Computational methods to optimize proton radiography and tomography for improved proton therapy.
Objective
People involved in the project
Jean Michel Létang, lecturer-researcher (enseignant-chercheur)
Simon Rit, researcher (chercheur CNRS)
Nils Krah, post-doc researcher
Feriel Khellaf, PhD student
Ilaria Rinaldi, researcher from partner institution
Background
Proton therapy offers high dose selectivity due to the protons' distinct depth dose profile. However, appropriate management of treatment uncertainties is required to fully exploit this advantage. Precise knowledge of the relative stopping power (RSP) of the patient tissues is needed to correctly predict the proton range in the treatment planning. Currently, this prediction is approximated from X-ray computed tomography (CT) and the associated uncertainties require additional safety margins. Proton radiography (pR) and/or CT (pCT) [1,2] could improve or even bypass this approximation by directly measuring the RSP. Additionally, it could be used to verify and monitor the positioning of the patient prior to or in-between the treatment, potentially in presence of motion.
Proton imaging suffers from limited spatial resolution, e.g., with respect to X-ray imaging, due to multiple Coulomb scattering (MCS). Most investigations concentrate on hardware improvements to cope with this limitation. We propose to develop complementary algorithmic solutions which will significantly improve the image quality. We have recently shown that MCS has an edge-enhancing effect in list-mode proton imaging which could be used to improve spatial resolution [3]. Similar effects have been investigated with integrating detectors [4].
So far, statistical descriptions of MCS only exist for the simplified case of homogeneous media. The purpose of this project is to develop a computationally efficient model of MCS inheterogeneous media and to integrate it into a typical tomographic reconstruction workflow. Both list-mode and integrated scenarios will be investigated. We will further investigate methods to merge proton and X-ray tomographic data and define a new treatment work-flow in which range information in the patient will be obtained from the optimized pCT and not solely from the conversion of the planning X-ray CT.