Brain Image Analysis Tools for Quantitative Longitudinal Assessment of MS

描述(申请人提供)：多发性硬化症(MS)是一种中枢神经系统疾病，以灰质和白质结构中的炎症和神经轴突变性为特征。多发性硬化症影响着全球超过250万人和美国超过25万人。这些患者可能会经历一系列令人衰弱的症状，包括认知障碍、部分或完全视力丧失、四肢无力、头晕和疲劳。这些症状通常在疾病开始时零星出现，但随着时间的推移，无论是频率还是强度都可能恶化。活体MR采集显示，MS患者出现全脑和皮质萎缩，脑白质病变增加，脑白质连通性降低。然而，这些脑变化的定量表征仍然是一个挑战，因为缺乏准确和可靠的图像分析工具来有效地模拟多发性硬化症中发生的解剖变化。为了解决这些问题，我们建议开发、验证和应用软件工具来对从多发性硬化症患者获得的磁共振脑图像进行纵向分析。我们将利用我们研究团队在全脑和病变分割、大脑皮层重建、白质束分割和软件工程方面的经验，创建一套工具，使多发性硬化症研究人员、临床医生以及最终多发性硬化症患者群体受益。在R01项目期间，我们将实现以下具体目标：1)开发专门为MS脑图像的纵向定量分析设计的图像分析工具；2)提供用于验证单个时间点和纵向MS图像分析算法的工具和数据；3)将开发的工具应用于正在进行的MS纵向研究，该研究将揭示脑体积、病变体积和位置、皮质萎缩以及横断面和纵向尺度上的临床结果之间的关联。拟议的工具将填补MS脑图像分析技术的关键空白，允许准确和稳定地测量病变体积、脑组织体积、皮质几何形状和白质连接。这个项目将对神经学、神经科学和图像分析社区产生重大影响。发布的工具将使人们能够更好地了解多发性硬化症进展过程中发生的解剖学变化，潜在地导致早期发现功能特定的残疾系统。此外，不仅多发性硬化症药物疗法的临床试验将得到极大的便利，而且所开发的工具还可以用于识别适合特定药物疗法的患者亚群。发布的数据和验证工具还将允许对现有方法和新开发的方法进行比较，不仅在多发性硬化症患者中，而且在健康人群中。 公共卫生相关性：多发性硬化症是一种使人衰弱的神经系统疾病，仅在美国就有超过25万人受到影响。开发稳健而准确的算法来定量分析多发性硬化症患者的脑图像将有助于更好地了解多发性硬化症进展过程中发生的解剖变化，并将促进多发性硬化症药物治疗的临床试验。这最终将改善多发性硬化症的诊断和治疗。

DESCRIPTION (provided by applicant): Multiple Sclerosis (MS) is a disease of the central nervous system characterized by inflammation and neuroaxonal degeneration in both grey and white matter structures. MS affects over 2.5 million people worldwide and over 250,000 people in the United States. Those afflicted may experience a wide range of debilitating symptoms including cognitive impairments, partial or complete vision loss, weakness in limbs, dizziness, and fatigue. These symptoms often occur sporadically at the onset of the disease but can worsen over time with respect to both frequency and intensity. In vivo MR acquisitions have shown that whole brain and cortical atrophy, an increased presence of white matter lesions, and a reduction in white matter connectivity occur in MS patients. Quantitative characterization of these brain changes, however, remains a challenge because of the lack of accurate and reliable image analysis tools that effectively model the anatomical changes that occur in MS. To address these issues, we propose to develop, validate, and apply software tools for the longitudinal analysis of MR brain images acquired from MS patients. We will leverage the experience of our research team in whole brain and lesion segmentation, reconstruction of the cerbral cortex, segmentation of white matter tracts, and software engineering to create a suite of tools that will benefit both MS researchers, clinicians, and ultimately the MS patient population. Over the duration of this R01 project, we will accomplish the following specific aims: 1) develop image analysis tools specifically designed for the quantitative longitudinal analysis of brain images with MS; 2) provide tools and data for validating single time point and longitudinal MS image analysis algorithms; 3) apply the developed tools to an ongoing MS longitudinal study that will reveal associations between brain volumes, lesion volume and location, cortical atrophy, and clinical outcomes on both a cross-sectional and longitudinal scale. The proposed tools will fill critical gaps in MS brain image analysis technology by allowing accurate and stable measurements of lesion volume, brain tissue volumes, cortical geometry, and white matter connectivity. This project will significantly impact the neurology, neuroscience, and image analysis communities. The released tools will enable a better understanding of the anatomical changes that occur during the progression of MS, potentially leading to early detection of functionally specific systems of disability. Furthermore, not only will clinical trials for MS drug therapies be greatly facilitated, but the developed tools may also be used to identify subsets of patients suitable for specific drug therapies. The released data and validation tools will also allow for a comparison of existing and newly developed methods, not only in MS patients, but also in healthy populations. PUBLIC HEALTH RELEVANCE: Multiple Sclerosis is a debilitating neurological disease that affects over 250,000 people in the United States alone. The development of robust and accurate algorithms for quantitatively analyzing brain images in MS patients will lead to a better understanding of the anatomical changes that occur during the progression of MS, and will facilitate clinical trials for MS drug therapies. This will ultimately lead to improved diagnosis and treatment of MS.