Uncertainty evaluation of image-based tumour control probability models in radiotherapy of prostate cancer using a visual analytic tool

Journal article (2018)

Authors

O. Casares-Magaz Aarhus University
R.G. Raidou Technische Universität Wien
Jarle Rørvik Haukeland University Hospital, University of Bergen
A. Vilanova Bartroli Computer Graphics and Visualisation - EEMCS
L.P. Muren Aarhus University
Research Group
Computer Graphics and Visualisation (EEMCS) (TU Delft)
Copyright: © 2018 Oscar Casares-Magaz, R.G. Raidou, Jarle Rørvik, A. Vilanova Bartroli, Ludvig P. Muren
DOI: https://doi.org/10.1016/j.phro.2017.12.003
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Published Date

2018

Language

English

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Computer Graphics and Visualisation

Abstract

Functional imaging techniques provide radiobiological information that can be included into tumour control probability (TCP) models to enable individualized outcome predictions in radiotherapy. However, functional imaging and the derived radiobiological information are influenced by uncertainties, translating into variations in individual TCP predictions. In this study we applied a previously developed analytical tool to quantify dose and TCP uncertainty bands when initial cell density is estimated from MRI-based apparent diffusion coefficient maps of eleven patients. TCP uncertainty bands of 16% were observed at patient level, while dose variations bands up to 8 Gy were found at voxel level for an iso-TCP approach.