Calibration of Multi-Parameter Models of Avascular Tumor Growth Using Time Resolved Microscopy Data.

ABSTRACT: Two of the central challenges of using mathematical models for predicting the spatiotemporal development of tumors is the lack of appropriate data to calibrate the parameters of the model, and quantitative characterization of the uncertainties in both the experimental data and the modeling process itself. We present a sequence of experiments, with increasing complexity, designed to systematically calibrate the rates of apoptosis, proliferation, and necrosis, as well as mobility, within a phase-field tumor growth model. The in vitro experiments characterize the proliferation and death of human liver carcinoma cells under different initial cell concentrations, nutrient availabilities, and treatment conditions. A Bayesian framework is employed to quantify the uncertainties in model parameters

SUBMITTER: Lima EABF 

PROVIDER: S-EPMC6162291 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature