Custom-made flow phantoms for quantitative ultrasound microvessel imaging

Characterization of Blood-Mimicking Fluids for Quantitative Flow Imaging with Ultrasound

OBJECTIVE

This study aimed at characterizing blood-mimicking fluids (BMFs), focusing on properties relevant to standardizing quantitative imaging biomarkers in vascular and microvascular ultrasound.

METHODS

Three BMF formulations (BMFs 1-3) were prepared following the International Electrotechnical Commission (IEC)-61685 standard, varying in dynamic viscosity and particle buoyancy. A novel figure of merit (FOM) assessed particle buoyancy over time. Density, dynamic viscosity, speed of sound, attenuation, and backscatter coefficient (BSC) were measured for unfiltered and filtered BMFs and compared to IEC-61685 reference values. BMFs were evaluated using power Doppler and contrast-enhanced ultrasound (CEUS) imaging in a calibrated custom-made microflow phantom at 5 and 20 mm/s, using contrast-to-noise ratio (CNR) as a performance metric.

RESULTS

The FOM accurately tracked particle distribution and enabled obtaining neutrally buoyant BMFs. Filtration significantly impacted BSC (p < 0.05) but did not affect other properties. BMF 2 matched all the IEC-61685 reference values (p > 0.05). BMF 1 exhibited the lowest dynamic viscosity, while BMF 3 had the highest BSC. BMF 2 yielded the highest CNR at 5 mm/s in both imaging modes. At 20 mm/s, BMF 3 yielded the highest CNR in power Doppler imaging, while all BMFs performed similarly in CEUS. BMF 2 provided similar CNRs across flow velocities in both imaging modes.

CONCLUSION

A comprehensive methodology for BMF preparation and characterization was developed, which enabled identifying a formulation that aligned with the IEC-61685 standard. This methodology could establish a foundation for developing reproducible and well-characterized BMFs, facilitating the advance of quantitative flow imaging techniques with ultrasound.

Towards Ultrasound Wearable Technology for Cardiovascular Monitoring: From Device Development to Clinical Validation

The advent of flexible, compact, energy-efficient, robust, and user-friendly wearables has significantly impacted the market growth, with an estimated value of 61.30 billion USD in 2022. Wearable sensors have revolutionized in-home health monitoring by warranting continuous measurements of vital parameters. Ultrasound is used to non-invasively, safely, and continuously record vital parameters. The next generation of smart ultrasonic devices for healthcare integrates microelectronics with flexible, stretchable patches and body-conformable devices. They offer not only wearability, and user comfort, but also higher tracking accuracy of immediate changes of cardiovascular parameters. Moreover, due to the fixed adhesion to the skin, errors derived from probe placement or patient movement are mitigated, even though placement at the correct anatomical location is still critical and requires a user's skill and knowledge. In this review, the steps required to bring wearable ultrasonic systems into the medical market (technologies, device development, signal-processing, in-lab validation, and, finally, clinical validation) are discussed. The next generation of vascular ultrasound and its future research directions offer many possibilities for modernizing vascular health assessment and the quality of personalized care for home and clinical monitoring.

Fast inter-frame motion correction in contrast-free ultrasound quantitative microvasculature imaging using deep learning

Contrast-free ultrasound quantitative microvasculature imaging shows promise in several applications, including the assessment of benign and malignant lesions. However, motion represents one of the major challenges in imaging tumor microvessels in organs that are prone to physiological motions. This study aims at addressing potential microvessel image degradation in in vivo human thyroid due to its proximity to carotid artery. The pulsation of the carotid artery induces inter-frame motion that significantly degrades microvasculature images, resulting in diagnostic errors. The main objective of this study is to reduce inter-frame motion artifacts in high-frame-rate ultrasound imaging to achieve a more accurate visualization of tumor microvessel features. We propose a low-complex deep learning network comprising depth-wise separable convolutional layers and hybrid adaptive and squeeze-and-excite attention mechanisms to correct inter-frame motion in high-frame-rate images. Rigorous validation using phantom and in-vivo data with simulated inter-frame motion indicates average improvements of 35% in Pearson correlation coefficients (PCCs) between motion corrected and reference data with respect to that of motion corrupted data. Further, reconstruction of microvasculature images using motion-corrected frames demonstrates PCC improvement from 31 to 35%. Another thorough validation using in-vivo thyroid data with physiological inter-frame motion demonstrates average improvement of 20% in PCC and 40% in mean inter-frame correlation. Finally, comparison with the conventional image registration method indicates the suitability of proposed network for real-time inter-frame motion correction with 5000 times reduction in motion corrected frame prediction latency.

Background Noise Removal in Non-Contrast- Enhanced Ultrasound Microvasculature Imaging Using Combined Collaborative, Morphological, and Vesselness Filtering

Suppression of background noise in clutter filtered contrast-free ultrasound microvasculature images is an important step towards better visualization, accurate segmentation, and subsequent morphological analysis of vascular structures. While different approaches to tackling this problem have been proposed, the use of denoising and vessel-enhancing filters has proven to be a straightforward and effective scheme. In this paper, we propose a multi-stage background noise removal framework, suited to microvasculature images, comprising sequential implementation of three different modes of suppressing noise and intensifying vascular patterns, namely self-similarity based collaborative filtering, mathematical morphology based denoising, and Hessian based vessel enhancement. We evaluate the effects of each filtering stage in the framework using in-vitro phantom data and compare the denoising performance of the framework with a number of existing noise removal approaches, as well as the clutter filtered images in the absence of noise suppression techniques, using in-vivo data from human subjects. The results indicate that the suggested method is, in many cases, capable of complete background noise removal, zeroing out most background regions, and improving signal-to-noise ratio and contrast-to-noise ratio in other regions by tens of dB compared to the other methods.

Development of an Artificial Soft Solid Gel Using Gelatin Material for High-Quality Ultrasound Diagnosis

For ultrasound diagnosis, a gel is applied to the skin. Ultrasound gel serves to block air exposure and match impedance between the skin and the probe, enhancing imaging efficiency. However, if use of the ultrasound gel exceeds a certain period of time, it may dry out and be exposed to air, causing impedance mismatch and reducing imaging resolution. In such cases, the use of a soft, solid gel proves advantageous, as it can be employed for an extended period without succumbing to the drying phenomenon and can be reused after disinfection. Its soft consistency ensures excellent skin adhesion. Our soft solid gel demonstrated approximately 1.2 times better performance than water, silicone, and traditional ultrasound gels. When comparing the dimensions of grayscale, dead zone, vertical, and horizontal regions, the measurements for the traditional ultrasound gel were 93.79 mm, 45.32 mm, 103.13 mm, 83.86 mm, and 83.86 mm, respectively. In contrast, the proposed soft solid gel exhibited dimensions of 105.64 mm, 34.48 mm, 141.1 mm, and 102.8 mm.

Superficial Bifurcated Microflow Phantom for High-Frequency Ultrasound Applications

OBJECTIVE

To evaluate and optimize high-frequency ultrasound (HFUS) imaging techniques that visualize the morphology of microscale vasculatures, many studies have used flow phantoms with straight channels. However, the previous phantoms lack the complexity of microvessels to simulate a realistic vascular environment in a shallow depth. This study was aimed at devising a new protocol for fabrication of a microflow phantom with bifurcated geometry at a superficial region.

METHODS

The proposed protocol involved the following features: (i) a bifurcated flow tract model 300 µm in diameter was debossed on the surface of a tissue slab made of polyvinyl alcohol cryogel, and (ii) a wall-less lumen was created via bonding tissue slabs to put a lid on the debossed flow tract. The structure of the created microflow phantom was evaluated using 2-D and 3-D power Doppler imaging with a 30 MHz HFUS modality.

RESULTS

Ultrasound imaging revealed that the desired flow tract with bifurcation was successfully created in the phantom at a depth of 2-5 mm from the ultrasound probe. The diameters of the flow tract measured in the axial direction were 307 ± 3.7 µm in the parent branch and 232 ± 18.2 and 256 ± 23.3 µm in the two daughter branches, respectively.

CONCLUSION

The experiments revealed that the proposed protocol for creating a microscale intricate flow tract with desired dimensions and depth is valid. This new phantom will facilitate further improvement in the ultrasound technologies for the precise visualization of superficial complex vasculatures such as those in skin layers.

Preliminary Numerical Analysis of Mechanical Wave Propagation Due to Elastograph Measuring Head Application in Non-Invasive Liver Condition Assessment

The authors of this paper focused their attention on developing numerical models of mechanical wave propagation along human tissue as a result of the application of the measuring head of the FibroScan® elastograph. The FibroScan® diagnostic device is used for diagnostic testing of liver fibrosis and steatosis. This examination is carried out using an in vivo method by directly applying the surface of the ultrasonic measuring probe to the patient’s skin at the site of the liver. The authors’ idea is to use this apparatus for non-invasive testing on the liver used for transplantation. In order to do this, the measuring head cap should be modified so that its application to the liver does not result in damage as a result of mechanical wave excitation. The purpose of the manuscript was to build numerical models of the liver and the tissues surrounding the liver. Then, the corresponding numerical simulations were carried out, the results of which corresponded to the mechanical–acoustic properties of the physical models of the tissues. The obtained results were validated on a set of commercial calibrated phantoms. High agreement of the numerical models was obtained.