Multimodality image-based assessment system for traumatic brain injury

描述（由申请人提供）：每年有近170万美国人遭受创伤性脑损伤（TBI），这构成了美国重要的医疗健康问题。虽然神经影像学在病理定位和手术计划中发挥着重要作用，但TBI临床护理目前并未充分利用神经影像学计算技术。我们建议开发和验证基于图像分割，配准和分析的计算算法，这些算法可以产生定量措施来表征损伤，监测病理演变，告知患者预后并优化患者护理工作流程。该项目解决了当前对TBI信息指标的临床需求以及对易于使用的图像分析工具的技术需求，这些工具能够处理导致严重脑变形的大型异质性病理。在目标1中，我们将进行多模态脑图像分割，用于评估急性和慢性TBI，并测量纵向变化。我们将生成TBI病理的定量测量，其基于从多模态图像数据集分割病变、脑血管、脑室、灰质（GM）、白色物质（WM）和脑中线。在临床上，这些指标将用于定量描述和评估任何时间点（急性、慢性）的损伤，并根据病理类型、位置和程度进行纵向跟踪。该项目的第二个目的是推进最先进的图像配准技术，用于TBI的急性和慢性评估以及纵向变化测量。可变形图像配准对准图像中的对应解剖结构，并返回封装它们之间的变形的位移或流场。我们将继续开发“几何变形”，可以注册图像与结构的生长或收缩，如TBI病理引起的显着外观变化。我们将获得新的体素量化和可视化的病理浸润和脑损伤或纵向脑变化引起的脑变形，无论是在 病变和GM和WM内。第三个目标是研究我们的新TBI指标的能力，来自图像分割和配准，预测结果和指导临床决策。重点是最终的临床影响和评价脑重塑（例如结构变化）与功能恢复或下降之间的关系。我们将使用多变量统计方法来评估目标1-2中基于图像的新型多模式TBI测量（基于体积和变形）在神经心理运动、认知和行为结果测量方面的预后能力，这些测量可用于每位TBI患者。多变量技术也将允许调查患者亚组的分组 基于描述其共性或最佳区分它们的统计特征的人口。这将有助于定制针对每个患者亚组的临床工作流程。最终，这里提出的技术进步将产生使用成像以综合的、纵向的方式监测大脑对创伤的反应的能力，具有最大的临床效用和特异性。

DESCRIPTION (provided by applicant): Nearly 1.7 million Americans suffer traumatic brain injury (TBI) annually, which constitutes an important and significant US medical health concern. Although neuroimaging plays an important role in pathology localization and surgical planning, TBI clinical care does not currently take full advantage of neuroimaging computational technology. We propose to develop and validate computational algorithms, based on image segmentation, registration and analysis, which yield quantitative measures to characterize injury, monitor pathology evolution, inform patient prognosis and optimize patient care workflows. This project addresses the current clinical need for informative TBI metrics and the technical need for easy-to-use image analysis tools capable of handling large, heterogenous pathologies that cause severe brain deformations. In Aim 1, we will perform multimodal brain image segmentation for the assessment of acute and chronic TBI, and for measuring longitudinal changes. We will generate quantitative measures of TBI pathology that are based on segmenting lesions, hemorrhages, ventricles, gray matter (GM), white matter (WM) and the brain midline from multimodal image datasets. Clinically, these metrics will be used to quantitatively describe and assess injury at any time point (acute, chronic) and for longitudinal tracking based on pathology type, location and extent. The second aim of this project is to advance the state-of-the-art in image registration for acute and chronic assessment of TBI and for longitudinal change measurement. Deformable image registration aligns corresponding anatomy in images and returns a displacement or flow field encapsulating the deformations between them. We will continue development of "geometric metamorphosis", can register images with significant appearance changes caused by structures that grow or contract, such as TBI pathologies. We will derive novel voxel-wise quantifications and visualizations of pathology infiltration and of brain deformations induced by injury or longitudinal brain changes, both within lesions and within GM and WM. The third aim is to investigate the ability of our novel TBI metrics, derived from image segmentation and registration, to predict outcome and guide clinical decision making. The focus is on final clinical impact and on evaluating the relationship between brain remodeling (e.g. structural changes) with functional recovery or decline. We will use multivariate statistical methods to evaluate the prognostic abilities of the novel multimodal image-based measures of TBI (volumetric and deformation-based) from Aims 1-2 with respect to the neuropsychological motor, cognitive and behavioral outcome measures available for each TBI patient. Multivariate techniques will also allow investigation into the grouping of patient sub populations based on statistical features that describe their commonalities or optimally differentiate between them. This will aid in the customization of clinical workflows specific to each patient sub- group. Ultimately, the technical advances being proposed here will yield the ability to use imaging to monitor brain responses to trauma in an integrative, longitudinal fashion, with maximal clinical utility and specificity.