Uncertainty evaluation of image-based tumour control probability models in radiotherapy of prostate cancer using a visual analytic tool
Oscar Casares-Magaz (Aarhus University)
R.G. Raidou (Technische Universität Wien)
J. Rørvik (University of Bergen, Haukeland University Hospital)
A. Vilanova Bartroli (TU Delft - Computer Graphics and Visualisation)
Ludvig P. Muren (Aarhus University)
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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.
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