The goal of this project is to overcome the currently unsolved problem of using magnetic resonance imaging (MRI) to measure temperature changes in fat-based tissues. Thermal therapies that use minimally invasive and non-invasive techniques such as radio frequency currents, microwaves, or high intensity focused ultrasound (HIFU) have the potential to revolutionize tumor ablation and drug delivery procedures. Due to the minimally invasive nature of these techniques, constant monitoring of energy deposition and temperature changes are required to ensure treatment efficacy and patient safety. Many investigators have chosen to perform these procedures under MRI guidance because of the improved contrast in soft tissue imaging, the elimination of ionizing radiation, and the ability to measure real time temperature changes in water-based tissues. However, the ability to use MRI for fast, accurate, and robust temperature measurements in fat-based tissues remains an unsolved problem. This limitation represents a large obstacle to the implementation of non- invasive thermal therapies in sites where thermal energy may be deposited in fatty tissue. MR thermometry techniques based on the temperature dependence of the water proton resonant frequency (PRF) are well established and in wide use for water-based tissues, however the method is ineffective in fat- based tissues. To measure temperature changes in fat, investigators have turned to the longitudinal relaxation time, T1, which is temperature dependent for both water- and fat-based tissues. Unfortunately, T1 based temperature measurements are significantly less accurate and stable than PRF temperature measurements in water-based tissues. In light of these challenges, we are taking a two pronged approach to solving the problem of MR temperature measurements in fat. First, the MR sequence will be designed to simultaneously acquire PRF and T1 information. This will allow PRF temperature measurements to be made in all water-based tissues, and T1 temperature measurements to be made in al fat-based tissues. Second, predictions from a thermal model will be incorporated into the process in order to improve the accuracy of the T1 temperature measurements in fat-based tissues. The project will be carried out in four steps. First, we will study the behavior of T1 as a function of temperature in a variety of tissue types. Second, we will develop and optimize the hybrid PRF/T1 sequence. Third, we develop thermal modeling techniques for inhomogeneous tissues. Fourth, we will test and optimize methods for combining the MR temperature measurements with the thermal model temperature predictions.

Public Health Relevance

Thermal therapies such as those using high intensity focused ultrasound offer the possibility of treating tumors without invasive surgery. For the treatment to be safe and effective, it is essential that there be a way to monitor temperature changes throughout the heating process in all tissues. The goal of this research project is to overcome the currently unsolved problem of using magnetic resonance imaging to measure temperature changes in fat-based tissues. If successful, the methods developed would help these promising thermal treatments to become clinically viable for a wider range of applications.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32EB012917-02
Application #
8307201
Study Section
Special Emphasis Panel (ZRG1-F15-D (20))
Program Officer
Erim, Zeynep
Project Start
2011-09-30
Project End
2013-09-29
Budget Start
2012-09-30
Budget End
2013-09-29
Support Year
2
Fiscal Year
2012
Total Cost
$49,214
Indirect Cost
Name
University of Utah
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
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
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
Todd, Nick; Prakash, Jaya; Odéen, Henrik et al. (2014) Toward real-time availability of 3D temperature maps created with temporally constrained reconstruction. Magn Reson Med 71:1394-404
Todd, Nick; Diakite, Mahamadou; Payne, Allison et al. (2014) In vivo evaluation of multi-echo hybrid PRF/T1 approach for temperature monitoring during breast MR-guided focused ultrasound surgery treatments. Magn Reson Med 72:793-9
Diakite, Mahamadou; Payne, Allison; Todd, Nick et al. (2013) Irreversible change in the T1 temperature dependence with thermal dose using the proton resonance frequency-T1 technique. Magn Reson Med 69:1122-30
Todd, Nick; Diakite, Mahamadou; Payne, Allison et al. (2013) Hybrid proton resonance frequency/T1 technique for simultaneous temperature monitoring in adipose and aqueous tissues. Magn Reson Med 69:62-70