MR Image Analysis in MS: Identification of a Surrogate

MS 中的 MR 图像分析：替代物的识别

• 批准号: 6644817
• 负责人: PONNADA A NARAYANA
• 金额: $ 58.26万
• 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 2007-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6644817
• 关键词: MR; Image; Analysis; MS; Identification

DESCRIPTION (provided by applicant): Multiple sclerosis (MS) is the most common demyelinating disease in humans and has a complex clinical course that includes unpredictable relapses and variable remissions. This makes clinical evaluation of MS difficult. Therefore, current clinical trial designs must incorporate large numbers of patients followed over long periods. These designs are expensive and may deprive patients of timely access to effective treatment. The use of robust surrogate marker(s) that have predictive value could reduce problems in evaluating new drugs and improve the management of individual patients. MRI-based measures such as volumes of lesions, black holes, contrast enhancements, atrophy, and magnetization transfer ratios, are expected to serve as robust surrogates. However, a number of studies have shown that the correlation between these MR measures and clinical score is weak. We hypothesize that this weak correlation is in part due to the use of improper image analysis tools necessary for robust image quantitation and in part due to failure to define the correct MRI surrogate. In these studies we propose to develop an integrated image analysis package that is robust and automatic for accurate quantitation of tissue volumes. An important feature of this analysis package is its ability to analyze images acquired on a wide range of MR scanners using a plethora of MR sequences, greatly extending its utility. This package allows us to follow temporal changes in individual lesions, as well as currently used global changes. This analysis package will be rigorously evaluated using an extensive database that contains images on more than 2,000 MS patients, followed over several years. Using this database, we propose to identify surrogate(s) based on individual or some combination of MRI-measures. Finally, this software will be distributed to a few select centers for multicenter evaluation. 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（由申请人提供）：多发性硬化症（MS）是人类最常见的脱髓鞘疾病，具有复杂的临床病程，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。因此，目前的临床试验设计必须纳入大量长期随访的患者。这些设计是昂贵的，并且可能使患者无法及时获得有效的治疗。使用具有预测价值的强有力的替代标志物可以减少评估新药的问题，并改善对个体患者的管理。基于MRI的测量，如病变体积、黑洞、对比度增强、萎缩和磁化传递率，预计将作为可靠的替代品。然而，许多研究表明，这些MR指标与临床评分之间的相关性较弱。我们假设这种弱相关性部分是由于使用了不适当的图像分析工具，这是进行稳健图像定量所必需的，部分是由于未能定义正确的MRI替代品。在这些研究中，我们建议开发一个集成的图像分析软件包，是强大的和自动的组织体积的准确定量。该分析包的一个重要特征是其能够分析使用大量MR序列在各种MR扫描仪上采集的图像，从而极大地扩展了其实用性。该软件包允许我们跟踪单个病变的时间变化，以及当前使用的全局变化。该分析包将使用一个广泛的数据库进行严格的评估，该数据库包含2,000多名MS患者的图像，并随访数年。使用这个数据库，我们建议识别替代（S）的基础上个别或一些MRI措施的组合。最后，该软件将分发给几个选定的中心进行多中心评价。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。