NOVEL MRI METHODS IRON QUALIFICATION IN PARKINSON'S DISEASE

该子项目是利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 在这个项目中，我们计划验证一种新的生物标志物（绝热T1 <$and T2 <$），在黑质MRI中无创测量，作为一种手段，以实现帕金森病（PD）患者与对照受试者之间的统计分离。新型绝热T1？而T2？这里提出的MRI弛豫方法用于测量神经元缺陷可能提供有用的见解神经系统疾病，特别是PD的发病机制。我们证明，T1 ²弛豫测量提供了有关大脑不同区域水旋转基本动态参数的直接信息。我们发现，神经元和它们的预测密度的变化反映在水旋转的翻滚。这表明，T1？这些测量可以潜在地用于量化PD患者的SNc中的神经元损失以及可能的其他神经退行性病症。关于T1由于在用于测量的绝热脉冲期间有效磁场的扫描，因此与传统的T1 MRI相比，这种测量提供了独特的信息。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，但是我们预计这项技术将证明能够检测任何给定的感兴趣的大脑区域中的细胞丢失。

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.