1 Department of Computer Science and Engineering, College of Engineering, Qatar University, Qatar.
2 Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Üsküdar University, Türkiye.
International Journal of Science and Research Archive, 2025, 16(02), 663-667
Article DOI: 10.30574/ijsra.2025.16.2.2375
Received on 05 July 2025; revised on 10 August; accepted on 13 August 2025
Accurate simulation of brain tumor growth is essential for predicting patient prognosis and evaluating treatment efficacy. The Tumor Growth Simulation Utility (TG-SU), based on the Reaction Diffusion Equation (RDE) and Finite Element (FE) method, provides a spatio-temporal framework to simulate glioma progression using segmented brain images. However, the choice of simulation time-step (dt) significantly impacts the accuracy and computational cost of the simulation. This study investigates the effect of varying time-step values on simulation error and computational rounds. Results show that while smaller time-steps improve accuracy, they increase simulation time. An equation is proposed to determine the optimal time-step for a given maximum acceptable error. This balance between speed and precision is crucial for practical neuro-oncology applications.
Brain tumor simulation; Glioma; Tumor growth modeling; Reaction Diffusion Equation; TG–SU
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Ihab ELAFF. Optimal time-step selection for accurate simulation results in the tumor growth simulation utility (TG-SU). International Journal of Science and Research Archive, 2025, 16(02), 663-667. Article DOI: https://doi.org/10.30574/ijsra.2025.16.2.2375.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
