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Mise en correspondance inter-individus pour la prédiction de la toxicité en radiothérapie du cancer de la prostate

Abstract : This thesis deals with the issue of predicting the toxicity within the context of prostate cancer radiotherapy. With the aim of analyzing the spatial correlations between dose and side effects, this problem is addressed in a population analysis framework. Inter-individual matching of both the anatomy and planned dose distribution raises difficulties related to high anatomical variability and low contrast in the CT images. We considered different strategies for non-rigid registration involving the use of information on anatomical structures, intensity-structure combinations, or inter-structures relations. The proposed methods are primarily based on the use of structural descriptors of organs such as Euclidean distance maps or scalar field solution of the Laplace equation. These methods allowed us to significantly improve the accuracy of the matching, at both the dosimetric and the anatomical level. The most accurate matching strategy has been used for analyzing a population of. Statistical comparisons of dose distributions between patients with or without rectal bleeding have been used to identify a rectal sub-region likely correlated with toxicity. The identified rectal sub-region appears potentially involved in side effects and highly predictive of the risk of bleeding. The proposed approach makes it possible to improve the performance of mathematical models for predicting the toxicity.
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https://tel.archives-ouvertes.fr/tel-01077966
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Submitted on : Monday, October 27, 2014 - 2:56:10 PM
Last modification on : Wednesday, September 14, 2022 - 10:20:04 AM
Long-term archiving on: : Wednesday, January 28, 2015 - 11:36:17 AM

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  • HAL Id : tel-01077966, version 1

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Gaël Dréan. Mise en correspondance inter-individus pour la prédiction de la toxicité en radiothérapie du cancer de la prostate. Traitement du signal et de l'image [eess.SP]. Université Rennes 1, 2014. Français. ⟨NNT : 2014REN1S041⟩. ⟨tel-01077966⟩

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