Abstract
In this paper, models are described which have been developed to model both the way in which a population of cells respond to radiation and the way in which a population of patients respond to radiotherapy to assist the conduct of clinical trials in silico. Population balance techniques have been used to simulate the age distribution of tumour cells in the cell cycle. Sensitivity to radiation is not constant round the cell cycle and a single fraction of radiation changes the age distribution. Careful timing of further fractions of radiation can be used to maximize the damage delivered to the tumour while minimizing damage to normal tissue. However, tumour modelling does not necessarily predict patient outcome. A separate model has been established to predict the course of a brain cancer called glioblastoma multiforme (GBM). The model considers the growth of the tumour and its effect on the normal brain. A simple representation is included of the health status of the patient and hence the type of treatment offered. It is concluded that although these and similar models have a long way yet to be developed, they are beginning to have an impact on the development of clinical practice.
Original language | English |
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Pages (from-to) | 13-17 |
Number of pages | 5 |
Journal | Nuclear Instruments & Methods in Physics Research. Section B: Beam Interactions with Materials and Atoms |
Volume | 255 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2007 |
Keywords
- Mathematical modelling
- Brain cancer
- Radiotherapy
- Glioblastoma
- Patient survival
- Tumour growth
Research Beacons, Institutes and Platforms
- Manchester Cancer Research Centre