@inproceedings{d9ba570e1fdb4db4a189bfd132a6df72,
title = "Deformable known component model-based reconstruction for coronary CT angiography",
abstract = "Purpose: Atherosclerosis detection remains challenging in coronary CT angiography for patients with cardiac implants. Pacing electrodes of a pacemaker or lead components of a defibrillator can create substantial blooming and streak artifacts in the heart region, severely hindering the visualization of a plaque of interest. We present a novel reconstruction method that incorporates a deformable model for metal leads to eliminate metal artifacts and improve anatomy visualization even near the boundary of the component. Methods: The proposed reconstruction method, referred as STF-dKCR, includes a novel parameterization of the component that integrates deformation, a 3D-2D preregistration process that estimates component shape and position, and a polyenergetic forward model for x-ray propagation through the component where the spectral properties are jointly estimated. The methodology was tested on physical data of a cardiac phantom acquired on a CBCT testbench. The phantom included a simulated vessel, a metal wire emulating a pacing lead, and a small Teflon sphere attached to the vessel wall, mimicking a calcified plaque. The proposed method was also compared to the traditional FBP reconstruction and an interpolation-based metal correction method (FBP-MAR). Results: Metal artifacts presented in standard FBP reconstruction were significantly reduced in both FBP-MAR and STF- dKCR, yet only the STF-dKCR approach significantly improved the visibility of the small Teflon target (within 2 mm of the metal wire). The attenuation of the Teflon bead improved to 0.0481 mm-1with STF-dKCR from 0.0166 mm-1 with FBP and from 0.0301 mm-1 with FBP-MAR - much closer to the expected 0.0414 mm-1. Conclusion: The proposed method has the potential to improve plaque visualization in coronary CT angiography in the presence of wire-shaped metal components.",
keywords = "CT reconstruction, Implant imaging, Metal artifact reduction, Penalized-likelihood estimation",
author = "X. Zhang and S. Tilley and S. Xu and A. Mathews and McVeigh, {E. R.} and Stayman, {J. W.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; Medical Imaging 2017: Physics of Medical Imaging ; Conference date: 13-02-2017 Through 16-02-2017",
year = "2017",
doi = "10.1117/12.2255303",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Schmidt, {Taly Gilat} and Lo, {Joseph Y.} and Flohr, {Thomas G.}",
booktitle = "Medical Imaging 2017",
}