MRI-guided high focused ultrasound (MRgFUS) has the potential to revolutionize many thermal therapy applications by providing a safe, effective and practical means of non-invasive surgery, targeted drug activation and physiological manipulation (e.g., enhanced blood flow). A fundamental limitation of currently used magnetic resonance temperature imaging (MRTI) techniques is their inability to accurately measure 3D temperature distributions simultaneously in real-time, with high temporal and spatial resolution over large volumes. This limitation is critical in transcranial MRgFUS of the brain where dangerous heating is known to occur near the skull and other bony structures. The goal of this project is to improve MRTI techniques by significantly expanding their current spatial and temporal resolution and field of view (FOV) capabilities. This project proposes a new MRTI approach which subsamples k-space in each time frame and uses a novel combination of methods, including parallel imaging and a biophysical model that incorporates subject-specific inhomogeneous tissue biothermal and acoustic properties, to dynamically (in real-time) predict k-space lines not measured. This new model predictive filtering (MPF) technique will achieve the required accurate, precise, and rapid high-resolution measurements of temperature distributions over regions sufficiently large to effectively monitor and control treatments in real-time. This proposal aims to develop the basic capabilities in a form in which temperature measurements can be made over the entire FOV with adequate time and spatial resolution and retrospective image reconstruction. Although these innovative techniques are of potential utility in many MRgFUS therapies, they will be of immediate value to improve the safety and efficacy of transcranial brain MRgFUS.
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