Key result
Implementation of inverted tags with phase-sensitive reconstruction in an SSFP sequence provides superior contrast-to-noise ratio and higher-precision tag detection compared to standard methods.
Why the study?
Does phase-sensitive reconstruction of inverted tags improve tag contrast-to-noise ratio compared to standard saturation tagging in cardiac MRI?
Does phase-sensitive reconstruction of inverted tags improve tag contrast-to-noise ratio compared to standard saturation tagging in cardiac MRI?
Phase-sensitive reconstruction of inverted tags in SSFP sequences improves cardiac MRI tagging contrast, allowing for higher precision and better spatial resolution in strain measurements.
Fully inverting spins, instead of merely saturating them, provides superior contrast for tagging procedures. The resulting improvement in tag contrast-to-noise ratio (CNR) yields higher-precision tag detection. Also, thinner slices and hence reduced tag separations can be employed, providing displacement and strain measurements with better spatial resolution. Alternatively, the improved tag contrast can be used to obtain cine images covering a greater portion of the cardiac cycle. The use of standard magnitude reconstruction for images of these inversion tags causes rectification of the negative-valued signals from the tags, confounding the image interpretation. Therefore, a phase-sensitive reconstruction scheme of the inverted tags must be employed. Here we demonstrate the implementation of inverted tags with phase-sensitive reconstruction in a ramped-flip-angle, steady-state free precession (SSFP) sequence.
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Derbyshire et al. (2007) studied Cardiac imaging. Phase-sensitive reconstruction of inverted tags (REALTAG) vs. Standard magnitude reconstruction / saturation tagging was evaluated on Tag contrast-to-noise ratio (CNR) and spatial resolution. Implementation of inverted tags with phase-sensitive reconstruction in an SSFP sequence provides superior contrast-to-noise ratio and higher-precision tag detection compared to standard methods.
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