CBCT Iterative Image Reconstruction Method Using Energy Spectrum Information for Adaptive Proton Therapy

Abstract

Cone-beam computed tomography (CBCT) is used to determine a patient's position in proton therapy. Its image quality is low compared to that of a conventional CT because data measured by a two-dimensional detector used in CBCT contain scattered X-ray components. Correcting for scattered X-rays using the Klein-Nishina’s formula can improve CBCT image quality, but the formula requires the atomic number and atomic number density of substances. In this work, I developed a photoncounting image reconstruction method for estimating the atomic number Z and atomic number density N using the energy information of X-rays. In this study, NZ and Z4 were calculated as variables in consideration of the convergence of the optimization algorithm. I applied the developed method to an X-ray energy spectrum of a gantry-mounted CBCT, which was simulated with a Monte Carlo simulation code. The result was possible to distinguish soft tissues from water in the simulated object, which was not possible without the energy information. An atomic number and number density obtained with our method allow calculating the stopping power of protons more accurately, which can contribute to improving dose calculation accuracy.