Probabilistic White and Gray Matter Atlas of the Adult Human Brain

成人大脑的概率白质和灰质图谱

• 批准号: 8303740
• 负责人: Konstantinos Arfanakis
• 金额: $ 17.91万
• 依托单位: ILLINOIS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-15 至 2014-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8303740
• 关键词: Address; Adopted; Adult; Affect; Age; Architecture; Atlases; Brain; Clinical; Complex; Data; Data Set; Databases; Development; Diagnostic; Diffusion; Diffusion Magnetic Resonance Imaging; Fiber; Human; Image; Informatics; Investigation; Label; Magnetic Resonance Imaging; Measurement; Morphologic artifacts; Neurons; Performance; Play; Population; Productivity; Research; Resolution; Resources; Role; Scanning; Seeds; Semantics; Skeleton; Structure; Techniques; Time; Work; base; brain tissue; digital; gray matter; in vivo; innovation; interest; neuroimaging; tool; web site; white matter

DESCRIPTION (provided by applicant): Diffusion MRI provides a wealth of information regarding the micro-structural integrity and connectivity of the human brain in vivo. High angular resolution diffusion imaging (HARDI) allows more accurate characterization of complex neuronal micro-architecture than conventional diffusion tensor imaging (DTI), and its once low scanning efficiency has recently become comparable to that of DTI. Therefore, HARDI is rapidly becoming a powerful research and clinical tool. Spatial normalization of HARDI information is necessary in a) whole-brain voxel-wise investigations, b) region-of-interest (ROI) studies comparing the underlying white matter fiber directions, and c) tract-specific HARDI investigations with automated atlas-based tract segmentation. The accuracy of such studies depends on the accuracy of spatial normalization. Accurate spatial normalization requires a high-quality HARDI template representative of the human brain. Study-specific templates can be constructed, but have several limitations. Furthermore, in the case of tract-specific HARDI investigations, accurate tract segmentation also requires that the HARDI template is accompanied by a set of semantic labels accurately delineating different white matter tracts (forming an accurate white matter atlas). Currently available white matter digital atlases are problematic, since they have been either generated based on anatomical landmarks, thus mixing tracts with substantially different roles, or using DTI tractography, which fails in regions with crossing fibers. Therefore, a detailed probabilistic brain atlas is needed, containing a) a high-quality HARDI template representative of the human brain, and b) accurate white matter labels generated with HARDI tractography. Since spatial misalignment can be detrimental in voxel-wise studies of white matter micro-structure, a number of investigations have adopted an alignment-invariant approach where information is first projected onto a white matter "skeleton", followed by voxel-wise analysis on the skeleton. Tract-specific studies using atlas-based segmentation can also be negatively affected by atlas-to-subject misregistration, and could benefit from the alignment-invariant approach if a skeletonized version of an accurate white matter atlas was available. Finally, information on both white and gray matter is often combined in neuroimaging research, and although it is possible to spatially match independently generated white and gray matter atlases, anatomical correspondence between atlases is not guaranteed due to registration errors, as well as due to anatomical differences between the populations used for atlas construction. Therefore, the objective of this project is to develop an accurate, comprehensive white and gray matter probabilistic atlas of the adult human brain (both conventional and skeletonized), also containing multi-channel, artifact-free anatomical MRI and HARDI information. Successful completion of this work will bring forth a powerful set of tools that will increase the accuracy of both voxel-wise and tract-specific investigations of the adult human brain micro-structure. The results of this project will dramatically enhance the role of diffusion MRI as a diagnostic tool for a wide range of clinical problems. PUBLIC HEALTH RELEVANCE: Diffusion MRI provides a wealth of information regarding the micro-structural integrity and connectivity of the human brain in vivo. The objective of this project is to develop an accurate, comprehensive white and gray matter digital atlas of the adult human brain, also containing high-quality anatomical and diffusion MRI information. Successful completion of this work will bring forth a powerful set of tools that will increase the accuracy of both voxel-wise and tract-specific investigations of the adult human brain micro-structure.

描述（由申请人提供）：扩散MRI提供了大量关于人体大脑在体内的微观结构完整性和连通性的信息。高角分辨率弥散成像（HARDI）可以更准确地表征复杂的神经元微结构比传统的扩散张量成像（DTI），其一度低的扫描效率最近已成为可比的DTI。因此，HARDI正在迅速成为一种强大的研究和临床工具。HARDI信息的空间标准化在以下研究中是必要的：a）全脑体素研究，B）比较潜在的白色物质纤维方向的感兴趣区域（ROI）研究，以及c）具有自动化的基于图谱的束分割的束特异性HARDI研究。这种研究的准确性取决于空间归一化的准确性。精确的空间归一化需要代表人脑的高质量HARDI模板。可以构建研究特定模板，但有几个限制。此外，在特定于束的HARDI研究的情况下，准确的束分割还需要HARDI模板伴随有一组语义标签，其准确地描绘不同的白色物质束（形成准确的白色物质图谱）。目前可用的白色物质数字图谱是有问题的，因为它们或者是基于解剖标志生成的，因此混合了具有实质上不同作用的纤维束，或者是使用DTI纤维束成像，其在区域中失败 有交叉纤维。因此，需要一个详细的概率脑图谱，包含a）代表人脑的高质量HARDI模板，以及B）使用HARDI纤维束成像生成的准确白色物质标签。由于空间错位可能是有害的白色物质的微观结构的体素明智的研究，一些调查已经采用了一个不变量的方法，其中信息首先投影到一个白色物质的“骨架”，然后由体素明智的骨架上的分析。使用基于图谱的分割的特定区域研究也可能受到图谱与受试者配准不良的负面影响，并且如果准确的白色物质图谱的简化版本可用，则可以从不变性方法中受益。最后，在神经影像学研究中，通常将关于白色和灰质的信息结合起来，尽管可以在空间上匹配独立生成的白色和灰质图谱，但由于配准误差以及用于图谱构建的群体之间的解剖差异，图谱之间的解剖对应性不能得到保证。因此，本项目的目标是开发一个准确、全面的成人大脑（常规和非离子化）白色和灰质概率图谱，其中还包含多通道、无伪影的解剖MRI和HARDI信息。这项工作的成功完成将带来一套强大的工具，这将提高成年人大脑微观结构的体素和特定区域研究的准确性。该项目的结果将大大提高扩散MRI作为诊断工具的作用，为广泛的临床问题。 公共卫生关系：扩散MRI提供了丰富的信息，有关的微观结构的完整性和连接的人脑在体内。该项目的目标是开发一个准确，全面的成年人脑白色和灰质数字图谱，还包含高质量的解剖和扩散MRI信息。这项工作的成功完成将带来一套强大的工具，这将增加的准确性， 对成年人大脑微观结构的体素和特定区域的研究。