- Poster presentation
- Open Access
Assessment of myocardial strain using strain-encoding (SENC) MRI: comparison of acquisition strategies
© Ibrahim et al; licensee BioMed Central Ltd. 2011
- Published: 2 February 2011
- Acquisition Strategy
- Typical SENC
- Myocardial Strain
- Strain Image
- Spiral Acquisition
Radial and Spiral acquisitions(2) were implemented in SENC, and the different sequences were tested on three volunteers on Siemens Tim-Trio 3.0-Tesla scanner. The imaging parameters were: FOV=350mm, slice-thickness =10mm, flip-angle=15°, # heart-phases=25, and scan time=17 s. The three sequences were optimized for the fixed scan-time. Maximum resolution obtained was 160x160 for Cartesian (80% phase-encoding coverage) and Radial (128 Radial spokes), and 256x256 for Spiral (10 spiralsx2 averages). The low-tuning and high-tuning images were combined together as described in(1) to construct the strain images. Strain values were measured at five different points along the lateral left-ventricular wall on all volunteers. Bland-Altman analysis was conducted to compare measurements from different sequences.
Data acquisition strategy (k-space trajectory) affects scan-time and the resulting image-quality in SENC. Image quality was similar in Cartesian and Radial. Less radial spokes can be acquired to reduce scan-time without much affecting image-quality. Due to its acquisition nature, spatial-resolution is compromised in Radial acquisition. For the same scan time, Spiral acquisition allowed for improving resolution by more than 60% and doubling # averages, compared to Cartesian or Radial, despite longer reconstruction time. High spatial-resolution would allow for accurate measurements in small structures, e.g. thinning myocardial wall, or it can be traded for faster or real-time imaging. The choice of the acquisition-technique depends on patient condition, available scan-time, and imaging features of importance.
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.