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Ultrasound temperature estimation based on probability variation of backscatter data
Author(s) -
Tsui PoHsiang,
Shu YuChen,
Chen WenShiang,
Liu HaoLi,
Hsiao IngTsung,
Chien YuTing
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3700235
Subject(s) - backscatter (email) , imaging phantom , ultrasound , envelope (radar) , materials science , statistics , acoustics , optics , physics , mathematics , radar , computer science , telecommunications , wireless
Purpose: In recent years, ultrasound imaging has become an attractive modality for noninvasive temperature monitoring. Temperature variations that occur during tissue heating could induce changes in various acoustic parameters that may affect the echo interference so as to make ultrasound backscattering a random process. In this study, we assumed that the degree of variation in the probability distribution of the backscattered signals is temperature dependent. The feasibility of using the variation in the backscatter statistics for ultrasound temperature estimation was investigated in this study.Methods: We tested this hypothesis by carrying out experiments on agar phantoms and tissue samples using a temperature‐regulated water tank and a microwave ablation system. During heating, raw images of the backscattered‐signal envelope of each phantom and tissue at temperatures ranging between 37 °C and 45 °C were acquired to construct the parametric matrix based on the ratio of the change in the Nakagami parameter (RCN), which was used as a quantitative measure of the backscatter statistics. The absolute value of the RCN (ARCN) matrix was obtained, to which a polynomial approximation was applied to obtain the ARCN pa image.Results: The results showed that the RCN matrix locally increased or decreased with increasing temperature, indicating bidirectional changes in the backscatter statistics. We also found that the ARCN significantly increased with the temperature, demonstrating that the magnitude of the variation in the probability distribution of the backscattered‐signal envelope is a monotonic function of temperature. Unlike the phantom, tissues tended to exhibit a nonlinear dependency of the ARCN on the temperature that may be attributable to tissue denaturation. Especially, the ARCN pa image is highly suitable for visualizing the contour of the temperature distribution during microwave ablation of tissue samples.Conclusions: This study has demonstrated that temperature changes are reflected in variations in the envelope statistics. This novel approach makes it possible to develop an ultrasound temperature imaging method for simultaneously estimating the thermal dose and the tissue properties.