NOVEL MRI METHODS IRON QUALIFICATION IN PARKINSON'S DISEASE

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 在这个项目中，我们计划验证一种在黑质MRI中非侵入性测量的新生物标记物(绝热T1和T2)，作为实现帕金森病(PD)患者和对照组之间统计分离的一种手段。本文提出的用于测量神经元缺陷的新的绝热T1和T2松弛方法可能为神经疾病，特别是帕金森病的发病机制提供有用的见解。我们证明，T1？松弛测量提供了关于大脑不同区域中水自旋的基本动态参数的直接信息。我们发现，神经元密度及其投射的变化反映在水自旋的翻滚中。这表明T1？测量可能被用来量化PD患者SNC中的神经元丢失，以及可能的其他神经退行性疾病。与传统的T1磁共振相比，T1？测量提供了独特的信息，因为在用于测量的绝热脉冲期间，有效磁场会被扫描。将有必要进行进一步的研究，以确认我们的技术对其他神经退行性疾病模型的适用性，然而，我们预计这项技术将被证明能够检测到任何给定的感兴趣的脑区的细胞丢失。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In this project, we plan to validate a new biomarker (adiabatic T1¿ and T2¿) measured non-invasively in the substantia nigra MRI as a means to achieve statistical separation between Parkinson's diseased (PD) patients from control subjects. The novel adiabatic T1¿ and T2¿ MRI relaxation methods proposed here for the measurement of neuronal deficiency may provide useful insights into the pathogenesis of neurological disorders, in particular PD. We demonstrated that the T1¿ relaxation measurements provide direct information about the fundamental dynamic parameters of the water spins in different areas of the brain. We show that the change in density of neurons and their projections is reflected in the tumbling of the water spins. This suggests that T1¿ measurements can potentially be used to quantify the neuronal loss in the SNc of PD patients, as well as likely other neurodegenerative conditions. The T1¿ measurements provide unique information as compared to conventional T1 MRI due to the sweep of the effective magnetic field during the adiabatic pulses used for the measurements. Further studies will be warranted to confirm the applicability of our technique to additional neurodegenerative disease models, however we expect that this technique will prove capable of detecting cell loss in any given brain region of interest.