Hutchinson Michael, Raff Ulrich
Department of Neurology, New York University School of Medicine, New York, NY 10016, USA.
Mov Disord. 2008 Oct 30;23(14):1991-7. doi: 10.1002/mds.22210.
We have developed an advanced MRI technique for detecting Parkinson's Disease (PD) which depends on an image constructed as a ratio of images from two inversion recovery sequences (one generating a white matter suppressed image, the other a gray matter suppressed image). This technique was designed to be exceptionally sensitive to the spin-lattice relaxation time T(1). It was refined with the introduction of segmentation analysis and given the acronym SIRRIM (Segmented Inversion Recovery Ratio Imaging). Our objectives are, first, to reinvestigate the sensitivity of MRI with new subjects and second, to investigate whether a new form of analysis, using the gray level distribution of signal in the image, may prove more sensitive than SIRRIM. For each subject, a ratio image was constructed (WMS/GMS) and the substantia nigra segmented out to be displayed as an isolated structure. From the segmented image a measure of disease severity, the Radiological Index (RI), was calculated for each subject. Since the pixel value in the ratio image is a strong function of the local T(1) relaxation time, the distribution of pixel values gives the distribution of spin-lattice relaxation times. A refinement in the analysis is introduced, the Spin-Lattice Distribution Index (SI), which is an automated measure of MRI signal in the Substantia Nigra pars compacta (SN(C)). Both RI and SI were calculated for each of 24 subjects, 12 patients and 12 controls. The SI may further improve the separation of patient and control groups, and may therefore be more sensitive than the RI. Unlike the RI it is completely automatic and circumvents two of the limitations of the RI. The work is consistent with the proposition that MRI, when properly configured, is a highly sensitive marker for PD.
我们开发了一种先进的磁共振成像（MRI）技术来检测帕金森病（PD），该技术依赖于通过两个反转恢复序列的图像构建的比率图像（一个生成白质抑制图像，另一个生成灰质抑制图像）。这项技术设计得对自旋晶格弛豫时间T(1)异常敏感。随着分割分析的引入，该技术得到了改进，并被赋予了首字母缩写SIRRIM（分段反转恢复比率成像）。我们的目标是，首先，用新的受试者重新研究MRI的敏感性；其次，研究一种使用图像中信号灰度分布的新分析形式是否可能比SIRRIM更敏感。对于每个受试者，构建一个比率图像（WMS/GMS），并分割出黑质以显示为一个孤立的结构。从分割图像中为每个受试者计算疾病严重程度的指标——放射学指数（RI）。由于比率图像中的像素值是局部T(1)弛豫时间的强函数，像素值的分布给出了自旋晶格弛豫时间的分布。引入了一种分析改进，即自旋晶格分布指数（SI），它是黑质致密部（SN(C)）中MRI信号的自动测量指标。为24名受试者（12名患者和12名对照）分别计算了RI和SI。SI可能会进一步改善患者组和对照组的区分，因此可能比RI更敏感。与RI不同，它是完全自动的，并且规避了RI的两个局限性。这项工作与以下观点一致，即经过适当配置的MRI是PD的一种高度敏感的标志物。
