In Vivo Ultrasound Localization Microscopy Imaging of the Kidney's Microvasculature With Block-Matching 3-D Denoising

Evaluation of tumor microvasculature with 3D ultrasound localization microscopy based on 2D matrix array

OBJECTIVE

Evaluation of tumor microvascular morphology is of great significance in tumor diagnosis, therapeutic effect prediction, and surgical planning. Recently, two-dimensional ultrasound localization microscopy (2DULM) has demonstrated its superiority in the field of microvascular imaging. However, it suffers from planar dependence and is unintuitive. We propose a novel three-dimensional ultrasound localization microscopy (3DULM) to avoid these limitations.

METHODS

We investigated 3DULM based on a 2D array for tumor microvascular imaging. After intravenous injection of contrast agents, all elements of the 2D array transmit and receive signals to ensure a high and stable frame rate. Microbubble signal extraction, filtering, positioning, tracking, and other processing were used to obtain a 3D vascular map, flow velocity, and flow direction. To verify the effectiveness of 3DULM, it was validated on double helix tubes and rabbit VX2 tumors. Cisplatin was used to verify the ability of 3DULM to detect microvascular changes during tumor treatment.

RESULTS

In vitro, the sizes measured by 3DULM at 3 mm and 13 mm were 178 μ m and 182 μ m , respectively. In the rabbit tumors, we acquired 9000 volumes to reveal vessels about 30 μ m in diameter, which surpasses the diffraction limit of ultrasound in traditional ultrasound imaging, and the results matched with micro-angiography. In addition, there were significant changes in vascular density and curvature between the treatment and control groups.

CONCLUSIONS

The effectiveness of 3DULM was verified in vitro and in vivo. Hence, 3DULM may have potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease.

CLINICAL RELEVANCE STATEMENT

3D ultrasound localization microscopy is highly sensitive to microvascular changes; thus, it has clinical potential for tumor diagnosis and treatment evaluation.

KEY POINTS

• 3D ultrasound localization microscopy is demonstrated on double helix tubes and rabbit VX2 tumors. • 3D ultrasound localization microscopy can reveal vessels about 30 μ m in diameter-far smaller than traditional ultrasound. • This form of imaging has potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease.

Deep learning for fast super-resolution ultrasound microvessel imaging

Objective. Ultrasound localization microscopy (ULM) enables microvascular reconstruction by localizing microbubbles (MBs). Although ULM can obtain microvascular images that are beyond the ultimate resolution of the ultrasound (US) diffraction limit, it requires long data processing time, and the imaging accuracy is susceptible to the density of MBs. Deep learning (DL)-based ULM is proposed to alleviate these limitations, which simulated MBs at low-resolution and mapped them to coordinates at high-resolution by centroid localization. However, traditional DL-based ULMs are imprecise and computationally complex. Also, the performance of DL is highly dependent on the training datasets, which are difficult to realistically simulate.Approach. A novel architecture called adaptive matching network (AM-Net) and a dataset generation method named multi-mapping (MMP) was proposed to overcome the above challenges. The imaging performance and processing time of the AM-Net have been assessed by simulation andin vivoexperiments.Main results. Simulation results show that at high density (20 MBs/frame), when compared to other DL-based ULM, AM-Net achieves higher localization accuracy in the lateral/axial direction.In vivoexperiment results show that the AM-Net can reconstruct ∼24.3μm diameter micro-vessels and separate two ∼28.3μm diameter micro-vessels. Furthermore, when processing a 128 × 128 pixels image in simulation experiments and an 896 × 1280 pixels imagein vivoexperiment, the processing time of AM-Net is ∼13 s and ∼33 s, respectively, which are 0.3-0.4 orders of magnitude faster than other DL-based ULM.Significance. We proposes a promising solution for ULM with low computing costs and high imaging performance.

Deep learning for fast denoising filtering in ultrasound localization microscopy

Objective.Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. However, previous image-denoising methods (e.g. block-matching 3D, BM3D) requires long data processing times, making ULM only able to be processed offline. This work introduces a new way to reduce data processing time through deep learning.Approach.In this study, we propose deep learning (DL) denoising based on contrastive semi-supervised network (CS-Net). The neural network is mainly trained with simulated MBs data to extract MB signals from noise. And the performances of CS-Net denoising are evaluated in bothin vitroflow phantom experiment andin vivoexperiment of New Zealand rabbit tumor.Main results.Forin vitroflow phantom experiment, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of single microbubble image are 26.91 dB and 4.01 dB, repectively. Forin vivoanimal experiment , the SNR and CNR were 12.29 dB and 6.06 dB. In addition, single microvessel of 24μm and two microvessels separated by 46μm could be clearly displayed. Most importantly,, the CS-Net denoising speeds forin vitroandin vivoexperiments were 0.041 s frame-1and 0.062 s frame-1, respectively.Significance.DL denoising based on CS-Net can improve the resolution of SR-US as well as reducing denoising time, thereby making further contributions to the clinical real-time imaging of ULM.

An improved Fourier Ptychography algorithm for ultrasonic array imaging

Inspired by the optical imaging algorithm, the Fourier Ptychography (FP) algorithm is adopted to improve the resolution of ultrasonic array imaging. In the FP algorithm, the steady-state spectrum is utilized to recover the high-resolution ultrasonic images. Meanwhile, the parameters of FP algorithm are empirical, which can affect the imaging quality of ultrasonic array. Then the particle swarm optimization (PSO) algorithm is used to optimize the parameters of FP algorithm to further improve the imaging quality of ultrasonic array. The tungsten imaging experiments and pig eye imaging experiments are conducted to demonstrate the feasibility and effectiveness of the developed algorithm. In addition, the proposed algorithm and the coherent wave superposition (CWS) algorithm are both based on single plane wave (SPW) algorithms and they are then compared. The results show that the CWS algorithm and FP algorithm have good longitudinal and lateral resolutions, respectively. The particle swarm optimization-based FP (PSOFP) imaging algorithm has both excellent lateral and longitudinal resolutions. The average lateral resolution of PSOFP imaging algorithm is improved by 34.47% compared with CWS imaging algorithm in the tungsten wires experiments, and the lateral boundary structure width of the lens is improved by 49.48% in the pig eye experiments. The proposed algorithm can effectively improve the ultrasonic imaging quality for medical application.

Assessment of Takayasu's arteritis activity by ultrasound localization microscopy

BACKGROUND

Ultrasound localization microscopy (ULM) based on ultrafast ultrasound imaging of circulating microbubbles (MB) can image microvascular blood flows in vivo up to the micron scale. Takayasu arteritis (TA) has an increased vascularisation of the thickened arterial wall when active. We aimed to perform vasa vasorum ULM of the carotid wall and demonstrate that ULM can provide imaging markers to assess the TA activity.

METHODS

Patients with TA were consecutively included with assessment of activity by the National Institute of Health criteria: 5 had active TA (median age 35.8 [24.5-46.0] years) and 11 had quiescent TA (37.2 [31.7-47.3] years). ULM was performed using a 6.4 MHz probe and a dedicated imaging sequence (plane waves with 8 angles, frame rate 500 Hz), coupled with the intravenous injection of MB. Individual MB were localised at a subwavelength scale then tracked, allowing the reconstruction of the vasa vasorum flow anatomy and velocity.

FINDINGS

ULM allowed to show microvessels and to measure their flow velocity within the arterial wall. The number of MB detected per second in the wall was 121 [80-146] in active cases vs. 10 [6-15] in quiescent cases (p = 0.0005), with a mean velocity of 40.5 [39.0-42.9] mm.s^-1 in active cases.

INTERPRETATION

ULM allows visualisation of microvessels within the thickened carotid wall in TA, with significantly greater MB density in active cases. ULM provides a precise visualisation in vivo of the vasa vasorum and gives access to the arterial wall vascularisation quantification.

FUNDING

French Society of Cardiology. ART (Technological Research Accelerator) biomedical ultrasound program of INSERM, France.

Sonodynamic Therapy With Concentric Ultrasound Imaging Array for Precision Theranostics for Atherosclerotic Plaque

Atherosclerotic cardiovascular disease is a major cause of human disability and mortality. Our previous study demonstrated the safety and efficacy of sonodynamic therapy (SDT) on atherosclerotic plaques. However, traditional single-element therapeutic transducer has single acoustic field, and positioning therapeutic and imaging transducers in the same position is difficult during ultrasound imaging-guided SDT. Continuously changing the position of transducers to intervene lesions in different positions is required, increasing the difficulty of treatment. Thus, an SDT device with precise theranostics is required. Therefore, we designed and fabricated a "concentric ultrasound transducer for theranostics" (CUST-T), comprising a central 8-MHz linear array transducer for ultrasound imaging, and a peripheral 1-MHz hollow two-dimensional (2-D) planar array transducer for generating phased-array focused ultrasound (PAFUS). The CUST-T exhibited high imaging resolution at a distance of up to 20 mm from the transducer and could generate a personalized complex PAFUS acoustic field to match various lesions. In vitro biomedical results showed that PAFUS-SDT induced RAW264.7-derived foam cell apoptosis leading to a targeting field apoptotic rate 4.36-6.24 times that of the nontargeting field and the significant apoptotic region was consistent with the PAFUS acoustic field. In vivo, PAFUS-SDT guided by ultrasound imaging significantly increased the lumen area ( ) and collagen level ( ), whereas the wall thickness ( ) and lipid content ( ) of rabbit femoral artery were reduced. In conclusion, CUST-T provided image guidance sufficient for accurate SDT for atherosclerotic plaques in peripheral arteries and could be applied in clinical practice.