Quantitative Magnetization Transfer Imaging for Early Detection of Alzheimer's Disease

项目摘要 阿尔茨海默病(AD)是导致痴呆的最常见原因，目前，一种不可逆转的神经病- 在美国，生殖性疾病的疾病负担不断增加。临床管理和脱贫 AD新疗法的发展将使fi受益于早期可重复性、健壮和非侵入性的标志物 活体AD病理，但没有这样的工具在常规临床实践中得到很好的确立。定量磁化 转移(QMT)是一种基于MRI的技术，用于检测微结构组织的变化，如脱髓鞘和 大分子的存在，包括淀粉样β蛋白。对艾米的多个方面的敏感性- Loid/tau/神经变性框架在单一、快速的诊断中为淀粉样蛋白PET提供了一种有前途的替代方案 和高分辨率影像检查。我的初步fi结论表明，使用混合态自由理论 在我的课题组开发的进动中，QMT图像可以在1 mm各向同性的活体12分钟内获得 具有良好的信噪比的分辨率。此外，通过与认知正常但淀粉样蛋白阳性的正电子发射计算机断层扫描直接比较 研究主题：qmt似乎对淀粉样β蛋白的早期积累和之前的文献中的firms敏感。 关于AD中QMT汇率上升的报道。我的提案旨在解决剩余的技术挑战 通过优化收购以提高对淀粉样β蛋白的敏感性来包围QMT(目标1)并开发 一种基于神经网络的重建流水线，大大减少了后处理时间，改善了重建流水线的性能 对磁fi不均匀的稳健性(目标2)，这在定量参数中产生偏差。这些 偏向对于抑制大脑深处的偏向尤其重要，据说在那里淀粉样β蛋白的积聚 开始于公元后。在目标3中，我将进行一项初步研究，以比较所建议的QMT方法对In的敏感性 活体淀粉样β蛋白在认知正常人群中直接转化为淀粉样蛋白PET。总之，这将使QMT成为一种 体内淀粉样蛋白的替代标志物及其在监测AD进展中的作用的进一步临床研究 对治疗的反应。

Project Summary Alzheimer's disease (AD) is the most common cause of dementia and, at present, an irreversible neurode- generative disease with an ever-increasing disease burden in the United States. Clinical management and de- velopment of novel therapeutics for AD will benefit from reproducible, robust and non-invasive markers of early in vivo AD pathology, but no such tools are well-established in routine clinical practice. Quantitative magnetization transfer (qMT) is an MRI based technique for detecting microstructural tissue changes such as demyelination and the presence of macromolecules, including amyloid beta protein. This sensitivity to multiple aspects of the amy- loid/tau/neurodegeneration framework offers a promising diagnostic alternative to amyloid PET in a single, rapid and high-resolution imaging exam. My preliminary findings suggest that, using the theory of hybrid state free precession developed in my research group, qMT images can be acquired in vivo in 12 minutes at 1mm isotropic resolution with good SNR. Additionally, by direct comparison to PET in a cognitively normal but amyloid positive subject, qMT appears to be sensitive to the early accumulation of amyloid beta and confirms previous literature reports of increased qMT exchange rates in AD. My proposal aims to solve the remaining technical challenges surrounding qMT by optimizing the acquisition for improved sensitivity to amyloid beta (Aim 1) and developing a neural network based reconstruction pipeline to substantially reduce the post-processing time and improve its robustness to magnetic field inhomogeneities (Aim 2), which create biases in the quantitative parameters. These biases are particularly important to curtail in the deep brain, where the accumulation of amyloid beta is purported to begin in AD. In Aim 3, I will perform a pilot study to compare the proposed qMT method's sensitivity for in vivo amyloid beta in a cognitively normal population directly to amyloid PET. Together, this will establish qMT as a surrogate marker for in vivo amyloid and motivate further clinical studies on its utility in monitoring AD progression and response to therapy.