Automated MR Image Analysis in MS: Identification of a Surrogate

MS 中的自动 MR 图像分析：替代物的识别

• 批准号: 7569982
• 负责人: PONNADA A NARAYANA
• 金额: $ 67.67万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2012-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7569982
• 关键词: Affect; Algorithms; Anisotropy; Biological Neural Networks; Brain; Central Nervous System Diseases; Chronic; Clinical; Clinical Research; Clinical Trials; Complex; Computer software; Correlative Study; Data; Detection; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Disease remission; Evaluation; FDA approved; Functional disorder; Human; Image Analysis; Imaging Techniques; Individual; Intervention; Lesion; Localized Lesion; Longitudinal Studies; Magnetic Resonance Imaging; Measurement; Measures; Metric; Microscopic; Modeling; Multi-Institutional Clinical Trial; Multiple Sclerosis; Neuraxis; Pathologic; Pathology; Patients; Performance; Pharmaceutical Preparations; Phase; Physiologic pulse; Play; Population; Process; Public Health; Recovery; Relapse; Relapsing-Remitting Multiple Sclerosis; Resolution; Risk; Role; Scanning; Severities; Slice; Spinal Cord; Spinal Cord Lesions; Structure; Surrogate Markers; System; Techniques; Technology Transfer; Testing; Time; Tissues; Treatment Efficacy; United States National Institutes of Health; Weight; base; cohort; diffusion anisotropy; disability; empowered; gray matter; image processing; imaging modality; improved; innovation; instrument; nervous system disorder; novel; parent grant; research clinical testing; sound; spinal cord white matter; white matter

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.

描述(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，多发性硬化症还没有治愈方法，但一些疾病修饰药物已经获得FDA的批准或正在进行临床试验。多发性硬化症有一个复杂的临床过程，包括不可预测的复发和可变的缓解。这使得MS的临床评估变得困难。目前临床上最常用的评估临床状态的仪器灵敏度有限，无法检测到亚临床活动。因此，需要识别提供疾病状态的客观且可重现的测量的替代物。磁共振成像(MRI)是对多发性硬化症进行无创性研究的最敏感的成像手段。根据反映多发性硬化症不同病理方面的多模型MRI测量结果，可以得出许多指标。然而，临床状态和各种MRI得出的指标之间的相关性充其量也只是适中的。这至少在一定程度上是因为许多相关研究都是基于单一的或几个MRI指标的组合。包括灰质、白质和脊髓在内的MRI指标的组合有望导致与临床指标更好的相关性。这项建议的主要目标是确定一种替代物，它结合了包括大脑和脊髓在内的各种MRI测量的信息。这些研究还将识别和量化多发性硬化症中已知的病理和被认为代表多发性硬化症的微观或弥漫性病理的所谓“正常外观组织”。为了实现这项建议的主要目标，我们将开发、实施和评估一些先进的磁共振成像采集和分析以及图像处理技术。我们将在一组MS患者中确定MRI衍生指标的纵向变化，并确定这些指标的最佳组合，这些指标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。拟议的多模型磁共振成像和纵向研究以及临床评估应该有助于基于多个磁共振成像衍生指标确定合适的替代者(S)。与公共健康相关：在多发性硬化症中识别代用品应该会给多发性硬化症临床试验带来革命性的变化，加快神经药物的技术转让，并真正节省数百万美元的临床试验费用。该系统还应使一般临床医生能够根据合理的原则定制对个别患者的管理，使用更广泛的定量磁共振成像。虽然主要的重点是多发性硬化，但这个系统应该很容易适应于调查和处理各种神经疾病，这些疾病需要准确地确定组织体积及其时间变化。