Computational methods for regional hippocampal morphometry in AD

描述（由申请人提供）：PI是一名定量研究员，具有计算机科学背景，并在图像分析方法，计算机视觉和机器学习领域发表过论文。他的目标是通过在定量分析方面的优势以及在痴呆症和衰老的生物医学方面新获得的专业知识，使自己成为阿尔茨海默病（AD）和痴呆症的高效独立研究员。宾夕法尼亚大学功能神经成像中心主任、国际知名神经学家John Detre医学博士教授将担任主要导师。共同发起人John Trojanowski教授（医学博士）和Murray Grossman教授（医学博士）表示，他们将帮助PI获得痴呆症病理和生理学方面的专业知识，以及痴呆症对记忆、语言和思维的影响。该研究计划包括开发一个先进的框架，用于检测和跟踪海马和海马旁回解剖亚区结构和功能的变化，使用体内神经成像。利用这一框架，PI将评估AD相关变化在这些颞叶结构的解剖亚区不同的假设，因此，它们的形态学和生理学可用于早期和准确地预测AD。这些假设将通过挖掘阿尔茨海默病患者、阿尔茨海默病风险人群和老年对照者的纵向MRI图像数据的庞大数据库来验证，该数据库是由NIA/NIH最近发起的ADNI倡议生成的。的相关性。随着婴儿潮一代的年龄增长，受阿尔茨海默病困扰的美国家庭数量以及由此带来的社会经济负担预计将急剧增加。虽然目前还没有治愈阿尔茨海默病的方法，但人们正在努力开发能够阻止或减缓导致阿尔茨海默病的神经退行性过程的药物。为了有效，这些治疗方法需要早期发现。派的职业目标，由

DESCRIPTION (provided by applicant): The PI is a quantitative researcher with a background in computer science and a record of publications in the areas of image analysis methodology, computer vision and machine learning. His objective is to establish himself as a highly productive independent researcher of Alzheimer's disease (AD) and dementia by complimenting his strengths in quantitative analysis with a newly acquired expertise in the biomedical aspects of dementia and aging. Prof. John Detre MD, the head of Penn's Center for Functional Neuroimaging and an internationally renowned neurologist, has offered to serve as the principal mentor. The co-sponsors, Prof. John Trojanowski, MD, PhD and Prof. Murray Grossman, MD, EdD have offered to help the PI acquire expertise in the pathology and physiology of dementia as well as its impact on memory, language and thinking. The research plan involves developing an advanced framework for detecting and tracking structural and functional changes in the anatomical subregions of the hippocampus and parahippocampal gyrus using in vivo neuroimaging. Using this framework, the PI will evaluate the hypotheses that AD-related changes differ across the anatomical subregions of these temporal lobe structures and, consequently, that their morphology and physiology can be used to predict AD early and accurately. These hypotheses will be tested by mining the massive database of longitudinal MRI image data of AD patients, people at risk for AD and elderly controls, which is being generated by the ADNI initiative launched recently by the NIA/NIH. RELEVANCE. As the baby boom generation ages, the number of US families devastated by AD and the associated financial burden on the society is expected to increase dramatically. While no cure for AD is known, a sizable effort is underway in developing pharmaceutical agents that may halt or slow down the neurodegenerative processes that cause AD. To be effective, these treatments will require early detection. The Pi's career objectives, addressed by the research proposed in this application, are to improve the accuracy of early AD diagnosis and to develop non-invasive analytic tools that would aid drug development and broaden what we know about the pathology and physiology of AD.