Volume 18 Supplement 1
Phase-Sensitive ChEmical Selection (PiSCES) method for fat signal removal in LGE
© Janich et al. 2016
Published: 27 January 2016
Late Gadolinium Enhancement (LGE) allows imaging of infarction by visualizing the accumulation of contrast agent within the myocardium using an inversion recovery (IR) prepared sequence. However, myocardial hyperenhancement can sometimes be poorly detected in the vicinity of epicardial fat because both fat and hyperenhanced tissue appear bright. Thus, a method for fat signal suppression is desired. One previous approach to fat-suppressed LGE was to null fat signal with appropriately timed tip-up/tip-down fat-selective RF pulses , but this technique can leave residual fat signal in the image due both to sensitivity to off-resonance and timing requirements to achieve fat nulling. The goal of the present work is to achieve more complete and robust fat suppression by introducing a Phase-Sensitive ChEmical Selection (PiSCES) method that combines phase-sensitive (PS) image reconstruction  with customized timing of fat-selective RF pulses.
After PS reconstruction fat appears black due to its opposite signal polarity (Mz < 0) vs. hyperenhanced tissue (Mz > 0). To achieve this the following condition for TIfat, the time between the fat tip-down pulse and the center of k-space acquisition, must be met: TIfat < -T1,fat*log(0.5 + exp(-(TI-Tt)/T1,fat) - exp(-TI/T1,fat) + 0.5*exp(-2*RR/T1,fat)), where Tt: time between IR and fat tip-up pulses, RR: R-R interval duration.
PiSCES was applied in 8 patients using Discovery MR750w 3.0T (GE Healthcare) and compared to conventional fat-suppressed magnitude LGE with heart rate adaptive timing .
The negative polarity of fat at readout and appropriate windowing of the image leads to complete elimination of fat signal with the new PiSCES approach. Additionally the technique is relatively insensitive to timing of the fat-selective RF pulses: fat appears black as long as fat has negative polarity, thus the method has potential to be more robust across a variety of imaging conditions.
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/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.