Exploratory Analysis Tools for Developmental Studies of Brain Microstructure with Diffusion MRI

利用扩散 MRI 进行脑微结构发育研究的探索性分析工具

• 批准号: 10645844
• 负责人: Ebrahim Ebrahim
• 金额: $ 25.22万
• 依托单位: KITWARE, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-23 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10645844
• 关键词: Acceleration; Adolescence; Adolescent; Adolescent Development; Adult; Affect; Algorithms; Anatomy; Antipsychotic Agents; Automobile Driving; Bipolar Disorder; Brain; Child Development; Child Health; Communities; Computer software; Consumption; Data; Data Set; Data Sources; Development; Diagnosis; Diffusion; Diffusion Magnetic Resonance Imaging; Dimensions; Disease; Effectiveness; Environmental Health; Fiber; Generations; Image; Life; Longitudinal Studies; Magnetic Resonance Imaging; Measures; Mental Health; Mental disorders; Methodology; Modeling; Mood Disorders; Neurites; Neurobiology; Pharmaceutical Preparations; Population; Process; Research; Resolution; Software Framework; Software Tools; Specificity; Speed; Structure; Symptoms; Techniques; Time; Visualization; Work; adolescent brain development; cloud based; cognitive development; data exploration; deep learning; deep learning model; density; early onset; experience; flexibility; graphical user interface; improved; indexing; longitudinal analysis; longitudinal dataset; multilevel analysis; neural; neuroimaging; open source; regional difference; research and development; response; serial imaging; software development; statistics; suicidal risk; tool; white matter

Project Summary Diffusion MRI analysis is the primary tool for studying brain white matter microstructure. Adolescent brain development involves significant microstructural changes due to brain reorganization and neural pruning. The trajectory of these changes can be altered by the onset of mental disorders, and longitudinal analysis of diffusion imaging is needed to capture these alterations. Our proposal aims to make available an open source software platform for exploratory analysis of longitudinal diffusion MRI datasets, and to apply it to study the early onset of bipolar disorder in the Adolescent Brain Cognitive Development (ABCD) data. Diffusion tensor imaging is not sufficient to distinguish the different types of changes that occur during adolescent brain development, so our software tool will support more advanced diffusion models such as Neurite Orientation Dispersion and Density Imaging. This takes advantage of the high angular resolution of ABCD diffusion images. The exploratory tools we develop will employ the widely used Tract-Based Spatial Statistics (TBSS) technique, which is a dimensionality reduction that is well suited for exploratory analysis. Going beyond standard TBSS, we will adapt the technique to work with improved registration techniques, to work with more advanced diffusion models, and to provide developmental trajectories based on longitudinal imaging data. The TBSS methodology requires high quality image alignment. In order to achieve this, we will develop a deep learning model for pairwise registration of diffusion datasets, speeding up an important step in diffusion MRI analysis. By generating fiber orientation distributions from the ABCD diffusion imaging, our registration model will align fiber orientations in addition to anatomical structures. These tools will be made available in an open source software platform. While there are many tools for exploring diffusion MRI data, this one will be unique in its support for longitudinal datasets with high angular resolution imaging.

项目概要 扩散 MRI 分析是研究脑白质微观结构的主要工具。青春期大脑 由于大脑重组和神经修剪，发育涉及显着的微观结构变化。这 这些变化的轨迹可以通过精神障碍的发作而改变，纵向分析 需要扩散成像来捕捉这些变化。我们的建议旨在提供开源 用于纵向扩散 MRI 数据集探索性分析的软件平台，并将其应用于研究 青少年大脑认知发展（ABCD）数据中双相情感障碍的早期发作。 扩散张量成像不足以区分过程中发生的不同类型的变化 青少年大脑发育，因此我们的软件工具将支持更先进的扩散模型，例如 神经突方向色散和密度成像。这利用了高角分辨率 ABCD 扩散图像。我们开发的探索性工具将采用广泛使用的基于区域的空间 统计（TBSS）技术，这是一种非常适合探索性分析的降维技术。 超越标准 TBSS，我们将调整该技术以与改进的配准技术一起使用，以 使用更先进的扩散模型，并提供基于纵向的发展轨迹 成像数据。 TBSS 方法需要高质量的图像对齐。为了实现这一目标，我们将开发一个 用于扩散数据集成对配准的深度学习模型，加速扩散的重要一步 核磁共振分析。通过从 ABCD 扩散成像生成纤维取向分布，我们的配准 除了解剖结构之外，模型还将对齐纤维方向。 这些工具将在开源软件平台中提供。虽然有很多工具可以 探索扩散 MRI 数据，该数据集的独特之处在于支持高角度纵向数据集 分辨率成像。