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

Oscar Casares-Magaz, Renata G. Raidou, Jarle Rørvik, Anna Vilanova , Ludvig P. Muren

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
18 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)5-8
Number of pages4
JournalPhysics and Imaging in Radiation Oncology
Volume5
DOIs
Publication statusPublished - 2018

Keywords

  • Tumour control probability
  • Visualization tool
  • Uncertainties
  • Apparent diffusion coefficient (ADC) maps
  • Prostate cancer

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