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

用于基于连通性的脑干解剖学分析的研究和临床工具

• 批准号: 7588414
• 负责人: SARAH H YING
• 金额: $ 22.86万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7588414
• 关键词: Address; Affect; Alzheimer' s Disease; Anatomy; Animals; Area; Basic Science; Behavior; Behavioral; Brain; Brain Stem; Brain imaging; Cause of Death; Central Nervous System Diseases; Cerebellar Ataxia; Cerebellar Diseases; Cerebellar degeneration; Cerebellum; Characteristics; Clinical; Clinical Research; Cognitive; Collaborations; Communities; Complex; Computer software; Condition; Data; Descriptor; Destinations; Development; Diagnosis; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Disease Marker; Ensure; Environment; Evaluation; Feasibility Studies; Fiber; Foundations; Fresh Tissue; Functional disorder; Future; Gold; Grant; Hereditary Disease; Histopathology; Image; Image Analysis; Imagery; Individual; Infection; International; Investments; Label; Life; MRI Scans; Magnetic Resonance Imaging; Malignant Neoplasms; Marshal; Measurement; Measures; Methods; Microscopic; Modeling; Monitor; Morbidity - disease rate; Motion; Nerve Degeneration; Neurocognitive; Neurodegenerative Disorders; Neurologic; Neurons; Parkinson Disease; Pathogenesis; Pathology; Pathway interactions; Patients; Pattern; Pilot Projects; Positioning Attribute; Process; Prospective Studies; Public Health; Recording of previous events; Recruitment Activity; Research; Research Design; Research Infrastructure; Research Project Grants; Resolution; Resources; Scanning; Shapes; Signal Transduction; Software Tools; Specimen; Spinocerebellar Ataxias; Staging; Standards of Weights and Measures; Stroke; Structure; Structure-Activity Relationship; Supratentorial; Syndrome; System; Testing; Therapeutic Intervention; Three-Dimensional Imaging; Time; Torsion; Type 6 Spinocerebellar Ataxia; United States National Institutes of Health; Universities; Validation; Water; White Matter Disease; Work; World Health Organization; base; behavior measurement; clinically significant; cognitive function; cohort; design; diagnosis evaluation; disability; executive function; gray matter; image processing; improved; in vivo; indexing; interest; morphometry; multidisciplinary; neurocognitive test; neuroimaging; novel; outcome forecast; response; software development; tissue fixing; tool; tumor; white matter; white matter change

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.

描述（由申请人提供）：神经退行性综合征包括广泛的疾病，具有显著的发病率，但治疗不足。更好地了解选择性神经元的脆弱性，区域结构-功能关系和系统连接性可以使我们加深对发病机制的理解，确定潜在治疗的途径，并制定疾病指数。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基本的发病机制，而且有助于诊断（特别是在早期和潜在的可治疗阶段）以及分期、预后和评估对治疗干预的反应的临床必要性。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“S-图像”的连接性为基础的参考框架作为一种新的临床和研究工具DT-MRI分析。s图像是多维数据的有组织的直线表示，使得每个纤维束的数据（纤维束的单体素细分）根据它们与感兴趣区域（ROI）的曲线距离来表示。s-图像框架将允许我们：1）解析个体脑干束，2）计算白色物质完整性的准确和具体的测量，以及3）比较随时间推移的值，跨个体，跨诊断。首先，我们将开发s-image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，我们将收集初步的数据，以设计一个未来的研究，使用神经和神经认知功能作为探针的结构功能相关性。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）额小脑分离可能对“额叶”执行功能（导致神经退行性疾病残疾的关键因素）的贡献。我们建议：1）通过验证S-图像允许我们检测白色物质病理，以及2）通过验证S-图像检测复杂脑干区域中临床上显著的病理性小脑脚变化的能力，合理地预期S-图像也将能够检测其它复杂区域中的病理变化。一个重要的子假设是，认知域的解剖定位将使我们能够使用行为测量来预测神经退行性疾病中白色疾病的解剖模式。第二个亚假设是，白色物质异常可能是退化的早期标志，因此可能先于行为或体积异常。虽然这是一个雄心勃勃的项目，但由于我们的多学科专业知识和与小脑/脑干成像和脊髓小脑共济失调的病理生理学相关的长期成功合作，我们的团队具有独特的成功优势。我们相信，这一建议的发展和验证的S-图像框架分析脑干和小脑病理学是一个非常有前途的研究途径，将引发进一步的基础研究，建立一个基础，改善诊断，分期和管理小脑变性，并提供一个方法适用于所有中枢神经系统疾病。公共卫生关系：神经退行性疾病，如阿尔茨海默氏症，帕金森氏症和小脑共济失调，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记物，不仅可以帮助了解疾病中大脑的行为，而且可以用作诊断，评估疾病阶段，预测疾病过程和监测治疗反应的工具。具体来说，我们将开发“s图像”，这是一种新的分析框架，它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中白色物质束沿着定向运动的方法。这不仅对神经退行性疾病，而且对影响大脑的所有疾病，包括中风，感染和肿瘤都有重要意义。