- Poster presentation
- Open Access
Self-calibrating through-time spiral GRAPPA for real-time CMR
© Seiberlich and Griswold; licensee BioMed Central Ltd. 2013
- Published: 30 January 2013
- Calibration Data
- Additional Calibration
- Calibration Dataset
- Separate Calibration
- Parallel Imaging Method
Through-Time non-Cartesian GRAPPA, a novel parallel imaging method for non-Cartesian trajectories, has recently been shown to provide real-time, free-breathing cardiac images with temporal resolutions of less than 35 ms per frame [Seiberlich N, et al. MRM 2011 Dec;66(6):1682-8]. The drawback to this method is the need for several fully-sampled datasets for calibration stemming from the non-Cartesian nature of the data, which leads to a longer overall scan time. By acquiring interleaved spiral datasets and combining them to form fully-sampled datasets for the generation of the GRAPPA weights, as in TGRAPPA [Breuer FA, et al. MRM 2005 Apr;53(4):981-5.], there is no need for additional calibration data. However, this interleaved calibration method poses the risk of increased artifacts if the temporal footprint of the calibration data is too long. The goal of this study is to test the extent to which self-calibrating through-time spiral GRAPPA can be used for real-time free-breathing CMR.
Interleaved spiral data were acquired from healthy volunteers on a 1.5T Espree (Siemens Medical Solutions) using 18 receiver channels and the following parameters: bSSFP spiral sequence, TR = 4.48 ms, TE = 2.24 ms, FoV = 300 mm2, slice thickness = 8 mm, base matrix=128, 940 read-out points, 48 spiral arms made up of 6 sets of 8 arms, R=6, imaging time =17s. The temporal resolution for this scan was 35 ms/frame. The volunteers were instructed to breathe normally and no EKG gating was employed. The interleaved spiral data were resorted for use as calibration data; special care was taken to assure that the interleaf to be reconstructed was centered temporally within the calibration data to assure a short temporal window for calibration. Additionally, a separate calibration scan was acquired (48 arms, 80 frames) and the interleaved spiral data were also reconstructed using this data as a comparison. Finally, images were generated from the interleaved data using a sliding window view-sharing method for comparison.
Self-Calibrating Through-Time Spiral GRAPPA can be used to generate real-time cardiac images with a temporal resolution of 35 ms without the need for an additional calibration dataset.
This work was funded by Case Western Reserve University/Cleveland Clinic CTSA UL1 RR024989, NIH/NIBIB R00EB011527 and RO1HL094557.
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.