The goal of this project is to improve magnetic resonance temperature imaging (MRTI) techniques to be used in high intensity focused ultrasound (HIFU) thermal treatments by significantly expanding their current spatial and temporal resolution and field of view (FOV) capabilities. These improvements will overcome the speed, resolution, and FOV roadblocks in transcranial MRI guided focused ultrasound therapy and thereby accelerate the acceptance of this technique into clinical practice. To realize this goal we propose to develop a completely new MRTI approach that increases speed by subsampling the measurement space (k-space) in each time frame and that uses a subject-specific biophysical model incorporating inhomogeneous tissue biothermal and acoustic properties to dynamically (in real-time) predict the missing measurements. The uniqueness of this approach is that it supplements 3D MRTI with additional subject-specific biophysical information. We refer to this method as model predictive filtering (MPF) because it is similar to other linear predictive filters, such as the Kalman filter. This new 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. The work will develop methods to improve temperature measurements in three stages: 1) First a temporally-constrained reconstruction (TCR) technique will be developed to obtain retrospective MRTI measurements with high spatial and temporal resolution over the volume of interest. 2) The TCR temperatures combined with tissue segmentation and beam modeling will be used to determine 3D subject- specific tissue acoustic and thermal properties. 3) The tissue acoustic and thermal properties will be incorporated into the MPF technique to obtain the desired temperature images over the full insonified volume in real-time. These methods will then be tested in vivo in animal models and in vitro and ex vivo in a transcranial MRgHIFU system. Transcranial brain MRgHIFU is an important application that requires the development of innovative treatment strategies and will definitely require rapid, accurate, high spatial resolution temperature measurements over the entire insonified volume. These techniques are highly novel, and upon success will facilitate experiments to accelerate the acceptance of transcranial brain MRgHIFU as well as potentially other new MRgHIFU applications.

Public Health Relevance

This project will be the first to develop and validate a method for obtaining MRI temperature measurements at very high spatial and temporal resolution covering the full image volume treated by High Intensity Focused Ultrasound and thus remove a major roadblock currently inhibiting clinical application of transcranial MRI guided focused ultrasound therapy. These techniques will improve the accuracy of thermal dose delivery measurements as well as develop methods to detect changes in tissue thermal and acoustic properties.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
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University of Utah
Schools of Medicine
Salt Lake City
United States
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Svedin, Bryant T; Parker, Dennis L (2017) Technical Note: The effect of 2D excitation profile on T1 measurement accuracy using the variable flip angle method with an average flip angle assumption. Med Phys 44:5930-5937
Svedin, Bryant T; Payne, Allison; Parker, Dennis L (2016) Respiration artifact correction in three-dimensional proton resonance frequency MR thermometry using phase navigators. Magn Reson Med 76:206-13
Odéen, Henrik; Almquist, Scott; de Bever, Joshua et al. (2016) MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling. J Ther Ultrasound 4:23
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Almquist, Scott; Parker, Dennis L; Christensen, Douglas A (2016) Rapid full-wave phase aberration correction method for transcranial high-intensity focused ultrasound therapies. J Ther Ultrasound 4:30
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Odéen, Henrik; Todd, Nick; Dillon, Christopher et al. (2016) Model predictive filtering MR thermometry: Effects of model inaccuracies, k-space reduction factor, and temperature increase rate. Magn Reson Med 75:207-16
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Odéen, Henrik; Todd, Nick; Diakite, Mahamadou et al. (2014) Sampling strategies for subsampled segmented EPI PRF thermometry in MR guided high intensity focused ultrasound. Med Phys 41:092301

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