Resolving Ultrasound Contrast Microbubbles Using Minimum Variance Beamforming

Super-resolution ultrasound imaging of ischaemia flow: An in silico study

Super-resolution ultrasound (SRU) is a new ultrasound imaging mode that promises to facilitate the detection of microvascular disease by providing new vascular bio-markers that are directly linked to microvascular pathophysiology, thereby augmenting current knowledge and potentially enabling new treatment. Such a capability can be developed through thorough understanding as articulated by means of mathematical models. In this study, a 2D numerical flow model is adopted for generating flow adaptation in response to ischaemia, in order to determine the ability of SRU to register the resulting flow perturbations. The flow model results demonstrate that variations in flow behaviour in response to locally induced ischaemia can be significant throughout the entire vascular bed. Measured velocities have variations that are dependent on the location of ischaemia, with median values ranging between 2-7 mms-1. Moreover, the distinction between healthy and ischaemic networks are recorded accurately in the SRU results showing excellent agreement between SRU maps and the model. Up to 7-fold spatial resolution improvement to conventional contrast ultrasound was achieved in microbubble localisation while the detection precision and recall was consistently above 98%. The microbubble tracking precision was of a similar accuracy, whereas the recall was reduced (77%) under varying ischaemic impacted flow. Further, regions with velocities up to 30 mms-1 are in excellent agreement with SRU maps, while at regions that include a proportion of higher velocities, the median velocity values are within 1.28%-3.32% of the ground-truth. In conclusion, SRU is a highly promising methodology for the direct measurement of microvascular flow dynamics and may provide a valuable tool for the understanding and subsequent modelling of behaviour in the vascular bed.

Vessel recovery using ultrasound localisation microscopy: An in silico comparative study between minimum variance and delay-and-sum beamformers

The use of particle localisation and tracking algorithms on Contrast Enhanced Ultrasound (CEUS) or other ultrasound mode image data containing sparse microbubble (MB) populations, can produce super-resolved vascularization maps. Typically such data stem from conventional delay and sum (DAS) beamforming that is used widely in ultrasound imaging modes. Recently, adaptive beamforming has shown significant improvement in spatial resolution, but its value to super-resolution image analysis approaches is not fully understood. The in silico study here evaluates the performance of combining minimum variance beamformers (MV BF), established to provide improved lateral resolution, compared to DAS BFs with single particle detection. The isolated effect of a range of simplified image-affecting factors such as flow profile, pulse length, noise, vessel separations and data availability is considered. The study aims to assess the vessel recovery performance using the different beamformers and investigate the link with MB detection and localisation. The MV BF was shown to provide improved microvessel position accuracy compared to conventional DAS BFs. In particular, vessel separations between 0.3-4 λ provided superior localisation uncertainty with the MV. In addition, for a separation of 0.36λ, vessel recovery was achieved with both methods but the use of MV eliminated artifacts that appear as additional vessels. These results were found to be linked to improved MB detection and localisation for the MV BF, which is proposed as suitable for testing in Ultrasound Localisation Microscopy (ULM) imaging using patient data.

Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study

The study of microcirculation can reveal important information related to pathology. Focusing on alterations that are represented by an obstruction of blood flow in microcirculatory regions may provide an insight into vascular biomarkers. The current in silico study assesses the capability of contrast enhanced ultrasound (CEUS) and super-resolution ultrasound imaging (SRU) flow-quantification to study occlusive actions in a microvascular bed, particularly the ability to characterise known and model induced flow behaviours. The aim is to investigate theoretical limits with the use of CEUS and SRU in order to propose realistic biomarker targets relevant for clinical diagnosis. Results from CEUS flow parameters display limitations congruent with prior investigations. Conventional resolution limits lead to signals dominated by large vessels, making discrimination of microvasculature specific signals difficult. Additionally, some occlusions lead to weakened parametric correlation against flow rate in the remainder of the network. Loss of correlation is dependent on the degree to which flow is redistributed, with comparatively minor redistribution correlating in accordance with ground truth measurements for change in mean transit time,dMTT(CEUS,R = 0.85; GT,R = 0.82) and change in peak intensity,dIp(CEUS,R = 0.87; GT,R = 0.96). Major redistributions, however, result in a loss of correlation, demonstrating that the effectiveness of time-intensity curve parameters is influenced by the site of occlusion. Conversely, results from SRU processing provides accurate depiction of the anatomy and dynamics present in the vascular bed, that extends to individual microvessels. Correspondence between model vessel structure displayed in SRU maps with the ground truth was>91%for cases of minor and major flow redistributions. In conclusion, SRU appears to be a highly promising technology in the quantification of subtle flow phenomena due ischaemia induced vascular flow redistribution.

Fast 3D Super-Resolution Ultrasound With Adaptive Weight-Based Beamforming

OBJECTIVE

Super-resolution ultrasound (SRUS) imaging through localising and tracking sparse microbubbles has been shown to reveal microvascular structure and flow beyond the wave diffraction limit. Most SRUS studies use standard delay and sum (DAS) beamforming, where high side lobes and broad main lobes make isolation and localisation of densely distributed bubbles challenging, particularly in 3D due to the typically small aperture of matrix array probes.

METHOD

This study aimed to improve 3D SRUS by implementing a new fast 3D coherence beamformer based on channel signal variance. Two additional fast coherence beamformers, that have been implemented in 2D were implemented in 3D for the first time as comparison: a nonlinear beamformer with p-th root compression and a coherence factor beamformer. The 3D coherence beamformers, together with DAS, were compared in computer simulation, on a microflow phantom and in vivo.

RESULTS

Simulation results demonstrated that all three adaptive weight-based beamformers can narrow the main lobe, suppress the side lobes, while maintaining the weaker scatter signals. Improved 3D SRUS images of microflow phantom and a rabbit kidney within a 3-second acquisition were obtained using the adaptive weight-based beamformers, when compared with DAS.

CONCLUSION

The adaptive weight-based 3D beamformers can improve the SRUS and the proposed variance-based beamformer performs best in simulations and experiments.

SIGNIFICANCE

Fast 3D SRUS would significantly enhance the potential utility of this emerging imaging modality in a broad range of biomedical applications.

Synthetic Aperture Ultrasound Imaging through Adaptive Integrated Transmitting-Receiving Beamformer

Synthetic aperture (SA) technique is very attractive for ultrafast ultrasound imaging, as the entire medium can be insonified by a single emission. It also permits applying the dynamic focusing as well as adaptive beamforming both in transmission and reception, which results in an enhanced image. In this paper, we firstly show that the problem of designing the transmit and receive beamformers in SA structure can be formulated as a problem of designing a one-way beamformer on a virtual array with a lateral response equal to that of the two-way beamformer on SA. It is also demonstrated that the length of the virtual aperture is increased to the sum of the transmit aperture length and the receive one, which can result in an enhanced resolution. Moreover, a better estimation of the covariance matrix can be obtained which can be utilized for applying adaptive minimum variance (MV) beamforming method on the virtual array, and consequently the resolution and contrast properties would be enhanced. The performance of the new method is compared with other existing MV-based methods and is quantified by some metrics such as the full width at half maximum (FWHM) and generalized contrast to noise ratio (GCNR). Our validations on simulations and experimental data have shown that the new method is capable of obtaining higher GCNR values while retaining or decreasing FWHM values almost all the time. Moreover, for the same subarray length for estimating the covariance matrices, the computational burden of the new method is significantly lower than those of the existing rival methods.

Adaptive subarray coherence based post-filter using array gain in medical ultrasound imaging

This paper presents an adaptive subarray coherence-based post-filter (ASCBP) applied to the eigenspace-based forward-backward minimum variance (ESB-FBMV) beamformer to simultaneously improve image quality and beamformer robustness. Additionally, the ASCBP can separate close targets. The ASCBP uses an adaptive noise power weight based on the concept of the beamformer's array gain (AG) to suppress the noise adaptively and achieve improved images. Moreover, a square neighborhood average was applied to the ASCBP in order to provide more smoothed square neighborhood ASCBP (SN-ASCBP) values and improve the speckle quality. Through simulations of point phantoms and cyst phantoms and experimental validation, the performance of the proposed methods was compared to that of delay-and-sum (DAS), MV-based beamformers, and subarray coherence-based post-filter (SCBP). The simulated results demonstrated that the ASCBP method improved the full width at half maximum (FWHM) by 57 % and the coherent interference suppression power (CISP) by 52 dB compared to the SCBP post-filter. Considering the experimental results, the SN-ASCBP method presented the best enhancement in terms of generalized contrast to noise ratio (gCNR) and contrast ratio (CR) while the ASCBP showed the best improvement in FWHM among other methods. Furthermore, the proposed methods presented a striking performance in low SNRs. The results of evaluating the different methods under aberration and sound speed error illustrated the better robustness of the proposed methods in comparison with others.

Combining ADMIRE and MV to Improve Image Quality

Aperture domain model image reconstruction (ADMIRE) is a frequency-domain, model-based beamformer, in part designed for removing reverberation and off-axis clutter. Minimum variance (MV) is alternatively designed to reduce off-axis interference and improve lateral resolution. MV is known to be less effective in high incoherent noise scenarios, and its performance in the presence of reverberation has not been evaluated. By implementing ADMIRE before MV, the benefits of both these beamformers can be achieved. In this article, the assumptions of MV are discussed, specifically their relationship to reverberation clutter. The use of ADMIRE as a preprocessing step to suppress noise from simulations with linear scanning and in vivo curvilinear kidney data is demonstrated, and both narrowband and broadband implementations of MV are applied. With optimal parameters, ADMIRE + MV demonstrated sizing improvements over MV alone by an average of 52.1% in 0-dB signal-to-clutter ratio reverberation cyst simulations and 14.5% in vivo while improving the contrast ratio compared to ADMIRE alone by an average of 15.1% in simulations and 14.0% in vivo. ADMIRE + MV demonstrated a consistent improvement compared to DAS, MV, and ADMIRE both in terms of sizing and contrast ratio.

Minimum variance beamforming combined with covariance matrix-based adaptive weighting for medical ultrasound imaging

BACKGROUND

The minimum variance (MV) beamformer can significantly improve the image resolution in ultrasound imaging, but it has limited performance in noise reduction. We recently proposed the covariance matrix-based statistical beamforming (CMSB) for medical ultrasound imaging to reduce sidelobes and incoherent clutter.

METHODS

In this paper, we aim to improve the imaging performance of the MV beamformer by introducing a new pixel-based adaptive weighting approach based on CMSB, which is named as covariance matrix-based adaptive weighting (CMSAW). The proposed CMSAW estimates the mean-to-standard-deviation ratio (MSR) of a modified covariance matrix reconstructed by adaptive spatial smoothing, rotary averaging, and diagonal reducing. Moreover, adaptive diagonal reducing based on the aperture coherence is introduced in CMSAW to enhance the performance in speckle preservation.

RESULTS

The proposed CMSAW-weighted MV (CMSAW-MV) was validated through simulation, phantom experiments, and in vivo studies. The phantom experimental results show that CMSAW-MV obtains resolution improvement of 21.3% and simultaneously achieves average improvements of 96.4% and 71.8% in average contrast and generalized contrast-to-noise ratio (gCNR) for anechoic cyst, respectively, compared with MV. in vivo studies indicate that CMSAW-MV improves the noise reduction performance of MV beamformer.

CONCLUSION

Simulation, experimental, and in vivo results all show that CMSAW-MV can improve resolution and suppress sidelobes and incoherent clutter and noise. These results demonstrate the effectiveness of CMSAW in improving the imaging performance of MV beamformer. Moreover, the proposed CMSAW with a computational complexity of [Formula: see text] has the potential to be implemented in real time using the graphics processing unit.

Measuring Image Resolution in Ultrasound Localization Microscopy

The resolution of an imaging system is usually determined by the width of its point spread function and is measured using the Rayleigh criterion. For most system, it is in the order of the imaging wavelength. However, super resolution techniques such as localization microscopy in optical and ultrasound imaging can resolve features an order of magnitude finer than the wavelength. The classical description of spatial resolution no longer applies and new methods need to be developed. In optical localization microscopy, the Fourier Ring Correlation has showed to be an effective and practical way to estimate spatial resolution for Single Molecule Localization Microscopy data. In this work, we wish to investigate how this tool can provide a direct and universal estimation of spatial resolution in Ultrasound Localization Microscopy. Moreover, we discuss the concept of spatial sampling in Ultrasound Localization Microscopy and demonstrate how the Nyquist criterion for sampling drives the spatial/temporal resolution tradeoff. We measured spatial resolution on five different datasets over rodent's brain, kidney and tumor finding values between [Formula: see text] and [Formula: see text] for precision of localization between [Formula: see text] and [Formula: see text]. Eventually, we discuss from those in vivo datasets how spatial resolution in Ultrasound Localization Microscopy depends on both the localization precision and the total number of detected microbubbles. This study aims to offer a practical and theoretical framework for image resolution in Ultrasound Localization Microscopy.

User Parameter-Free Minimum Variance Beamformer in Medical Ultrasound Imaging

The minimum variance beamformer (MVB) is a well-known adaptive beamformer in medical ultrasound imaging. Accurate estimation of the covariance matrix has a great effect on the performance of the MVB. In adaptive ultrasound imaging, parameters such as the subarray length, the number of samples used for temporal averaging, and the value of diagonal loading (DL) have the main role in the true estimation of the covariance matrix. The optimal values for these parameters are different from one scenario to another one. Thus, the MVB is not a parameter-free method, and its behavior is scenario-dependent. In the field of telecommunications and radar, the shrinkage method was proposed to determine the DL factor, but no method has been provided yet to determine other parameters. In this article, an adaptive approach is developed to determine the MVB parameters, which is completely independent of the user. The minimum variance variable loading along with the modified shrinkage (MVVL-MSh) algorithm is introduced to adaptively calculate the optimal DL. Also, two methods based on the coherence factor (CF) are proposed to determine the subarray length in the spatial smoothing and the number of samples required for temporal averaging. The performance of the proposed methods is evaluated using simulated and experimental RF data. It is shown that the methods preserve the contrast and improve the resolution by about 35% and 38% compared to the MV having a fix loading coefficient and the MV-Sh algorithm.

Sub-wavelength lateral detection of tissue-approximating masses using an ultrasonic metamaterial lens

Practically applied techniques for ultrasonic biomedical imaging employ delay-and-sum (DAS) beamforming which can resolve two objects down to 2.1λ within the acoustic Fresnel zone. Here, we demonstrate a phononic metamaterial lens (ML) for detection of laterally subwavelength object features in tissue-like phantoms beyond the phononic crystal evanescent zone and Fresnel zone of the emitter. The ML produces metamaterial collimation that spreads 8x less than the emitting transducer. Utilizing collimation, 3.6x greater lateral resolution beyond the Fresnel zone limit was achieved. Both hard objects and tissue approximating masses were examined in gelatin tissue phantoms near the Fresnel zone limit. Lateral dimensions and separation were resolved down to 0.50λ for hard objects, with tissue approximating masses slightly higher at 0.73λ. The work represents the application of a metamaterial for spatial characterization, and subwavelength resolution in a biosystem beyond the Fresnel zone limit.

Traditional methods for ultrasound detection in biomedical application suffer from limited lateral resolution. Here, the authors show that a phononic metamaterial lens can be used for spatial characterisation of subwavelength objects, even beyond the Fresnel zone of the emitting transducer.

Super-resolution Ultrasound Imaging

The majority of exchanges of oxygen and nutrients are performed around vessels smaller than 100 μm, allowing cells to thrive everywhere in the body. Pathologies such as cancer, diabetes and arteriosclerosis can profoundly alter the microvasculature. Unfortunately, medical imaging modalities only provide indirect observation at this scale. Inspired by optical microscopy, ultrasound localization microscopy has bypassed the classic compromise between penetration and resolution in ultrasonic imaging. By localization of individual injected microbubbles and tracking of their displacement with a subwavelength resolution, vascular and velocity maps can be produced at the scale of the micrometer. Super-resolution ultrasound has also been performed through signal fluctuations with the same type of contrast agents, or through switching on and off nano-sized phase-change contrast agents. These techniques are now being applied pre-clinically and clinically for imaging of the microvasculature of the brain, kidney, skin, tumors and lymph nodes.

Super-Resolution Contrast-Enhanced Ultrasound Methodology for the Identification of In Vivo Vascular Dynamics in 2D

OBJECTIVES

The aim of this study was to provide an ultrasound-based super-resolution methodology that can be implemented using clinical 2-dimensional ultrasound equipment and standard contrast-enhanced ultrasound modes. In addition, the aim is to achieve this for true-to-life patient imaging conditions, including realistic examination times of a few minutes and adequate image penetration depths that can be used to scan entire organs without sacrificing current super-resolution ultrasound imaging performance.

METHODS

Standard contrast-enhanced ultrasound was used along with bolus or infusion injections of SonoVue (Bracco, Geneva, Switzerland) microbubble (MB) suspensions. An image analysis methodology, translated from light microscopy algorithms, was developed for use with ultrasound contrast imaging video data. New features that are tailored for ultrasound contrast image data were developed for MB detection and segmentation, so that the algorithm can deal with single and overlapping MBs. The method was tested initially on synthetic data, then with a simple microvessel phantom, and then with in vivo ultrasound contrast video loops from sheep ovaries. Tracks detailing the vascular structure and corresponding velocity map of the sheep ovary were reconstructed. Images acquired from light microscopy, optical projection tomography, and optical coherence tomography were compared with the vasculature network that was revealed in the ultrasound contrast data. The final method was applied to clinical prostate data as a proof of principle.

RESULTS

Features of the ovary identified in optical modalities mentioned previously were also identified in the ultrasound super-resolution density maps. Follicular areas, follicle wall, vessel diameter, and tissue dimensions were very similar. An approximately 8.5-fold resolution gain was demonstrated in vessel width, as vessels of width down to 60 μm were detected and verified (λ = 514 μm). Best agreement was found between ultrasound measurements and optical coherence tomography with 10% difference in the measured vessel widths, whereas ex vivo microscopy measurements were significantly lower by 43% on average. The results were mostly achieved using video loops of under 2-minute duration that included respiratory motion. A feasibility study on a human prostate showed good agreement between density and velocity ultrasound maps with the histological evaluation of the location of a tumor.

CONCLUSIONS

The feasibility of a 2-dimensional contrast-enhanced ultrasound-based super-resolution method was demonstrated using in vitro, synthetic and in vivo animal data. The method reduces the examination times to a few minutes using state-of-the-art ultrasound equipment and can provide super-resolution maps for an entire prostate with similar resolution to that achieved in other studies.