Abstract
This study investigates the dependence of the translational velocity of lipid-coated microbubbles in an ultrasound field on the viscosity of the surrounding Newtonian fluid. Plane burst waves with a center frequency of 7.34 MHz were used to uniformly drive microbubbles with a radius of 1.4 ± 0.3 m (mean ± standard deviation) in a flow channel. Bubbles were detected using the Doppler method using pulse waves with a center frequency of 5.2 MHz, and the velocities of individual bubbles were analyzed by tracking them in consecutive images. Examinations were conducted at various viscosities from 1 to 3 mPa∙s. The experimentally determined velocity–viscosity relationship qualitatively agreed with numerical simulations. This was written as a power-law dependence and used as a calibration curve to evaluate the local viscosity coefficient for the trajectories of individual bubbles. We succeeded in demonstrating viscosity imaging by multiplying the obtained viscosity coefficient with the bubble trajectories, convoluted with the point spread function of ultrasound imaging.
Japanese Journal of Applied Physics 2025年2月14日 査読有り最終著者責任著者
Abstract
We conducted a fundamental study to elucidate the relationship between acoustic and electrical properties in the context of liver steatosis. The speed of sound, attenuation coefficient, conductivity, and relative permittivity were measured in rat livers with varying degrees of fat deposition. Fat deposition result in a decrease in the speed of sound, an increase in the attenuation coefficient, and reductions in conductivity and relative permittivity. However, no linear correlation was observed between these properties and fat content or droplet size individually. However, a notable correlation between changes in acoustic and electrical properties was identified when the structural and organizational effects of fat were considered in combination. Especially, attenuation changes were found to correlate with corresponding changes in electrical properties. These findings underscore the importance of comprehensively considering structural factors, such as fat droplet size and distribution, to better understand the physical mechanisms underlying the relationship between acoustic and electrical properties.
Hemorheological properties, such as erythrocyte aggregation can be assessed by ultrasonic backscatter coefficient analysis. In this study, a data-acquisition sequence with dual-frequency (dual-f) excitation was proposed to expand the ultrasonic frequency bandwidth with high-frame-rate imaging. The approach was experimentally validated using ex vivo porcine blood measurements and in vivo human imaging. The center frequency of the excitation wave was alternated between 7.8 (f1) and 12.5 (f2) MHz in the frequency spectral analysis using the reference phantom method. The frequency spectra revealed that the dual-f sequence achieved a bandwidth of 4.5-15 MHz at -20 dB, almost equivalent to those achieved with conventional single-frequency excitation (5.0-15 MHz) with a short-duration wave at 10 MHz (mono-f) in reference media with the sufficient condition of signal-to-noise ratio. The aggregation and disaggregation states of porcine blood suspended in high-molecular-weight dextran were determined by the isotropic diameter and packing factor using the structure factor size estimator. The discrimination performance of the dual-f approach increased, owing to the broadband frequency responses, in contrast with the limited performance of mono-f due to a low signal-to-noise ratio. This approach incorporating dual-f sequence is beneficial for obtaining robustly frequency spectra of hemorheological properties from in vivo scenarios.
Journal of Medical Ultrasonics 52(1) 5-15 2024年11月23日 査読有り
Abstract
Purpose
Early detection and quantitative evaluation of liver steatosis are crucial. Therefore, this study investigated a method for classifying ultrasound images to fatty liver grades based on echo-envelope statistics (ES) and convolutional neural network (CNN) analyses.
Methods
Three fatty liver grades, i.e., normal, mild, and moderate-to-severe, were defined using the thresholds of the magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF). There were 10 cases of each grade, totaling 30 cases. To visualize the texture information affected by the deposition of fat droplets within the liver, the maps of first- and fourth-order moments and the heat maps formed from both moments were employed as parametric images derived from the ES. Several dozen to hundreds of regions of interest (ROIs) were extracted from the liver region in each parametric image. A total of 7680 ROIs were utilized for the transfer learning of a pretrained VGG-16 and classified using the transfer-learned VGG-16.
Results
The classification accuracies of the ROIs in all types of the parametric images were approximately 46%. The fatty liver grade for each case was determined by hard voting on the classified ROIs within the case. In the case of the fourth-order moment maps, the classification accuracy of the cases through hard voting mostly increased to approximately 63%.
Conclusions
The formation of parametric images derived from the ES and the CNN classification of the parametric images were proposed for the quantitative diagnosis of liver steatosis. In more than 60% of the cases, the fatty liver grade could be estimated solely using ultrasound images.
Jungtaek Choi, Jeffrey A. Ketterling, Jonathan Mamou, Cameron Hoerig, Shinnosuke Hirata, Kenji Yoshida, Tadashi Yamaguchi
Sensors 24(22) 7118-7118 2024年11月5日 査読有り最終著者責任著者
The objective of this work is to address the need for versatile and effective tissue characterization in abdominal ultrasound diagnosis using a simpler system. We evaluated the backscattering coefficient (BSC) of several tissue-mimicking phantoms utilizing three different ultrasonic probes: a single-element transducer, a linear array probe for clinical use, and a laboratory-made annular array probe. The single-element transducer, commonly used in developing fundamental BSC evaluation methods, served as a benchmark. The linear array probe provided a clinical comparison, while the annular array probe was tested for its potential in high-frequency and high-resolution ultrasonic observations. Our findings demonstrate that the annular array probe meets clinical demands by providing accurate BSC measurements, showcasing its capability for high-frequency and high-resolution imaging with a simpler, more versatile system.
PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS) 2020年
Elastography is a non-invasive technique for quantitatively measuring tissue viscoelasticity. To calibrate the elastography system or to evaluate bias and variance between several different elastography systems, a standardized viscoelastic phantom is needed. We have developed a viscoelastic dual-use phantom for ultrasound elastography (USE) and magnetic resonance elastography (MRE) that satisfies the QIBA acoustics specification.
Kazuki Tamura, Jonathan Mamou, Hiroyuki Hachiya, Kenji Yoshida, Tadashi Yamaguchi
PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS) 2020年
Quantitative ultrasound (QUS) methods have been widely used for soft tissue characterization. Spatial resolution (i.e., ultrasound frequency) is an important factor for QUS methods. In our previous study, we proposed double Nakagami distribution (DND) model for the analysis of fatty liver and high frequency ultrasound (HFU) which allows finer-resolution QUS. Healthy liver structure filter (HLSF) classified each ROI based on the DND model parameter distribution which acquired from healthy liver samples. This approach was able to successfully diagnose fatty livers (>20 % steatosis percentage) in a dataset of 12 livers ranging from 0 to 90 % steatosis. This study proposed a compensation method to expand effective depth range of HLSF based on DND model using HFU measurement. Radio-frequency data was experimentally acquired from 12 excised rat livers (three healthy (0 % of hepatocytes contain lipid droplets) and nine fatty (10 to 70 %)). Healthy liver structure filter (HLSF) classified each ROI based on the DND model parameter distribution which acquired from healthy liver samples. The functions of the depth-dependent Nakagami parameters were obtained by fitting the modified Gaussian distribution to the Nakagami parameters obtained from the three normal liver samples. HLSF(x) was constructed using healthy liver datasets from focal depth - 0.5 mm to focal deplth + 3.5 mm in 1 mm interval. The filter applied to estimated DND parameters at the same depth. For comparison, the conventional method used a fixed value of the Nakagami parameter for DND model parameter estimation and HLSF constructed at focal depth. Depth dependent of the Nakagami parameter and HLSF decreased the depth dependency of DND model parameter. AUROC classifying over than 15 % steatosis progress improved the performance at a distance from focal depth of +3.5 mm (0.64 to 0.86). The proposed method expanded reliable QUS (area under the receiver operating characteristic > 0.85) depth range by 250 % against half of depth of field and demonstrate QUS can be used reliably with clinical HFU.