Proton computed tomography from multiple physics processes.

Proton CT (pCT) nowadays aims at improving hadron therapy treatment planning by mapping the relative stopping power (RSP) of materials with respect to water. The RSP depends mainly on the electron density of the materials. The main information used is the energy of the protons. However, during a pCT acquisition, the spatial and angular deviation of each particle is recorded and the information about its transmission is implicitly available. The potential use of those observables in order to get information about the materials is being investigated. Monte Carlo simulations of protons sent into homogeneous materials were performed, and the influence of the chemical composition on the outputs was studied. A pCT acquisition of a head phantom scan was simulated. Brain lesions with the same electron density but different concentrations of oxygen were used to evaluate the different observables. Tomographic images from the different physics processes were reconstructed using a filtered back-projection algorithm. Preliminary results indicate that information is present in the reconstructed images of transmission and angular deviation that may help differentiate tissues. However, the statistical uncertainty on these observables generates further challenge in order to obtain an optimal reconstruction and extract the most pertinent information.