LibreGrowth: A tumor growth code based on reaction–diffusion equations using shared memory

Published: 24 May 2019| Version 1 | DOI: 10.17632/zp2my52xpv.1


In recent years, in-silico experimentation within the field of oncological medicine has been intensively investigated with the aim of better understanding tumor dynamics and dose–response relationships in cancer treatments. In a series of previous works, Luján et al. (2018, 2017, 2016)we described the micro-environmental influence on micro-tumor infiltration patterns through in-silico/in-vitro experimentation. Here we present the latest version of the software utilized for, but not limited to, those studies: LibreGrowth, a libre tumor growth code able to simulate the core growth and peripheral tumor cell infiltration, considering a benign and a malignant stages. We implemented a reaction–diffusion based model, with spatially variable diffusion coefficient, into a three-dimensional domain, using C++ and OpenMP over a GNU/Linux system. LibreGrowth aims to provide a flexible implementation for depicting heterogeneous tissues and infiltration processes, and to shed light in current therapy optimization strategies.



Computational Physics, Shared Memory, Tumor Growth