Automated MR Image Analysis in MS: Identification of a Surrogate

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，但是一些疾病修饰药物已经被批准， FDA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， 可变缓解。这使得MS的临床评价变得困难。最常用的临床 用于评估临床状态的仪器在其灵敏度方面受到限制，并且不能检测亚临床活性。 因此，需要鉴定提供客观且可再现的测量结果的替代物。 疾病状态。磁共振成像（MRI）是最敏感的成像方式，用于非侵入性 有可能导出基于多模型MRI的许多度量 反映MS的不同病理方面的测量。然而，临床测量之间的相关性 状态和各种MRI导出的度量充其量是适度的。这至少部分是因为， 相关研究是基于单个或几个MRI度量的组合。结合MRI 包括灰质、白色物质和脊髓的指标预计将导致与 临床措施。这项建议的主要目的是确定一个代理人，结合信息， 包括大脑和脊髓的各种MRI测量。这些研究还将确定和量化 MS中所谓的“正常外观组织”，其已知是病理性的，并被认为代表 为了实现本发明的主要目的，我们将开发， 实施并评估了许多先进的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 并确定与临床残疾相关的这些指标的最佳组合， 扩展残疾状态评分（EDSS）和MS功能评分（MSFC）。提出的多模型MRI和 纵向研究沿着临床评价应有助于识别适当的替代物， 多个MRI衍生指标。与公共卫生的相关性：MS中替代药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，实际上节省了数百万美元的临床试验费用。的 系统还应该使临床医生能够基于以下内容定制对个体患者管理 使用更广泛可用的定量MRI的有根据的合理原则。虽然主要的重点是 在MS上，该系统应易于适应于调查和管理各种神经系统疾病， 需要精确确定组织体积及其时间变化。

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 surroagte that combines information from various MRI measures that include both brain and spinal cord. These studies will also identify and quantify the 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 bjective of this proposal, we wiil develop, implement, and evaluate a number of 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.