MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance.

Published

Journal Article

BACKGROUND:Computer simulations are important for validating novel image acquisition and reconstruction strategies. In cardiovascular magnetic resonance (CMR), numerical simulations need to combine anatomical information and the effects of cardiac and/or respiratory motion. To this end, a framework for realistic CMR simulations is proposed and its use for image reconstruction from undersampled data is demonstrated. METHODS:The extended Cardiac-Torso (XCAT) anatomical phantom framework with various motion options was used as a basis for the numerical phantoms. Different tissue, dynamic contrast and signal models, multiple receiver coils and noise are simulated. Arbitrary trajectories and undersampled acquisition can be selected. The utility of the framework is demonstrated for accelerated cine and first-pass myocardial perfusion imaging using k-t PCA and k-t SPARSE. RESULTS:MRXCAT phantoms allow for realistic simulation of CMR including optional cardiac and respiratory motion. Example reconstructions from simulated undersampled k-t parallel imaging demonstrate the feasibility of simulated acquisition and reconstruction using the presented framework. Myocardial blood flow assessment from simulated myocardial perfusion images highlights the suitability of MRXCAT for quantitative post-processing simulation. CONCLUSION:The proposed MRXCAT phantom framework enables versatile and realistic simulations of CMR including breathhold and free-breathing acquisitions.

Full Text

Duke Authors

Cited Authors

  • Wissmann, L; Santelli, C; Segars, WP; Kozerke, S

Published Date

  • August 20, 2014

Published In

Volume / Issue

  • 16 /

Start / End Page

  • 63 -

PubMed ID

  • 25204441

Pubmed Central ID

  • 25204441

Electronic International Standard Serial Number (EISSN)

  • 1532-429X

International Standard Serial Number (ISSN)

  • 1097-6647

Digital Object Identifier (DOI)

  • 10.1186/s12968-014-0063-3

Language

  • eng