Evaluation of Classical Mathematical Models of Tumor Growth Using an On-Lattice Agent-Based Monte Carlo Model

Purpose: To analyze the capabilities of different classical mathematical models to describe growth multicellular spheroids simulated with an on-lattice agent-based Monte Carlo model that has already been validated. Methods: The exponential, Gompertz, logistic, potential, and Bertalanffy have fitted in situations volume data generated a simulates spheroid growth. Two samples pseudo-data, obtained by assuming variability simulation parameters, were considered. whole curves also parts them, thus permitting predictive power (both prospective retrospective) models. Results: consideration larger parameters increases width χ2 distributions fits. Gompertz provided best fits curves, yielding average value per degree freedom 3.2, order magnitude smaller than those found for other gave similar retrospective prediction capability. In what refers power, showed far performance. Conclusions: analyzed show poor reproduce MTS not used fit them. Within these results, proves be one better describes simulated. tumors or permits follow-up periods longer usual experimental studies much number samples: this permitted performing type analysis presented here.