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In recent imaging-based clinical tria ls, quantitative image analysis (QIA) and computer-aided diag nosis (CAD) methods are increasing in productivity due to higher resolution imagi ng capabilities. A radiology core doing clinical trials have been analyzing more treatment methods and there is a growing quantity of metadata that need to be stored and managed. These radiology centers are also collaborating with many off-site imaging field sites and need a way to communicate metadata between one another in a secure infrastructure. Our solution is to implement a data storage grid with a fault-tolerant and dynamic metadata database design to unify metada ta from different clinical trial experiments and field sites. Although metadata from images follow the DICOM standard, clin ical trials also produce meta data specific to regions-of-interest and quantitative image analysis. We have implemen ted a data access and integration (DAI) server layer where multiple field sites can access multiple metadata databases in the data grid through a single web-based grid service. The centralization of metadata database management simplifies the task of adding new databases into the grid and also decreases the risk of configuration errors seen in peer-to-peer grids. In this paper, we address the design and implementation of a data grid metadata storage that has fault-tolerance and dynamic integration for imaging-based clinical trials. Keywords: Clinical Trials, Metadata, Fau lt-Tolerance, Data Grid, Globus Toolkit, Open Grid Services Architecture Data Access and Integration, Quantitative Image Analysis, Computer-Aided Detection |
