Development of diffusion-weighted ultra-fast magnetic resonance spectroscopic metabolite imaging

本研究的目的是利用超快磁共振成像(MRSI)方法建立脑代谢物的扩散加权成像。我们使用了三种不同的MRI设备：一台用于动物的7T高分辨率核磁共振光谱仪，一台工作在临床MRI磁体(MR MICS)上的显微成像设备和一台1.5T临床MRI扫描仪。使用MR MICS将高分辨率核磁共振波谱仪上设计的软件传输到临床扫描仪。首先，我们开发了回声平面成像(EPI)序列以获得超快速MRSI(EPI-MRSI)。其次，我们试图将这项技术应用于脑部代谢物的扩散加权成像。再次，我们开发了扩散张量成像来获取代谢物扩散的信息，并在临床MRI扫描仪上成功地开发了用于人脑的EPI-MRSI。比较EPI-MRSI和常规MRSI(SE-MRSI)的数据，EPI-MRSI的测量时间略短于SE-MRSI，但光谱分辨率较差。我们认识到，EPI-MRSI的测量时间需要更高的信号强度才能得到明显的改善，将该方法应用于扩散加权代谢物成像也需要提高信号强度。通过获得特征向量映射、特征值映射和分数各向异性映射，可以成功地进行扩散张量成像。这些图像清楚地显示了神经纤维的方向和各向异性。下一步，我们将尝试应用这些方法来获取脑内扩散代谢物的信息。尽管完成扩散加权EPI-MRSI存在许多技术困难，但发展这种方法是必要的，因为它具有很高的潜力来研究大脑代谢物的动态方面，在实验和临床上都是有前景的。从这个意义上讲，还需要继续深入研究。

The aim of this research was to develop a diffusion-weighted imaging of brain metabolite by using ultra-fast magnetic resonance imaging (MRSI) methods. We used three different MRI devices ; a 7T high-resolution NMR spectrometer for animal use, a microimaging deice worked in a clinical MRI magnet (MR mics) and a 1.5T clinical MRI scanner. The MR mics was used to transfer the software designed on the high-resolution NMR spectrometer to the clinical scanner. First, we have developed the echo planar imaging (EPI) sequence to get the ultra-fast MRSI (EPI-MRSI). Secondary, we tried to apply this technique to a diffusion-weighted imaging of brain metabolites. Thirdly, we developed the diffusion tensor imaging to get the information of metabolite diffusion.We successfully developed the EPI-MRSI for human brain on the clinical MRI scanner. Comparing data of EPI-MRSI with conventional MRSI (SE-MRSI), the measurement time was slightly shorter in EPI-MRSI than in SE-MRSI but the spectral resolution was worse in EPI-MRSI.We realized that the more increased signal intensity was necessary to get a marked improvement of measuring time with EPI-MRSI.Also, it is necessary to have the improvement of the signal-intensity to apply this method to the diffusion weighted metabolite imaging.We could succeed to develop the diffusion tensor imaging by obtaining the Eigenvector mapping, Eigenvalue mapping and fractional anisotropy mapping. These images clearly demonstrate the nerve fiber direction and anisotropy. We will try to apply these methods to get the information of diffusion metabolite in the brain as a next step.Although there existed many technical difficulty in completing diffusion-weighted EPI-MRSI, it is indispensable to develop this method, because it has a high potentiality to investigate dynamic aspect of brain metabolites and is promising for both experimentally and clinically. In this sense, further research should be continued.