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.

Custom-made flow phantoms for quantitative ultrasound microvessel imaging

Morphologically realistic flow phantoms are essential experimental tools for quantitative ultrasound-based microvessel imaging. As new quantitative flow imaging tools are developed, the need for more complex vessel-mimicking phantoms is indisputable. In this article, we propose a method for fabricating phantoms with sub-millimeter channels consisting of branches and curvatures in various shapes and sizes suitable for quantifying vessel morphological features. We used different tissue-mimicking materials (TMMs) compatible with ultrasound imaging as the base and metal wires of different diameters (0.15-1.25 mm) to create wall-less channels. The TMMs used are silicone rubber, plastisol, conventional gelatin, and medical gelatin. Mother channels in these phantoms were made in diameters of 1.25 mm or 0.3 mm and the daughter channels in diameters 0.3 mm or 0.15 mm. Bifurcations were created by soldering wires together at branch points. Quantitative parameters were assessed, and accuracy of measurements from the ground truth were determined. Channel diameters were seen to have increased (76-270%) compared to the initial state in the power Doppler images, partly due to blood mimicking fluid pressure. Amongst the microflow phantoms made from the different TMMs, the medical gelatin phantom was selected as the best option for microflow imaging, fulfilling the objective of being easy to fabricate with high transmittance while having a speed of sound and acoustic attenuation close to human tissue. A flow velocity of 0.85 ± 0.01 mm/s, comparable to physiological flow velocity was observed in the smallest diameter phantom (medical gelatin branch) presented here. We successfully constructed more complex geometries, including tortuous and multibranch channels using the medical gelatin as the TMM. We anticipate this will create new avenues for validating quantitative ultrasound microvessel imaging techniques.

Adaptive and Robust Vessel Quantification in Contrast-Free Ultrafast Ultrasound Microvessel Imaging

The morphological features of vasculature in diseased tissue differ significantly from those in normal tissue. Therefore, vasculature quantification is crucial for disease diagnosis and staging. Ultrasound microvessel imaging (UMI) with ultrafast ultrasound acquisitions has been determined to have potential in clinical applications given its superior sensitivity in blood flow detection. However, the presence of spatial-dependent noise caused by a low imaging signal-to-noise ratio and incoherent clutter artifacts caused by moving hyperechoic scatterers degrades the performance of UMI and the reliability of vascular quantification. To tackle these issues, we proposed an improved UMI technique along with an adaptive vessel segmentation workflow for robust vessel identification and vascular feature quantification. A previously proposed sub-aperture cross-correlation technique and a normalized cross-correlation technique were applied to equalize the spatially dependent noise level and suppress the incoherent clutter artifact. A square operator and non-local means filter were then used to better separate the blood flow signal from residual background noise. On the de-noised ultrasound microvessel image, an automatic and adaptive vessel segmentation method was developed based on the different spatial patterns of blood flow signal and background noise. The proposed workflow was applied to a CIRS phantom, to a Doppler flow phantom and to an inflammatory bowel, kidney and liver, to validate its feasibility. Results revealed that automatic adaptive, and robust vessel identification performance can be achieved using the proposed method without the subjectivity caused by radiologists/operators.

Improved Ultrasound Microvessel Imaging Using Deconvolution with Total Variation Regularization

Singular value decomposition-based clutter filters can robustly reject tissue clutter, allowing for detection of slow blood flow in imaging microvasculature. However, to identify microvessels, high ultrasound frequency must be used to increase the spatial resolution at the expense of shorter depth of penetration. Deconvolution using Tikhonov regularization is an imaging processing method widely used to improve spatial resolution. The ringing artifact of Tikhonov regularization, though, can produce image artifacts such as non-existent microvessels, which degrade image quality. Therefore, a deconvolution method using total variation is proposed in this study to improve spatial resolution and mitigate the ringing artifact. Performance of the proposed method was evaluated using chicken embryo brain, ex ovo chicken embryo chorioallantoic membrane and tumor data. Results revealed that the reconstructed power Doppler (PD) images are substantially improved in spatial resolution compared with original PD images: the full width half-maximum (FWHM) of the cross-sectional profile of a microvessel was improved from 132 to 83 µm. Two neighboring microvessels that were 154 µm apart were better separated using the proposed method than conventional PD imaging. Additionally, 223 FWHMs measured from the cross-sectional profiles of 223 vessels were used to determine the improvement in FWHM with the proposed method statistically. The mean ± standard deviation of the FWHM without and with the proposed method was 233.19 ± 85.08 and 172.31 ± 75.11 μm, respectively; the maximum FWHM without and with the proposed method was 693.01 and 668.69 μm; and the minimum FWHM without and with the proposed method was 73.92 and 45.74 μm. There were statistically significant differences between FWHMs with and without the proposed method according to the rank-sum test, p < 0.0001. The contrast-to-noise ratio improved from 1.06 to 4.03 dB with use of the proposed method. We also compared the proposed method with Tikhonov regularization using ex ovo chicken embryo chorioallantoic membrane data. We found that the proposed method outperformed Tikhonov regularization as false microvessels appeared using the Tikhonov regularization but not with the proposed method. These results indicate that the proposed method is capable of providing more robust PD images with higher spatial resolution and higher contrast-to-noise ratio.

Ultrasensitive Ultrasound Microvessel Imaging for Characterizing Benign and Malignant Breast Tumors

Tumor angiogenesis plays an important role during breast tumor growth. However, conventional Doppler has limited sensitivity to detect small blood vessels, resulting in a large overlap of Doppler features between benign and malignant tumors. An ultrasensitive ultrasound microvessel imaging (UMI) technique was recently developed. To evaluate the performance of UMI, we studied 44 patients with 51 breast masses. Tumor pathology served as the gold standard: 28 malignancies and 23 benignities. UMI provided a significant improvement in depicting smaller vessels compared with conventional Doppler. The microvessel morphologies observed on UMI were associated with tumor benign/malignant classification. The diagnostic accuracy of correct Breast Imaging Reporting and Data System (BI-RADS) classification rate (BI-RADS ≥4a: test positive; BI-RADS ≤3: test negative) as a fraction of total mass population was improved by 16% after combining conventional ultrasound with UMI compared with using conventional ultrasound alone. This improvement indicates the potential of UMI in reducing unnecessary benign biopsies and avoiding missed malignant biopsies.