It has been shown that within the range of acoustic pressures used in ultrasound imaging, waveforms are distorted during propagation in tissue due to the physically nonlinear behavior of the tissue. This distortion leads to changes in the spectrum of the received ultrasound echoes, causing the transfer of signal energy from the fundamental frequency to higher harmonics. Interestingly, adipose tissue exhibits up to 50 % stronger nonlinear behavior compared to other soft tissues. The tissue nonlinearity parameter B/A is typically measured ex vivo using an ultrasound method in transmission mode, which requires extensive receiving systems. Currently, there is no improved ultrasound method for measuring the B/A nonlinearity parameter in vivo, which could be used in assessing the degree of fatty liver disease. We propose a new, simple approach to estimating nonlinear tissue properties. The proposed method involves transmitting ultrasound waves at significantly different acoustic pressures, recording echoes only in the fundamental frequency band at various depths, and introducing a nonlinearity index (NLI) based on specific echo amplitude ratios. The NLI at a given depth is calculated using the ratio of two dimensionless parameters. The first parameter is a predetermined constant obtained by dividing the total echo values from transmitting a signal at higher sound pressure by those from a signal at lower sound pressure, summed over a small tissue sample volume located near the transducer. The second parameter is calculated at a fixed distance from the transducer, determined by dividing the total echo values from transmitting a signal at higher sound pressure by those from a signal at lower pressure, summed over a small tissue volume of the tissue at that distance from the transducer. The reliability of the proposed measurements for assessing tissue nonlinearity has been substantiated through experimental confirmation of the existing correlations between the values of NLI and B/A in water, sunflower oil, and animal liver tissue samples with oil-enriched regions. The NLI was more than 15 % higher in sunflower oil than in water. The NLI in bovine liver sample below the area with injected oil (mimicking “steatosis”) was more than 35 % higher than in regions without oil. This method represents a promising modality for the nonlinear characterization of tissue regions in vivo, particularly for diagnosing fatty liver disease.
Fast and high-quality ultrasound imaging allows to increase the effectiveness of detecting tissue changes at the initial stage of disease. The aim of the study was to assess the quality of ultrasound imaging using mutually orthogonal, complementary Golay coded sequences (MOCGCS). Two 16-bits MOCGCS sets were implemented in the Verasonics Vantage™ scanner. Echoes from a perfect reflector, a custom-made nylon wire phantom, a tissue-mimicking phantom, and in-vivo scans of abdominal aorta and common carotid artery were recorded. Three parameters of the detected MOCGCS echoes: signal-to-noise ratio (SNR), side-lobe level (SLL), and axial resolution were evaluated and compared to the same parameters of the echoes recorded using standard complementary Golay sequences (CGS) and a short, one sine cycle pulse. The results revealed that MOCGCS transmission maintained comparable echo quality metrics (SNR, SLL, and axial resolution) compared to CGS and short pulses. Notably, both MOCGCS and CGS offered similar SNR improvements (5 dB–9 dB) in comparison to the short pulse for wires placed at depths up to 8 cm. Analysis of axial resolution, estimated at the full width at half maximum level, revealed near-identical values for all transmitted signals (0.17 μs for MOCGCS, 0.16 μs for CGS, and 0.18 μs for short pulse). MOCGCS implementation in ultrasound imaging offers the potential to significantly reduce image reconstruction time while maintaining image quality comparable to CGS sequences. In the experimental study we have shown that MOCGCS offers advantages over conventional CGS by enabling two times faster data acquisition and image reconstruction without compromising image quality.
Portable, hand-held ultrasound devices capable of 3D imaging in real time are the next generation of the medical imaging apparatus adapted not only for professional medical stuff but for a wide group of less advanced users. Limited power supply capacity and the relatively small number of channels used for the ultrasound data acquisition are the most important limitations that should be taken into account when designing such devices and when developing the corresponding image reconstruction algorithms. The aim of this study was to develop a new 3D ultrasound imaging method which would take into account the above-mentioned features of the new generation of ultrasonic devices – low-cost portable general access scanners. It was based on the synthetic transmit aperture (STA) method combined with the Fourier spectrum domain (SD) acoustic data processing. The STA using a limited number of elements in transmit and receive modes for ultrasound data acquisition allowed both aforementioned constraints to be obeyed simultaneously. Moreover, the computational speed of the fast Fourier transform (FFT) algorithm utilized for the ultrasound image synthesis in the spectrum domain makes the proposed method to be more competitive compared to the conventional time domain (TD) STA method based on the delay-and-sum (DAS) technique, especially in the case of 3D imaging in real time mode. Performance of the proposed method was verified using numerical 3D acoustic data simulated in the Field II program for MATLAB and using experimental data from the custom design 3D scattering phantom collected by means of the Verasonics Vantage 256™ research ultrasound system equipped with the dedicated 1024-element 2D matrix transducer. The method proposed in this paper was about 80 times faster than its counterpart based on the time domain synthetic transmit aperture (TD-STA) approach in the numerical example of a single 3D ultrasound image synthesized from 4 partial images each containing 64 × 64 × 512 pixels. It was also shown that the acceleration of the image reconstruction was achieved at the cost of a slight deterioration in the image quality assessed by the contrast and contrast-to-noise ratio (CNR).
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