IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 1, JANUARY 2010 185 Local Harmonic Motion Monitoring of Focused Ultrasound Surgery—A Simulation Model Janne Heikkil¨ a ∗ , Laura Curiel, Member, IEEE, and Kullervo Hynynen, Senior Member, IEEE Abstract—In this paper, a computational model for localized har- monic motion (LHM) imaging-based monitoring of high-intensity focused ultrasound surgery (FUS) is presented. The LHM tech- nique is based on a focused, time-varying ultrasound radiation force excitation, which induces local oscillatory motions at the fo- cal region. These vibrations are tracked, using pulse-echo imag- ing, and then, used to estimate the mechanical properties of the sonication region. LHM is feasible for FUS monitoring because changes in the material properties during the coagulation process affect the measured displacements. The presented model includes separate models to simulate acoustic sonication fields, sonication- induced temperature elevation and mechanical motion, and pulse- echo imaging of the induced motions. These 3-D simulation models are based on Rayleigh–Sommerfield integral, finite element, and spatial impulse response methods. Simulated-tissue temperature elevation and mechanical motion were compared with previously published in vivo measurements. Finally, the simulation model was used to simulate coagulation and LHM monitoring, as would occur with multiple, neighbouring sonication locations covering a large tumor. Index Terms—Biomedical applications of acoustic radiation, finite-element (FE) methods, focused ultrasound surgery (FUS), local harmonic motion (LHM) imaging, simulation. I. INTRODUCTION W HEN an ultrasound wave propagates in a medium, such as soft tissue, some of its energy is absorbed, resulting in an increase in the tissue temperature. Many applications of noninvasive thermal therapy, using high-intensity focused ultra- sound surgery (FUS) have been published [1]–[3]. In order to achieve consistent tissue coagulation, the actual temperature must be monitored during the therapy. For ex- ample, some tissue-specific parameters (e.g., blood perfusion and ultrasound absorption coefficient) may have local vari- ations that affect the temperature elevation and distribution. Presently, the tissue temperature distribution around the son- ication point is monitored by using magnetic resonance imag- Manuscript received November 28, 2008; revised June 19, 2009. First pub- lished October 9, 2009; current version published January 4, 2010. This work was supported by the Academy of Finland, Finnish Cultural Foundation, North Savo Regional fund, National Institutes of Health (NIH) Grant R33 CA102884, the CRC program, and a grant from Ontario Research Fund. Asterisk indicates corresponding author. ∗ J. Heikkil¨ a was with the Department of Physics, University of Kuopio, 70211 Kuopio, Finland. He is now with the Department of Oncology, Kuopio Univer- sity Hospital, 70211 Kuopio, Finland (e-mail: janne.heikkila@ kuh.fi). L. Curiel is with the High Intensity Focused Ultrasound (HIFU) Laboratory, Thunder Bay Regional Research Institute, Thunder Bay, ON P7B 6V4, Canada (e-mail: curiell@ tbh.net). K. Hynynen is with the Imaging Research, Sunnybrook Health Science Cen- ter, Toronto, ON M4N 3M5, Canada (e-mail: khynynen@ sri.utoronto.ca). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TBME.2009.2033465 ing (MRI) during clinical treatments. Due to the high-cost and technical limitations of MRI monitoring, alternative treatment monitoring techniques are being studied. Most of these alterna- tive approaches to real-time temperature monitoring are based on diagnostic ultrasound and the detection of changes in the tis- sue’s temperature-dependent properties, such as backscattered power [4], speed of sound [5], and stiffness [6]–[8]. Estima- tion of stiffness changes has been proven feasible for FUS monitoring, since the contrast between thermally coagulated and surrounding tissues can be as high as one order of mag- nitude [9]. Several ultrasound radiation force-based techniques estimating stiffness-related tissue parameters have been pub- lished, including acoustic radiation force impulse (ARFI) imag- ing [10], ultrasound-stimulated acoustic emission (USAE) [11], ultrasound-stimulated vibro-acoustography (USVA) [12], shear wave elasticity imaging (SWEI) [13], or localized harmonic motion (LHM) imaging [14]. LHM imaging [14] is a recently developed technique that evaluates the mechanical properties of soft tissue. In LHM, mechanical properties of tissue are estimated, using pulse- echo imaging to detect tissue harmonic displacements in- duced by a time-varying ultrasound radiation force. Different sonication beam configurations can be used to produce this time-varying radiation force excitation; for two-element ex- citation systems, overlapping beams at slightly different fre- quencies are used, whereas for single-beam configurations, bursts or amplitude-modulated sonication are used [10]–[15]. The LHM technique is considered an elastographic tool be- cause the characteristics of the induced harmonic motions at the sonication point are dependent on local mechanical tissue properties. FUS monitoring based on LHM has shown to be feasible for FUS monitoring [7], [8], [16], [17], as tissue motion induced by amplitude-modulating. A therapy beam can be monitored by a separate diagnostic pulse-echo transducer. The advantage of combining LHM with FUS is that the time-varying sonication beam used to make tissues vibrate that can also be used to coagulate the target tissue. The aim of our study was to develop and optimize a com- plete simulation model of the LHM monitoring technique that can potentially be used to understand the physical phenomenon involved. A simulation study of LHM imaging has been pub- lished [17], however that study investigated only the mechanical properties of the tissue. In our study, an ultrasound propagation model was combined with a mechanical and thermal model of the tissue. In addition, a second ultrasound model was used to simulate the detection of tissue motion. The effects of tempera- ture elevation and thermal coagulation on the tissue parameters 0018-9294/$26.00 © 2009 IEEE