High intensity focused ultrasound (HIFU), applied in multiple, short pulses has great promise as a noninvasive therapy for several diseases, particularly cancer. At present, this and all other """"""""High Temperature Therapy"""""""" heating modalities 1) deliver unknown and potentially highly variable, thermal dose distributions (resulting in patient pain, normal tissue damage and/or inadequate treatment of the clinical target) and/or 2) can require inordinate amounts of time (to deliver a complete, yet safe dose), particularly for """"""""large"""""""" tumors. To overcome these limitations we propose to develop and comparatively evaluate a MR temperature based, optimization and feedback control approach for implementing such treatments, using HIFU as the heating modality. The optimized plans will serve as the feed-forward signal to a model predictive, thermal dose controller to vary the applied power magnitude (in both time and space) on-line during the treatment. Several recent research advances at the University of Utah make our proposed optimization/control approach particularly unique and promising, including the development of: 1) Model Predictive HTT Control techniques--the best control methodology to apply to these non-linear, distributed systems; 2) new, reduced order models (ROMs) for use in on-line, real time model based control, and; 3) Dynamic Inversion to help plan treatments. The comparative studies will concentrate on determining 1) the advantages that dose based optimization and control approaches have over the current, non-optimized, """"""""model-less"""""""", ad hoc power, temperature and imaging control approaches and 2) the level of modeling needed for delivering high quality clinical treatments. Our newly developed MRA method for detecting, locating, and segmenting thermally significant blood vessels and our recent advances in thermal and ultrasound modeling will be used to construct accurate, detailed patient models for the comparative studies. Those studies will use simulations, dynamic phantoms and animal tests, and will initially concentrate on brain and sarcoma sites. The successful development and testing of the proposed approach will result in an overall system that will make HIFU optimally prescribable, controllable and evaluable (i.e. clinically practical), important features that do not exist at present. More generally, because of the basic nature of the optimization and control tools to be developed, these advances will be readily other HTT heating modalities.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA087785-03
Application #
6778367
Study Section
Radiation Study Section (RAD)
Program Officer
Stone, Helen B
Project Start
2002-08-02
Project End
2006-07-31
Budget Start
2004-08-12
Budget End
2006-07-31
Support Year
3
Fiscal Year
2004
Total Cost
$291,748
Indirect Cost
Name
University of Utah
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Johnson, Sara L; Dillon, Christopher; Odéen, Henrik et al. (2016) Development and validation of a MRgHIFU non-invasive tissue acoustic property estimation technique. Int J Hyperthermia 32:723-34
Dillon, Christopher; Roemer, Robert; Payne, Allison (2015) Magnetic resonance temperature imaging-based quantification of blood flow-related energy losses. NMR Biomed 28:840-51
Dillon, C R; Todd, N; Payne, A et al. (2013) Effects of MRTI sampling characteristics on estimation of HIFU SAR and tissue thermal diffusivity. Phys Med Biol 58:7291-307
Niu, Ran; Skliar, Mikhail (2012) Identification of reduced-order thermal therapy models using thermal MR images: theory and validation. IEEE Trans Med Imaging 31:1493-504
Dillon, C R; Vyas, U; Payne, A et al. (2012) An analytical solution for improved HIFU SAR estimation. Phys Med Biol 57:4527-44
Niu, Ran; Skliar, Mikhail (2011) Identification of controlled-complexity thermal therapy models derived from magnetic resonance thermometry images. PLoS One 6:e26830
Todd, Nick; Adluru, Ganesh; Payne, Allison et al. (2009) Temporally constrained reconstruction applied to MRI temperature data. Magn Reson Med 62:406-19
Guo, Jun-Yu; Kholmovski, Eugene G; Zhang, Ling et al. (2007) Evaluation of motion effects on parallel MR imaging with precalibration. Magn Reson Imaging 25:1130-7
Guo, Jun-Yu; Kholmovski, Eugene G; Zhang, Ling et al. (2006) k-space inherited parallel acquisition (KIPA): application on dynamic magnetic resonance imaging thermometry. Magn Reson Imaging 24:903-15
Arora, Dhiraj; Minor, Mark A; Skliar, Mikhail et al. (2006) Control of thermal therapies with moving power deposition field. Phys Med Biol 51:1201-19

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