Bao Yufang, Maudsley Andrew A
MR Center (R308), 1115 NW 14th Street, Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
IEEE Trans Med Imaging. 2007 May;26(5):686-95. doi: 10.1109/TMI.2007.895482.
Sensitivity limitations of in vivo magnetic resonance spectroscopic imaging (MRSI) require that the extent of spatial-frequency (k-space) sampling be limited, thereby reducing spatial resolution and increasing the effects of Gibbs ringing that is associated with the use of Fourier transform reconstruction. Additional problems occur in the spectral dimension, where quantitation of individual spectral components is made more difficult by the typically low signal-to-noise ratios, variable lineshapes, and baseline distortions, particularly in areas of significant magnetic field inhomogeneity. Given the potential of in vivo MRSI measurements for a number of clinical and biomedical research applications, there is considerable interest in improving the quality of the metabolite image reconstructions. In this report, a reconstruction method is described that makes use of parametric modeling and MRI-derived tissue distribution functions to enhance the MRSI spatial reconstruction. Additional preprocessing steps are also proposed to avoid difficulties associated with image regions containing spectra of inadequate quality, which are commonly present in the in vivo MRSI data.
体内磁共振波谱成像（MRSI）的灵敏度限制要求空间频率（k空间）采样的范围受到限制，从而降低空间分辨率，并增加与使用傅里叶变换重建相关的吉布斯振铃效应。在频谱维度还会出现其他问题，由于典型的低信噪比、可变的线形和基线失真，特别是在磁场不均匀性显著的区域，使得单个频谱成分的定量变得更加困难。鉴于体内MRSI测量在许多临床和生物医学研究应用中的潜力，提高代谢物图像重建的质量引起了人们的极大兴趣。在本报告中，描述了一种利用参数建模和MRI衍生的组织分布函数来增强MRSI空间重建的方法。还提出了额外的预处理步骤，以避免与体内MRSI数据中通常存在的、包含质量不足频谱的图像区域相关的困难。
