In vivo ultrasound thermography in presence of temperature heterogeneity and natural motions.

Real-time ultrasound thermography has been recently demonstrated on commercially available diagnostic imaging probes. In vitro experimental results demonstrate high sensitivity to small, localized temperature changes induced by subtherapeutic focused ultrasound. Most of the published results, however, are based on a thermally induced echo strain model that assumes infinitesimal change in temperature between imaging frames. Under this assumption, the echo strain is computed using a low-pass axial differentiator, which is implemented by a finite-impulse response digital filter. In this paper, we introduce a new model for temperature estimation, which employs a recursive axial filter that acts as a spatial differentiator-integrator of echo shifts. The filter is derived from first principles and it accounts for a nonuniform temperature baseline, when computing the spatial temperature change between two frames. This is a major difference from the previously proposed infinitesimal echo strain filter ( δ-ESF) approach. We show that the new approach can be implemented by a first-order infinite-impulse response digital filter with depth-dependent spatial frequency response. Experimental results in vitro demonstrate the advantages over the δ-ESF approach in terms of suppressing the spatial variations in the estimated temperature without resorting to ad hoc low-pass filtering of echo strains. The performance of the new recursive echo strain filter (RESF) is also illustrated using echo data obtained during subtherapeutic localized heating in the hind limb of Copenhagen rat in vivo. In addition to the RESF, we have used an adaptive spatial filter to remove motion and deformation artifacts during real-time data collection. The adaptive filtering algorithm is described and comparisons with uncompensated estimated spatio-temporal temperature profiles are given. The results demonstrate the feasibility of in vivo ultrasound thermography with high sensitivity and specificity.