An inverse method using Cross spectral Matrix Fitting for passive cavitation imaging.

High intensity focused ultrasound (HIFU) can produce cavitation, which requires monitoring for specific applications such as sonoporation, targeted drug delivery or histotripsy. Passive acoustic mapping has been proposed in the literature as a method for monitoring cavitation, but it lacks spatial resolution, primarily in the axial direction, due to the absence of a time reference. This is a common issue with passive imaging compared to standard pulse-echo ultrasound. In order to improve the axial resolution, we propose an adaptation of the Cross spectral Matrix Fitting (CMF) method for passive cavitation imaging, which is based on the resolution of an inverse problem with different regularizations that promote sparsity in the reconstructed cavitation maps: Elastic Net (CMF-ElNet) and sparse Total Variation (CMF-spTV). The results from both simulated and experimental data are presented and compared to state-of-the-art approaches, such as the frequential Delay-and-Sum (DAS) and the frequential Robust Capon Beamformer (RCB). We show the interest of the method for improving the axial resolution, with an axial Full Width Half Maximum (FWHM) divided by 3 and 5 compared to RCB and DAS, respectively. Moreover, CMF based methods improve Contrast-to-Noise Ratio (CNR) by more than 15 dB in experimental conditions compared to RCB. We also show the advantage of the sparse Total Variation prior over Elastic Net when dealing with cloud shaped cavitation sources, that can be assumed as sparse grouped sources.

SIMUS3: An open-source simulator for 3-D ultrasound imaging.

BACKGROUND AND OBJECTIVE: Computational Ultrasound Imaging (CUI) has become increasingly popular in the medical ultrasound community, facilitated by free simulation software. These tools enable the design and exploration of transmit sequences, transducer arrays, and signal processing. We recently introduced SIMUS, a frequency-based ultrasound simulator within the open-source MUST toolbox, which offers numerical advantages and allows easy consideration of frequency-dependent factors. In response to the growing interest in simulating ultrasound imaging with 2-D matrix arrays, we present 3-D versions, PFIELD3 and SIMUS3. METHOD: The linear acoustic equations driving these functions are described, with theoretical assumptions reviewed for user guidance. RESULTS: Comparative analyses with Field II, using a 32×32 element 3-MHz matrix array, highlight the performance of PFIELD3 and SIMUS3 under various transmission conditions. CONCLUSIONS: This work extends the capabilities of existing CUI tools and provides researchers with valuable resources for advanced ultrasound simulations.

Reply to "Comment on "So you think you can DAS? A viewpoint on delay-and-sum beamforming" - Think twice before f-numbering", published by M.F. Schiffner and G. Schmitz.

In a 2021 paper, we delved into the details of delay-sum beamforming (DAS) in high-frame-rate ultrasound for medical imaging [1]. We also proposed a simple and fast method of determining an f-number, which is based on the directivity of the transducer elements. In their comment, Martin F. Schiffner and Georg Schmitz argue that we mistakenly link image quality enhancement to the reduction of measurement noise. They disapprove our proposed f-number, claiming it deteriorates the signal-to-noise ratio (SNR). Based on their previous work [2], they also highlight that the f-number should be derived from the grating lobe angles. In this reply, we explain their error in the SNR argument. We also illustrate the potential drawbacks of exclusively relying on grating lobes to establish an f-number with a DAS, suggesting that alternative approaches might be worthy of consideration.

3-D Passive Cavitation Imaging Using Adaptive Beamforming and Matrix Array Transducer With Random Apodization.

With the development of promising cavitation-based treatments, the interest in cavitation monitoring with passive acoustic mapping (PAM) is significantly increasing. While most of studies regarding PAM are performed in 2-D, 3-D imaging modalities are getting more attention relying on either custom-made or commercial matrix probes. Unless specific phased-arrays are used for a specific application, limitations due to probe apertures often results in poor performances of the 3-D mapping, due to the use of a delay-and-sum (DAS) classic beamformer, which results in strong artifacts and large main lobe sizes. In this article, 3D-PAM is achieved by performing adaptive beamforming in the frequency domain (FD) in 3-D, and using a random sparse apodization of a commercial matrix array driving only 256 elements among the 1024 available. It reduces the computation time and makes use of only one 256-channel research platform. Three beamformers have been implemented in 3-D and in the FD: the DAS beamformer, which corresponds to the beamformer used in previous 3D-PAM studies, the robust capon beamformer (RCB), an adaptive algorithm widely used in 2D-PAM for its high performances, and the MidWay (MW) beamformer, an adaptive algorithm with a computation complexity equivalent to the one of DAS. These algorithms are evaluated both in simulations and experiments with a harmonic source at different positions, and are also applied to real cavitation signals. The results show that, in the case of matrix arrays of small aperture such as generic commercial matrix probes, the DAS beamformer leads to large main lobe sizes, while adaptive beamformers largely improve the performances of the mapping. The low computation time and its parameter-free character make MW beamformer a good compromise for 3D-PAM applications. It thus appears that a random sparse apodization combined with adaptive beamforming is a good solution to achieve high-performance 3D-PAM with manageable devices.

Use of the intrusion angle to describe the radial orientation of local cardiomyocytes in the left ventricle.

The projected transverse angle and the nonprojected intrusion angle can be used to describe the radial orientation of local cardiomyocytes in the left ventricle wall, although to date their descriptive relevance has not been demonstrated. This paper compares the evolution of the transverse angle and the intrusion angle in five left ventricle wall samples, and investigates in more detail their respective behaviors when the nonprojected helical angle varies. We show that the intrusion angle avoids the "projection" effect, and contrary to the transverse angle, it remains stable whatever the values taken by the nonprojected helical angle, even when this approaches 90°. The intrusion angle is the better choice, rather than the transverse angle, in describing the radial orientation of local cardiomyocytes. Furthermore, the oscillation of the intrusion angle in the samples is assessed, whose results indicate that the intrusion angle's oscillation amplitude and period are regional and related to the local tissue architecture.

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-velocity tissue motion if motion compensation (MoCo) is not considered. While many studies have recently shown the interest of deep learning for the reconstruction of high-quality static images from PW or DW, its ability to achieve such performance while maintaining the capability of tracking cardiac motion has yet to be assessed. In this article, we addressed such issue by deploying a complex-weighted convolutional neural network (CNN) for image reconstruction and a state-of-the-art speckle-tracking method. The evaluation of this approach was first performed by designing an adapted simulation framework, which provides specific reference data, i.e., high-quality, motion artifact-free cardiac images. The obtained results showed that, while using only three DWs as input, the CNN-based approach yielded an image quality and a motion accuracy equivalent to those obtained by compounding 31 DWs free of motion artifacts. The performance was then further evaluated on nonsimulated, experimental in vitro data, using a spinning disk phantom. This experiment demonstrated that our approach yielded high-quality image reconstruction and motion estimation, under a large range of velocities and outperforms a state-of-the-art MoCo-based approach at high velocities. Our method was finally assessed on in vivo datasets and showed consistent improvement in image quality and motion estimation compared to standard compounding. This demonstrates the feasibility and effectiveness of deep learning reconstruction for ultrafast speckle-tracking echocardiography.

A simplified and accelerated implementation of SVD for filtering ultrafast power Doppler images.

BACKGROUND AND OBJECTIVE: Ultrafast Power Doppler (UPD) is a growing ultrasound modality for imaging and diagnosing microvasculature disease. A key element of UPD is using singular value decomposition (SVD) as a highly selective filter for tissue and electronic noise. However, two significant drawbacks of SVD are its computational burden and the complexity of its algorithms. These limitations hinder the development of fast and specific SVD algorithms for UPD imaging. This study introduces power SVD (pSVD), a simplified and accelerated algorithm for filtering tissue and noise in UPD images. METHODS: pSVD exploits several mathematical properties of SVD specific to UPD images. In particular, pSVD allows the direct computation of blood-related SVD components from the temporal singular vectors. This feature simplifies the expression of SVD while significantly accelerating its computation. After detailing the theory behind pSVD, we evaluate its performances in several in vitro and in vivo experiments and compare it to SVD and randomized SVD (rSVD). RESULTS: pSVD strongly decreases the running time of SVD (between 5 and 12 times in vivo) without impacting the quality of UPD images. Compared to rSVD, pSVD can be significantly faster (up to 3 times) or slightly slower but gives access to more estimators to isolate tissue subspaces. CONCLUSION: pSVD is highly valuable for implementing UPD imaging in clinical ultrasound and provides a better understanding of SVD for ultrasound imaging in general.

Adaptive noise reduction for power Doppler imaging using SVD filtering in the channel domain and coherence weighting of pixels.

Objective. Ultrafast power Doppler (UPD) is an ultrasound method that can image blood flow at several thousands of frames per second. In particular, the high number of data provided by UPD enables the use of singular value decomposition (SVD) as a clutter filter for suppressing tissue signal. Notably, is has been demonstrated in various applications that SVD filtering increases significantly the sensitivity of UPD to microvascular flows. However, UPD is subjected to significant depth-dependent electronic noise and an optimal denoising approach is still being sought.Approach. In this study, we propose a new denoising method for UPD imaging: the Coherence Factor Mask (CFM). This filter is first based on filtering the ultrasound time-delayed data using SVD in the channel domain to remove clutter signal. Then, a spatiotemporal coherence mask that exploits coherence information between channels for identifying noisy pixels is computed. The mask is finally applied to beamformed images to decrease electronic noise before forming the power Doppler image. We describe theoretically how to filter channel data using a single SVD. Then, we evaluate the efficiency of the CFM filter for denoisingin vitroandin vivoimages and compare its performances with standard UPD and with three existing denoising approaches.Main results. The CFM filter gives gains in signal-to-noise ratio and contrast-to-noise ratio of up to 22 dB and 20 dB, respectively, compared to standard UPD and globally outperforms existing methods for reducing electronic noise. Furthermore, the CFM filter has the advantage over existing approaches of being adaptive and highly efficient while not requiring a cut-off for discriminating noise and blood signals nor for determining an optimal coherence lag.Significance. The CFM filter has the potential to help establish UPD as a powerful modality for imaging microvascular flows.

Oscillation of the orientation of cardiomyocyte aggregates in human left ventricle free wall.

Orientation of local cardiomyocyte aggregates in the human left ventricle free wall experiences an oscillation in the laminar structure regions, besides its gradual change trend. We described this oscillation using five transmural samples imaged at the European Synchrotron Radiation Facility with an isotropic voxel size of 3.5 × 3.5 × 3.5 µm3 . In the reconstructed volume of each sample, we manually selected a region containing a regular laminar structure as the region of interest and measured the distribution of the orientation of local cardiomyocyte aggregates inside using a Fourier-based method. Then, we extracted the gradual change part of the orientation of cardiomyocyte aggregates with a three-dimensional centered Gaussian filter and measured the angle between the original orientation vector of local cardiomyocyte aggregates and its gradual change part. Further, we assessed the measured angles in different local coordinates. The results indicate that the oscillation amplitude of the orientation of cardiomyocyte aggregates is regional in the left ventricle wall, which may promote our understanding of the rearrangement mechanism of the cardiomyocyte aggregates and provide a new biomarker to study the heart physiological status.

SIMUS: An open-source simulator for medical ultrasound imaging. Part II: Comparison with four simulators.

BACKGROUND AND OBJECTIVE: Computational ultrasound imaging has become a well-established methodology in the ultrasound community. In the accompanying paper (part I), we described a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the Matlab UltraSound Toolbox (MUST). SIMUS can generate pressure fields and radiofrequency RF signals for simulations in medical ultrasound imaging. It works in a harmonic domain and uses far-field and paraxial linear equations. METHODS: In this article (part II), we illustrate how SIMUS compares with other ultrasound simulators (Field II, k-Wave, FOCUS, and Verasonics) for a homogeneous medium. We designed different transmit sequences (focused, planar, and diverging wavefronts) and calculated the corresponding 2-D and 3-D (with elevation focusing) RMS pressure fields. RESULTS: SIMUS produced pressure fields similar to those of Field II, FOCUS, and k-Wave. The acoustic fields provided by the Verasonics simulator were significantly different from those of SIMUS and k-Wave, although the overall appearance remained consistent. CONCLUSION: Our simulations tend to demonstrate that SIMUS is reliable and can be used for realistic medical ultrasound simulations.

The IPASC data format: A consensus data format for photoacoustic imaging.

Photoacoustic imaging (PAI) is an emerging modality that has shown promise for improving patient management in a range of applications. Unfortunately, the current lack of uniformity in PAI data formats compromises inter-user data exchange and comparison, which impedes: technological progress; effective research collaboration; and efforts to deliver multi-centre clinical trials. To overcome this challenge, the International Photoacoustic Standardisation Consortium (IPASC) has established a data format with a defined consensus metadata structure and developed an open-source software application programming interface (API) to enable conversion from proprietary file formats into the IPASC format. The format is based on Hierarchical Data Format 5 (HDF5) and designed to store photoacoustic raw time series data. Internal quality control mechanisms are included to ensure completeness and consistency of the converted data. By unifying the variety of proprietary data and metadata definitions into a consensus format, IPASC hopes to facilitate the exchange and comparison of PAI data.

Measurement of local orientation of cardiomyocyte aggregates in human left ventricle free wall samples using X-ray phase-contrast microtomography.

Most cardiomyocytes in the left ventricle wall are grouped in aggregates of four to five units that are quasi-parallel to each other. When one or more "cardiomyocyte aggregates" are delimited by two cleavage planes, this defines a "sheetlet" that can be considered as a "work unit" that contributes to the thickening of the wall during the cardiac cycle. In this paper, we introduce the skeleton method to measure the local three-dimensional (3D) orientation of cardiomyocyte aggregates in the sheetlets in three steps: data segmentation; extraction of the skeleton of the sheetlets; and calculation of the local orientation of the cardiomyocyte aggregates inside the sheetlets. These data include a series of virtual tissue volumes and five transmural human left ventricle free wall samples, imaged with 3D synchrotron radiation phase-contrast microtomography, and reconstructed with a 3.5×3.5×3.5µm3 voxel size. We computed the local orientation of the cardiomyocyte aggregates inside the sheetlets with a working window of 112×112×112µm3 in size. These data demonstrate that the skeleton method can provide accurate 3D measurements and reliable screening of the 3D evolution of the orientation of cardiomyocyte aggregates within the sheetlets. We showed that in regions that contain one population of quasi-parallel sheetlets, the orientation of the cardiomyocyte aggregates undergo "oscillations" along the perpendicular direction of the sheetlets. In regions that contain two populations of sheetlets with a different angular range, we demonstrate some discontinuity of the helix angle of the cardiomyocyte aggregates at the interface between the two populations.

Piezoelectric Micromachined Ultrasonic Transducer for Arterial Wall Dynamics Monitoring.

In this article, a [Formula: see text] piezoelectric micromachined ultrasonic transducer (PMUT) array is designed and driven with one cycle of a 5-MHz sinusoid at 10 [Formula: see text] for radial artery motion tracking. The transmit and receive performance figure of merit (FOM) of an individual PMUT over operating frequency is modeled and validated using laser Doppler vibrometer (LDV) measurements. Given a fixed cross section, the FOM inversely scales with frequency. The array aperture size is selected to obtain enough pressure and received signal to measure the radial artery wall reflection at a 5-mm depth in tissue. The 2-mm acoustic beamwidth provides enough lateral resolution for radial artery wall motion tracking. Single-line ultrasonic pulse-echo measurements with high time resolution, also called M-mode ultrasound imaging, are demonstrated to reproduce a known target motion profile with a precision of around 0.5 [Formula: see text]. In vivo radial artery dynamics are measured by placing the sensor on the wrist of a volunteer. The measured diameter change waveform of the radial artery is consistent with reports in the literature and captures key arterial pulse waveform features, including systolic upstroke, systolic decline, dicrotic notch, and diastolic runoff. The system has sufficient accuracy and precision to measure both the 50 [Formula: see text] overall diameter change and the 5- [Formula: see text] diameter change due to the dicrotic notch. A heart rate of 70 beats/min is also derived. This demonstrates the great potential of custom PMUT arrays for continuous cardiovascular system monitoring.

In Vitro and In Vivo Multispectral Photoacoustic Imaging for the Evaluation of Chromophore Concentration.

Multispectral photoacoustic imaging is a powerful noninvasive medical imaging technique that provides access to functional information. In this study, a set of methods is proposed and validated, with experimental multispectral photoacoustic images used to estimate the concentration of chromophores. The unmixing techniques used in this paper consist of two steps: (1) automatic extraction of the reference spectrum of each pure chromophore; and (2) abundance calculation of each pure chromophore from the estimated reference spectra. The compared strategies bring positivity and sum-to-one constraints, from the hyperspectral remote sensing field to multispectral photoacoustic, to evaluate chromophore concentration. Particularly, the study extracts the endmembers and compares the algorithms from the hyperspectral remote sensing domain and a dedicated algorithm for segmentation of multispectral photoacoustic data to this end. First, these strategies are tested with dilution and mixing of chromophores on colored 4% agar phantom data. Then, some preliminary in vivo experiments are performed. These consist of estimations of the oxygen saturation rate (sO2) in mouse tumors. This article proposes then a proof-of-concept of the interest to bring hyperspectral remote sensing algorithms to multispectral photoacoustic imaging for the estimation of chromophore concentration.

Sparse Convolutional Beamforming for 3-D Ultrafast Ultrasound Imaging.

Real-time 3-D ultrasound (US) provides a complete visualization of inner body organs and blood vasculature, crucial for diagnosis and treatment of diverse diseases. However, 3-D systems require massive hardware due to the huge number of transducer elements and consequent data size. This increases cost significantly and limit both frame rate and image quality, thus preventing the 3-D US from being common practice in clinics worldwide. A recent study presented a technique called sparse convolutional beamforming algorithm (SCOBA), which obtains improved image quality while allowing notable element reduction in the context of 2-D focused imaging. In this article, we build upon previous work and introduce a nonlinear beamformer for 3-D imaging, called COBA-3D, consisting of 2-D spatial convolution of the in-phase and quadrature received signals. The proposed technique considers diverging-wave transmission and achieves improved image resolution and contrast compared with standard delay-and-sum beamforming while enabling a high frame rate. Incorporating 2-D sparse arrays into our method creates SCOBA-3D: a sparse beamformer that offers significant element reduction and, thus, allows performing 3-D imaging with the resources typically available for 2-D setups. To create 2-D thinned arrays, we present a scalable and systematic way to design 2-D fractal sparse arrays. The proposed framework paves the way for affordable ultrafast US devices that perform high-quality 3-D imaging, as demonstrated using phantom and ex-vivo data.

So you think you can DAS? A viewpoint on delay-and-sum beamforming.

Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its functioning and limitations. In particular, we discuss the importance of the f-number and speed of sound on image quality, and propose one solution to set their values from a physical viewpoint. We suggest determining the f-number from the directivity of the transducer elements and the speed of sound from the phase dispersion of the delayed signals. Simplified Matlab codes are provided for the sake of clarity and openness. The effect of the f-number and speed of sound on the lateral resolution and contrast-to-noise ratio was investigated in vitro and in vivo. If not properly preset, these two factors had a substantial negative impact on standard metrics of image quality (namely CNR and FWHM). When beamforming with DAS in vitro or in vivo, it is recommended to optimize these parameters in order to use it wisely and prevent image degradation.

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.

Sparse hand-held probe for optoacoustic ultrasound volumetric imaging: an experimental proof-of-concept study.

We present an experimental proof-of-concept study on the performance of a sparse segmented annular array for optoacoustic imaging. A capacitive micromachined ultrasonic transducer was equipped with a negatively focused acoustic lens and scanned in an annular fashion to exploit the performance of the sparse array geometry proposed in our recent numerical studies [Biomed. Opt. Express10, 1545 (2019)BOEICL2156-708510.1364/BOE.10.001545; J. Biomed. Opt.23, 025004 (2018)JBOPFO1083-366810.1117/1.JBO.23.2.025004]. A dedicated water tank was made using a 3D printer for light delivery and mounting the sample. A phantom experiment was carried out to showcase the possibility of full-field optoacoustic ultrasound (OPUS) imaging and confirm the earlier numerical results. This proof of concept opens the door towards a prototype of OPUS imaging for (pre-) clinical studies.

Liposomes Containing Nickel-Bis(dithiolene) Complexes for Photothermal Theranostics.

New thermosensitive liposomes with a phase transition at 42 °C, containing nickel-bis(dithiolene) complexes as efficient and stable photothermal agents, have been formulated and characterized. These liposomes are highly stable and keep their contents at 37 °C for more than 30 days. On the contrary, the mild hyperthermia generated by the nickel-bis(dithiolene) complex under 940 nm NIR irradiation allows for the fine controlled release of the liposome contents, making such liposomes highly suitable for on-demand drug delivery in the human body under NIR laser irradiation. These liposomes can also be directly used, as shown here, as nanoagents for photothermal therapy. In fact, strong cell death can be generated under laser irradiation in the presence of these photothermally active nanocargos containing less than 10% w/w of metal complex. We also demonstrate, for the first time, that nickel-bis(dithiolene) complexes are good photoacoustic agents, generating easily detectable ultrasonic signals directly proportional to the concentration of complexes and the used laser power.

Experimental Implementation of a Pulse Compression Technique Using Coherent Plane-Wave Compounding.

The axial resolution of an ultrasound imaging system is inversely proportional to the bandwidth of the emitted signal. When conventional pulsing (CP) is used, the impulse response of the transducer and the excitation signal determine together the shape of the emitted pulse and its bandwidth. A way to increase the ultrasound image resolution is to increase the transducer's limited passband. The resolution enhancement compression (REC) is a coding technique that boosts the signal energy in the transition frequency bands, where the energy transduction of the ultrasound probe is less efficient. Consequently, image quality metrics including axial resolution, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) can be improved. In this paper, the objective is to combine REC with coherent plane-wave compounding (CPWC) in order to achieve better image quality at an ultrafast acquisition rate. Promising results are obtained from both wire and cyst phantoms using an excitation signal designed to provide a 54% increase in bandwidth over the one obtained with a broadband pulse excitation at -6 dB. The experimental bandwidth measured from the backscattered echoes was improved by 49% for the wire phantom, when using the CPWC-REC technique compared to CPWC-CP. Furthermore, the axial resolution as derived from the modulation transfer function of the envelope of the wire target was enhanced by 29%. The CNR and SNR were improved up to 9 and up to 4 dB, respectively, in the cyst phantom. These results reveal that CPWC-REC is able to achieve higher spatial resolution, compared to CPWC-CP, with better SNR and CNR. Moreover, experimental results show that an effective implementation on a research scanner of REC using plane-wave imaging is possible. Consistent in vivo acquisition results on rabbit are presented and discussed.