MORPHOMETRY BIOMEDICAL INFORMATICS RESEARCH NETWORK

形态学生物医学信息学研究网络

• 批准号: 7724584
• 负责人: BRUCE R ROSEN
• 金额: $ 257.04万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7724584
• 关键词: Area; Arts; Biomedical Informatics Research Network; Calibration; Clinical; Clinical Data; Collaborations; Collection; Computational Science; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Databases; Development; Diagnostic; Disease; Ensure; Environment; Funding; Grant; Health; Human Genetics; Image; Image Analysis; Imagery; Incentives; Institution; Investigation; Knowledge; Machine Learning; Magnetic Resonance Imaging; Methodology; Modality; Network-based; Numbers; Protocols documentation; Recruitment Activity; Research; Research Infrastructure; Research Personnel; Resources; Services; Site; Source; Technology; Testing; Translations; United States National Institutes of Health; Universities; Validation; Washington; Work; base; cluster computing; data acquisition; data management; data structure; design; morphometry; prognostic; transmission process

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. DESCRIPTION (provided by applicant): Technological advances in imaging have revolutionized the biomedical investigation of illness. The tremendous potential that this methodology brings to advancing diagnostic and prognostic capabilities and in treatment of illnesses has as yet remained largely an unfulfilled promise. This potential has been limited by a number of technological impediments that could be in large part overcome by the availability of a federated imaging database and the attendant infrastructure. Specifically, the ability to conduct clinical imaging studies across multiple sites, to analyze imaging data with the most powerful software regardless of development site, and to test new hypotheses on large collections of subjects with well characterized image and clinical data would have a demonstrable and positive impact on progress in this field. The Morphometry BIRN (mBIRN), established in October 2001, has made substantial progress in the development of this national infrastructure to develop a data and computational network based on a federated data acquisition and database across seven sites in the service of facilitating multi-site neuroanatomic analysis. Standardized structural MRI image acquisition protocols have been developed and implemented that demonstrably reduce initial sources of inter-site variance. Data structure, transmission, storage and querying aspects of the federated database have been implemented. In this continuation of the mBIRN efforts, we propose three broad areas of work: 1) continuing structural MRI acquisition optimization, calibration and validation to include T2 and DTI; 2) translation of site specific state-of-the-art image analysis, visualization and machine learning technologies to work in the federated, multi-site BIRN environment; and 3) extension of data management and database query capabilities to include additional imaging modalities, clinical disorders and individualized human genetic covariates. These broad areas of work will come together in through key collaborations that will ensure utilization promotion by facilitating data entry into the federated database and creation of database incentive functionality. Our participating sites include MGH (PI), BWH, UCI, Duke, UCLA, UCSD, John Hopkins, and newly added Washington University and MIT. We have made a concerted effort to bridge the gap that can exist between biomedical and computational sciences by recruiting to our group leaders in both of these domains. Our efforts will be coordinated with those of the entire BIRN consortium in order to insure that acquisition and database functionality, and application-based disorder queries are interoperable across sites and designed to advance the capabilities to further knowledge and understanding of health and disease.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 描述（由申请人提供）： 成像的技术进步彻底改变了对疾病的生物医学研究。这种方法带来促进诊断和预后能力的巨大潜力以及对疾病的治疗，但仍在很大程度上尚未实现。这种潜力受到许多技术障碍的限制，这些障碍可能会因联合成像数据库和随之而来的基础架构的可用性而很大程度上克服。具体而言，无论开发地点如何，都可以在多个站点进行临床成像研究，分析具有最强大软件的成像数据的能力，并在具有良好表征的图像和临床数据的大量受试者中测试新的假设，对该领域的进展具有明显的积极影响。成立于2001年10月的形态计量学BIRN（MBIRN）在该国家基础设施的开发方面取得了重大进展，以基于跨七个站点的联合数据采集和数据库来开发数据和计算网络，以促进多壁画神经瘤分析。已经开发和实施了标准化的结构MRI图像采集方案，这些方案明显地降低了地点间差异的初始来源。已经实施了联合数据库的数据结构，传输，存储和查询方面。在MBIRN努力的延续中，我们提出了三个广泛的工作领域： 1）持续结构性MRI获取优化，校准和验证，包括T2和DTI； 2）在联邦多站点的BIRN环境中使用特定网站的特定最先进的图像分析，可视化和机器学习技术； 3）扩展数据管理和数据库查询功能，包括其他成像方式，临床疾病和个性化的人类遗传协变量。这些广泛的工作领域将通过关键的协作聚集在一起，通过促进数据将数据输入到联合数据库中并创建数据库激励功能，从而确保利用促销。我们的参与网站包括MGH（PI），BWH，UCI，DUKE，UCLA，UCSD，JOHN HOPKINS和新添加的华盛顿大学和MIT。我们通过在这两个领域中招募我们的小组领导者来招募生物医学和计算科学之间可能存在的差距。我们的努力将与整个Birn联盟的努力进行协调，以确保获得和数据库功能，基于应用程序的疾病查询在跨站点可以互操作，并旨在提高能力，以进一步了解健康和疾病。