Methods for Quantitative Neuroimaging of Tau Burden inPre-symptomatic AD

症状前 AD 中 Tau 负载的定量神经影像学方法

基本信息

批准号：
10390919
负责人：
Georges El Fakhri
金额：
$ 72.98万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-01 至 2027-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10390919
关键词：
Address Affinity Age Alzheimer&apos s Disease Amyloid Amyloid beta-Protein Amyloid deposition Behavior Binding Blood flow Blood specimen Brain Cerebrum Clinic Clinical Complement Complex Data Data Analyses Data Collection Data Set Deposition Differential Diagnosis Diffusion Disease Evolution Excision Exhibits Factor Analysis Future Generations Goals Gold Image Image Analysis Image Enhancement Imaging technology Individual Kinetics Logistics Magnetic Resonance Imaging Maps Measurement Measures Methodology Methods Modeling Motion Nature Network-based Pathology Patients Pattern Perfusion Phase Physiological Positron-Emission Tomography Property Protocols documentation Reaction Time Reporting Research Resolution Scanning Signal Transduction Structure Techniques Testing Time Tracer Training Water base deep learning deep learning model deep neural network follow-up healthy aging high resolution imaging human subject hyperphosphorylated tau image reconstruction imaging agent improved in vivo indexing innovative technologies insight kernel methods kinetic model learning strategy locus ceruleus structure molecular imaging nervous system disorder neuroimaging novel predictive modeling preservation quantitative imaging radiotracer reconstruction research study simulation spatiotemporal tau Proteins uptake

项目摘要

Whereas amyloid deposition tends to occur broadly throughout cortical regions and with relatively uniform pattern of progression over time, the distribution of tau is highly focal at the early stages of pathology and its propagation to other regions demonstrates a more complex spatiotemporal evolution. In addition the relatively lower abundance in brain of tau compared to amyloid imparts greater requirements for binding affinity and selectivity of tau radiotracers. Although second generation tau tracers reported within the past few years appear to have more favorable properties in this regard, all tau tracers studied to date have been reported to exhibit off-target binding to various substrates that can confound the quantification and interpretation of imaging data. The goal of this application is to develop innovative technologies that improve the quantification of tau PET imaging and enhance its utility in both research and eventual clinical settings. To address the focal nature of tau deposition especially at prodromal stages of disease, we propose a novel kernel-based reconstruction method that uses structural MR images as prior information and incorporates motion correction to obtain images with unprecedented spatial resolution, allowing improved localization and quantification of tau in small structures such as the rhinal cortex and the locus coeruleus. To mitigate the effects of off-target binding, we propose a kinetic analysis strategies to identify non-specific, tau-specific, and off-target components. We also propose modeling tactics to estimate maps of cerebral perfusion and to complement measures of tau burden as an additional index of brain function. Lastly, we propose deep learning strategies to gain new insights into the spreading of tau and to predict this progression in individual subjects.

而淀粉样蛋白沉积往往广泛发生在整个皮质区域并且具有相对均匀的模式随着时间的推移，tau 蛋白的分布在病理学及其传播的早期阶段高度集中到其他地区表现出更复杂的时空演化。另外相对较低与淀粉样蛋白相比，大脑中 tau 蛋白的丰度对结合亲和力和选择性提出了更高的要求 tau 放射性示踪剂。尽管过去几年报道的第二代 tau 示踪剂似乎已经在这方面有更有利的特性，据报道迄今为止研究的所有 tau 示踪剂都表现出脱靶现象与各种底物的结合可能会混淆成像数据的量化和解释。该应用的目标是开发创新技术来提高 tau PET 的定量成像并增强其在研究和最终临床环境中的实用性。解决 tau 蛋白的焦点性质特别是在疾病的前驱阶段，我们提出了一种新的基于内核的重建方法使用结构 MR 图像作为先验信息并结合运动校正来获取图像前所未有的空间分辨率，可以改善 tau 在小型结构（如如鼻皮质和蓝斑。为了减轻脱靶结合的影响，我们提出了一种动力学识别非特异性、tau 特异性和脱靶成分的分析策略。我们还建议建模评估脑灌注图并补充 tau 负荷测量作为附加指标的策略的大脑功能。最后，我们提出了深度学习策略，以获得对 tau 和 tau 的传播的新见解。预测个体受试者的这种进展。