Partnership for MR Spectroscopic Imaging Data Processing

磁共振波谱成像数据处理合作伙伴关系

• 批准号: 7576811
• 负责人: Andrew A. Maudsley
• 金额: $ 113.94万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7576811
• 关键词: Address; Area; Arts; Biomedical Engineering; Brain; Brain Mapping; Brain region; California; Characteristics; Clinical; Clinical Research; Clinical effectiveness; Computer Systems; Computer software; Cost Savings; Data; Databases; Detection; Development; Diagnostic; Diagnostic Imaging; Disease Progression; Education; Educational Materials; Effectiveness; Engineering; Evaluation; Funding; Human; Image; Image Analysis; Individual; Institution; Knowledge; Label; Los Angeles; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Manufacturer Name; Maps; Measurement; Measures; Metabolic; Metabolic Marker; Methods; Metric; Modality; Multivariate Analysis; Outcome; Patients; Performance; Procedures; Process; Protocols documentation; Protons; Quality Control; Reproducibility; Research; Research Personnel; Running; Signal Transduction; Site; Spatial Distribution; Standardization; System; Techniques; Testing; Therapeutic Studies; Tissues; Universities; Validation; age related; clinical research site; cluster computing; computerized data processing; data sharing; image processing; image reconstruction; imaging modality; improved; in vivo; instrument; multicore processor; neuroimaging; patient population; response; spectroscopic imaging

DESCRIPTION (provided by applicant): Measurement of tissue metabolite distributions by 1H MR Spectroscopic Imaging (MRSI) provides a sensitive diagnostic neuroimaging modality; however, it remains underutilized in the clinical setting. One requirement that has limited a wider use of these techniques is the need for comprehensive data processing procedures, which optimally make extensive use of prior information, including tissue and morphological analysis from MRI and knowledge of normal metabolite distributions. In the previous funding period this project has developed an integrated software package that provides comprehensive and automated MRI and MRSI processing that includes signal normalization and spatial transformation, thereby enabling formation of a reference image database of MR-observed human metabolite values as a function of acquisition, spatial, and subject parameters. This database enables mapping of brain metabolite distributions and provides valuable normative information for analysis of individual patient studies. In this project period these processing methods will be further developed and integrated with standardized MRSI acquisition protocols implemented on MR instruments from three major manufacturers, and the metabolite database will be expanded to support the developed acquisition protocols. This project will therefore develop standardized 1H MRSI protocols, including cross-site and long-term validation and quality control, that will maximize the impact of MRSI for clinical studies and facilitate multi-site quantitative metabolic imaging studies. The effectiveness of these standardized metabolic neuroimaging protocols will be evaluated by installing a turnkey system at a clinical research site where performance metrics will be developed and data acquired to test the sensitivity of the standardized MRSI methods for detection of metabolic changes in individual subjects. All developments will be made freely available to researchers involved in the application of MRSI for clinical diagnostic imaging. The bioengineering focus areas of this project include signal and image processing, MR neuroimaging sequence development, multiparametric image analysis methods, and networked image databases. The partnership sites are the University of Miami (leading institution), University of California Los Angeles, Johns Hopkins University, Stanford University, and Duke University. This development will improve the quality of the diagnostic neuroimaging information obtained using MR spectroscopy; provide cost savings by sharing data from normal subject; establish standardized metabolic imaging methods; and map metabolite distributions in human brain.

描述（由申请人提供）：通过 1H MR 光谱成像 (MRSI) 测量组织代谢物分布提供了一种灵敏的诊断神经成像方式；然而，它在临床环境中仍未得到充分利用。限制这些技术更广泛使用的一项要求是需要全面的数据处理程序，该程序最好地广泛利用先验信息，包括 MRI 的组织和形态分析以及正常代谢物分布的知识。在上一个资助期间，该项目开发了一个集成软件包，提供全面和自动化的 MRI 和 MRSI 处理，包括信号归一化和空间变换，从而能够形成 MR 观察到的人体代谢值作为采集、空间和受试者参数函数的参考图像数据库。该数据库能够绘制大脑代谢物分布图，并为分析个体患者研究提供有价值的规范信息。在此项目期间，这些处理方法将得到进一步开发，并与三大制造商的 MR 仪器上实施的标准化 MRSI 采集协议相集成，并且代谢物数据库将得到扩展，以支持已开发的采集协议。因此，该项目将开发标准化的 1H MRSI 协议，包括跨站点和长期验证和质量控制，这将最大限度地发挥 MRSI 对临床研究的影响，并促进多站点定量代谢成像研究。这些标准化代谢神经影像方案的有效性将通过在临床研究场所安装交钥匙系统进行评估，在该系统中将制定性能指标并获取数据，以测试标准化 MRSI 方法检测个体受试者代谢变化的敏感性。所有开发成果都将免费提供给参与 MRSI 临床诊断成像应用的研究人员。该项目的生物工程重点领域包括信号和图像处理、MR 神经成像序列开发、多参数图像分析方法和网络图像数据库。合作伙伴包括迈阿密大学（领先机构）、加州大学洛杉矶分校、约翰·霍普金斯大学、斯坦福大学和杜克大学。这一发展将提高使用磁共振波谱获得的诊断神经影像信息的质量；通过共享正常受试者的数据来节省成本；建立标准化代谢成像方法；并绘制人脑中代谢物的分布图。