ALGORITHMS FOR FUNCTIONAL AND ANATOMICAL BRAIN ANALYSIS

大脑功能和解剖分析算法

• 批准号: 7602572
• 负责人: MICHAEL I MILLER
• 金额: $ 43.16万
• 依托单位: HUGO W. MOSER RES INST KENNEDY KRIEGER
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7602572
• 关键词: Algorithms; Alzheimer' s Disease; Anatomy; Arts; Attention; Basal Ganglia; Brain; Brain Diseases; Brain Mapping; Brain imaging; Brain region; Cell Nucleus; Cerebral Ischemia; Childhood; Childhood Brain Neoplasm; Clinical; Cognitive; Cognitive deficits; Communities; Computer Retrieval of Information on Scientific Projects Database; Daily; Data; Dementia; Depth; Development; Developmental Disabilities; Diffusion; Diffusion Magnetic Resonance Imaging; Discipline; Disease; Drug Formulations; Epilepsy; Fiber; Funding; Generations; Grant; Gray unit of radiation dose; Growth; Hippocampus (Brain); Human; Imagery; Imaging technology; Impaired cognition; Institution; Investigation; Ischemia; Knowledge; Life; Magnetic Resonance; Magnetic Resonance Imaging; Maps; Measurement; Memory; Mental Depression; Metabolic Diseases; Methodology; Methods; Metric; Mood Disorders; Multiple Sclerosis; Neocortex; Nerve Degeneration; Neuroanatomy; Neurobiology; Neurons; Normal tissue morphology; Parahippocampal Gyrus; Pattern; Pediatrics; Physiological; Prefrontal Cortex; Process; Property; Psychiatry; Range; Reading; Research; Research Personnel; Resolution; Resources; Schizophrenia; Shapes; Site; Source; Staging; Standards of Weights and Measures; Stroke; Structure; Surface; System; Thalamic structure; Trauma; Traumatic Brain Injury; United States National Institutes of Health; Work; biomedical informatics; computerized data processing; data structure; design; frontal lobe; gray matter; reconstruction; shape analysis; size; software systems; tool; tool development; tumor; white matter

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The development of high dimensional brain mapping in the field of computational anatomy (CA) and its integration with other state-of-the-art brain imaging technologies continues to be a unique opportunity to study both the underlying neurobiology of brain structure and its connections, and the relationships between brain structure abnormalities and patterns of cognitive deficits. Such mapping tools permit the precise formulation of hypotheses concerning brain structure and function determined by patterns of connectivity and shape particularly in development and neurodegeneration. Over the past fifteen years, many investigators have been studying the shape and structure of the human brain in multiple anatomies in common coordinates (e.g.8, 33, 39, 41, 42, 61, 63, 65, 80, 88, 90, 101, 136, 151, 152). Further, emerging methodologies that integrate anatomical and functional information from multiple data provide an opportunity to ask detailed anatomical questions in a single set of standard coordinates. It is now possible to perform functional measurements and anatomical measurements at roughly 1.0 mm resolution. Systems now exist in isolation of each other for examining gray matter reconstructions of the neocortex, studying the gyrification, folding and sulcal patterning of the gray/white boundary of the neocortex, as well as the anatomical size and shape of deep nuclei in the brain such as the hippocampus, thalamus and caudate. Our own group has been involved in the development of these tools, including surface and volume mapping tools, cortical and surface generation tools, gyral and sulcal curve generation and the analysis of these structural data. Designed and developed in the 1st grant period, these methods are now being used by investigators around the world in structural studies of the neocortex and deep nuclei in a variety of neurodevelopmental and neurodegenerative processes. Recent developments in observing the activation of brain regions via functional magnetic resonance imagery (fMRI) while different tasks are being processed are now providing a clear look at the working of this marvellous machinery. Such studies are expected to reveal an in depth understanding of the intricate and effortless processing humans can perform while they go about in their daily lives. Knowledge gained from such studies is expected to provide better understanding of the normal mechanisms and aberrations to these mechanisms in developmental situations. Furthermore, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) provides useful physiological information noninvasively, not only about the fiber structure of normal tissue, but also about its changes in development, disease and degeneration. It has already been shown to be of value in studies of neuroanatomy, fiber connectivity, and brain development. DT-MRI has been used in the investigation of cerebral ischemia, brain maturation and traumatic brain injury. It also promises to further our understanding of brain disorders and abnormalities such as stroke, tumors and metabolic disorders, epilepsy, multiple sclerosis, schizophrenia, Alzheimers disease and cognitive impairment. Our collaborators have now begun to use fMRI and DT-MRI data to understand the intricate functional properties of the whole brain as well as the neocortex. To this end, the aims of TRD4 are to extend previously developed CA tools for the neocortex to the whole brain and develop additional CA tools for analyzing functional and connectivity data in brain and cortical structures. The tools will be made available to the wider scientific community. In particular, the proposed developments should benefit a wide range of clinical disciplines from psychiatry to pediatrics including those funded by the following NIH grants: 1. developmental disability (Denckla, Mostofsky, Cutting, Scarborough, Naidu) - perform functional and longitudinal analysis of cognitive processes on frontal lobe, basal ganglia and subcortical regions associated with developmental disability (Aims 1, 4, 5) 2. attention and memory (Yantis, Stark and Courtney-Faruqee)  perform structural and functional analysis of cognitive processes on hippocampus and associated cortical surfaces implicated in attention and memory (Aims 1, 4, 5) 3. neurodegeneration/dementia (Albert, Csernansky, Reading) - perform structural and functional analysis of stages of neurodegeneration associated with the hippocampus, caudate, cingulate, parahippocampal gyrus, prefrontal cortex as well as gyral and sulcal folds of these structures (Aims 1, 4, 5), and co-register neuronal connections (Aims 2,3) 4. pediatric ischemia/trauma (Graham, Hoon, Christensen, Levin) - perform structural and functional analysis of stages of neurodegeneration associated with white matter tracts and structures (Aims 1, 4, 5), and co-register neuronal connections (Aims 2,3) during growth 5. Stroke (Hillis) - perform structural and functional analysis of developmental stages of neuronal diseases (Aims 1, 4, 5), and co-register neuronal connections (Aims 2, 3) 6. pediatric brain tumors (Horska) - perform structural and functional analysis of stages of neurodegeneration associated with white matter tracts and structures (Aims 1, 4, 5), and coregister neuronal connections (Aims 2,3) during growth 7. depression and mood disorders (Botteron, Pearlson)  perform structural and functional analysis of developmental stages of diseases associated with the prefrontal cortex and hippocampus as well as gyral and sulcal folds of these structures (Aims 1, 4, 5); co-register neuronal connections between substructures (Aims 3, 4). 8. biomedical informatics (Rosen)  perform large scale multi-site shape analysis of brain structures and substructures (Aims 1, 4, 5) and of neuronal connections (Aims 2, 3) Our specific aims are to integrate such structural and functional analysis tools into a software system by developing the following algorithms: Aim 1: Large Deformation Diffeomorphic Metric Mapping (LDDMM) for landmarks, curves, surfaces and volumes in whole brain analysis and registration; Aim 2: LDDMM for Diffusion Tensor images (LDDMM-DT) and tensor algebra; Aim 3: LDDMM for longitudinal and developmental analysis; Aim 4: LDDMM and signal processing methods for Functional Anatomy Building a software system that supports the data structures of curves, surfaces, and scalar and tensorial lattices of volumes will be essential in utilizing methods developed in TRD1 and TRD3 in studying brain structure and function.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 在计算解剖学领域（CA）中高维大脑映射的发展 它与其他最先进的大脑成像技术的集成仍然是独特的 有机会研究大脑结构及其联系的潜在神经生物学以及 大脑结构异常和认知缺陷模式之间的关系。这样的映射 工具允许精确制定有关大脑结构和功能确定的假设 通过连通性和形状的模式，尤其是在发育和神经变性方面。 在过去的十五年中，许多研究人员一直在研究 常见坐标中多个解剖学中的人脑（例如8、33、39、41、42、61、63、63、65、80、88， 90、101、136、151、152）。此外，整合解剖学和功能的新兴方法学 来自多个数据的信息提供了一个机会，可以在单个中询问详细的解剖问题 一组标准坐标。现在可以执行功能测量和解剖学 分辨率约为1.0毫米的测量。现在的系统彼此孤立存在 检查新皮层的灰质重建，研究旋转，折叠和沟渠 新皮层的灰色/白色边界的图案，以及解剖学的大小和形状 大脑中的深核，例如海马，丘脑和尾状。 我们自己的小组参与了这些工具的开发，包括表面和音量 映射工具，皮质和表面生成工具，陀螺和沟曲线的产生以及 这些结构数据的分析。这些方法是在第一个赠款期间设计和开发的 现在被世界各地的调查人员在新皮层和深层的结构研究中使用 各种神经发育和神经退行性过程中的核。 通过功能磁性观察大脑区域激活的最新发展 共鸣图像（fMRI）在处理不同的任务时，现在可以清楚地了解 这种奇妙的机械的工作。这些研究有望揭示深度 了解人类在进行时可以执行复杂而轻松的处理 他们的日常生活。从此类研究中获得的知识有望更好地了解 在发育情况下这些机制的正常机制和畸变。 此外，扩散张量磁共振成像（DT-MRI或DTI）提供了有用的 生理信息无创，不仅与正常组织的纤维结构有关 关于其发育，疾病和变性的变化。它已经被证明是 在神经解剖学，纤维连通性和大脑发育的研究中的价值。 DT-MRI已被使用 在研究脑缺血，脑部成熟和创伤性脑损伤时。这也有望 为了进一步了解脑部疾病和异常，例如中风，肿瘤和 代谢疾病，癫痫，多发性硬化症，精神分裂症，阿尔茨海默氏病和认知 损害。 我们的合作者现在已经开始使用fMRI和DT-MRI数据来了解复杂的 整个大脑以及新皮层的功能特性。为此，TRD4的目标是 扩展了先前开发的新皮层的CA工具到整个大脑，并开发出其他CA 用于分析大脑和皮质结构中功能和连通性数据的工具。工具将是 提供给更广泛的科学界。特别是，拟议的发展应该 受益于从精神病学到儿科的广泛临床学科，包括由 遵循NIH赠款： 1。发育障碍（Denckla，Mostofsky，Cutt，Scarborough，Naidu） - 执行 对额叶，基底神经节和纵向分析的功能和纵向分析 与发育障碍相关的皮质下区域（目标1、4、5） 2。注意与记忆（Yantis，Stark和Courtney-Faruqee）执行结构和 海马和相关皮质表面上认知过程的功能分析 与注意力和记忆有关（目标1、4、5） 3。神经变性/痴呆症（Albert，Csernansky，阅读） - 执行结构和功能 分析与海马，尾状，扣带相关的神经变性阶段 这些结构的帕拉希峰环，前额叶皮层以及陀螺和沟褶 （目标1、4、5）和共同注册的神经元连接（目标2,3） 4。小儿缺血/创伤（Graham，Hoon，Christensen，Levin） - 执行结构和 与白质区相关的神经变性阶段的功能分析 结构（目标1、4、5）和在生长过程中共同注册的神经元连接（目标2,3） 5。卒中（Hillis） - 对神经元的发育阶段进行结构和功能分析 疾病（目标1、4、5）和共同注册的神经元连接（目标2、3） 6。小儿脑肿瘤（HORSKA） - 对阶段进行结构和功能分析 与白质区和结构相关的神经变性（目的1、4、5）和核焦点 在生长期间神经元连接（目标2,3） 7。抑郁症和情绪障碍（波特顿，珍珠）执行结构和功能 分析与前额叶皮层相关的疾病的发育阶段和 这些结构的海马以及陀螺和沟褶（目标1、4、5）；共同注册 下部结构之间的神经元连接（目标3，4）。 8。生物医学信息学（Rosen）进行大规模的大脑形状分析 结构和子结构（目标1，4，5）和神经元连接（目标2，3） 我们的具体目的是将这种结构和功能分析工具集成到软件中 通过开发以下算法来系统： AIM 1：大变形差异度度映射（LDDMM），地标，曲线，表面 和整个大脑分析和注册中的数量； AIM 2：用于扩散张量图像（LDDMM-DT）和张量代数的LDDMM； 目标3：lddmm用于纵向和发育分析； AIM 4：功能解剖结构的LDDMM和信号处理方法 构建支持曲线，表面和标量数据结构的软件系统，并 体积的张力晶格对于利用在trd1和trd3中开发的方法至关重要 研究大脑结构和功能。