This paper describes a new ultrasound elastography technique, power strain imaging, based on vibro-elastography (VE) techniques. With this method, tissue is compressed by a vibrating actuator driven by low-pass or band-pass filtered white noise, typically in the 0-20 Hz range. Tissue displacements at different spatial locations are estimated by correlation-based approaches on the raw ultrasound radio frequency signals and recorded in time sequences. The power spectra of these time sequences are computed by Fourier spectral analysis techniques. As the average of the power spectrum is proportional to the squared amplitude of the tissue motion, the square root of the average power over the range of excitation frequencies is used as a measure of the tissue displacement. Then tissue strain is determined by the least squares estimation of the gradient of the displacement field. The computation of the power spectra of the time sequences can be implemented efficiently by using Welch's periodogram method with moving windows or with accumulative windows with a forgetting factor. Compared to the transfer function estimation originally used in VE, the computation of cross spectral densities is not needed, which saves both the memory and computational times. Phantom experiments demonstrate that the proposed method produces stable and operator-independent strain images with high signal-to-noise ratio in real time. This approach has been also tested on a few patient data of the prostate region, and the results are encouraging.
Accurate and fast seed localization plays a key role in computing dosimetry for prostate brachytherapy. Because
transrectal ultrasound is the primary imaging modality providing the guidance for prostate brachytherapy, an
ultrasound-only approach for dosimetry would offer many benefits. In this paper, we propose an ultrasound only
dosimetry solution, in which the brachytherapy seeds are located in reflected power images computed from
ultrasonic radio frequency signals and the boundary of the prostate is delineated from B-mode TRUS and vibroelastography
images as the prostate is stiffer than the surrounding tissue. The location of the implanted seeds
relative to the prostate boundary is thus obtained. As only one imaging modality, ultrasound, is used, image
registration is easy to implement. A prostate phantom with seeds embedded within it was built to evaluate the
proposed approach. To measure the seed localization accuracy in the reflected power images, the phantom was
scanned by CT as well. Experimental results show that the implanted seeds can be successfully located in the
reflected power images with high contrast and accuracy, and that the contour of the "prostate" can be detected
in the ultrasound vibro-elastography images outside the shadow of the seeds.
This paper proposed a novel ultrasonic imaging approach for detecting brachytherapy seeds. Accurate and fast seed localization plays a key role in computing dosimetry for prostate brachytherapy. However, currently used B-mode transrectal ultrasound (TRUS) does not adequately visualize implanted seeds, because the diameter of the seed is quite small and visualization is hampered by speckle noise and angulation of the specular reflection of the seeds. Based on the fact that much more ultrasound wave energy is reflected from metal seeds than from other scatterers in tissue, we developed a new seed detection method directly using ultrasound radio frequency (RF) signals (the raw high frequency echoes before the formation of B-mode TRUS images). It monitors the average power (a version of 2-norm) of the RF signals to measure the reflected wave energy. Each RF scan line is subdivided into a sequence of short segments with the same length and spacing. The average power of each segment is computed by the Fourier based spectra or parametric spectral analysis approaches. In the new method, the logarithmic compression is not applied to the raw RF data, and the average power is proportional to the sum of the square of the signal amplitude. Therefore, it produces significantly higher contrast than conventional B-mode TRUS. Furthermore, the average power algorithm can be implemented very efficiently since no numerical optimization is required. Phantom and ex-vivo experiments show that the average power technique successfully detects implanted brachytherapy seeds, and produces superior results compared with B-mode TRUS imaging.
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