The main objective of our proposed research is to develop, implement and improve fast 3D dynamic adaptive MRI techniques to meet the specific needs of several interventional MRI applications. Adaptive MRI methods aim to use the wealth of a priori known information available during dynamic imaging to increase the efficiency of subsequent data acquisition and hence speed imaging, all without the need for additional specialized gradient or RF hardware. No other MRI method development effort existing today in our field exploits this advantage. Beginning in 1995, our research initiative in adaptive in adaptive MRI had with no software or hardware infrastructure. Now, our facility is equipped for studies of adaptive spatial encoding during real-time imaging using a commercial MR scanner, extraordinary computer tools, and significant research experience. We propose here two complementary approaches to develop adaptive 3D methods. One approach to be taken in our study concentrates on innovative pulse sequence design, combined with the tailoring of control systems models and the use of feedback, based upon our Linear Systems theory view of adaptive MRI. Another approach is to emphasize the study of the specificity of the encoding basis sets determined using the 3D SVD, and the optimization of the numerical mathematical and acquisition software. With their recent introduction into hospitals, open configuration interventional MR systems have eliminated the distinctions between surgery, therapy and imaging. Real-time image data is now viewed as an extraordinary resource to be exploited in innovative computer-assisted procedures, and provide intra-operative guidance or monitoring for the surgeon. Our research objective of 3D adaptive MRI is specifically chosen to meet the challenges of anatomy, the heterogeneous thermal distribution in tissue during therapy, the introduction of flexible rather than fixed probes, and the need for advanced computer-produced visualization tools for the surgeon. Our specific objectives include building the infrastructure for 3D adaptive MRI volume acquisition, and the development of methods that specifically meet the 3D MRI needs of Adaptive 3D Functional MRI; 3D Monitoring of Thermal Therapies; 3D Tip Tracking of Catheters and Probes; and 3D Data Acquisition for Intraoperative Guidance Software. Finally, we plan to evaluate our methods using phantoms.
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