Imaging has emerged as one of the key tools used by biomedical investigators to further our understanding of human biology in health and disease. While the scale and scope of imaging research have exploded, informatics tools to support this research have not kept pace. The overarching aim of this proposal is to develop a comprehensive open source imaging informatics platform built to the highest engineering standards and using the most advanced software technologies available. This platform - XNAT 2.0 - will build on the existing XNAT platform, which is widely used by research institutions across the world and is a component of the National Institutes of Health-sponsored research informatics backbone that includes the Biomedical Informatics Research Network (BIRN) and Cancer Biomedical Informatics Grid (caBIG). The XNAT 2.0 platform will be implemented as service-oriented architecture (SOA), and a suite of services will be built on this architecture to support the core requirements of the imaging research enterprise. Software interfaces will also be designed and implemented in XNAT 2.0 to support the development of third party XNAT tools and components and to encourage developers of image processing and analysis tools to interoperate with XNAT. Finally, methods will be designed and implemented to deploy XNAT services on massively scalable computing systems. The resulting platform will improve the quality and scale of imaging research and will greatly facilitate multi-site collaboration and data sharing. Most importantly, it will provide researchers and their institutions with the necessary tools to maximize the potential of imaging to improve health and our understanding of human biology.

Public Health Relevance

In vivo imaging is one of the key methods used by biomedical researchers to study human biology in health and disease. The imaging informatics platform described in this application will enable biomedical researchers to capture, analyze, and share imaging and related data. These capabilities address key bottlenecks in the pathway to discovering cures to complex diseases such as Alzheimer's disease, cancer, and heart disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB009352-04
Application #
8322815
Study Section
Special Emphasis Panel (ZRG1-SBIB-Q (90))
Program Officer
Pai, Vinay Manjunath
Project Start
2009-09-01
Project End
2013-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
4
Fiscal Year
2012
Total Cost
$325,443
Indirect Cost
$111,336
Name
Washington University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Lee, Megan H; Miller-Thomas, Michelle M; Benzinger, Tammie L et al. (2016) Clinical Resting-state fMRI in the Preoperative Setting: Are We Ready for Prime Time? Top Magn Reson Imaging 25:11-8
Babulal, Ganesh M; Ghoshal, Nupur; Head, Denise et al. (2016) Mood Changes in Cognitively Normal Older Adults are Linked to Alzheimer Disease Biomarker Levels. Am J Geriatr Psychiatry 24:1095-1104
Soosman, Steffan K; Joseph-Mathurin, Nelly; Braskie, Meredith N et al. (2016) Widespread white matter and conduction defects in PSEN1-related spastic paraparesis. Neurobiol Aging 47:201-209
Lim, Yen Ying; Hassenstab, Jason; Cruchaga, Carlos et al. (2016) BDNF Val66Met moderates memory impairment, hippocampal function and tau in preclinical autosomal dominant Alzheimer's disease. Brain 139:2766-2777
Vos, Stephanie J B; Gordon, Brian A; Su, Yi et al. (2016) NIA-AA staging of preclinical Alzheimer disease: discordance and concordance of CSF and imaging biomarkers. Neurobiol Aging 44:1-8
Hodge, Michael R; Horton, William; Brown, Timothy et al. (2016) ConnectomeDB--Sharing human brain connectivity data. Neuroimage 124:1102-7
Herrick, Rick; Horton, William; Olsen, Timothy et al. (2016) XNAT Central: Open sourcing imaging research data. Neuroimage 124:1093-6
Kogan, Alex; Alpert, Kathryn; Ambite, Jose Luis et al. (2016) Northwestern University schizophrenia data sharing for SchizConnect: A longitudinal dataset for large-scale integration. Neuroimage 124:1196-201
Gordon, Brian A; Blazey, Tyler; Su, Yi et al. (2016) Longitudinal β-Amyloid Deposition and Hippocampal Volume in Preclinical Alzheimer Disease and Suspected Non-Alzheimer Disease Pathophysiology. JAMA Neurol 73:1192-1200
Fouke, Sarah Jost; Benzinger, Tammie L; Milchenko, Mikhail et al. (2014) The comprehensive neuro-oncology data repository (CONDR): a research infrastructure to develop and validate imaging biomarkers. Neurosurgery 74:88-98

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