Highly undersampled peripheral Time-of-Flight magnetic resonance angiography: optimized data acquisition and iterative image reconstruction

MAGMA. 2015 Oct;28(5):437-46. doi: 10.1007/s10334-014-0477-9. Epub 2015 Jan 22.

Abstract

Object: The aim of this study was to investigate the acceleration of peripheral Time-of-Flight magnetic resonance angiography using Compressed Sensing and parallel magnetic resonance imaging (MRI) while preserving image quality and vascular contrast.

Materials and methods: An analytical sampling pattern is proposed that combines aspects of parallel MRI and Compressed Sensing. It is used in combination with a dedicated Split Bregman algorithm. This approach is compared with current state-of-the-art patterns and reconstruction algorithms.

Results: The acquisition time was reduced from 30 to 2.5 min in a study using ten volunteer data sets, while showing improved sharpness, better contrast and higher accuracy compared to state-of-the-art techniques.

Conclusion: This study showed the benefits of the proposed dedicated analytical sampling pattern and Split Bregman algorithm for optimizing the Compressed Sensing reconstruction of highly accelerated peripheral Time-of-Flight data.

Keywords: Compressed Sensing; Iterative reconstruction; Non-contrast-enhanced MRA; Peripheral angiography.

MeSH terms

  • Algorithms
  • Artifacts*
  • Data Compression / methods*
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods
  • Imaging, Three-Dimensional / methods*
  • Magnetic Resonance Angiography / methods*
  • Peripheral Arterial Disease / pathology*
  • Reproducibility of Results
  • Sample Size
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted