Towards patient connected imaging with ACROBEAT: Adaptive CaRdiac cOne BEAm computed Tomography

Phys Med Biol. 2019 Mar 11;64(6):065006. doi: 10.1088/1361-6560/ab03f4.

Abstract

Robotic C-arm cone beam computed tomography (CBCT) systems are playing an increasingly pivotal role in interventional cardiac procedures and high precision radiotherapy treatments. One of the main challenges in any form of cardiac imaging is mitigating the intrinsic motion of the heart, which causes blurring and artefacts in the 3D reconstructed image. Most conventional 3D cardiac CBCT acquisition techniques attempt to combat heart motion through retrospective gating techniques, whereby acquired projections are sorted into the desired cardiac phase after the completion of the scan. However, this results in streaking artefacts and unnecessary radiation exposure to the patient. Here, we present our Adaptive CaRdiac cOne BEAm computed Tomography (ACROBEAT) acquisition protocol that uses the patient's electrocardiogram (ECG) signal to adaptively regulate the gantry velocity and projection time interval in real-time. It enables prospectively gated patient connected imaging in a single sweep of the gantry. The XCAT digital software phantom was used to complete a simulation study to compare ACROBEAT to a conventional multi-sweep retrospective ECG gated acquisition, under a variety of different acquisition conditions. The effect of location and length of the acquisition window and total number of projections acquired on image quality and total scan time were examined. Overall, ACROBEAT enables up to a 5 times average improvement in the contrast-to-noise ratio, a 40% reduction in edge response width and an 80% reduction in total projections acquired compared to conventional multi-sweep retrospective ECG gated acquisition.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Cone-Beam Computed Tomography / methods*
  • Heart / diagnostic imaging
  • Heart / physiology*
  • Humans
  • Movement*
  • Phantoms, Imaging*
  • Retrospective Studies