Automated MR Image Analysis in MS: Identification of a Surrogate

描述（由申请人提供）：多发性硬化症（MS）是一种慢性中枢神经系统疾病，影响全球250万患者。目前，没有治愈MS的方法，但一些疾病修饰药物已被FDA批准或正在进行临床试验。MS具有复杂的临床过程，包括不可预测的复发和可变的缓解。这使得MS的临床评价变得困难。最常用的用于评估临床状态的临床仪器的灵敏度有限，并且不能检测亚临床活性。因此，需要鉴定提供疾病状态的客观和可再现测量的替代物。磁共振成像（MRI）是最敏感的成像方式，用于非侵入性调查MS。它是可能的，以获得一些指标，是基于多模型的MRI测量，反映不同的病理方面的MS。然而，临床状态和各种MRI衍生的指标之间的相关性是，在最好的，适度的。这至少部分是由于许多相关研究是基于单个或几个MRI指标的组合。包括灰质、白色物质和脊髓在内的MRI指标的组合预期将导致与临床测量的更好相关性。该提案的主要目的是确定一种替代品，该替代品结合了来自包括大脑和脊髓的各种MRI测量的信息。这些研究还将确定和量化所谓的“正常出现的组织”在MS中，已知是病理性的，并认为代表微观或弥漫性病理MS。为了实现这一建议的主要目标，我们将开发，实施和评估一些先进的MRI采集和分析，以及图像处理技术。我们将确定MS患者队列中MRI衍生指标的纵向变化，并确定与扩展残疾状态评分（EDSS）和MS功能评分（MSFC）评估的临床残疾相关的这些指标的最佳组合。拟定的多模型MRI和纵向研究沿着临床评价应有助于根据多个MRI衍生指标识别适当的替代物。与公共卫生的相关性：MS中替代物的识别应该彻底改变MS临床试验，加快神经药物的技术转让，并节省数百万美元的临床试验费用。该系统还应使临床医生能够根据使用更广泛可用的定量MRI的有充分依据的合理原则来定制对个体患者的管理。虽然主要重点是MS，但该系统应易于适应调查和管理需要准确确定组织体积及其时间变化的各种神经系统疾病。

DESCRIPTION (provided by applicant): Multiple sclerosis (MS) is a chronic central nervous system disease that affects 2.5 million patients worldwide. Currently, there is no cure for MS, but a number of disease modifying drugs have been either approved by the FDA or undergoing clinical trials. MS has a complex clinical course that includes unpredictable relapses and variable remissions. This makes clinical evaluation of MS difficult. The most commonly used clinical instruments for assessing the clinical status are limited in their sensitivity and can not detect subclinical activity. Thus, there is a need for identifying a surrogate that provides an objective and reproducible measure of the disease state. Magnetic resonance imaging (MRI) is the most sensitive imaging modality for noninvasively investigating MS. It is possible to derive a number of metrics that are based on multi-model MRI measurements that reflect different pathological aspects of MS. However, the correlation between the clinical status and various MRI-derived metrics is, at best, modest. This is, at least, in part due to the fact that many of the correlative studies are based on a single or a combination of a few MRI metric. A combination of MRI metrics that include gray matter, white matter, and spinal cord is expected to result in better correlation with clinical measures. The main objective of this proposal is to identify a surrogate that combines information from various MRI measures that include both brain and spinal cord. These studies will also identify and quantify the so called "normal appearing tissue" in MS that is known to be pathological and thought to represent microscopic or diffuse pathology in MS. In order to realize the main objective of this proposal, we will develop, implement, and evaluate a number of advanced MRI acquisition and analysis, and image processing techniques. We will determine the longitudinal changes in the MRI-derived metrics in a cohort of MS patients and identify an optimum combination of these metrics that correlate with clinical disability as assessed by the extended disability status score (EDSS) and MS functional score (MSFC). The proposed multi-model MRI and longitudinal studies along with clinical evaluation should help identify appropriate surrogate(s), based on multiple MRI-derived metrics. Relevance to Public Health: Identification of surrogate in MS should revolutionize MS clinical trials, expedite technology transfer in neuropharmaceuticals and literally save millions of dollars in clinical trial expenses. The system should also empower clinicians in general to customize management of individual patients based on well-founded sound principles of the use of more widely available quantitative MRI. While the main emphasis is on MS, this system should be readily adaptable to investigate and manage various neurological disorders that require accurate determination of tissue volumes and their temporal change.