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An enhanced hybrid MRI thermometry technique for monitoring microwave thermal therapy
Author(s): A. Alivar; P. Faridi; P. Prakash; B. Natarajan
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Paper Abstract

The proton resonance frequency shift (PRFS) method is the most frequently used method to perform volumetric thermometry during MRI-guided thermal therapies. However, one of the main drawbacks of the PRFS method is its sensitivity to inter-frame motion and magnetic field drifts, which can result in incorrect estimation of temperature profiles. To address these problems, several techniques have been proposed, such as the reference less, multi-baseline, and hybrid methods. While the hybrid method has demonstrated the best performance, it assumes focal heating, which may be valid when using energy modalities such as high intensity focused ultrasound, but does not hold for heating using diffuse sources such as needle- and catheter-based microwave applicators. Here, we present an enhanced hybrid method suitable for MRI thermometry in the presence of motion during microwave thermal therapy. The presented model-based method uses the sparsity of wavelet coefficients of the phase shift based on the fact that heat-induced phase shifts exhibit a correlation structure due to smoothness. The presented enhanced hybrid method is compared to the previously presented hybrid and conventional PRFS methods for temperature estimation during microwave heating of a tissue-mimicking phantom with a 2.45 GHz directional microwave antenna integrated with 14.1 T high-field MRI. Experimental results demonstrate that the proposed method estimates microwave heating-induced temperature changes within 0.3-0.5 oC (mean error of 5.9 % over 5 min of heating) of fiber-optic temperature sensors, compared to 1.5 oC (mean error of 36.3% over 5 min of heating) with the hybrid technique.

Paper Details

Date Published: 8 March 2019
PDF: 6 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109512P (8 March 2019); doi: 10.1117/12.2511666
Show Author Affiliations
A. Alivar, Kansas State Univ. (United States)
P. Faridi, Kansas State Univ. (United States)
P. Prakash, Kansas State Univ. (United States)
B. Natarajan, Kansas State Univ. (United States)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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