2018/03/22 by Peter G. Hufton, Hufton, Peter G., Elizabeth Buckingham-Jeffery +3
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Physics and Astronomy · #Effects of Radiation Exposure #FOS: Biological sciences #FOS: Physical sciences #Mathematical Biology Tumor Growth #Populations and Evolution (q-bio.PE) #Statistical Mechanics (cond-mat.stat-mech) #Tissues and Organs (q-bio.TO) #cond-mat.stat-mech #q-bio.PE #q-bio.TO
paper · pdf · doi:10.48550/arxiv.1803.08595
27 pages, 5 figures, 4 tables
arxiv created 2018/03/22 · openalex publication_date 2018/03/22 · arxiv updated 2018/03/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We use a stochastic birth-death model for a population of cells to estimate the normal tissue complication probability (NTCP) under a particular radiotherapy protocol. We specifically allow for interaction between cells, via a nonlinear logistic growth model. To capture some of the effects of intrinsic noise in the population we develop several approximations of NTCP, using Kramers-Moyal expansion techniques. These approaches provide an approximation to the first and second moments of a general first-passage time problem in the limit of large, but finite populations. We use this method to study NTCP in a simple model of normal cells and in a model of normal and damaged cells. We also study a combined model of normal tissue cells and tumour cells. Based on existing methods to calculate tumour control probabilities, and our procedure to approximate NTCP, we estimate the probability of complication free tumour control.