One-step Iterative Estimation of Effective Atomic Number and Electron Density for Dual Energy CT

TL;DR

This paper introduces a one-step iterative method using multi-domain gradient $L_0$-norm minimization for reconstructing effective atomic number and electron density maps in dual-energy CT, aiming for real-time clinical application.

Contribution

It presents a novel GPU-accelerated iterative algorithm for simultaneous Z and $ ho_e$ estimation in DECT, enhancing speed and potential for real-time adaptive proton therapy planning.

Findings

Effective Z and $ ho_e$ maps reconstructed accurately in phantom and patient studies.

GPU implementation enables potential real-time processing.

Improved material differentiation and treatment planning accuracy.

Abstract

Dual-energy computed tomography (DECT) is a promising technology that has shown a number of clinical advantages over conventional X-ray CT, such as improved material identification, artifact suppression, etc. For proton therapy treatment planning, besides material-selective images, maps of effective atomic number (Z) and relative electron density to that of water ($\rho_e$) can also be achieved and further employed to improve stopping power ratio accuracy and reduce range uncertainty. In this work, we propose a one-step iterative estimation method, which employs multi-domain gradient $L_0$-norm minimization, for Z and $\rho_e$ maps reconstruction. The algorithm was implemented on GPU to accelerate the predictive procedure and to support potential real-time adaptive treatment planning. The performance of the proposed method is demonstrated via both phantom and patient studies.