Madore Bruno
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massaschusetts 02115, USA.
Magn Reson Med. 2004 Aug;52(2):310-20. doi: 10.1002/mrm.20133.
This work aims at improving the performance of parallel imaging by using it with our "unaliasing by Fourier-encoding the overlaps in the temporal dimension" (UNFOLD) temporal strategy. A self-calibration method called "self, hybrid referencing with UNFOLD and GRAPPA" (SHRUG) is presented. SHRUG combines the UNFOLD-based sensitivity mapping strategy introduced in the TSENSE method by Kellman et al. (5), with the strategy introduced in the GRAPPA method by Griswold et al. (10). SHRUG merges the two approaches to alleviate their respective limitations, and provides fast self-calibration at any given acceleration factor. UNFOLD-SENSE further includes an UNFOLD artifact suppression scheme to significantly suppress artifacts and amplified noise produced by parallel imaging. This suppression scheme, which was published previously (4), is related to another method that was presented independently as part of TSENSE. While the two are equivalent at accelerations < or = 2.0, the present approach is shown here to be significantly superior at accelerations > 2.0, with up to double the artifact suppression at high accelerations. Furthermore, a slight modification of Cartesian SENSE is introduced, which allows departures from purely Cartesian sampling grids. This technique, termed variable-density SENSE (vdSENSE), allows the variable-density data required by SHRUG to be reconstructed with the simplicity and fast processing of Cartesian SENSE. UNFOLD-SENSE is given by the combination of SHRUG for sensitivity mapping, vdSENSE for reconstruction, and UNFOLD for artifact/amplified noise suppression. The method was implemented, with online reconstruction, on both an SSFP and a myocardium-perfusion sequence. The results from six patients scanned with UNFOLD-SENSE are presented.
这项工作旨在通过将并行成像与我们的“通过在时间维度上对重叠部分进行傅里叶编码来消除混叠”(UNFOLD)时间策略相结合,来提高其性能。提出了一种名为“基于UNFOLD和GRAPPA的自混合参考”(SHRUG)的自校准方法。SHRUG将Kellman等人(5)在TSENSE方法中引入的基于UNFOLD的灵敏度映射策略与Griswold等人(10)在GRAPPA方法中引入的策略相结合。SHRUG合并了这两种方法以减轻它们各自的局限性,并在任何给定的加速因子下提供快速自校准。UNFOLD-SENSE还包括一种UNFOLD伪影抑制方案,以显著抑制并行成像产生的伪影和放大噪声。这种抑制方案先前已发表(4),它与作为TSENSE一部分独立提出的另一种方法有关。虽然这两种方法在加速因子≤2.0时等效,但本文所示的当前方法在加速因子>2.0时明显更优,在高加速因子下伪影抑制能力提高了一倍。此外,还引入了对笛卡尔SENSE的轻微修改,这允许偏离纯笛卡尔采样网格。这种技术称为可变密度SENSE(vdSENSE),它允许以笛卡尔SENSE的简单性和快速处理能力来重建SHRUG所需的可变密度数据。UNFOLD-SENSE由用于灵敏度映射的SHRUG、用于重建的vdSENSE和用于伪影/放大噪声抑制的UNFOLD组合而成。该方法在SSFP和心肌灌注序列上均实现了在线重建。展示了用UNFOLD-SENSE扫描的六名患者的结果。