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Real-Time 2-D Temperature Imaging Using Ultrasound

Dalong Liu, Emad S. Ebbini
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
IEEE Transactions on Biomedical Engineering, 2010

@article{liu2010real,

   title={Real-time 2-D temperature imaging using ultrasound},

   author={Liu, D. and Ebbini, E.S.},

   journal={Biomedical Engineering, IEEE Transactions on},

   volume={57},

   number={1},

   pages={12–16},

   year={2010},

   publisher={IEEE}

}

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We have previously introduced methods for noninvasive estimation of temperature change using diagnostic ultrasound. The basic principle was validated both in vitro and in vivo by several groups worldwide. Some limitations remain, however, that have prevented these methods from being adopted in monitoring and guidance of minimally invasive thermal therapies, e.g., RF ablation and high-intensity-focused ultrasound (HIFU). In this letter, we present first results from a real-time system for 2-D imaging of temperature change using pulse-echo ultrasound. The front end of the system is a commercially available scanner equipped with a research interface, which allows the control of imaging sequence and access to the RF data in real time. A high-frame-rate 2-D RF acquisition mode, M2D, is used to capture the transients of tissue motion/deformations in response to pulsed HIFU. The M2D RF data is streamlined to the back end of the system, where a 2-D temperature imaging algorithm based on speckle tracking is implemented on a graphics processing unit. The real-time images of temperature change are computed on the same spatial and temporal grid of the M2D RF data, i.e., no decimation. Verification of the algorithm was performed by monitoring localized HIFU-induced heating of a tissue-mimicking elastography phantom. These results clearly demonstrate the repeatability and sensitivity of the algorithm. Furthermore, we present in vitro results demonstrating the possible use of this algorithm for imaging changes in tissue parameters due to HIFU-induced lesions. These results clearly demonstrate the value of the real-time data streaming and processing in monitoring, and guidance of minimally invasive thermotherapy.
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