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

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, t...

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Bibliographic Details
Main Authors: Oscar Casares-Magaz, Renata G. Raidou, Jarle Rørvik, Anna Vilanova, Ludvig P. Muren
Format: Article
Language:English
Published: Elsevier 2018-01-01
Series:Physics and Imaging in Radiation Oncology
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631617300581
Description
Summary: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. Keywords: Tumour control probability, Visualization tool, Uncertainties, Apparent diffusion coefficient (ADC) maps, Prostate cancer
ISSN:2405-6316