Stochastic models for tumoral growth
Carlos Escudero
Abstract
Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border, and surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stochastic partial differential equations are introduced in this work in order to correctly model the physical properties of tumoral growth in (1+1) and (2+1) dimensions. The advantages of these models is that they reproduce the correct geometry of the tumor and are defined in terms of polar variables. Analysis of these models allow us to quantitatively estimate the response of the tumor to an unfavorable perturbation during the growth.
Create a lesson
Related papers
Surf2Volume: a workflow for converting CIFTI parcellations to NIfTI volume space
Shuguang Yang, Ziyi Wang, Yujing Shen et al.
DINIRS: Digital Twin for Individualized Treatment Effects of Non-Invasive Respiratory Support Strategies
Md Fantacher Islam, Jarrod Mosier, Vignesh Subbian
RegimeFormer: A Large Protein Model of Global Perturbation Regimes
Siyuan Ma, Yi Chai, Yi Wu et al.
Interpreting Latent Protein Language Model Features with Geometric Annotations
Siddharth Setlur, Djordje Mihajlovic, Darrick Lee
PathoMIC: A Benchmark for Cross-Species Antimicrobial Peptide Activity Prediction
Yeqing Lu, Xiaoyan Zhao, Fuli Feng
Multimodal risk trajectories reveal heterogeneous paths to dementia
Zhiqi Lee, Haowen Li, Tao Liu et al.