Multiscale computational modeling of cancer growth using features derived from microCT images.

ABSTRACT: Advances in medical imaging technologies now allow noninvasive image acquisition from individual patients at high spatiotemporal resolutions. A relatively new effort of predictive oncology is to develop a paradigm for forecasting the future status of an individual tumor given initial conditions and an appropriate mathematical model. The objective of this study was to introduce a comprehensive multiscale computational method to predict cancer and microvascular network growth patterns. A rectangular lattice-based model was designed so different evolutionary scenarios could be simulated and for predicting the impact of diffusible factors on tumor morphology and size. Further, the model allows prediction-based simulation of cell and microvascular behavior. Like a single cell, each agent is ful

SUBMITTER: Zangooei MH 

PROVIDER: S-EPMC8448838 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature