Objective Acoustic radiation force (ARF)-based approaches to measure tissue elasticity require transmission of a focused high-energy acoustic pulse from a stationary ultrasound probe and ultrasound-based tracking of the resulting tissue displacements to obtain stiffness images or shear wave speed estimates. The method has established benefits in biomedical applications such as tumor detection and tissue fibrosis staging. One limitation, however, is the dependence on applied probe pressure, which is difficult to control manually and prohibits standardization of quantitative measurements. To overcome this limitation, we built a robot prototype that controls probe contact forces for shear wave speed quantification. Methods The robot was evaluated with controlled force increments applied to a tissue-mimicking phantom and in vivo abdominal tissue from three human volunteers. Results The root-mean-square error between the desired and measured forces was 0.07 N in the phantom and higher for the fatty layer of in vivo abdominal tissue. The mean shear wave speeds increased from 3.7 to 4.5 m/s in the phantom and 1.0 to 3.0 m/s in the in vivo fat for compressive forces ranging from 2.5 to 30 N. The standard deviation of shear wave speeds obtained with the robotic approach were low in most cases (< 0.2 m/s) and comparable to that obtained with a semiquantitative landmark-based method. Conclusion Results are promising for the introduction of robotic systems to control the applied probe pressure for ARF-based measurements of tissue elasticity. Significance This approach has potential benefits in longitudinal studies of disease progression, comparative studies between patients, and large-scale multidimensional elasticity imaging.
In Part I of this paper, we detected elements blocked by ribs during simulated and in vivo transcostal liver scans, and we turned those elements OFF to compensate for the loss in visibility of liver vasculature. Here, we apply blocked-element detection and adaptive compensation to large synthetic-aperture (SA) data collected through rib samples ex vivo, in order to reduce near-field clutter and to recover lateral resolution. To construct large synthetic transmit and receive apertures, we collected the individual-channel signals from a fully sampled matrix array at multiple and known array locations across the tissue samples. The blocked elements in SAs were detected using the method presented in Part I and retroactively turned OFF, while the subapertures covering intercostal spaces were either compounded, or coherently summed using uniform and adaptive element-weighting schemes. Turning OFF the blocked elements reduced the reverberation clutter by 5 dB on average. Adaptive weighing of the nonblocked elements to rescale the attenuated spatial frequencies reduced sidelobe levels by up to 5 dB for the transcostal acquisitions, and demonstrated a potential to restore lateral resolution to the nonblocked levels. In addition, the arrival-time surfaces were reconstructed to estimate the aberration from intercostal spaces and to offer further means to compensate for the loss of focus quality in transthoracic imaging.
When imaging with ultrasound through the chest wall, it is not uncommon for parts of the array to get blocked by ribs, which can limit the acoustic window and significantly impede visualization of the structures of interest. With the development of large-aperture, high-element-count, 2-D arrays and their potential use in transthoracic imaging, detecting and compensating for the blocked elements is becoming increasingly important.We synthesized large coherent 2-D apertures and used them to image a point target through excised samples of canine chest wall. Blocked elements are detected based on low amplitude of their signals. As a part of compensation, blocked elements are turned off on transmit (Tx) and receive (Rx), and point-target images are created using: coherent summation of the remaining channels, compounding of intercostal apertures, and adaptive weighting of the available Tx/Rx channel-pairs to recover the desired k-space response. The adaptive compensation method also includes a phase aberration correction to ensure that the non-blocked Tx/Rx channel pairs are summed coherently.To evaluate the methods, we compare the point-spread functions (PSFs) and near-field clutter levels for the transcostal and control acquisitions. Specifically, applying k-space compensation to the sparse aperture data created from the control acquisition reduces sidelobes from -6.6 dB to -12 dB. When applied to the transcostal data in combination with phase-aberration correction, the same method reduces sidelobes only by 3 dB, likely due to significant tissue induced acoustic noise. For the transcostal acquisition, turning off blocked elements and applying uniform weighting results in maximum clutter reduction of 5 dB on average, while the PSF stays intact. Compounding reduces clutter by about 3 dB while the k-space compensation increases clutter magnitude to the non-compensated levels.
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