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Proceedings Paper

Quantification of dose uncertainties for the bladder in prostate cancer radiotherapy based on dominant eigenmodes
Author(s): Richard Rios; Oscar Acosta; Caroline Lafond; Jairo Espinosa; Renaud de Crevoisier
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Paper Abstract

In radiotherapy for prostate cancer the dose at the treatment planning for the bladder may be a bad surrogate of the actual delivered dose as the bladder presents the largest inter-fraction shape variations during treatment. This paper presents PCA models as a virtual tool to estimate dosimetric uncertainties for the bladder produced by motion and deformation between fractions. Our goal is to propose a methodology to determine the minimum number of modes required to quantify dose uncertainties of the bladder for motion/deformation models based on PCA. We trained individual PCA models using the bladder contours available from three patients with a planning computed tomography (CT) and on-treatment cone-beam CTs (CBCTs). Based on the above models and via deformable image registration (DIR), we estimated two accumulated doses: firstly, an accumulated dose obtained by integrating the planning dose over the Gaussian probability distribution of the PCA model; and secondly, an accumulated dose obtained by simulating treatment courses via a Monte Carlo approach. We also computed a reference accumulated dose for each patient using his available images via DIR. Finally, we compared the planning dose with the three accumulated doses, and we calculated local dose variability and dose-volume histogram uncertainties.

Paper Details

Date Published: 17 November 2017
PDF: 14 pages
Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 1057214 (17 November 2017); doi: 10.1117/12.2283505
Show Author Affiliations
Richard Rios, INSERM (France)
Univ. de Rennes 1 (France)
Univ. Nacional de Colombia (Colombia)
Oscar Acosta, INSERM (France)
Univ. de Rennes 1 (France)
Caroline Lafond, CLCC Eugéne Marquis (France)
Jairo Espinosa, Univ. Nacional de Colombia (Colombia)
Renaud de Crevoisier, INSERM (France)
Univ. de Rennes 1 (France)
CLCC Eugéne Marquis (France)


Published in SPIE Proceedings Vol. 10572:
13th International Conference on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Juan David García, Editor(s)

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