Étude de la tomodensitométrie spectrale quantitative et ses applications en radiothérapie

X-ray computed tomography (CT) is an imaging modality that produces a tridimensional map of the attenuation of X-rays by the scanned object. In radiation therapy, CT provides anatomical and quantitative information on the patient that is required for treatment planning. However, CT has some issues, notably (1) a limited accuracy in the estimation of quantitative physical parameters of the patient, and (2) a sensitivity to biases caused by beam hardening artifacts. Finally, (3) in the case where contrast-enhanced CT is performed to help treatment planning, a second scan with no contrast agent is required for dose calculation purposes, which increases the overall dose to the patient. Those 3 problems limit the efficiency of CT for some treatment modalities more sensitive to uncertainties, such as proton therapy.  Spectral CT regroups a set of methods that allows the production of multiple X-ray attenuation maps evaluated over various energy windows. The additional energy-weighted information that is obtained allows better material characterization. The potential of one spectral CT modality, dual-energy CT (DECT), is already well demonstrated for radiation therapy, while an upcoming method, spectral photon counting CT (SPCCT), promises more spectral information with the help of energy discriminating detectors. Unfortunately, SPCCT suffers from increased noise and poor conditioning. This thesis thus investigates the following question: is there a benefit to using more, but lower quality energy-resolved information for radiotherapy? The question is studied in the context of the three problems discussed earlier.  First, a maximum a posteriori (MAP) estimator is introduced for post-reconstruction tissue characterization for denoising purposes in spectral CT. The estimator is validated experimentally using a commercial DECT. The noise level on the proton stopping power is reduced, on average, by a factor of 3.2 with the MAP estimator. The estimator also generally con- serves the quantitative accuracy of estimated physical parameters. For instance, the stopping power varies on average by 0.9% with respect to the conventional approach. Then, the MAP estimation framework is adapted to the context of contrast-enhanced imaging. Numerical results show clear benefits when using SPCCT for virtual non-contrast imaging compared to DECT, with a reduction of the RMS error on the proton stopping power from 2.7 to 1.4%. Third, the developed tools are validated experimentally on a micro-SPCCT from MARS Bioimaging, which uses the Medipix 3 chip as a photon counting detector. Small benefits in the accuracy of physical parameters of tissue substitutes materials are obtained. Finally, a new parametrization of the attenuation coefficient for pre-reconstruction imaging is pro- posed, whose ultimate aim is to correct beam hardening artifacts. In a simulation study, the proposed parametrization eliminates all biases in the estimated physical parameters of human tissues, which is an improvement upon existing parametrizations. However, no ad- vantage has been obtained with SPCCT compared to DECT, which suggests the need to incorporate MAP estimation in the pre-reconstruction framework using an iterative reconstruction approach.

Keyphrases: MARS Bioimaging, Medipix 3, X-ray computed tomography, Multi-energy computed tomography, Radiation therapy, Spectral computed tomography, Photon counting detector, Proton therapy, Contrast-enhanced imaging, Virtual non-contrast imaging, MARS Bioimaging, Medipix 3