
==== Front
Ultrason Sonochem
Ultrason Sonochem
Ultrasonics Sonochemistry
1350-4177
1873-2828
Elsevier

S1350-4177(24)00299-2
10.1016/j.ultsonch.2024.107051
107051
Original Research Article
2D spatiotemporal passive cavitation imaging and evaluation during ultrasound thrombolysis based on diagnostic ultrasound platform
Zhang Qi a1
Zhu Yifei a1
Zhang Guofeng a
Xue Honghui ab
Ding Bo c
Tu Juan juantu@nju.edu.cn
a⁎
Zhang Dong dzhang@nju.edu.cn
a⁎
Guo Xiasheng a
a Key Laboratory of Modern Acoustics (MOE), Department of Physics, Collaborative Innovation Center of Advanced Microstructure, Nanjing University, Nanjing 210093, China
b Wuxi Vocational Institute of Commerce, Wuxi 214153, Jiangsu, China
c Zhuhai Ecare Electronics Science & Technology Co., Ltd., Zhuhai 519041, China
⁎ Corresponding authors. juantu@nju.edu.cndzhang@nju.edu.cn
1 These authors contributed equally to this work.

31 8 2024
11 2024
31 8 2024
110 10705130 7 2024
20 8 2024
27 8 2024
© 2024 The Authors. Published by Elsevier B.V.
2024

https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Acoustic cavitation plays a critical role in various biomedical applications. However, uncontrolled cavitation can lead to undesired damage to healthy tissues. Therefore, real-time monitoring and quantitative evaluation of cavitation dynamics is essential for understanding underlying mechanisms and optimizing ultrasound treatment efficiency and safety. The current research addressed the limitations of traditionally used cavitation detection methods by developing introduced an adaptive time-division multiplexing passive cavitation imaging (PCI) system integrated into a commercial diagnostic ultrasound platform. This new method combined real-time cavitation monitoring with B-mode imaging, allowing for simultaneous visualization of treatment progress and 2D quantitative evaluation of cavitation dosage within targeted area. An improved delay-and-sum (DAS) algorithm, optimized with a minimum variance (MV) beamformer, is utilized to minimize the side lobe effect and improve the axial resolution typically associated with PCI. In additional to visualize and quantitatively assess the cavitation activities generated under varied acoustic pressures and microbubble concentrations, this system was specifically applied to perform 2D cavitation evaluation for ultrasound thrombolysis mediated by different solutions, e.g., saline, nanodiamond (ND) and nitrogen-annealed nanodiamond (N-AND). This research aims to bridge the gap between laboratory-based research systems and real-time spatiotemporal cavitation evaluation demands in practical uses. Results indicate that this improved 2D cavitation monitoring and evaluation system could offer a useful tool for comprehensive evaluating cavitation-mediated effects (e.g., ultrasound thrombolysis), providing valuable insights into in-depth understanding of cavitation mechanisms and optimization of cavitation applications.

Keywords

Passive cavitation imaging
Cavitation dosage
Delay and sum beamforming
Minimum variance adaptive beamformer
Ultrasound thrombolysis
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pmc1 Introduction

Ultrasound offers significant research value and application prospects in clinical diagnosis and treatment. Its benefits include non-invasiveness, absence of radiation, low cost, ease of use, and the precise delivery of acoustic energy to deep tissues. In recent years, the great advances in the design and application of multifunctional nanomaterials and ultrasound contrast agents have greatly promoted the rapid development of precise diagnostic imaging and targeted ultrasound therapy technologies [1], [2]. By introducing ultrasound contrast agent microbubbles [3], phase-change nanodroplets [4], sono-sensitizers [5], and micro-/nano-particles [6] into the target tissue as cavitation nuclei, the cavitation threshold of biological tissue is significantly lowered. This concentration of incident acoustic energy creates extreme physical conditions—high temperature, high pressure, and shock waves—that induce biological effects. These effects include acoustic perforation of cell membranes [7] and localized tissue heating [8], thereby enhancing therapeutic efficacy. In biomedical research, acoustic cavitation has been demonstrated to play a crucial role in various therapeutic applications such as sonodynamic therapy [9], including tumor treatment [10], [11], [12], lithotripsy [13], [14], thrombolysis [15], [16], [17], and drug/gene delivery [18], [19], [20], [21], [22]. However, cavitation activities may lead to unpredictable damage or irreversible injury in normal tissues [23], [24], [25]. Therefore, monitoring and evaluating the spatiotemporal variations in cavitation activity is crucial for understanding cavitation mechanisms, controlling and optimizing therapeutic processes, and enhancing treatment efficiency.

Currently, cavitation monitoring methods are mainly classified into two categories: optical and acoustic. Acoustic methods, which are non-invasive and do not require a transparent medium, provide faster data acquisition and processing. Consequently, they are better suited for real-time monitoring compared to optical methods such as high-speed photography [26] and sonoluminescence [27]. Commonly used acoustic techniques primarily include 1D active and passive cavitation detection. In active cavitation detection (ACD), transmitting and receiving transducers are typically positioned with a certain intersection angle or are set up for self-emission and reception [28]. Conversely, passive cavitation detection (PCD) captures cavitation scattering signals from a direction that is perpendicular to the emitted sound waves, making it more sensitive to subtle cavitation signals [29], [30] as it is not affected by direct sound signals [31], [32].

Although it can detect the occurrence and provide certain quantitative information of cavitation activity, the 1D PCD technology, which utilizes a single-element receiving transducer, is generally limited to measuring cavitation intensity and duration within a specific region along the transducer’s axial direction. By employing cavitation mapping technology, particularly 2D passive cavitation imaging (PCI) using transducer arrays, it is possible to effectively overcome the spatial limitations of 1D detection and substantially broaden the scope of cavitation monitoring [33], [34], [35]. 2D PCI typically utilizes delay and sum (DAS) beamforming to reconstruct spatial distributions of the signal [36], [37], [38]. However, the axial resolution of images obtained with the DAS algorithm is low, because the ultrasound pulses inducing cavitation usually have longer duration than conventional B-mode ultrasound imaging pulses, which certainly decrease its resolution [39], [40].

Meanwhile, the current applications of PCI with linear arrays normally limited to qualitatively visualize the cavitation location occurring in the processes as thermal ablation [41], [42], magnetic microbubble localization [43], [44], [45], drug delivery [46], [47], and blood–brain barrier disruption [48], [49]. Unfortunately, these studies rarely manage to both qualitatively display the cavitation occurrence regions and quantitatively evaluate the accumulated cavitation dosage within the regions over a certain ultrasound exposure period [50], thus making it incapable to comprehensively and accurately quantify the spatiotemporal properties of cavitation generated in practical ultrasound applications.

Another significant limitation of existing PCI systems is their design for laboratory research, requiring connection to larger research platforms (e.g., Verasonics Vantage ultrasound system). This necessitates transferring I/Q (in-phase/quadrature) data from the Verasonics system to a personal computer for subsequent signal processing and image analysis, greatly reducing the system’s convenience and clinical applicability.

For above reasons, the current research focused on developing an improved time-division multiplexing PCI system based on a commercial diagnostic ultrasound platform. Specifically, this platform could collaboratively control therapeutic ultrasound emissions, enabling real-time 2D cavitation mapping alongside B-mode imaging during ultrasound application. It also integrated post-processing for the quantitative evaluation of accumulated cavitation dosage within the targeted region throughout the treatment. To address the issue of low axial resolution, a modified DAS algorithm, optimized by a minimum variance (MV) beamformer, was employed to suppress side lobe and tail-like artifacts. Additionally, upon the demands of integrating more sophisticated adaptive beamforming algorithms, graphic processing units (GPUs) were employed to ensure real-time visualization of the cavitation area. Furthermore, to verify the practical performance to the current 2D PCI and inertial cavitation dose (ICD) quantification system, we specifically employed this system on situations where cavitation-facilitated thrombolysis is realized by introducing nanodiamond (ND) and nitrogen-annealed nanodiamond (N-AND) nuclei. The results of this study indicated that, by using this easy-use 2D PCI system that can real-time monitor and accurately quantify cavitation behavior in practical situation, it could be expected to further enhance the safety and effectiveness of ultrasound cavitation applications.

2 Materials and methods

2.1 N-AND synthesis

Identified as a novel cavitation nuclei source, N-AND has showcased its heightened cavitation potential in ultrasound thrombolysis [17], [51]. It was prepared by mixing ND (XFNANO Materials Tech Co., Ltd, China) and melamine (Shanghai Aladdin Biochemical Technology Co., Ltd, China) in a mass ratio of 3:1. The mixture was then placed in a vacuum furnace, whose vacuum degree was reduced to 1–10 Pa. Nitrogen gas (Shanghai Yangtai Chemical Technology Co., Ltd, China) was introduced into the furnace, and the temperature was raised at a rate of 5 °C/min to 1000 °C, where it was maintained for 4 h. Subsequently, the samples were cooled down to room temperature under a nitrogen atmosphere.

2.2 Clot preparation

The clot sample was prepared from 1 mL of bovine whole blood (EDTA anticoagulant, Beibo Biology Inc., China). The bovine whole blood, 1 M calcium dioxide solution (Yuanye Biology Inc., China), and 20 U/ml bovine thrombin (Prospect Inc., USA) were mixed in a cylindrical container with a volumetric ratio of 25:1:1, and incubated in a water bath at 37 °C for 1 h. After clot formation, the sample was washed with normal saline (0.9 % NaCl; Yuanye Biology Inc., China) and stored for further use.

2.3 Experimental system to perform 2D PCI for ultrasound thrombolysis under different parameters

Fig. 1 illustrates the experimental setup to perform 2D PCI monitoring and evaluation of cavitation effect generated in the ultrasound thrombolysis process. The experiments were conducted in a 50 × 40 × 30 cm3 acrylic tank filled with degassed water. A 3-mm diameter silicone tube with a wall thickness of 0.5 mm was positioned within a hollow acrylic mold to mimic the phantom vessel. The 3D positioning platform was utilized to accurately align the center of the silicone tube with the focal region of a customized 1.1-MHz focusing ultrasound transducer (10-cm aperture and 10-cm focal distance). A sinusoidal wave driving signal, produced by an arbitrary waveform generator (33250A, Agilent, USA), was amplified by a radio frequency (RF) power amplifier (2200l, Electronics Innovation, USA) with a gain of 53 dB. Scattered and emitted signals were captured by a customized 128-element linear array transducer (7.5-MHz central frequency). The frequency response of the linear array transducer was measured by deconvoluting the receiving response from the two-way response (1 to 10 MHz). The raw data of the cavitation signals were captured by a specially designed diagnostic ultrasound platform (EC50D, Zhuhai Ecare Ltd., China) with a sampling frequency of 50 MHz. Data were then transferred to a computer via USB for further 2D PCI generation and cavitation dosage quantification. Considering the computational demands of PCI and B-mode image fusion, GPU technology was employed in the imaging acceleration unit to ensure real-time performance.Fig. 1 Experimental setup for the passive cavitation imaging (PCI) system.

It is noteworthy that the specially designed diagnostic ultrasound platform used in the present work, unlike commonly used PCI systems that rely on specially designed research platforms (e.g., Verasonics Vantage), can collaboratively perform passive cavitation and B-mode fusion imaging and focused ultrasound treatment tasks by embedding an innovative time-division multiplexed trigger control module. Detailed information is provided in the Supplementary materials 1.

In this study, every channel’s image data was supported by a raw data buffer containing 4096 samples, suitable for holding passive acoustic data up to 12 cm deep or active acoustic data up to 6 cm deep. For passive data at a depth of 12 cm, the peak real-time data transfer rate across 128 channels reached 400 frames per second (FPS), surpassing the pulse repetition frequency (PRF) of 100 Hz for the ultrasound pulses transmitted in this work.

In the present work, different parameters encompass variations in acoustic pressure and microbubble concentration. The PRF and individual pulse length of driving signals were set to be 100 Hz and 20 cycles, respectively. According to the manufacturer’s instructions, the commercial contrast agent SonoVue (Bracco Diagnostics Inc, Italy) was prepared by injecting 5 ml of saline into the powder vial. The standard microbubble solution concentration was approximately 5 × 107 bubbles/ml and was subsequently diluted in later experiments to get various bubble concentration.

For the acoustic pressure group, the SonoVue solution was diluted 100 times. The peak negative pressures were set as 144, 429, 691 and 961 kPa. A control group was established using saline as a reference baseline. For the microbubble concentration group, acoustic peak negative pressure of the driving signal was set at 691 kPa. The SonoVue solution was diluted 50, 100, 250, 500, and 1000 times from the standard concentration, yielding corresponding concentrations of 1 × 106, 5 × 105, 2 × 105, 1 × 105, and 5 × 104 bubbles/mL. Again, saline served as a control.

To further verify the practical performance of 2D real-time PCI and ICD assessment technology, the current system was adopted to evaluate the spatiotemporal cavitation activities involved in ultrasound thrombotic treatments, with employing different kinds of cavitation nuclei (e.g., N-AND, ND and saline). Due to the large volume of mimic thrombus, a hollow rectangular sample chamber (measuring 1 × 5 × 1 cm3) enveloped by acoustically transparent thin films was used as the container to hold the samples. Besides the mimic thrombus, the experimental chamber contained a suspension of N-AND or ND at a concentration of 5 mg/ml, whereas the control group contained saline only. Recognizing that cavitation of the nanoparticles requires higher acoustic energy excitation, the acoustic driving pressure was set as 2.83 MPa, with a PRF of 100 Hz and a cycle number of 20.

2.4 2D passive cavitation imaging algorithm

The classic DAS algorithm reconstructs the signal from the i-th channel (i = 1, 2, …, N) of each imaging point (with coordinates x and z) as:(1) six,z,t=pi(t+τx,z),

where t represents time, pi is the raw signal recorded by each channel of the transducer, τ is the relative time delay determined by:(2) τx,z=xi-x2+z2c0,

where xi represents the position of the i-th channel along the x-axis, c0 is the sound speed.

To suppress the side lobe of reconstructed signal, the DAS algorithm was combined with MV beamforming to generate optimized delayed signal for the i-th channel, so that the PCI quality could be effectively enhanced:(3) si˙x,z,t=wi(x,z)si(x,z,t),

where the weight coefficient wi, which determines the contribution of signals in each channel to different parts of the imaging, can be represented as [52]:(4) wix,z=RDLx,z-1aaHRDLx,z-1a,

where RDL is the diagonal loading spatial covariance matrix, a is the equivalent steering vector. The superscript “H” represents the operation of taking the conjugate transpose of a matrix, while the superscript “-1” represents the operation of taking the inverse of a matrix.

2.5 2D passive cavitation dosage quantification

In order to accurately visualize cavitation occurrence locations in PCI with enhanced signal-to-noise ratio (SNR), a 63-order FIR high-pass filter (5-MHz cutoff frequency) was implemented in PCI module. This filter provides a total signal suppression of −100 dB at 1.1 MHz (analog plus digital), effectively mitigating the influence of the HIFU excitation signal. To accurately determine the 2D passive cavitation dosage from a 2-s focused ultrasound exposure, the filtered raw data from the region of interest (ROI)—where inertial cavitation occurred—was saved as a DAT file. This data was then analyzed using Matlab (R2019a, MathWorks, USA).

Fig. 2 illustrates the overall processing flowchart of the PCI system. The process begins with high-pass filtering of each channel’s data to remove the fundamental frequency component. Beamforming is then performed using the MV-DAS algorithm to obtain temporal sampled signals at each position. Subsequent processing diverges into two paths to either generate real-time 2D cavitation images or visualize 2D ICD quantification results within an ultrasound treatment duration of 2 s. The upper path (blue section) outlines the procedures for 2D cavitation image generation. Square norm calculations were performed to display the cavitation intensity of signals, resulting in 2D cavitation image [53]. The lower path (orange section) represents the process for 2D ICD image generation over a focusing ultrasound exposure period. ICD calculation for individual spatial points follows the method introduced in previous works [17], [51], [54], [55], [56], [57], [58]. In brief, fast Fourier transform (FFT) is applied to individual received waveforms. Then, the ICD quantification is achieved by computing the root mean square (RMS) amplitude of the spectrum within a specific frequency window centered at the average frequency of the third (f3) and the fourth (f4) harmonic components, with a width of (f4- f3)/2. In this study, the frequency range of the window is 3.62 to 4.18 MHz. Finally, the ICD is determined by calculating the integrated area under the RMS amplitude-time curve within the specific ultrasound exposure period.Fig. 2 Overall processing flowchart of the 2D PCI monitoring and ICD calculation system.

Specifically in the current work, ICD calculation was performed encompassing the 1.1-MHz ultrasound transducer focal region, measuring ∼ 2.1 mm in width and ∼ 10.3 mm in depth. Since the customized linear array transducer had a width of 0.3 mm for each element and a sampling frequency of 50 MHz, the ROI comprised 7 × 335 ultrasound imaging points. To enhance computational efficiency, uniform spatial down-sampling was applied in the depth direction. Consequently, ICD values were calculated for 7 × 34 ultrasound imaging points, generating a 2D ICD image of the ROI. Eventually, the overall ICD level of the ROI could be obtained by integrating the total ICD values within the region.

2.6 Data analysis

In the experiments, each data recording was repeated three times. For the 2D images depicting cavitation imaging results and the variation of ICD over time, only the average of the three measurements is presented. The maximum cavitation imaging signal intensity and overall ICD were expressed as the mean value with the standard error. Data differences were analyzed using a one-sided Student’s t-test with a significance level of p-value below 0.05.

3 Results and discussions

3.1 Real-time 2D passive cavitation localization in B-mode image

Fig. 3a shows the B-mode image of the silicone tube in the experimental setup, where the signal intensity is normalized. The x-direction aligns with the receiving transducer’s orientation, while the z-direction represents the imaging depth. The silicone tube is located within a depth range between approximately 30–35 mm, with the upper and lower boundaries of the tube wall clearly visible. Fig. 3b presents a typical instantaneous 2D PCI and B-mode fusion image applying high-pass filtering, for SonoVue solution in the silicone tube exposed by ultrasound pulses. The color in the figure indicates the intensity of the normalized cavitation imaging signal. For ease of comparison, the normalization reference value in this figure is based on the maximum signal intensity prior to high-pass filtering. Notably, a specific region within the silicone tube exhibits strong cavitation activity induced by ultrasound excitation. The dynamic 2D PCI results are available in Supplementary video 1.Fig. 3 Demonstration of cavitation localization using the PCI system. (a) B-mode image showcasing the silicone tube; (b) overlay merging the B-mode image with the 2D cavitation imaging results, with colors representing the intensity of the normalized cavitation imaging signal.

Fig. 4 illustrates the impact of the high-pass filter in the PCI system under different conditions: saline samples without high-pass processing, saline samples with high-pass processing, SonoVue samples without high-pass processing, and SonoVue samples with high-pass processing. The primary purpose of the high-pass filter is to suppress the impact from the strong fundamental frequency component of the ultrasound signal, so that the signal-to-noise ratio could be enhanced in passive cavitation detection. The first column in Fig. 4 presents 2D PCI results, where colors represent the intensity of the normalized cavitation imaging signal. For ease of comparison, the normalization reference value for this series of images in Fig. 4 is set as the maximum signal intensity generated by the corresponding sample without high-pass filtering. The second column of Fig. 4 exhibits the normalized signal intensity along the central scan line (x = 19.50 mm) in the imaging area, marked by a dashed line on the corresponding 2D PCI result. The third column illustrates the FFT spectrum of a point (x = 19.50 mm, z = 32.49 mm) situated along the scan line, highlighting the frequency components under various conditions.Fig. 4 Illustration of the effect of the high-pass filter (HPF) in the PCI System. (a)-(c) correspond to saline without HPF, where (a) shows the 2D cavitation imaging result, (b) displays the normalized cavitation imaging signal intensity along the marked reference line (x = 19.50 mm) in the corresponding 2D cavitation imaging result, and (c) presents the spectrum at a point (x = 19.50 mm, z = 32.49 mm) along the reference line; (d)-(f) show results of saline with HPF; (g)-(i) show results of SonoVue without HPF; (j)-(l) show results SonoVue with HPF, and the descriptions of the three images in each row are identical to those in the first row.

Upon comparing results with and without high-pass filtering, such as Fig. 4a-4c and Fig. 4d-4f (or Fig. 4g-4i and Fig. 4j-4 l), it is evident that the high-pass filter effectively suppresses both the fundamental and second harmonic components. It is obvious that the remaining frequency components after filtering effectively illustrate the occurrence of microbubble cavitation activity. In the case of saline samples, where cavitation does not take place under P-= 691 kPa, the outcomes post-filtering confirms an absence of cavitation signals (e.g., Fig. 4d-4f). For SonoVue samples, the 2D cavitation imaging results after high-pass filtering reveal specific locations of cavitation activity (Fig. 4j). Further FFT results (Fig. 4l) confirm the presence of inertial cavitation, characterized by the emergence of broadband noise between high-order harmonic components.

3.2 2D PCI monitoring under different acoustic pressures

Fig. 5 illustrates the cavitation imaging results utilizing the PCI system at varying acoustic pressures. Specifically, Fig. 5a exhibits the PCI result obtained at P- = 961 kPa for the saline sample. Based on the normalization criteria employed here (the maximum intensity of SonoVue group’s cavitation signal after high-pass filtering at P- = 961 kPa as the normalized reference value), no obvious differences can be observed in the PCI results for saline samples under varied acoustic pressures. Hence, only the result of P- = 961 kPa (viz., the maximum acoustic pressure applied in the experiments), are shown as representative image. Fig. 5b-5e show the PCI results for the SonoVue groups exposed to P- = 144, 429, 691 and 961 kPa, respectively. It is evident that as the acoustic pressure increases, the detected cavitation intensity rises, and the cavitation occurrence area expands as well.Fig. 5 2D cavitation imaging and relevant results of saline and SonoVue group at different pressures: (a) 2D cavitation image of saline group when P- = 961 kPa (while dashed line represents the reference line); (b)-(e): 2D cavitation images of SonoVue group when P- = 144, 429, 691 and 961 kPa; (f) normalized cavitation imaging signal intensity along the marked reference line (z = 32.49 mm); (g) normalized max cavitation imaging signal intensity in the corresponding 2D cavitation images.

Given our interest in the cavitation activity within the silicone tube, we selected a reference line parallel to the tube wall and positioned inside the tube (z = 32.49 mm, as shown in Fig. 5a) to monitor cavitation signal intensity. Fig. 5f shows the cavitation intensity along this reference line. Notably, the control group demonstrates the lowest cavitation intensity. The peak, roughly centered, indicates the ultrasound focus position. At P- = 144 kPa, there is no substantial increase in cavitation intensity at the focus position for the SonoVue group, though noise levels slightly rise at other positions. As P- reaches 429 kPa or higher (e.g., Fig. 5c-5e), cavitation intensity at the focal region gradually increases, and tends to saturation. The comparison between P- = 691 and 961 kPa reveals that the cavitation occurrence area at P- = 961 kPa is notably larger than at 691 kPa. (Fig. 5d and 5e).

Fig. 5g shows the maximum cavitation signal intensity in the 2D cavitation images across various acoustic pressures (averaged results from three independent measurements). In this case, due to minimal variation between measurements for the control group, its error bars are not prominently visible. When examining the results of the SonoVue groups, it becomes apparent that as the acoustic pressure increases, the cavitation intensity gradually increases and eventually saturates, aligning with previous analytical findings.

3.3 2D PCI monitoring under different microbubble concentrations

It is well known that microbubble concentration playing a critical impact on the cavitation intensity. Insufficient microbubble concentration leads to weaker cavitation activity due to the lack of cavitation nuclei. Conversely, excessive microbubble concentration can hinder cavitation activity to some extent through the shielding effect [17]. Thus, maintaining cavitation nuclei concentration within an appropriate range is crucial in practical applications. Fig. 6 presents the PCI results across solutions with varying microbubble concentrations. Fig. 6a-6f depict the outcomes of microbubble solution concentration changes from low to high, with the control group representing a microbubble solution with a concentration of 0. Apart from the control group, SonoVue solutions are diluted by 1000, 500, 250, 100, and 50 times based on the standard solution, corresponding to microbubble concentrations of 5 × 104, 1 × 105, 2 × 105, 5 × 105, and 1 × 106 microbubbles/mL, respectively. The 2D PCI results suggest SonoVue solutions diluted between 100 and 500 times (within a concentration range of 1 × 105 to 5 × 105 microbubbles/mL) should be more suitable for cavitation applications, because more obvious cavitation activities can be observed Fig. 6c-6e.Fig. 6 2D cavitation imaging and relevant results of saline and SonoVue group at different solution concentrations: (a) 2D cavitation image of saline group (while dashed line represents the reference line); (b)-(f): 2D cavitation images of SonoVue group when the microbubble solution is diluted 1000, 500, 250, 100 and 50 times (corresponding to the concentration of 5 × 104, 1 × 105, 2 × 105, 5 × 105 and 1 × 106 microbubbles/mL); (g) normalized cavitation imaging signal intensity along the marked reference line (z = 32.49 mm); (h) normalized max cavitation imaging signal intensity in the corresponding 2D cavitation images.

Fig. 6g illustrates the cavitation intensity along the reference line positioned inside the silicone tube and parallel to the tube wall in the 2D cavitation imaging. Meanwhile, Fig. 6h shows the maximum cavitation intensity observed in the 2D cavitation images obtained at various concentrations. Similarly, SonoVue solutions diluted by factors of 500, 250, and 100 exhibit higher cavitation intensity along the reference line. In Fig. 6h, a slight decrease in the detected maximum cavitation intensity is observed as the concentration greater than 2 × 105 microbubbles/mL, indicating the influence of cavitation shielding effect. No obvious cavitation activity was detected in the control group.

3.4 2D ICD assessments under different acoustic pressures and microbubble concentrations

While the PCI and B-mode fusion imaging successfully enables 2D localization of cavitation activity after high-pass filtering, it lacks the precision to accurately quantify the cumulative cavitation dose during ultrasound exposure. Hence, we conducted further processing on the acquired cavitation imaging data within a certain ultrasound exposure duration. By employing FFT processing, we assessed the broadband noise level between high-order harmonic components, allowing for the quantification of cumulated 2D ICD for different cases. The spatial characteristics of the ultrasound focus guided the selection of a ROI slightly larger than the focus area for analysis, which was measured approximately 2.1 mm in width and 10.3 mm in depth, encompassing 7 × 335 ultrasound imaging points. For computational efficiency, spatial down-sampling in the depth direction was performed, resulting in the calculation of ICD at 7 × 34 ultrasound imaging points and the creation of a 2D ICD image. The overall ICD, calculated from all points within the region, served as the comprehensive measurement for subsequent quantitative comparisons.

Fig. 7 displays the temporal evolution of ICD within the selected ROI in 2D cavitation images and associated data. Fig. 7a and 7b show stronger cavitation activity at P- = 691 kPa than the results measured at P- = 144 kPa (Fig. 7c and 7d). The subfigures in Fig. 7a represent measurement time points of 0, 0.5, 1, 1.5, and 2 s, respectively. It is apparent that the accumulated cavitation dose within the ROI gradually increases over time. More intense ICD accumulation is observed at specific positions after 2 s, suggesting heightened cavitation activity at the focal point due to increased acoustic pressure. Fig. 7b presents the overall ICD accumulated across 7 × 34 ultrasound imaging points throughout the measurement duration, with the solid line representing the mean value and the shaded area indicating the standard deviation. At the initial stage of measurement, only slight difference (less than 0.3 V×ms) can be observed between the SonoVue and saline groups. However, as time progresses, areas with heightened cavitation activity accumulate larger doses, leading to an obvious difference (about 60 V×ms) between the SonoVue and saline groups by the end of the measurement period.Fig. 7 2D images and associated results of the inertial cavitation dose (ICD) within the selected region over time: (a) typical images of SonoVue sample at 691 kPa and measurement time points of 0, 0.5, 1, 1.5, and 2 s; (b) overall ICD variation over the measurement time at 691 kPa; (c) typical images of SonoVue sample at 144 kPa and measurement time points of 0, 0.5, 1, 1.5, and 2 s; (d) overall ICD variation over the measurement time at 144 kPa.

It should be noticed that, Fig. 7c and 7d show similar results for weaker cavitation activity at P- = 144 kPa, where slight ICD accumulation is still observable despite the 2D cavitation imaging is insensitive in Fig. 5b. This observation suggests that the accumulated 2D ICD quantification analysis is even more sensitive than regular PCI for cavitation detection.

Fig. 8 compares the cumulative overall 2D ICD for different experimental groups over the measurement period. Fig. 8a shows the results taken under different acoustic pressures, with the SonoVue group demonstrating increasing inertial cavitation activity intensity with higher pressures. At a relatively low P- = 144 kPa, where 2D cavitation imaging fails to detect weak activity, more precise 2D ICD calculations still reveal slightly higher cavitation activity than the control group. Fig. 8b illustrates the outcomes of 2D ICD calculations at different microbubble concentrations, confirming that microbubble solutions with the concentration range between 1 × 105 to 5 × 105 bubbles/mL are more suitable for cavitation applications, as they effectively generate cavitation activity under similar ultrasound conditions. However, when the microbubble solution concentration falls below 1 × 105 or rises above 1 × 106 bubbles/mL, the detected cavitation intensity will diminish.Fig. 8 The cumulative overall ICD over the measurement time for the saline solution group and the SonoVue group under different conditions: (a) different peak negative acoustic pressures; (b) different cavitation nuclei concentrations.

3.5 2D ICD assessment of cavitation activity in ultrasound thrombolysis application

Moreover, the feasibility of the current system was practically verified by providing 2D PCI monitoring and ICD assessment for ultrasound thrombolysis effect. Fig. 9 presents the results of 2D spatiotemporal cavitation assessments obtained during ultrasound thrombolysis using different solutions(e.g., saline, ND or N-AND nanoparticles). Fig. 9a to 9c show 2D PCI maps for the saline, ND and N-AND groups, respectively. No significant cavitation activity is detected in the control group (Fig. 9a). Although cavitation activity was visible in the ND group (Fig. 9b), it appears weaker compared to the N-AND group (Fig. 9c), consistent with previous findings [17]. Fig. 9d and 9e demonstrate the maximum cavitation intensity in the corresponding 2D cavitation maps and the cumulative ICD within the ROI over 2 s. These findings indicate that both ND and N-AND can induce substantial cavitation activity during ultrasound therapy, while N-AND generating more intense cavitation. Utilizing the PCI system allows for real-time monitoring of cavitation occurrence time, location, and intensity in practical applications like ultrasound thrombolysis, thus being beneficial to improve the effectiveness and safety of ultrasound therapy. Fig. 9f illustrates the outcomes of ultrasound thrombolysis employing ND or N-AND. The black and red contours depict the clot outlines before and after treatment, respectively. It is evident that treatment with N-AND would lead to more obvious reduction in clot size, while treatment with ND resulted in a slight clot decrease only. Conversely, there is no significant alteration in clot size observed in the control group.Fig. 9 PCI and ultrasound thrombolysis results obtained during ultrasound thrombolysis using nanodiamond (ND) and nitrogen-doped nanodiamond (N-AND): (a)-(c) 2D cavitation imaging maps; (d) maximum cavitation signal intensity (normalized) corresponding to the 2D cavitation images; (e) cumulative overall ICD over the measurement time; (f) photos and outlines of the clot before (black contour) and after (red contour) treatment.

3.6 Comparison between the 2D PCI system with single element PCD detection system

In traditional studies [17], [51], [54], [55], [56], [57], [58], [59], PCD detections were performed with single element transducer, which only determined whether cavitation occurred within a specific area along the axial direction of the transducer. However, by utilizing linear array transducers for PCI via the current diagnostic ultrasound platform, it can easily provide precise spatial information regarding cavitation occurrence, as well as quantitatively evaluating cavitation activity within the ROI over the ultrasound treatment duration more accurately.

Fig. 10 illustrates the measurement outcomes of cavitation activity induced by ND and N-AND using both single-element PCD system and the current linear array PCI system. It is observed that both systems successfully depict the cavitation potential of ND and N-AND (with N-AND exhibiting higher potential than ND). However, PCI results suggest heightened sensitivity in detecting cavitation activity, particularly in discerning differences in cavitation levels between different groups. The higher sensitivity of the PCI system was inferred by normalizing the ICD results to the control group. In the PCD system, the ICD of the ND and N-AND groups increased by only 15.1 % and 28.3 %, respectively, compared to the control. In contrast, the PCI system showed a much greater increase, with normalized ICD values 20.8 and 41.6 times higher. This makes the PCI system particularly effective for detecting weak cavitation activity, which the PCD system might only slightly differentiate from the control.Fig. 10 The ICD induced by ND and N-AND, measured using a passive cavitation detection (PCD) system based on the single-element transducer and a PCI system based on the multi-element linear array transducer.

Notably, due to noise within the experimental setup, ICD from the single-element PCD system are computed based on broadband noise between the 2nd and 3rd harmonics. This is because noise in the acquired signal masks weaker broadband noise between the 3rd and 4th harmonics, making extraction of valid information from this frequency range unfeasible. Conversely, the current 2D PCI system extracts information from higher order components, such as broadband noise between the 3rd and 4th harmonic components. Such information is more sensitive to cavitation activity, as lower-order components (e.g., the 2nd and 3rd harmonics) are susceptible to influence from the fundamental frequency, leading to relatively low SNR in cavitation-related features.

3.7 Limitations and prospects

This research utilized a specially designed PCI system based on a time-division multiplexing control diagnostic ultrasound platform to systematically examine the cavitation activities across various parameters (e.g., acoustic pressures and microbubble concentrations). This time-division multiplexing technology appropriately sequences B-mode diagnosis, ultrasound exposure and passive cavitation receiving signals, so that the interference between the ultrasound stimulation and reception signals can be effectively prevented to generate high-quality B-mode and PCI pictures. By doing so, the current time-division multiplexed 2D PCI system is capable to eliminate the mismatch between the diagnosed and actual treatment areas, which can occur when diagnostic and therapeutic processes are conducted separately. In contrast to the commonly used single-element PCD transducer, the current PCI system not only can provide 2D spatial information to precisely localized cavitation activity in real-time, but also allows for more accurate accumulated ICD evaluation in targeted areas, so as to avoid excessive cavitation in local regions that may cause undesirable side-effects, and improve ultrasonic application safety as much as possible.

Due to the high acoustic pressure thresholds needed to induce cavitation in materials like N-AND, we used megapascal-level pressures in our in vitro thrombolysis experiments. While these pressures are FDA-approved for clinical procedures like tumor ablation, they require careful use. To protect normal tissues, we used focusing transducer with a focal region at centimeter scale and emitted ultrasound in pulses with a low duty cycle (0.18 %). Additionally, the real-time monitoring techniques from this study enhance the safety of using megapascal-level pressures in clinical settings.

There are still some limitations in this study. For instance, the current PCI system employed high pass filter to quickly suppress the influence of the fundamental frequency component from the driving ultrasound signal on the passive scattering signal [60], [61]. But this filtering process may also filter out the low-frequency components of the broadband noise related to cavitation activity, causing the PCI system to be less sensitive to weak cavitation activity.

Hence, further improvement of the current PCI system could involve using a band-pass or comb filter [62] to precisely extract frequency components associated with cavitation activity, distinguishing between stable cavitation and inertial cavitation activities [60], [63], [64], and then quantitatively evaluate the cumulative cavitation dosage in real-time at each point within the ROI. Looking ahead to the future, the integration of this 2D PCI system with clinically employed ultrasound therapeutic equipment could achieve more precise intraoperative cavitation evaluation and even feedback control, which is crucial for ensuring the efficacy and safety of various applications that utilize ultrasound cavitation effects, such as tumor therapy, ultrasound thrombolysis, drug delivery, etc.

4 Conclusions

In summary, a novel PCI system integrated with commercial diagnostic ultrasound platform was developed to achieve real-time monitoring and quantification of cavitation activity during ultrasound applications. By combined with adaptive MV beamformer, traditional DAS-based PCI algorithm could be significantly improved to addresses previous limitations of axial resolution and provides accurate spatiotemporal mapping of cavitation events. Moreover, by adopting specially designed time-division multiplexing triggering module, this system can synergistically manage focused ultrasound emission as well as real-time B-mode imaging and passive cavitation mapping during ultrasound applications. Additionally, it enabled post-processing capability to quantitatively assess accumulated cavitation dosage in the targeted region. Particularly, the effectiveness of the current system was further verified by accurately visualizing and quantitatively evaluating cavitation events occurred during ultrasound thrombolysis applications. The results showcased the potential of N-AND nanoparticles as cavitation nuclei that could significantly enhance thrombotic efficiency. This system transcends the conventional barriers of separated diagnostics and treatment systems, providing a flexible and sensitive real-time treatment monitoring solution by conveniently using commercialized diagnostic ultrasound platform. Unlike traditional PCD systems based on single-element transducer, it offers extensive 2D spatial information, substantially improving physicians’ grasp and management of cavitation dynamics within the treatment area. Utilizing this technology, physicians can more accurately detect rapid changes in cavitation during the treatment process and make timely adjustments to treatment plans. This not only helps prevent tissue damage from excessive cavitation intensity but also significantly enhances the safety and effectiveness of the therapy. The development of this system not only marks a major advancement in medical ultrasound technology in the field of precision therapy but also provides clinicians with a powerful tool to achieve optimized treatment outcomes.

CRediT authorship contribution statement

Qi Zhang: Writing – original draft, Investigation, Data curation. Yifei Zhu: Writing – original draft, Investigation, Data curation. Guofeng Zhang: Methodology, Investigation. Honghui Xue: Visualization, Validation. Bo Ding: Resources, Methodology. Juan Tu: Writing – review & editing, Writing – original draft, Supervision, Conceptualization. Dong Zhang: Validation, Project administration. Xiasheng Guo: Visualization, Validation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the Supplementary data to this article:Supplementary Data 1

Acknowledgments

This work was supported by the 10.13039/501100001809 National Natural Science Foundation of China (Nos. 12227808 , 12274220 , 52100014 , 11874216 , 11934009 , and 11911530173 ).

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.ultsonch.2024.107051.
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