Spatially Oriented Database for Digital Brain Images

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DESCRIPTION (provided by applicant): The overall goal of this project is the integration of advanced image-processing, data-analysis, and data management techniques into a brain-image database (BRAID), for the support of image-based clinical trials. The integration of these components has greatly aided our collaborators' management and analysis of image-based clinical trials (IBCTs) for the elucidation of structure-function associations for the human brain. In the previous cycle, we added segmentation capabilities, implemented Bayesian methods for lesion-deficit analysis, and began construction of a functional white-matter atlas based on lesion-deficit data. These methods, in conjunction with BRAID's visualization and other statistical tools, have resulted in contributions to the peer-reviewed clinical and engineering literature. However, our experience also demonstrates the need for extensions to BRAID. First, our segmentation algorithm is limited by its foundation on a statistical signal-intensity model of T 1-weighted spoiled gradient-recalled echo images. Second, given improvements in our registration techniques, we now have high-quality morphological data from our collaborators' IBCTs, but lack sophisticated methods for morphology-function analysis. Third, given the brain's plasticity, construction of an advanced functional atlas requires access to acute lesion-deficit data; our current collaborators are collecting subacute or chronic lesion-deficit data. Finally, we could facilitate the interchange of data, software, and analytic results with our collaborators and other colleagues by implementing BRAID based on open-source software. Towards these ends, we propose four specific aims to further extend BRAID's functionality: extension of our segmentation algorithm to incorporate more complex spatial and signal-intensity information; development of Bayesian methods for morphological analysis, to complement our Bayesian methods for lesion-deficit analysis; extension of BRAID to accommodate acute-stroke data, including magnetic-resonance (MR) perfusion and diffusion sequences; and reimplementation of BRAID using open-source components. We will test these image analysis, segmentation, and acutestroke extensions to BRAID using data from three IBCTs.