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无网格交互式和自动化磁共振化学位移成像数据处理。

Grid-free interactive and automated data processing for MR chemical shift imaging data.

机构信息

Centre de Résonance Magnétique Biologique et Médicale (CRMBM), UMR CNRS No 6612, Faculté de Médecine de Marseille, Université de la Méditerranée, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.

出版信息

MAGMA. 2010 Feb;23(1):23-30. doi: 10.1007/s10334-009-0186-y. Epub 2009 Nov 3.

Abstract

PURPOSE

Today's available chemical shift imaging (CSI) analysis tools are based on Fourier transform of the entire data set prior to interactive display. This strategy is associated with limitations particularly when arbitrary voxel positions within a 3D spatial volume are needed by the user. In this work, we propose and demonstrate a processing-resource-efficient alternative strategy for both interactive and automated CSI data processing up to three spatial dimensions.

METHODS

This approach uses real-time voxel-shift by first-order phase manipulation as a basis and therefore allows grid-free voxel positioning within the 3D volume. The corresponding spectrum is extracted from the 4D data (3D spatial/1D spectral) at each time a voxel position is selected. The spatial response function and hence the exact voxel size and shape are calculated in parallel including the same processing parameters. Using this mechanism sequentially along with AMARES time-domain modeling, we also implemented automated quantitative and B (0)-insensitive metabolite mapping.

RESULTS

Metabolite maps of N-acetyl aspartate, choline and creatine were generated using (1)H-CSI data from the brain of healthy volunteers and patients with tumor and epilepsy. (31)P-3D-CSI of the heart of a healthy volunteer is also shown.

CONCLUSION

The calculated metabolite maps demonstrate good stability and accuracy of the algorithm in all situations tested. The suggested algorithm constitutes therefore an attractive alternative to existing CSI processing strategies.

摘要

目的

现今可用的化学位移成像(CSI)分析工具基于在交互式显示之前对整个数据集进行傅里叶变换。这种策略存在局限性,特别是当用户需要在 3D 空间体积内任意体素位置时。在这项工作中,我们提出并演示了一种适用于交互式和自动化 CSI 数据处理的处理资源高效替代策略,最高可达三个空间维度。

方法

该方法使用一阶相位操纵的实时体素移位作为基础,因此允许在 3D 体积内无网格体素定位。在每次选择体素位置时,从 4D 数据(3D 空间/1D 光谱)中提取相应的光谱。空间响应函数以及精确的体素大小和形状在包括相同处理参数的情况下并行计算。使用这种机制,结合 AMARES 时域建模,我们还实现了自动化定量和 B(0)不敏感代谢物映射。

结果

使用来自健康志愿者和肿瘤和癫痫患者大脑的(1)H-CSI 数据生成了 N-乙酰天冬氨酸、胆碱和肌酸的代谢物图。还显示了健康志愿者心脏的(31)P-3D-CSI。

结论

计算出的代谢物图表明该算法在所有测试情况下均具有良好的稳定性和准确性。因此,所提出的算法构成了现有 CSI 处理策略的有吸引力的替代方案。

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