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J Magn Reson Imaging. 2016 Dec;44(6):1474-1482. doi: 10.1002/jmri.25304. Epub 2016 May 30.
2
HERMES: Hadamard encoding and reconstruction of MEGA-edited spectroscopy.赫尔墨斯:MEGA编辑光谱的哈达玛编码与重建。
Magn Reson Med. 2016 Jul;76(1):11-9. doi: 10.1002/mrm.26233. Epub 2016 Apr 19.
3
Echo time optimization for J-difference editing of glutathione at 3T.3T下谷胱甘肽J-差异编辑的回波时间优化
Magn Reson Med. 2017 Feb;77(2):498-504. doi: 10.1002/mrm.26122. Epub 2016 Feb 25.
4
Advanced processing and simulation of MRS data using the FID appliance (FID-A)-An open source, MATLAB-based toolkit.使用FID设备(FID-A)对磁共振波谱数据进行高级处理和模拟——一个基于MATLAB的开源工具包。
Magn Reson Med. 2017 Jan;77(1):23-33. doi: 10.1002/mrm.26091. Epub 2015 Dec 30.
5
Parallel reconstruction in accelerated multivoxel MR spectroscopy.加速多体素磁共振波谱中的并行重建
Magn Reson Med. 2015 Sep;74(3):599-606. doi: 10.1002/mrm.25718. Epub 2015 Jun 17.
6
Two-voxel spectroscopy with dynamic B0 shimming and flip angle adjustment at 7 T in the human motor cortex.在7T磁场下对人体运动皮层进行具有动态B0匀场和翻转角调整的双体素波谱分析。
NMR Biomed. 2015 Jul;28(7):852-60. doi: 10.1002/nbm.3328. Epub 2015 May 14.
7
Gannet: A batch-processing tool for the quantitative analysis of gamma-aminobutyric acid–edited MR spectroscopy spectra.塘鹅:一种用于γ-氨基丁酸编辑磁共振波谱定量分析的批处理工具。
J Magn Reson Imaging. 2014 Dec;40(6):1445-52. doi: 10.1002/jmri.24478. Epub 2013 Nov 13.
8
Multivendor implementation and comparison of volumetric whole-brain echo-planar MR spectroscopic imaging.多厂商容积全脑回波平面磁共振波谱成像的实施与比较
Magn Reson Med. 2015 Nov;74(5):1209-20. doi: 10.1002/mrm.25510. Epub 2014 Oct 29.
9
3D GABA imaging with real-time motion correction, shim update and reacquisition of adiabatic spiral MRSI.具有实时运动校正、匀场更新和绝热螺旋磁共振波谱成像重新采集功能的3Dγ-氨基丁酸成像
Neuroimage. 2014 Dec;103:290-302. doi: 10.1016/j.neuroimage.2014.09.032. Epub 2014 Sep 26.
10
Frequency and phase drift correction of magnetic resonance spectroscopy data by spectral registration in the time domain.通过时域中的频谱配准对磁共振波谱数据进行频率和相位漂移校正。
Magn Reson Med. 2015 Jan;73(1):44-50. doi: 10.1002/mrm.25094. Epub 2014 Jan 16.

使用切片选择性编辑脉冲对 J 编辑光谱进行空间哈达玛编码。

Spatial Hadamard encoding of J-edited spectroscopy using slice-selective editing pulses.

作者信息

Chan Kimberly L, Oeltzschner Georg, Schär Michael, Barker Peter B, Edden Richard A E

机构信息

Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

出版信息

NMR Biomed. 2017 May;30(5). doi: 10.1002/nbm.3688. Epub 2017 Jan 27.

DOI:10.1002/nbm.3688
PMID:28128481
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5388576/
Abstract

A new approach for simultaneous dual-voxel J-difference spectral editing is described, which uses spatially selective spectral-editing pulses and Hadamard encoding. A theoretical framework for spatial Hadamard editing and reconstruction for parallel acquisition (SHERPA) was developed, applying gradient pulses during the frequency-selective editing pulses. Spectral simulations were performed for either one (gamma-aminobutyric acid, GABA) or two molecules (glutathione and lactate) simultaneously detected in two voxels. The method was tested in a two-compartment GABA phantom, and finally applied to the left and right hemispheres of 10 normal control subjects, scanned at 3 T. SHERPA was successfully implemented at 3 T and gave results in close agreement with conventional MEGA-PRESS scans in both the phantom and in vivo experiments. Simulations for GABA editing for (3 cm) voxels in the left and right hemispheres suggest that both editing efficiency losses and contamination between voxels are about 2%. Compared with conventional single-voxel single-metabolite J-difference editing, two- or fourfold acceleration is possible without significant loss of SNR using the SHERPA method. Unlike some other dual-voxel methods, the method can be used with single-channel receiver coils, and there is no SNR loss due to unfavorable receive-coil geometry factors.

摘要

本文描述了一种用于同时进行双体素J-差异光谱编辑的新方法,该方法使用空间选择性光谱编辑脉冲和哈达玛编码。开发了一种用于并行采集的空间哈达玛编辑和重建的理论框架(SHERPA),即在频率选择性编辑脉冲期间应用梯度脉冲。对在两个体素中同时检测到的一种(γ-氨基丁酸,GABA)或两种分子(谷胱甘肽和乳酸)进行了光谱模拟。该方法在双室GABA模型中进行了测试,最后应用于10名正常对照受试者的左右半球,在3T下进行扫描。SHERPA在3T下成功实现,在模型和体内实验中得到的结果与传统的MEGA-PRESS扫描结果非常一致。对左右半球(3cm)体素的GABA编辑模拟表明,编辑效率损失和体素间污染均约为2%。与传统的单体素单代谢物J-差异编辑相比,使用SHERPA方法可以实现两倍或四倍的加速,而不会显著损失SNR。与其他一些双体素方法不同,该方法可以与单通道接收线圈一起使用,并且不会因不利的接收线圈几何因素而导致SNR损失。