Improved blood suppression in three-dimensional (3D) fast spin-echo (FSE) vessel wall imaging using a combination of double inversion-recovery (DIR) and diffusion sensitizing gradient (DSG) preparations

J Magn Reson Imaging. 2010 Feb;31(2):398-405. doi: 10.1002/jmri.22042.

Abstract

Purpose: To provide improved blood suppression in three-dimensional inner-volume fast spin-echo (3D IV-FSE) carotid vessel wall imaging by using a hybrid preparation consisting of double inversion-recovery (DIR) and diffusion sensitizing gradients (DSG).

Materials and methods: Multicontrast black-blood MRI is widely used for vessel wall imaging and characterization of atherosclerotic plaque composition. Blood suppression is difficult when using 3D volumetric imaging techniques. DIR approaches do not provide robust blood suppression due to incomplete replacement of blood spins, and DSG approaches compromise vessel wall signal, reducing the lumen-wall contrast-to-noise ratio efficiency (CNR(eff)). In this work a hybrid DIR+DSG preparation is developed and optimized for blood suppression, vessel wall signal preservation, and vessel-wall contrast in 3D IV-FSE imaging. Cardiac gated T(1)-weighted carotid vessel wall images were acquired in five volunteers with 0.5 x 0.5 x 2.5 mm(3) spatial resolution in 80 seconds.

Results: Data from healthy volunteers indicate that the proposed method yields a statistically significant (P < 0.01) improvement in blood suppression and lumen-wall CNR(eff) compared to standard DIR and standard DSG methods alone.

Conclusion: A combination of DIR and DSG preparations can provide improved blood suppression and lumen-wall CNR(eff) for 3D IV-FSE vessel wall imaging.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Blood*
  • Carotid Arteries / anatomy & histology*
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Magnetic Resonance Imaging / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity