This proposal aims to continue the development of XNAT. XNAT is an imaging informatics platform designed to facilitate common management and productivity tasks for imaging and associated data. We will develop the next generation of XNAT technology to support the ongoing evolution of imaging research. Development will focus on modernizing and expanding the current system.
In Aim 1, we will implement new web application infrastructure that includes a new archive file management system, a new event bus to manage cross-service orchestration and a new Javascript library to simplify user interface development. We will also implement new core services, including a Docker Container service, a dynamic scripting engine, and a global XNAT federation.
In Aim 2, we will implement two innovative new capabilities that build on the services developed in Aim 1. The XNAT Publisher framework will streamline the process of data sharing by automating the creation and curation of data releases following best practices for data publication and stewardship. The XNAT Machine Learning framework will streamline the development and use of machine learning applications by integrating XNAT with the TensorFlow machine learning environment and implementing provenance and other monitoring features to help avoid the pitfalls that often plague machine learning efforts. For both Aim 1 and 2, all capabilities will be developed and evaluated in the context of real world scientific programs that are actively using the XNAT platform.
In Aim 3, we will provide extensive support to the XNAT community, including training workshops, online documentation, discussion forums, and . These activities will be targeted at both XNAT users and developers.

Public Health Relevance

Medical 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 #
2R01EB009352-09
Application #
9384200
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Peng, Grace
Project Start
2009-09-01
Project End
2021-08-31
Budget Start
2017-09-07
Budget End
2018-08-31
Support Year
9
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Washington University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Su, Yi; Flores, Shaney; Hornbeck, Russ C et al. (2018) Utilizing the Centiloid scale in cross-sectional and longitudinal PiB PET studies. Neuroimage Clin 19:406-416
Javaherian, Kavon; Newman, Brianne M; Weng, Hua et al. (2018) Examining the Complicated Relationship Between Depressive Symptoms and Cognitive Impairment in Preclinical Alzheimer Disease. Alzheimer Dis Assoc Disord :
Lee, Seonjoo; Zimmerman, Molly E; Narkhede, Atul et al. (2018) White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer's disease. PLoS One 13:e0195838
Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500
Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank et al. (2018) Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer's disease. Brain 141:1186-1200
Wildburger, Norelle C; Gyngard, Frank; Guillermier, Christelle et al. (2018) Amyloid-? Plaques in Clinical Alzheimer's Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity. Front Neurol 9:169
Vlassenko, Andrei G; Gordon, Brian A; Goyal, Manu S et al. (2018) Aerobic glycolysis and tau deposition in preclinical Alzheimer's disease. Neurobiol Aging 67:95-98
Gordon, Brian A; Blazey, Tyler M; Su, Yi et al. (2018) Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study. Lancet Neurol 17:241-250
Lim, Yen Ying; Hassenstab, Jason; Goate, Alison et al. (2018) Effect of BDNFVal66Met on disease markers in dominantly inherited Alzheimer's disease. Ann Neurol 84:424-435
Mishra, Shruti; Blazey, Tyler M; Holtzman, David M et al. (2018) Longitudinal brain imaging in preclinical Alzheimer disease: impact of APOE ?4 genotype. Brain 141:1828-1839

Showing the most recent 10 out of 39 publications