Brain Image Analysis Tools for Quantitative Longitudinal Assessment of MS

描述（由申请人提供）：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，在美国超过25万人。患者可能会出现各种衰弱症状，包括认知障碍、部分或完全视力丧失、四肢无力、头晕和疲劳。这些症状通常在发病时零星出现，但随着时间的推移，在频率和强度方面可能会恶化。活体MR显示，MS患者出现全脑和皮质萎缩，白质病变增加，白质连通性降低。然而，由于缺乏准确可靠的图像分析工具来有效地模拟MS中发生的解剖变化，因此对这些大脑变化的定量表征仍然是一个挑战。为了解决这些问题，我们建议开发、验证和应用软件工具，对MS患者获得的MR脑图像进行纵向分析。我们将利用我们的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MS研究人员、临床医生和最终的MS患者受益。在R01项目期间，我们将完成以下具体目标：1)开发专门用于MS定量纵向分析脑图像的图像分析工具；2)为验证单时间点和纵向MS图像分析算法提供工具和数据；3)将开发的工具应用于正在进行的MS纵向研究，该研究将在横断面和纵向尺度上揭示脑容量、病变体积和位置、皮质萎缩和临床结果之间的关系。所提出的工具将填补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通性。该项目将对神经学、神经科学和图像分析领域产生重大影响。发布的工具将使人们更好地了解MS进展过程中发生的解剖变化，有可能导致早期发现功能特异性残疾系统。此外，不仅将大大促进MS药物治疗的临床试验，而且开发的工具也可用于确定适合特定药物治疗的患者亚群。发布的数据和验证工具也将允许对现有和新开发的方法进行比较，不仅在MS患者中，而且在健康人群中。

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.