A research and clinical tool for connectivity-based analysis of brainstem anatomy

描述(由申请人提供)：神经退行性综合征包括多种疾病，发病率很高，但治疗不充分。更好地了解选择性神经元脆弱性、区域结构-功能关系和系统连通性可以帮助我们磨练对发病机制的理解，确定潜在的治疗途径，并开发疾病指数。特别是，开发和验证一种测量疾病标志物的工具不仅有助于了解疾病的基本发病机制，而且有助于诊断(特别是在早期和潜在的可治疗阶段)以及临床分期、预后和治疗干预反应评估的必要性。为了满足未来临床研究的可行性标准，我们建议开发、验证并准备验证基于“S图像”连接性的参考框架作为DT-MRI分析的一种新的临床和研究工具。S图像是多维数据的有组织的直线表示，使得每个纤维束(纤维束的单体素细分)的数据根据它们到感兴趣区域(ROI)的曲线距离来表示。S图像框架将允许我们：1)解析单个脑干束；2)计算准确而具体的脑白质完整性测量；3)比较不同时间、不同个体和不同诊断的值。首先，我们将开发S图像软件框架，并使用小脑脚的活体和死后数据进行解剖学验证。然后，我们将收集初步数据，以设计一项未来的研究，使用神经学和神经认知功能作为结构-功能相关性的探针。定量神经认知测试与DT-MRI测量的相关性也将使我们能够阐明1)额叶受累，2)小脑受累，或3)额小脑断开对“额叶”执行功能的影响，这是导致神经退行性疾病致残的关键因素。我们建议：1)通过验证S图像允许我们检测白质病变，以及2)通过验证S图像检测复杂脑干区临床上有意义的病理性小脑脚改变的能力，我们有理由期望S图像也能够检测到其他复杂区域的病变。一个重要的假设是，认知域的解剖定位将允许我们使用行为测量来预测神经退行性变中白质疾病的解剖模式。第二个假设是，白质异常可能是变性的早期标志，因此可能先于行为或体积异常。尽管这是一个雄心勃勃的项目，但我们的团队处于独特的成功地位，因为我们拥有多学科的专业知识，以及将小脑/脑干成像与脊髓小脑性共济失调的病理生理学联系起来的长期成功合作历史。我们相信，开发和验证用于脑干和小脑病理分析的S图像框架是一条非常有希望的研究途径，将带来进一步的基础研究，为改进小脑变性的诊断、分期和治疗奠定基础，并提供一种适用于所有中枢神经系统疾病的方法。公共卫生相关性：项目叙事神经退行性疾病，如阿尔茨海默氏症、帕金森氏症和小脑性共济失调，对许多人的生活有毁灭性的影响。我们建议开发一种疾病标志物，不仅可以帮助了解大脑在疾病中的行为，而且可以作为诊断、评估疾病阶段、预测疾病进程和监测治疗反应的工具。具体地说，我们将开发“S图像”，这是一种新的分析框架，将从扩散张量磁共振成像中获取数据-一种观察水沿活体大脑白质束定向运动的方法。这不仅对神经退行性疾病有重要影响，而且对所有影响大脑的疾病，包括中风、感染和肿瘤都有重要影响。

DESCRIPTION (provided by applicant): The neurodegenerative syndromes comprise a wide spectrum of disease with significant morbidity yet inadequate therapy. A better understanding of the selective neuronal vulnerability, regional structure-function relationships, and systems connectivity could allow us to hone our understanding of pathogenesis, identify avenues of potential therapy, and develop an index of disease. In particular, development and validation of a tool to measure a disease marker could help not only to understand the basic pathogenesis but also with diagnosis (particularly in the early and potentially treatable stages) and the clinical imperatives of staging, prognosis, and evaluation of response to therapeutic interventions. In order to meet feasibility criteria for a future clinical study, we propose to develop, verify, and prepare to validate the "s-image" connectivity-based reference framework as a novel clinical and research tool for DT-MRI analysis. An s-image is an organized rectilinear representation of multidimensional data, such that data for each fiber bundlet (a single-voxel subdivision of a fiber bundle) are represented according to their curvilinear distance from a region of interest (ROI). The s-image framework will allow us: 1) to resolve individual brainstem tracts, 2) to calculate accurate and specific measures of white matter integrity, and 3) to compare values over time, across individuals, and across diagnoses. First we will develop the s-image software framework and perform anatomic validation using in vivo and post-mortem data from the cerebellar peduncles. Then, we will collect preliminary data to design a future study using neurologic and neurocognitive function as probes for structure-function correlations. Correlation of quantitative neurocognitive testing with DT-MRI measures will also allow us to elucidate what contribution 1) frontal involvement, 2) cerebellar involvement, or 3) frontocerebellar disconnection may make to "frontal" executive function, a key factor leading to disability from neurodegenerative disease. We propose that: 1) by verifying that s-images allow us to detect white matter pathology, and 2) by validating the ability of s-images to detect clinically significant pathological cerebellar peduncle changes in complex brainstem regions, it is reasonable to expect that s-images would also be able to detect pathological changes in other complex regions. An important subhypothesis is that the anatomic localization of cognitive domains will allow us to use behavioral measures to predict anatomic patterns of white matter disease in neurodegeneration. A second subhypothesis is that white matter abnormalities may be an early marker of degeneration and thus may precede behavioral or volumetric abnormalities. Although this is an ambitious project, our team is uniquely positioned to succeed because of our multidisciplinary expertise and long history of successful collaboration correlating cerebellar/brainstem imaging and pathophysiology of spinocerebellar ataxias. We believe that this proposal for development and validation of the s-image framework for analysis of brainstem and cerebellar pathology is a highly promising avenue of research that will beget further basic research, establish a basis for improved diagnosis, staging, and management of cerebellar degeneration, and provide an approach applicable to all central nervous system disease. PUBLIC HEALTH RELEVANCE: Project narrative Neurodegenerative diseases, such as Alzheimer's, Parkinson's, and cerebellar ataxia, have a devastating impact on many lives. We propose to develop a disease marker that not only could help to understand the behavior of the brain in disease, but also could be used as a tool for diagnosis, evaluation of the stage of disease, prediction of disease course, and monitoring response to therapy. Specifically, we will develop the "s-image," a new framework for analysis that will take data from diffusion tensor magnetic resonance imaging - a way to observe the directed motion of water along the white matter tracts in the living brain. This has important implications not only for neurodegenerative disease but for all conditions affecting the brain, including strokes, infections, and tumors.