High-spatial-resolution, instantaneous passive cavitation imaging with temporal resolution in histotripsy: a simulation study

Abstract

Purpose: In histotripsy, a shock wave is transmitted, and the resulting inertial bubble cavitation that disrupts tissue is used for treatment. Therefore, it is necessary to detect when cavitation occurs and track the position of cavitation occurrence using a new passive cavitation (PC) imaging method.

Methods: An integrated PC image, which is constructed by collecting the focused signals at all times, does not provide information on when cavitation occurs and has poor spatial resolution. To solve this problem, we constructed instantaneous PC images by applying delay and sum beamforming at instantaneous time instants. By calculating instantaneous PC images at all data acquisition times, the proposed method can detect cavitation when it occurs by using the property that when signals from the cavitation are focused, their amplitude becomes large, and it can obtain a high-resolution PC image by masking out side lobes in the vicinity of cavitation.

Results: Ultrasound image simulation confirmed that the proposed method has higher resolution than conventional integrated PC imaging and showed that it can determine the position and time of cavitation occurrence as well as the signal strength.

Conclusion: Since the proposed novel PC imaging method can detect each cavitation separately when the incidence of cavitations is low, it can be used to monitor the treatment process of shock wave therapy and histotripsy, in which cavitation is an important mechanism of treatment.

Keywords: Beamforming; Passive cavitation imaging; Strength of cavitation.

Fig. 1.. The medium, image, and radiofrequency (RF) data planes.

A. Acoustic emission that occurred at point P₁ in the medium plane at t₀ is propagated to the receiving array. B. The RF data are passively received by the linear array ultrasound probe and stored in memory. The arrival time of signals from point P₁ in the medium plane (time versus channel) takes the form of a curve. C. The arrival time curve of signals from point P₁ is the same as that of receive focusing curve P₁’. P₁ is assumed to have occurred at t₀. The RF data from point P₁ coincide with receive focusing curve P₁’. D. The RF data focused using receive focusing curve P₁’ are mapped to imaging point P₁. Since there are no RF data available in receive focusing curve P₂’, side lobes appear at P₂ since parts of P₁’ and P₂’ overlap.

Fig. 2.. Acoustic signal waveform and receive channel radiofrequency (RF) data.

A. The acoustic signal waveform p(t) due to bubble collapse is modeled as a short-time pulse in the form of a Gaussian function. B. The RF data for acoustic emission p(t) of a single bubble collapsing at z=30 mm passively detected by a 64-channel receiving system with a linear array ultrasound probe shows a curve shape in the time-channel representation. Note that the dotted line is the signal arrival time t_arrival and that the bubble collapse time is calculated by t₀=t_arrival-z/c.

Fig. 3.. Comparison of integrated and instantaneous passive cavitation (PC) images of a single cavitation.

A. Integrated PC image shows high side lobe levels. B. Instantaneous PC image constructed at t=t₀ shows high spatial resolution. C. A circular mask is placed where cavitation was detected. D. Integrated PC image with circular mask shows high-spatial resolution cavitation image with side lobe masked out. The images were normalized to the maximum value of each image to make its maximum brightness the same.

Fig. 4.. The time sequence of instantaneous passive cavitation images.

The sequence of instantaneous passive cavitation images was constructed at the following time instants: t=t₀-2 µs (A), t=t₀-1 µs (B), t=t₀ (C), t=t₀+1 µs (D), and t=t₀+2 µs (E). Note that the color map is adjusted to the peak pixel value of each image.

Fig. 5.. Temporal variation of the maximum pixel value of each instantaneous passive cavitation image for the whole time period of the radiofrequency data.

The peak corresponds to the main lobe of the image obtained by focusing the cavitation signals, and the values around the peak correspond to the side lobes. The reference time is assumed to be t₀=0 s.

Fig. 6.. The time-channel representation of the radiofrequency data passively detected by the ultrasound linear probe (64 channels) for the acoustic emission from five cavitations collapsing at different times and locations.

Note that the arrival time t_arrival is defined with respect to the acoustic emission from cavitation 3 collapsing at z=30 mm.

Fig. 7.. The time sequence of instantaneous passive cavitation images.

The sequence of instantaneous passive cavitation images was constructed at the following time instants: t=t₀-2 µs (A), t=t₀-1 µs (B), t=t₀ (C), t=t₀+1 µs (D), and t=t₀+2 µs (E). Note that the color map is adjusted to the peak pixel value of each image.

Fig. 8.. Five cavitations imaged by tracking temporal variation.

A. Cavitation can be detected using temporal variation of the maximum pixel value of each instantaneous passive cavitation image for the whole time period of radiofrequency data. B. Five cavitation regions (right column) are separated at time instants of cavitation occurrence by placing a circular mask (middle column) around the position of the peak value pixel (left column). It is assumed cavitation 3 occurs at t₀=0 s.

Fig. 9.. The superposition of five detected cavitations.

The superposition of five detected cavitations produces a highresolution passive cavitation (PC) image in which the locations and relative strengths of five cavitations can be identified: circular masks at detected cavitation positions (A); high-spatial-resolution cavitation image with side lobe masked out, two-dimensional cavitation map of five detected cavitations (B); map of relative strength (C); map of occurrence time (D); and integrated PC image of five cavitations (E).