Microbubble detection with adaptive beamforming for Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) represents a significant advancement over traditional ultrasound (US) imaging, enabling super-resolution (SR) imaging of microvascular structures with unprecedented detail, by using microbubbles (MBs) as highly reflective contrast agents. After injection into the bloodstream, MBs are localized in US images to reconstruct the microvasculature. However, this technique faces a tradeoff between MB localization accuracy and acquisition time. Perfusion with low MB concentrations reduces signal overlap and achieves high localization accuracy but requires extended acquisition times. Conversely, higher MB concentrations shorten acquisition times but increase signal overlap, limiting localization precision. Traditionally, ULM consists of five main steps: tissue filtering, MB detection, MB super-localization, tracking, and rendering. In this study, we present a novel approach that combines a robust principal component analysis (RPCA) with a computational SR technique, replacing the first three steps of ULM with a single process based on solving an SR inverse problem. This method isolates MB signals from background noise and enhances the localization of overlapping MBs, thereby improving overall ULM performance. The experimental results from simulated and in vivo data demonstrate that our proposed approach increases the SR factor by up to 30% and enhances the contrast ratio (CR) by 3.5 dB. It also produces comparable results across other image quality metrics. These improvements enable denser, higher contrast vascular images.

Ultrasound Localization Microscopy (ULM) is a milestone in the medical vascular imaging context, enabling the precise characterization of micro-vascular structures using ultrasound imaging. By accurately localizing contrast microbubbles (MBs) flowing in the circulatory system, ULM generates micro-resolved vascular images, overcoming the ultrasonic diffraction limit. However, as ULM relies on precise localization and tracking of individual MBs, high MB concentrations yield to increased localization errors and, ultimately, ULM failure. This constraint limits ULM to low MB concentrations, resulting in long acquisition times that pose challenges in clinical settings. Methods: Here, we show the feasibility of uncoupling a bi-disperse MB population, composed of two monodisperse MB populations. The uncoupling is performed through a signal processing pipeline that exploits the strong nonlinear response of MBs having resonance frequency tuned with the transmission frequency. After uncoupling, ULM density and velocity flow maps are generated. Results: Density and velocity maps are generated after uncoupling, when injecting the bi-disperse population individually and simultaneously in a vascular 3D-printed phantom. Furthermore, density maps generated after uncoupling are compared with the one obtained using standard ULM. Results demonstrate the capability of the proposed uncoupling pipeline to separate the bi-disperse population. Conclusion: This work presents a signal processing pipeline to uncouple a bi-disperse MB population, formed by two monodisperse MB populations. Results are validated in a 3D-printed phantom and demonstrate the feasibility of the uncoupling which, in turn, would enable higher concentrations and reduce acquisition times for micro-vascular imaging.

Super-resolution ultrasound (SRUS) has become a tool for in vivo microvascular imaging. Most of the SRUS methods are based on microbubble localization: namely, ultrasound localization microscopy (ULM). The aim of this study was to develop a nonlocalization SRUS method and verify its feasibility in microvascular imaging. We introduce a new super-resolution strategy based on the postprocessing of contrast-enhanced ultrasound. The proposed method, which is termed ultrasound diffraction attenuation microscopy (UDAM), uses super-resolution radial fluctuations instead of microbubble localization to overcome acoustic diffraction limits. Biceps of Japanese long-ear white rabbits were adopted to validate its feasibility on muscle vascular imaging, using a clinical accessible ultrasound system at a frame rate of 30 Hz under a single bolus injection of SonoVue (Bracco SpA, Milan, Italy). The super-resolution image was compared with the maximum-intensity projection and ULM. The animal study illustrates that the proposed UDAM can obtain super-resolution microvascular images of rabbits' muscles under a single bolus injection of SonoVue with a 150-second contrast-enhanced ultrasound video. Both ULM and UDAM can achieve a very similar vascular structure with the maximum-intensity projection but much higher spatial resolution. The measurement of 1-dimensional signals shows that UDAM can distinguish the subwavelength structures and substantial reduce the full width at half-maximum of microvessels. We conclude UDAM provides a noninvasive tool for in vivo super-resolution microvascular imaging.

Neovascularisation of carotid plaques contributes to their vulnerability. Current imaging methods such as contrast-enhanced ultrasound (CEUS) usually lack the required spatial resolution and quantification capability for precise neovessels identification. We aimed at quantifying plaque vascularisation with ultrasound localization microscopy (ULM) and compared the results to histological analysis. We conducted a prospective, monocentric, study involving patients who were undergoing carotid endarterectomy (CEA) for carotid artery stenosis. The day before CEA ultrasound examination coupled with the injection of microbubbles (MB) as a contrast agent (CEUS) to image the MB circulating within and around the carotid plaque was performed. CEUS images analysis classified patients into 2 groups: absence of neovascularisation (group A) or presence of neovascularisation (group B). ULM was performed by localising and tracking individual MB centres to reconstruct the neovessels structure with a resolution of around 60μm. Plaques were manually segmented on the images to quantify the number of neovessels and various haemodynamic metrics inside the plaques. Histological analysis of the excised carotid plaque specimens classified patients into 2 groups: absence of neovascularisation (group I) or presence of neovascularisation (group II). Among the 26 patients included, classification was as follows: group I: n=8 and group II: n=18, 18 patients had analysable CEUS images and were classified as follows: group A: n=10, group B: n=8. The median (Q1-Q3) number of MB tracked per second inside the plaque was 0.03 (0-0.37) for patients in group I and 0.51 (0-3) for patients in group A versus (vs.) 3.55 (1.26-17.68) for patients in group II and 9.69 (5.83-34.68) for patients in group B (p=0.00049; p=0.010 respectively). The length of the MB tracks was 0.02mm (0-0.16) in group I vs. 0.29mm (0.22-0.45) in group II (p=0.0069). The study also showed that flow in the neovessels was greater during systole than during diastole period: 9.38 (1.67-19.17) MB tracked per second vs. 1.35 (0.28-6.56) (p=0.021). ULM allows the detection of neovessels within the carotid atherosclerotic plaque. Thus, ULM provides a precise picture of plaque neovascularisation in patients and could be used as a non-invasive imaging technique to assess carotid plaque vulnerability. The study was sponsored and funded by Assistance Publique-Hôpitaux de Paris (CRC 1806 APHP INNOVATION 2018). Co-funding by ART (Technological Research Accelerator) biomedical ultrasound program of INSERM, France.

As a typical chronic kidney disease (CKD), hypertensive nephrosclerosis (HN) is a common syndrome of hypertension, characterized by chronic kidney microvascular damage. Early diagnosis of microvascular damage using conventional ultrasound imaging encounters challenges in sensitivity and specificity owing to the inherent diffraction limit. Ultrasound localization microscopy (ULM) has been developed to obtain microvasculature and microvascular hemodynamics within the kidney, and would be a promising tool for the early diagnosis of CKD. In this study, the advantage of quantitative indexes obtained by using ULM (mean arterial blood flow speeds of different segments of interlobular arteries) over indexes obtained using conventional clinical serum (β2-microglobulin, serum urea nitrogen, and creatinine) and urine (24-h urine volume and urine protein) tests and ultrasound Doppler imaging (peak systolic velocity [PSV], end-diastolic velocity [EDV], and resistance index [RI]) and contrast-enhanced ultrasound imaging (CEUS; rise time [RT], peak intensity [IMAX], mean transit time [mTT], and area under the time-intensity curve [AUC]) for early diagnosis of HN were investigated. Examinations were carried out on six spontaneously hypertensive rats (SHR) and five normal Wistar-Kyoto (WKY) rats at the age of 10weeks. The experimental results show that the indicators derived from conventional clinical inspections (serum and urine tests) and ultrasound imaging (PSV, EDV, RI, RT, IMAX, mTT, and AUC) do not show significant difference between hypertensive and healthy rats (p>0.05), while the TTP of the SHR group (28.52 ± 5.52 s) derived from CEUS is significantly higher than that of the WKY group (18.68 ± 7.32 s; p<0.05). The mean blood flow speed in interlobular artery of SHR (12.47 ± 1.06mm/s) derived from ULM is significantly higher than that of WKY rats (10.13 ± 1.17mm/s; p<0.01). The advantages of ULM over conventional clinical inspections and ultrasound imaging methods for early diagnosis of HN were validated. The quantitative results show that ULM can effectively diagnose HN at the early stage by detecting the blood flow speed changes of interlobular arteries. ULM may promise a reliable technique for early diagnosis of HN in the future.

In this study, by using super-resolution radial fluctuations (SRRF), we propose a non-localizing ultrasound super-resolution method termed ultrasound diffraction attenuation microscopy (UDAM). By applying spatial and temporal analysis to the contrast-enhanced ultrasound image sequence, the point spread functions (PSFs) of diffraction can be significantly attenuated. In human study illustrates the proposed approach can obtain a super-resolved skeletomuscular vessel structure using only hundreds of frames at a frame rate of 30Hz in contrast-enhanced ultrasound (CEUS) imaging mode, after a 2mL dose bolus injection of microbubbles. Compared with the conventional maximum intensity projection (MIP), the UDAM can significantly reduce the full-width-half-maximum (FWHM) of the one-dimensional microvessel signal and distinguish micro structure beyond the diffraction limitation. We conclude from our study that the UDAM provides a perspective non-invasive super- resolution imaging tool for the assessment of microvascular structure in clinical.

Ultrasound Localization Microscopy (ULM) enables to accurately characterize micro-vascular structures by means of ultrasound imaging. In ULM, the backscattering signals of injected microbubbles (MBs) are utilized to sub-wavelength localize and track MBs flowing in the circulatory system. To ensure precise MB localizations, ULM is constrained to low MB concentrations, leading to prolonged acquisition times. Owing to patient comfort, motion, and computational cost to elaborate data, the constraint on low MB concentrations is a bottleneck for ULM clinical translation. To mitigate the need of low MB concentration, we propose to uncouple a bi-disperse MB population. The bi-disperse population is composed of two monodisperse MB populations having diameter (and resonance frequency) of 2.5 μm (3 MHz) and 3.8 μm (5.5 MHz), respectively. The different diameter determines a different resonance response. Experiments are performed injecting the populations singularly and simultaneously in a 3-D printed phantom. Uncoupling is performed by means of a signal processing pipeline, which exploits the strong nonlinear response of MBs having resonance frequency tuned with the transmission frequency. After uncoupling, super-resolved density and velocity flow maps are generated for each MB population. The results demonstrate the capability of uncoupling the selected pair of MB populations, thus potentially permitting increased MB concentrations.

Ultrasound localization microscopy (ULM) has recently enabled the mapping of the cerebral vasculature in vivo with a resolution ten times smaller than the wavelength used, down to ten microns. However, with frame rates up to 20000 frames per second, this method requires large amount of data to be acquired, transmitted, stored, and processed. The transfer rate is, as of today, one of the main limiting factors of this technology. Herein, we introduce a novel reconstruction framework to decrease this quantity of data to be acquired and the complexity of the required hardware by randomly subsampling the channels of a linear probe. Method performance evaluation as well as parameters optimization were conducted in silico using the SIMUS simulation software in an anatomically realistic phantom and then compared to in vivo acquisitions in a rat brain after craniotomy. Results show that reducing the number of active elements deteriorates the signal-to-noise ratio and could lead to false microbubbles detections but has limited effect on localization accuracy. In simulation, the false positive rate on microbubble detection deteriorates from 3.7% for 128 channels in receive and 7 steered angles to 11% for 16 channels and 7 angles. The average localization accuracy ranges from 10.6 μm and 9.93 μm for 16 channels/3 angles and 128 channels/13 angles respectively. These results suggest that a compromise can be found between the number of channels and the quality of the reconstructed vascular network and demonstrate feasibility of performing ULM with a reduced number of channels in receive, paving the way for low-cost devices enabling high-resolution vascular mapping.

The microvasculature plays an important role in many pathologic conditions but cannot be characterized in high resolution via conventional ultrasound methods. Doppler-based techniques, contrast-enhanced sonography as well as dynamic contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) are commonly used to characterize tissue vascularization. However, these techniques cannot visualize the microvasculature adequately. Ultrasound localization microscopy (ULM) consists of contrast-enhanced ultrasound measurements in combination with acomplex post-processing algorithm which detects microbubbles with high precision. The vasculature can then be visualized by accumulating the microbubble positions in afinal image. Compared to conventional ultrasound techniques, ULM improves the image resolution by afactor of more than10. This currently results in resolutions down to 10 µm and allows, therefore, the visualization of capillaries and the assessment of their perfusion. Also, this does not lead to areduction of the penetration depth or the signal-to-noise ratio (SNR). The method enables the visualization of vascular structures in unsurpassed detail and has the potential to offer new possibilities for the diagnosis of various diseases and for gaining insights into physiological processes. However, ULM is not commercially available yet but is intensely being tested in clinical studies. ULM could potentially be applied to all fields in which the vasculature is relevant. Current fields of application include oncology, nephrology, and neurological research.

Ultrasound Localization Microscopy (ULM) offers great advances compared to conventional ultrasound imaging, enabling the reconstruction of microvascular structures with micrometer-scale precision. Most model-based localization approaches for ULM rely on a sequential five-step framework, which complicates parameter tuning and results in intricate tissue filtering. In addition, insufficient consideration of point spread function (PSF) also affects the final results. End-to-end data-driven solutions offer promising results yet require training data and ground-truths. In this study, we introduced a novel approach, based on computational super-resolution referred to as BSRPCA - Blind Super-Resolved Robust Principal Component Analysis, to address these challenges. Our method replaces the first three steps of the ULM process with a single super-resolution step. Experimental results on both in silico and in vivo datasets have proven the effectiveness of our method compared to the other benchmarks.

Transcranial ultrasound plays a limited role in neuroradiology due to its lack of resolution, planar imaging, and user dependency. By breaching the diffraction limit using injected microbubbles, volumetric ultrasound localization microscopy (ULM) could help alleviate those issues. However, performing 3-D ultrasound imaging at a high frame rate with sufficient signal-to-noise ratio (SNR) to track individual microbubbles through the skull remains a challenge, especially with a portable scanner. In this study, we describe a ULM sequence suitable for volumetric transcranial imaging exploiting cylindrical emissions on multiplexed matrix probes, through simulations, hydrophone measurements, and flow phantoms. This geometry leads to a doubling of the peak acoustic pressure, up to 400 kPa, with respect to spherical emission and improved volume rate, up to 180 Hz. Cylindrical emissions also improve the ULM saturation rate by 60% through a skull phantom. The assessment of microbubble velocity was also improved from a 33% error in the average flow measured with spherical waves to a 5% error with cylindrical waves. Conversely, we demonstrate the detrimental impacts of cylindrical waves toward the field of view and isotropic sensitivity. Nevertheless, due to its enhanced SNR and 3-D nature, such a cylindrical volumetric sequence could be beneficial for ULM as a diagnostic tool in humans, especially when portability is a necessity.

Usefulness of Contrast-Enhanced Intraoperative Ultrasonography (CE-IOUS) in Patients with Colorectal Liver Metastases after Preoperative Chemotherapy

One of the challenges in Super-Resolution Ultrasound Imaging (SRUI) based on Ultrasound Localization Microscopy (ULM) is that we need a large number of localized points to form the final image, so a significant number of frames is needed. In this study, we propose a method that significantly reduces the number of frames while eventually having an acceptable output image. Also, in this method, we no longer need to localize the center of the microbubbles, and we will create images only by the accumulation of binary images. This requires using a suitable adaptive beamformer for each frame to achieve the best possible quality of work. Investigation of beamformers in our other work proved that the Eigenspace-Based Minimum Variance (EIB-MV) beamformer with Coherence Factor (CF) coefficient was better than other beamformers in creating suitable binary frames. To compare the proposed method with the ULM method, parameters of SNR, PSNR and MSE were investigated. First, 100 frames were used to create the final images. Obtained results showed that the proposed method improves SNR and PSNR by 2 dB. Also, to investigate the effect of the number of frames on imaging parameters, only 8 frames were used to create the final image in the proposed method. By comparing the results of our proposed method with 8 frames and the ULM method with 100 frames, it was observed that the proposed method improves the SNR and PSNR by 0.8 dB relative to the ULM method.

Heterogenity of tumor structure and function (e.g., stromal density, vascularization, and oxygen distribution) can influence local cellular proliferation and therapeutic resistance. Emerging ultrasound imaging techniques can map parameters related to these features but such approaches are not yet in standard clinical practice. The goal of our work is to develop robust protocols to provide more complete information during therapy by quantitatively mapping and interpreting tumor heterogeneity using emerging ultrasonic techniques. Within murine tumor models Shear Wave Elastography (SWE), Contrast-Enhanced Ultrasound (CEUS) and Quantitative Ultrasound (QUS) techniques have been applied with clinical imaging systems to compare changes observed during anti-angiogenic and cytotoxic therapy as compared to controls. In a Lewis Lung Carcinoma model, mice receiving an anti-angiogenic therapy had the highest levels of necrosis and fibrosis and presented the highest number of correlations between quantitative parameters related to microvascular function and tumor structure. This indirectly demonstrates, for this tumor-type, that quantitative parameters measured with clinical imaging systems can help differentiate tumor therapeutic responses. Promising results with ultrasound localization microscopy and photoacoustics will also be reviewed because of the important new information they offer. Finally, the path towards integration of these quantitative ultrasound techniques in clinical practice will be discussed.

Nanoscale phase-variant ultrasound contrast agents have attracted the interest of many researchers. However, it is a challenge to design nanobubbles that are activated by low-frequency medical ultrasound that do not cause damage to normal tissues. In this study, we designed a new type of nanoparticle consisting of perfluoropentane and iron polyphthalocyanine loaded into liposomes. These nanoparticles can be activated by a low-frequency medical ultrasound imager at a frequency of 5 MHz for ultrasound imaging and clear reactive oxygen species at a rate of more than 50%. This ability to scavenge excess reactive oxygen species can alleviate the damage these species cause and protect macrophages. Moreover, these nanoparticles can effectively enhance ultrasound contrast imaging for real-time visualization in the diagnosis and treatment of diseases.