MORPHOMETRY BIOMEDICAL INFORMATICS RESEARCH NETWORK

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 描述(由申请人提供)： 成像技术的进步使疾病的生物医学研究发生了革命性的变化。这一方法为提高诊断和预测能力以及治疗疾病带来的巨大潜力迄今在很大程度上仍是一个未兑现的承诺。这种潜力受到一些技术障碍的限制，这些障碍在很大程度上可以通过提供联合成像数据库和配套的基础设施来克服。具体地说，能够跨多个地点进行临床成像研究，使用最强大的软件分析成像数据而不考虑开发地点，并使用具有良好特征的图像和临床数据在大量受试者身上测试新假设的能力，将对该领域的进展产生明显和积极的影响。形态测量BIRN(MBIRN)成立于2001年10月，在这一国家基础设施的发展方面取得了实质性进展，以七个站点的联合数据采集和数据库为基础，开发了一个数据和计算网络，以促进多站点神经解剖分析。标准化的结构性MRI图像采集协议已经开发和实施，可以明显减少站点间差异的初始来源。实现了联邦数据库的数据结构、传输、存储和查询等方面的功能。在继续mBIRN努力的过程中，我们提出了三个广泛的工作领域： 1)继续进行结构磁共振成像采集的优化、校准和验证，以包括T2和DTI；2)翻译特定地点最先进的图像分析、可视化和机器学习技术，以便在联合的多地点BIRN环境中工作；以及3)扩展数据管理和数据库查询能力，以包括其他成像方式、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协作汇聚在一起，这些协作将通过促进数据进入联合数据库和创建数据库激励功能来确保提高利用率。我们的参与网站包括MGH(PI)、BWH、UCI、Duke、UCLA、UCSD、John Hopkins，以及新加入的华盛顿大学和麻省理工学院。我们已经共同努力，通过招募生物医学和计算科学这两个领域的小组负责人来弥合这两个领域之间存在的差距。我们的努力将与整个BIRN联盟的努力相协调，以确保获取和数据库功能以及基于应用的障碍查询可以跨站点互操作，并旨在提高对健康和疾病的进一步了解和了解的能力。

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.