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List-mode proton CT reconstruction

Abstract : Proton therapy is used for cancer treatment to achieve better dose conformity by exploiting the energy-loss properties of protons. Proton treatment planning systems require knowledge of the stopping-power map of the patient’s anatomy to compute the absorbed dose. In clinical practice, this map is generated through a conversion from X-ray computed tomography (CT) Hounsfield units to proton stopping power relative to water (RSP). This calibration generates uncertainties as photon and proton physics are different, which leads to the use of safety margins and the reduction of dose conformity. In order to reduce uncertainties, proton CT (pCT) was proposed as a planning imaging modality since the reconstructed quantity is directly the RSP. In addition to energy loss, protons also undergo multiple Coulomb scattering (MCS) inducing non-linear paths, thus making the pCT reconstruction problem different from that of X-ray CT. The objective of this thesis is to improve image quality of pCT list-mode reconstruction. The use of a most likely path (MLP) formalism for protons to account for the effects of MCS has improved the spatial resolution in pCT. This formalism assumes a homogeneous medium. The first contribution of this thesis is a study on proton paths in heteregeneous media: the accuracy of the MLP was evaluated against a Monte Carlo generated path in different heterogeneous configurations. Results in terms of spatial, angular, and energy distributions were analyzed to assess the impact on reconstruction. The second contribution is a 2D directional ramp filter used for pCT data reconstruction. An intermediate between a filtered backprojection and a backproject-filter approach was proposed, based on the extension of the usual ramp filter to two dimensions, in order to preserve the MLP spatial information. An expression for a band-limited 2D version of the ramp filter was derived and tested on simulated pCT list-mode data. Then, a comparison of direct reconstruction algorithms in terms of spatial resolution and RSP accuracy was conducted. Five algorithms, including the 2D directional ramp, were tested to reconstruct different simulated phantoms. Results were compared between reconstruction from data acquired using idealized or realistic trackers. Finally, the last contribution is a deconvolution method using the information on the MLP uncertainty in order to improve spatial resolution of pCT images.
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Submitted on : Wednesday, February 10, 2021 - 3:53:18 PM
Last modification on : Friday, February 12, 2021 - 6:07:35 PM


Version validated by the jury (STAR)


  • HAL Id : tel-03131226, version 2


Feriel Khellaf. List-mode proton CT reconstruction. Medical Imaging. Université de Lyon, 2020. English. ⟨NNT : 2020LYSEI074⟩. ⟨tel-03131226v2⟩



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