Passive acoustic mapping of cavitation using eigenspace-based robust Capon beamformer in ultrasound therapy

Passive Acoustic Mapping for Convex Arrays With the Helical Wave Spectrum Method

Passive acoustic mapping (PAM) has emerged as a valuable imaging modality for monitoring the cavitation activity in focused ultrasound therapies. When it comes to imaging in the human abdomen, convex arrays are preferred due to their large acoustic window. However, existing PAM methods for convex arrays rely on the computationally expensive delay-and-sum (DAS) operation limiting the image reconstruction speed when the field-of-view (FOV) is large. In this work, we propose an efficient and frequency-selective PAM method for convex arrays. This method is based on projecting the helical wave spectrum (HWS) between cylindrical surfaces in the imaging field. Both the in silico and in vitro experiments showed that the HWS method has comparable image quality and similar acoustic cavitation source localization accuracy as the DAS-based methods. Compared to the frequency-domain and time-domain DAS methods, the time-complexity of the HWS method is reduced by one order and two orders of magnitude, respectively. A parallel implementation of the HWS method realized millisecond-level image reconstruction speed. We also show that the HWS method is inherently capable of mapping microbubble (MB) cavitation activity of different status, i.e., no cavitation, stable cavitation, or inertial cavitation. After compensating for the lens effects of the convex array, we further combined PAM formed by the HWS method and B-mode imaging as a real-time dual-mode imaging approach to map the anatomical location where MBs cavitate in a liver phantom experiment. This method may find use in applications where convex arrays are required for cavitation activity monitoring in real time.

Improved assessment sensitivity of time-varying cavitation events based on wavelet analysis

Ultrasonic cavitation, characterized by the oscillation or abrupt collapse of cavitation nuclei in response to ultrasound stimulation, plays a significant role in various applications within both industrial and biomedical sectors. In particular, inertial cavitation (IC) has garnered considerable attention due to the resulting mechanical, chemical, and thermal effects. Passive cavitation detection (PCD) has emerged as a valuable technique for monitoring this procedure. While the fast Fourier transform (FFT) is a widely used algorithm to analyze IC-induced broadband noise detected by PCD system, it may not adequately capture the time-varying instability of cavitation due to potential nuclei collapse during ultrasound irradiation. In contrast, the continuous wavelet transform offers a more flexible approach, enabling more sensitive analysis of signals with varying frequencies over time. In this study, nanodiamond (ND) and its derivative, nitro-doped nanodiamond (N-AND), known to possess cavitation potential from previous research, were chosen as the source of cavitation nuclei. The cavitation signals detected by PCD were subjected to both FFT and wavelet analyses, with their results comprehensively compared. This research showcased the feasibility of employing wavelet analysis for effective inertial cavitation evaluation. It provided the advantage of monitoring the temporal evolution of cavitation events in real-time, enhancing sensitivity to weak and unstable cavitation signals, especially those in higher order components (3rd and 4th order). Additionally, it yielded a higher level of precision in determining IC thresholds and doses. Furthermore, the inclusion of time information through wavelet analysis offered insights into the limitations of low-cycle ultrasound in inducing IC. This study introduces a novel perspective for more sensitive and precise cavitation assessment, leveraging time and frequency data from wavelet analysis, and holds promise for effective utilization of cavitation effects while minimizing losses and damages resulting from unintended cavitation events.

Real-Time Passive Acoustic Mapping With Enhanced Spatial Resolution in Neuronavigation-Guided Focused Ultrasound for Blood-Brain Barrier Opening

OBJECTIVE

Passive acoustic mapping (PAM) provides the spatial information of acoustic energy emitted from microbubbles during focused ultrasound (FUS), which can be used for safety and efficacy monitoring of blood-brain barrier (BBB) opening. In our previous work with a neuronavigation-guided FUS system, only part of the cavitation signal could be monitored in real time due to the computational burden although full-burst analysis is required to detect transient and stochastic cavitation activity. In addition, the spatial resolution of PAM can be limited for a small-aperture receiving array transducer. For full-burst real-time PAM with enhanced resolution, we developed a parallel processing scheme for coherence-factor-based PAM (CF-PAM) and implemented it onto the neuronavigation-guided FUS system using a co-axial phased-array imaging transducer.

METHODS

Simulation and in-vitro human skull studies were conducted for the performance evaluation of the proposed method in terms of spatial resolution and processing speed. We also carried out real-time cavitation mapping during BBB opening in non-human primates (NHPs).

RESULTS

CF-PAM with the proposed processing scheme provided better resolution than that of traditional time-exposure-acoustics PAM with a higher processing speed than that of eigenspace-based robust Capon beamformer, which facilitated the full-burst PAM with the integration time of 10 ms at a rate of 2 Hz. In vivo feasibility of PAM with the co-axial imaging transducer was also demonstrated in two NHPs, showing the advantages of using real-time B-mode and full-burst PAM for accurate targeting and safe treatment monitoring.

SIGNIFICANCE

This full-burst PAM with enhanced resolution will facilitate the clinical translation of online cavitation monitoring for safe and efficient BBB opening.

Passive Cavitation Imaging Artifact Reduction Using Data-Adaptive Spatial Filtering

Passive cavitation imaging (PCI) with a clinical diagnostic array results in poor axial localization of bubble activity due to the size of the point spread function (PSF). The objective of this study was to determine if data-adaptive spatial filtering improved PCI beamforming performance relative to standard frequency-domain delay, sum, and integrate (DSI) or robust Capon beamforming (RCB). The overall goal was to improve source localization and image quality without sacrificing computation time. Spatial filtering was achieved by applying a pixel-based mask to DSI- or RCB-beamformed images. The masks were derived from DSI, RCB, or phase or amplitude coherence factors (ACFs) using both receiver operating characteristic (ROC) and precision-recall (PR) curve analyses. Spatially filtered passive cavitation images were formed from cavitation emissions based on two simulated sources densities and four source distribution patterns mimicking cavitation emissions induced by an EkoSonic catheter. Beamforming performance was assessed via binary classifier metrics. The difference in sensitivity, specificity, and area under the ROC curve (AUROC) differed by no more than 11% across all algorithms for both source densities and all source patterns. The computational time required for each of the three spatially filtered DSIs was two orders of magnitude less than that required for time-domain RCB and thus this data-adaptive spatial filtering strategy for PCI beamforming is preferable given the similar binary classification performance.

Barrier-breaking effects of ultrasonic cavitation for drug delivery and biomarker release

Recently, emerging evidence has demonstrated that cavitation actually creates important bidirectional channels on biological barriers for both intratumoral drug delivery and extratumoral biomarker release. To promote the barrier-breaking effects of cavitation for both therapy and diagnosis, we first reviewed recent technical advances of ultrasound and its contrast agents (microbubbles, nanodroplets, and gas-stabilizing nanoparticles) and then reported the newly-revealed cavitation physical details. In particular, we summarized five types of cellular responses of cavitation in breaking the plasma membrane (membrane retraction, sonoporation, endocytosis/exocytosis, blebbing and apoptosis) and compared the vascular cavitation effects of three different types of ultrasound contrast agents in breaking the blood-tumor barrier and tumor microenvironment. Moreover, we highlighted the current achievements of the barrier-breaking effects of cavitation in mediating drug delivery and biomarker release. We emphasized that the precise induction of a specific cavitation effect for barrier-breaking was still challenged by the complex combination of multiple acoustic and non-acoustic cavitation parameters. Therefore, we provided the cutting-edge in-situ cavitation imaging and feedback control methods and suggested the development of an international cavitation quantification standard for the clinical guidance of cavitation-mediated barrier-breaking effects.

Passive acoustic mapping with absolute time-of-flight information and delay-multiply-sum beamforming

BACKGROUND

Passive acoustic mapping (PAM) is showing increasing application potential in monitoring ultrasound therapy by spatially resolving cavitation activity. PAM with the relative time-of-flight information leads to poor axial resolution when implemented with ultrasound diagnostic transducers. Through utilizing the absolute time-of-flight information preserved by the transmit-receive synchronization and applying the common delay-sum (DS) beamforming algorithm, PAM axial resolution can be greatly improved in the short-pulse excitation scenario, as with active ultrasound imaging. However, PAM with the absolute time-of-flight information (referred as AtPAM) suffers from low imaging resolution and weak interference suppression when the DS algorithm is applied.

PURPOSE

This study aims to propose an enhanced AtPAM algorithm based on delay-multiply-sum (DMS) beamforming, to address the shortcomings of the DS-based AtPAM algorithm.

METHODS

In DMS beamforming, the element signals delayed by the absolute time delays are first processed with a signed square-root operation and then multiplied in pairs and finally summed, the resulting beamformed output is further band-pass filtered. The performances of DS- and DMS-based AtPAMs are compared by experiments, in which an ultrasound diagnostic transducer (a linear array) is employed to passively sense the wire signals generated by an unfocused ultrasound transducer and the cavitation signals generated by a focused therapeutic ultrasound transducer in a flow phantom. The AtPAM image quality is assessed by main-lobe width (MLW), intensity valley value (IVV), area of pixels (AOP), signal-to-interference ratio (SIR), and signal-to-noise ratio (SNR).

RESULTS

The single-wire experimental results show that compared to the DS algorithm, the DMS algorithm leads to an enhanced AtPAM image with a decreased transverse MLW of 0.15 mm and an improved SIR and SNR of 31.50 and 18.77 dB. For the four-wire images, the transverse (axial) IVV is decreased by 18.37 dB (13.11 dB) and the SIR (the SNR) is increased by 26.13 dB (18.47 dB) when using the DMS algorithm. The cavitation activity is better highlighted by DMS-based AtPAM, which decreases the AOP by 0.81 mm² (-10-dB level) and 4.43 mm² (-20-dB level) and increases the SIR and SNR by 20.14 and 10.48 dB respectively. The pixel distributions of AtPAM images of both wires and cavitation activity also indicate a better suppression of the DMS algorithm in sidelobe and noise.

CONCLUSIONS

The experimental results illustrate that the DMS algorithm can improve the image quality of AtPAM compared to the DS algorithm. DMS-based AtPAM is beneficial for detecting cavitation activity during short-pulse ultrasound exposure with high resolution, and further for monitoring short-pulse ultrasound therapy.

Towards controlled drug delivery in brain tumors with microbubble-enhanced focused ultrasound

Brain tumors are particularly challenging malignancies, due to their location in a structurally and functionally distinct part of the human body - the central nervous system (CNS). The CNS is separated and protected by a unique system of brain and blood vessel cells which together prevent most bloodborne therapeutics from entering the brain tumor microenvironment (TME). Recently, great strides have been made through microbubble (MB) ultrasound contrast agents in conjunction with ultrasound energy to locally increase the permeability of brain vessels and modulate the brain TME. As we elaborate in this review, this physical method can effectively deliver a wide range of anticancer agents, including chemotherapeutics, antibodies, and nanoparticle drug conjugates across a range of preclinical brain tumors, including high grade glioma (glioblastoma), diffuse intrinsic pontine gliomas, and brain metastasis. Moreover, recent evidence suggests that this technology can promote the effective delivery of novel immunotherapeutic agents, including immune check-point inhibitors and chimeric antigen receptor T cells, among others. With early clinical studies demonstrating safety, and several Phase I/II trials testing the preclinical findings underway, this technology is making firm steps towards shaping the future treatments of primary and metastatic brain cancer. By elaborating on its key components, including ultrasound systems and MB technology, along with methods for closed-loop spatial and temporal control of MB activity, we highlight how this technology can be tuned to enable new, personalized treatment strategies for primary brain malignancies and brain metastases.

Use of the Cross-Spectral Density Matrix for Enhanced Passive Ultrasound Imaging of Cavitation

Passive ultrasound imaging is of great interest for cavitation monitoring. Spatiotemporal monitoring of cavitation bubbles in therapeutic applications is possible using an ultrasound imaging probe to passively receive the acoustic signals from the bubbles. Fourier-domain (FD) beamformers have been proposed to process the signals received into maps of the spatial localization of cavitation activity, with reduced computing times with respect to the time-domain approach, and to take advantage of frequency selectivity for cavitation regime characterization. The approaches proposed have been mainly nonadaptive, and these have suffered from low resolution and contrast, due to the many reconstruction artifacts. Inspired by the array-processing literature and in the context of passive ultrasound imaging of cavitation, we propose here a robust estimation of the second-order statistics of data through spatial covariance matrices in the FD or cross-spectral density matrices (CSMs). The benefits of such formalism are illustrated using advanced reconstruction algorithms, such as the robust Capon beamformer, the Pisarenko class beamformer, and the multiple signal classification approach. Through both simulations and experiments in a water tank, we demonstrate that enhanced localization of cavitation activity (i.e., improved resolution and contrast with respect to nonadaptive approaches) is compatible with the rapid and frequency-selective approaches of the FD. Robust estimation of the CSM and the derived adaptive beamformers paves the way to the development of powerful passive ultrasound imaging tools.

Imaging With Therapeutic Acoustic Wavelets-Short Pulses Enable Acoustic Localization When Time of Arrival is Combined With Delay and Sum

Passive acoustic mapping (PAM) is an algorithm that reconstructs the location of acoustic sources using an array of receivers. This technique can monitor therapeutic ultrasound procedures to confirm the spatial distribution and amount of microbubble activity induced. Current PAM algorithms have an excellent lateral resolution but have a poor axial resolution, making it difficult to distinguish acoustic sources within the ultrasound beams. With recent studies demonstrating that short-length and low-pressure pulses-acoustic wavelets-have the therapeutic function, we hypothesized that the axial resolution could be improved with a quasi-pulse-echo approach and that the resolution improvement would depend on the wavelet's pulse length. This article describes an algorithm that resolves acoustic sources axially using time of flight and laterally using delay-and-sum beamforming, which we named axial temporal position PAM (ATP-PAM). The algorithm accommodates a rapid short pulse (RaSP) sequence that can safely deliver drugs across the blood-brain barrier. We developed our algorithm with simulations (k-wave) and in vitro experiments for one-, two-, and five-cycle pulses, comparing our resolution against that of two current PAM algorithms. We then tested ATP-PAM in vivo and evaluated whether the reconstructed acoustic sources mapped to drug delivery within the brain. In simulations and in vitro, ATP-PAM had an improved resolution for all pulse lengths tested. In vivo, experiments in mice indicated that ATP-PAM could be used to target and monitor drug delivery into the brain. With acoustic wavelets and time of flight, ATP-PAM can locate acoustic sources with a vastly improved spatial resolution.

Correlation Between Brain Tissue Damage and Inertial Cavitation Dose Quantified Using Passive Cavitation Imaging

Focused ultrasound (FUS)-induced cavitation-mediated brain therapies have become emerging therapeutic modalities for neurologic diseases. Cavitation monitoring is essential to ensure the safety of all cavitation-mediated therapeutic techniques as inertial cavitation can be associated with tissue damage. The objective of this study was to reveal the correlation between the inertial cavitation dose, quantified by passive cavitation imaging (PCI), and brain tissue histologic-level damage induced by FUS in combination with microbubbles. An ultrasound image-guided FUS system consisting of a single-element FUS transducer (1.5 MHz) and a co-axially aligned 128-element linear ultrasound imaging array was used to perform FUS treatment of mice. Mice were sonicated by FUS with different peak negative pressures (0.5 MPa, 1.1 MPa, 4.0 MPa and 6.5 MPa) in the presence of systemically injected microbubbles. The acoustic emissions from the FUS-activated microbubbles were passively detected by the imaging array. The pre-beamformed channel data were acquired and processed offline using the frequency-domain delay, sum and integration algorithm to generate inertial cavitation maps. All the mice were sacrificed after the FUS treatment, and their brains were harvested and processed for hematoxylin and eosin staining. The obtained inertial cavitation maps revealed the dynamic changes of microbubble behaviors during FUS treatment at different pressure levels. It was found that the inertial cavitation dose quantified based on PCI had a linear correlation with the scale of histologic-level tissue damage. Findings from this study suggested that PCI can be used to predict histologic-level tissue damage associated with the FUS-induced cavitation.

Delay multiply and sum beamforming method applied to enhance linear-array passive acoustic mapping of ultrasound cavitation

PURPOSE

Passive acoustic mapping (PAM) has been proposed as a means of monitoring ultrasound therapy, particularly nonthermal cavitation-mediated applications. In PAM, the most common beamforming algorithm is a delay, sum, and integrate (DSAI) approach. However, using DSAI leads to low-quality images for the case where a narrow-aperture receiving array such as a standard B-mode linear array is used. This study aims to propose an enhanced linear-array PAM algorithm based on delay, multiply, sum, and integrate (DMSAI).

METHODS

In the proposed algorithm, before summation, the delayed signals are combinatorially coupled and multiplied, which means that the beamformed output of the proposed algorithm is the spatial coherence of received acoustic emissions. We tested the performance of the proposed DMSAI using both simulated and experimental data and compared it with DSAI. The reconstructed cavitation images were evaluated quantitatively by using source location errors between the two algorithms, full width at half maximum (FWHM), size of point spread function (A₅₀ area), signal-to-noise ratio (SNR), and computational time.

RESULTS

The results of simulations and experiments for single cavitation source show that, by introducing DMSAI, the FWHM and the A₅₀ area are reduced and the SNR is improved compared with those obtained by DSAI. The simulation results for two symmetric or nonsymmetric cavitation sources and multiple cavitation sources show that DMSAI can significantly reduce the A₅₀ area and improve the SNR, therefore improving the detectability of multiple cavitation sources.

CONCLUSIONS

The results indicate that the proposed DMSAI algorithm outperforms the conventionally used DSAI algorithm. This work may have the potential of providing an appropriate method for ultrasound therapy monitoring.

Passive cavitation mapping using dual apodization with cross-correlation in ultrasound therapy monitoring

Recently, passive acoustic mapping (PAM) has been successfully applied for dynamic monitoring of ultrasound therapy by beamforming acoustic emissions of cavitation activity during ultrasound exposure. The most widely used PAM algorithm in the literature is time exposure acoustics (TEA), which is a standard delay, sum, and integrate algorithm. However, it results in large point spread function (PSF) and serious imaging artifacts for the case where a narrow-aperture receiving array such as a standard B-mode linear array is used, therefore degrading the quality of cavitation image. To address these challenges, in this paper, we proposed a novel PAM algorithm namely dual apodization with cross-correlation (DAX)-based TEA, in which DAX was originally used as a reconstruction algorithm in medical ultrasound imaging. In the proposed algorithm, two sets of signals were beamformed by two receive apodization functions with alternating elements enabled, and the cross-correlation coefficient of the two signals served as a weighting factor that would be multiplied to the sum of the two signals. The performance of the proposed algorithm was tested on simulated channel data obtained using a multi-bubble model, and experiments were also performed in an in vitro vessel phantom with flowing microbubbles as cavitation nuclei. The reconstructed cavitation images were evaluated quantitatively using established quality metrics including full width at half maximum (FWHM), A_-6dB area, and signal-to-noise ratio (SNR). The results suggested that the proposed algorithm significantly outperformed the conventionally used TEA algorithm. This work may have the potential of providing a useful tool for highly accurate localization of cavitation activity during ultrasound therapy.

Passive Acoustic Mapping Using Data-Adaptive Beamforming Based on Higher Order Statistics

Sources of nonlinear acoustic emissions, particularly those associated with cavitation activity, play a key role in the safety and efficacy of current and emerging therapeutic ultrasound applications, such as oncological drug delivery, blood-brain barrier opening, and histotripsy. Passive acoustic mapping (PAM) is the first technique to enable real-time and non-invasive imaging of cavitation activity during therapeutic ultrasound exposure, through the recording and passive beamforming of broadband acoustic emissions using an array of ultrasound detectors. Initial limitations in PAM spatial resolution led to the adoption of optimal data-adaptive beamforming algorithms, such as the robust capon beamformer (RCB), that provide improved interference suppression and calibration error mitigation compared to non-adaptive beamformers. However, such approaches are restricted by the assumption that the recorded signals have a Gaussian distribution. To overcome this limitation and further improve the source resolvability of PAM, we propose a new beamforming approach termed robust beamforming by linear programming (RLPB). Along with the variance, this optimization-based method uses higher-order-statistics of the recorded signals, making no prior assumption on the statistical distribution of the acoustic signals. The RLPB is found via numerical simulations to improve resolvability over time exposure acoustics and RCB. In vitro experimentation yielded improved resolvability with respect to the source-to-array distance on the order of 22% axially and 13% transversely relative to RCB, whilst successfully accounting for array calibration errors. The improved resolution and decreased dependence on accurate calibration of RLPB is expected to facilitate the clinical translation of PAM for diagnostic, including super-resolution, and therapeutic ultrasound applications.

Closed Loop Spatial and Temporal Control of Cavitation Activity with Passive Acoustic Mapping

Ultrasonically actuated microbubble oscillations hold great promise for minimally invasive therapeutic interventions. While several preclinical studies have demonstrated the potential of this technology, real-time methods to control the amplitude and type of microbubble oscillations (stable vs inertial acoustic cavitation) and ensure that cavitation occurs within the targeted region are needed for their successful translation to the clinic. In this paper, we propose a real-time nonlinear state controller that uses specific frequency bands of the microbubble acoustic emissions (harmonic, ultra-harmonic, etc.) to control cavitation activity (observer states). To attain both spatial and temporal control of cavitation activity with high signal to noise ratio, we implement a controller using fast frequency-selective passive acoustic mapping (PAM) based on the angular spectrum approach. The controller includes safety states based on the recorded broadband signal level and is able to reduce sensing inaccuracies with the inclusion of multiple frequency bands. In its simplest implementation the controller uses the peak intensity of the passive acoustic maps, reconstructed using the 3rd harmonic (4.896 × 0.019 MHz) of the excitation frequency. Our results show that the proposed real-time nonlinear state controller based on PAM is able to reach the targeted level of observer state (harmonic emissions) in less than 6 seconds and remain within 10 % of tolerance for the duration of the experiment (45 seconds). Similar response was observed using the acoustic emissions from single element passive cavitation detection, albeit with higher susceptibility to background noise and lack of spatial information. Importantly, the proposed PAM-based controller was able to control cavitation activity with spatial selectivity when cavitation existed simultaneously in multiple regions. The robustness of the controller is demonstrated using a range of controller parameters, multiple observer states concurrently (harmonic, ultra-harmonic, and broadband), noise levels (°6 to 12 dB SNR), and bubble concentrations (0.3 to 180 × 103 bubbles per microliter). More research in this direction under preclinical and clinical conditions is warranted.