Abstract
Modelling of tumour control probability (TCP) and normal tissue complication probability (NTCP) has been continuously used to estimate the therapeutic window of radiotherapy. In recent years, available data on tumour and normal tissue biology and from multimodal imaging have increased substantially, in particular, due to image-guided radiotherapy (see previous chapters of this book) and novel high-throughput sequencing technologies. Accordingly, more complex modelling algorithms are applied and issues of data quality, structured modelling procedures, and model validation need to be addressed. This chapter outlines general modelling principles in the era of big data, provides definitions of classical TCP and NTCP models, and presents two applications of outcome modelling in radiotherapy: the model-based approach for assigning patients to photon or proton-beam therapy and radiomics analyses based on clinical imaging data.
Original language | English |
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Title of host publication | Image-Guided High-Precision Radiotherapy |
Publisher | Springer International Publishing AG |
Chapter | 13 |
Pages | 285-314 |
Number of pages | 30 |
ISBN (Electronic) | 9783031086014 |
ISBN (Print) | 9783031086007 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- Model development and validation
- Model-based approach
- NTCP models
- Outcome prediction
- Radiomics
- TCP models