Estimation of Plaque Burden in Alzheimer's Mouse Models using SPECT Imaging

描述(申请人提供)：拟议研究的总体目标是开发体内成像方法，用于使用SPECT或替代核成像方式对转基因小鼠的斑块进行检测和分类。降低β-淀粉样蛋白(A2)斑块负荷是阿尔茨海默病(AD)治疗的主要目标之一。已经建立了转基因阿尔茨海默病小鼠模型，在小鼠大脑中进行A2的体内成像将有助于研究斑块发展和测试可能治愈人类阿尔茨海默病的药物。然而，由于成像系统的灵敏度和/或分辨率不足或缺乏良好的对比剂机制或放射性示踪剂的特异性，微尺度斑块的异质性结构使得在体内检测和定量斑块分布的方法具有挑战性。通过使用基于数学观察者和随机目标模型的新型计算算法作为图像重建的替代技术，这些问题可以在很大程度上被克服。这些算法利用关于斑块分布和成像系统的噪声特性的先验知识，基于观察数据和斑块负荷的潜在阶段之间的最佳匹配来做出分类决策。应聘者在K99阶段的培训将提供在这一跨学科领域建立自己的技能，也是她过去在SPECT/PET仪器和图像重建方面经验的合理延伸。这种培训是为了适应应聘者在获取神经科学知识和技能方面的需要。除了授课培训外，她还将在范德比尔特大学导师的监督下，获得斑块研究和AD转基因小鼠模型小动物成像方面的实验室培训。这项培训与这些导师目前的研究很好地协调一致，并将作为具体目标I.A的一部分进行，其中体视学斑块研究将有助于确定斑块分布的统计对象模型。具体目标I.A还将包括对二进制分类方法的计算研究，以从噪声投影数据中检测模拟斑块分布的存在。目标I.B的目的是进一步提高应聘者在开发SPECT扫描仪系统模型方面的技能。这一培训加上他过去在PET系统的培训，将使她能够使用最合适的SPECT或PET系统进行R00研究。到K99阶段结束时，她将拥有开发对象模型和分类方法的技能。具体目标二.a和二.b概述R00研究，以探索使用三类观察者分析的可行性，既有实验幻影，也有动物扫描。这项研究的最终目标是获取不同年龄段的转基因小鼠的扫描结果，并准确地对斑块负荷的阶段进行分类。候选人的长期目标是开发信号检测和模式识别工具，以克服当前放射性示踪剂的实际限制，同时保持其在AD研究中的实施。 公共卫生相关性：我的研究提出了使用转基因小鼠模型进行阿尔茨海默病(AD)分子成像的新计算技术。这些技术可能适用于研究AD的新的放射性示踪剂和治疗方法。有可能将这些方法转化为人类，以便在非常早期的阶段检测AD。

DESCRIPTION (provided by applicant): The overall goal of the proposed research is to develop in vivo imaging methods for plaque detection and classification in transgenic mice using SPECT or alternative nuclear imaging modalities. The reduction of beta-amyloid (A2) plaque burden is one of the main therapeutic objectives for the treatment of Alzheimer's disease (AD). Transgenic mouse models of AD have been created, and in vivo imaging of A2 in a mouse brain would facilitate the study of plaque development and testing of drugs that could potentially cure AD in human. However, the heterogeneous plaque structure of micro-scale range makes an in vivo approach to detecting and quantifying the plaque distribution challenging due to insufficient sensitivity and/or resolution of imaging systems or a lack of good contrast mechanism or radiotracer specificity. These problems can be largely overcome by using novel computational algorithms based on mathematical observers and stochastic object models as an alternative technique to image reconstruction. These algorithms take advantage of prior knowledge about plaque distributions and the noise characteristics of an imaging system to make classification decisions that are based on the best match between the observed data and the underlying stage of plaque burden. The candidate's training in the K99 phase will provide skills to establish herself in this interdisciplinary field, and is also a logical extension of her past experiences in SPECT/PET instrumentation and image reconstruction. This training is adapted to the candidate's needs in acquiring knowledge and skills in neuroscience. In addition to didactic training, she will obtain laboratory training in plaque studies and small-animal imaging of transgenic mouse models of AD under the supervision of mentors at Vanderbilt. This training is well-coordinated with the current research of these mentors, and will be carried out as a part of specific aim I.a, where the stereological plaque studies will help to define a statistical object model of plaque distributions. Specific aim I.a will also include computational studies of binary classification methods to detect the presence of simulated plaque distributions from noisy projection data. The objective of aim I.b is to further advance the candidate's skill in developing system models for SPECT scanners. This training together with he past training in PET systems will allow her to perform the R00 research with the most suitable SPECT or, alternatively, PET systems. By the end of the K99 phase, she will have the skills for developing object models and classification methods. Specific aims II.a and II.b outline R00 studies to explore the feasibility of using a three-class observer analysis with both experimental phantoms and animal scans. The ultimate goal of this study is to acquire scans of transgenic mice from different age groups and to accurately classify the stage of plaque burden. The candidate's long-term goal is to develop signal detection and pattern recognition tools to overcome the practical limitations of current radiotracers while maintaining her focus on their implementation in AD research. PUBLIC HEALTH RELEVANCE: My studies propose new computational techniques for conducting molecular imaging of Alzheimer's disease (AD) using transgenic mouse models. These techniques are likely to be applicable for studying new radiotracers and therapies for AD. There is a potential for translating these methods to human for detecting AD at very early stages.