IMPROVEMENTS IN DIFFUSION TENSOR IMAGING (DTI)

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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. The overall aim of this project is to map the potential pathways of cognitive and motor activation. This has progressed in the last year to add several improvements in the DTI image reconstruction and processing software (?Tensorcalc?) that we wrote and maintain for the P41 RR09784. Diffusion tensor imaging (DTI) is a promising new technique for the assessment of white matter (WM) structural integrity and connectivity. We have written and refined 3 key core DTI map tracking algorithms that are being used to track white matter fibers for determining the potential white matter trafficking patterns. One of the more exciting methods to arise from the noninvasive mapping of white matter tracks is the potential of tracking the white matter fibers from one region of brain to another. This in essence, reveals the underlying ?wiring? of the activated brain. Our algorithm allows for real-time connectivity maps that can be generated from planting a seed in one white matter tract region. We have constructed software ?phantoms? to check the algorithms for accuracy and reproducibility. Our diffusion tensor imaging protocol is performed using a spin echo EPI technique and we have added a host of new spiral methods. The vector maps hold the orientation of the fibers as well as the magnitude of the orientation. From the fiber maps, one can compose several general approaches to finding connectivity from fiber to fiber from a variety of model algorithms that we have built.