. These two models are investigated from phenomenological view by measuring some parameters for characterizing avascular tumour growth over time. It is found that both the models offer realistic and insightful information for tumour growth at the macroscopic level, and approximate well the physical phenomena. The fixed-order model always overestimates clinical data like tumour radius, and tumour volume. The cell counts in both the models lie in the clinically established range. As the simulation parameters get modified due to different biochemical and biophysical processes, the robustness of the model is determined. It is found that, the sensitivity of the fixed-order model is low while the variable-order model is moderately sensitive to the parameters.