Notes

Venous thromboembolism threat stratification throughout injury while using Caprini chance evaluation design.
Large field-of-view acoustic field simulations were carried out to investigate potential grating lobe formation. The focal beam size obtained when targeting the array's geometric focus was [Formula see text] mm in water. The array can steer the FUS beam electronically over cylindrical volumes of 4.5 mm in diameter and 6 mm in height without introducing grating lobes. Insertion of a rat skullcap resulted in substantial distortion of the acoustic field ( [Formula see text]% [Formula see text]); however, phase corrections restored partial focal quality ( [Formula see text]% [Formula see text]). Using phase corrections, the array is capable of generating a trans-rat skull peak negative focal pressure of up to ~2.0 MPa, which is sufficient for microbubble-mediated blood-brain barrier permeabilization at this frequency.Speckle tracking using optimum comparison frames (STO) is proposed to improve the blood flow velocity profile (BFVP) estimation based on ultrafast ultrasound with coherent plane-wave compounding. The optimum comparison frames are as far as possible from the reference frame image while possessing a speckle correlation above a given threshold. The correlation thresholds for different kernel sizes are determined via an experiment based on a vascular-mimicking phantom. In in vitro experiments with different peak velocities of the flow ranging from 0.38 to 1.18 m/s, the proposed STO method with three kernel sizes ( 0.46 × 0.46 , 0.31 × 0.69 , and 0.92 × 0.92 mm2) is used for the BFVP estimations. #link# The normalized root mean square errors (NRMSEs) between the estimated and theoretical BFVPs are calculated and compared with the results based on the speckle tracking using adjacent-frame images. For the three kernel sizes, the mean relative decrements in the STO-based NRMSEs are 46.6%, 44.7%, and 52.9%, and the standard deviations are 36.8%, 37.6%, and 35.9%, respectively. link2 The STO method is also validated by in vivo experiments using rabbit iliac arteries with contrast agents. With parabolic curves fitting to the mean velocity estimates, the average relative increments for the STO-based R2 (coefficients of determination) are 7.22% and 6.25% for kernel sizes of 0.46 × 0.46 and 0.31 × 0.69 mm2, respectively. In conclusion, the STO method improves the BFVP measurement accuracy, whereby accurate diagnosis information can be acquired for clinical applications.An inexpensive, accurate focused ultrasound stereotactic targeting method guided by pretreatment magnetic resonance imaging (MRI) images for murine brain models is presented. link3 An uncertainty of each sub-component of the stereotactic system was analyzed. The entire system was calibrated using clot phantoms. The targeting accuracy of the system was demonstrated with an in vivo mouse glioblastoma (GBM) model. The accuracy was quantified by the absolute distance difference between the prescribed and ablated points visible on the pre treatment and posttreatment MR images, respectively. A precalibration phantom study ( N = 6 ) resulted in an error of 0.32 ± 0.31, 0.72 ± 0.16, and 1.06 ± 0.38 mm in axial, lateral, and elevational axes, respectively. A postcalibration phantom study ( N = 8 ) demonstrated a residual error of 0.09 ± 0.01, 0.15 ± 0.09, and 0.47 ± 0.18 mm in axial, lateral, and elevational axes, respectively. The calibrated system showed significantly reduced ( ) error of 0.20 ± 0.21, 0.34 ± 0.24, and 0.28 ± 0.21 mm in axial, lateral, and elevational axes, respectively, in the in vivo GBM tumor-bearing mice ( N = 10 ).The application of ultrasound imaging to the diagnosis of lung diseases is nowadays receiving growing interest. However, lung ultrasound (LUS) is mainly limited to the analysis of imaging artifacts, such as B-lines, which correlate with a wide variety of diseases. Therefore, the results of LUS investigations remain qualitative and subjective, and specificity is obviously suboptimal. Focusing on the development of a quantitative method dedicated to the lung, in this work, we present the first clinical results obtained with quantitative LUS spectroscopy when applied to the differentiation of pulmonary fibrosis. A previously developed specific multifrequency ultrasound imaging technique was utilized to acquire ultrasound images from 26 selected patients. The multifrequency imaging technique was implemented on the ULtrasound Advanced Open Platform (ULA-OP) platform and an LA533 (Esaote, Florence, Italy) linear-array probe was utilized. RF data obtained at different imaging frequencies (3, 4, 5, and 6 MHz) were acquired and processed in order to characterize B-lines based on their frequency content. In particular, B-line native frequencies (the frequency at which a B-line exhibits the highest intensity) and bandwidth (the range of frequencies over which a B-line shows intensities within -6 dB from its highest intensity), as well as B-line intensity, were analyzed. The results show how the analysis of these features allows (in this group of patients) the differentiation of fibrosis with a sensitivity and specificity equal to 92% and 92%, respectively. These promising results strongly motivate toward the extension of the clinical study, aiming at analyzing a larger cohort of patients and including a broader range of pathologies.Clutter produced using bright acoustic sources can obscure weaker acoustic targets, degrading the quality of the image in scenarios with high dynamic ranges. Many adaptive beamformers seek to improve image quality by reducing these sidelobe artifacts, generating a boost in contrast ratio or contrast-to-noise ratio. However, some of these beamformers inadvertently introduce a dark region artifact in place of the strong clutter, a situation that occurs when both clutter and the underlying signal of interest are removed. We introduce the iterative aperture domain model image reconstruction (iADMIRE) method that is designed to reduce clutter while preserving the underlying signal. We compare the contrast ratio dynamic range (CRDR) of iADMIRE to several other adaptive beamformers plus delay-and-sum (DAS) to quantify the accuracy and reliability of the reported measured contrast for each beamformer over a wide range of contrast levels. We also compare all beamformers in the presence of bright targets ranging from 40 to 120 dB to observe the presence of sidelobes. In cases with no added reverberation clutter, iADMIRE had a CRDR of 75.6 dB when compared with the next best method DAS with 60.8 dB. iADMIRE also demonstrated the best performance for levels of reverberation clutter up to 0-dB signal-to-clutter ratio. Finally, iADMIRE restored underlying speckle signal in dark artifact regions while suppressing sidelobes in bright target cases up to 100 dB.For oil and gas seismic exploration, rock velocities are essential parameters to tease out reservoir properties from seismic data. The ultrasonic pulse transmission (UPT) method has been a gold standard to estimate reservoir rock velocities in the laboratory. Regarding AP20187 price , accurate determination of the travel time of waves plays a significant role in robustly measuring rock velocities. One of the most conventional ways to obtain the travel time is through the arrival picking. However, unclear noise virtually exists preceding the arrival of S-wave interfering with this arrival picking, which, sometimes, can cause enormous errors to measured S-wave velocity. Herein, we develop a 2-D, three-component (2D-3C) finite-element modeling (FEM) algorithm aiming to interpret the noise by combining with UPT measurements. The proposed 2D-3C FEM not only can efficiently compute ultrasonic wavefield radiated by circular P- or S-wave transducers but also able to obtain synthetic waveforms in the testing of S-wave velocity where polarization directions of S-wave transducers are arranged as nonparallel. To analyze the simulated ultrasonic waveforms, we introduce frequently-used concepts of edge and direct plane waves to build elastodynamic models of the ultrasonic wavefield. Then, we compare numerical results with experimental measurements. Our 2D-3C FEM results show good agreement with experimental waveforms both in P- and S-wave velocity testings. Whereafter, we pinpoint constitutions of the noise preceding the arrival of S-wave. Comparison of numerical and experimental waveforms suggests that the edge P-wave with its reflected and converted modes partially contributes to this noise, while the rest part of the noise may stem from the effects of the compressional dipole, the couplant smeared between a transducer and a sample, and inherently parasitic longitudinal vibrations of S-wave transducers. The interpretations on this noise have the potential to benefit future design of more effective S-wave transducers.Doppler ultrasound technology is widespread in clinical applications and is principally used for blood flow measurements in the heart, arteries, and veins. A commonly extracted parameter is the maximum velocity envelope. However, current methods of extracting it cannot produce stable envelopes in high noise conditions. This can limit clinical and research applications using the technology. In this article, a new method of automatic envelope estimation is presented. The method can handle challenging signals with high levels of noise and variable envelope shapes. Envelopes are extracted from a Doppler spectrogram image generated directly from the Doppler audio signal, making it less device-dependent than existing image-processing methods. The method's performance is assessed using simulated pulsatile flow, a flow phantom, and in vivo ascending aortic flow measurements and is compared with three state-of-the-art methods. The proposed method is the most accurate in noisy conditions, achieving, on average, for phantom data with signal-to-noise ratios (SNRs) below 10 dB, bias and standard deviation of 0.7% and 3.3% lower than the next-best performing method. In addition, a new method for beat segmentation is proposed. When combined, the two proposed methods exhibited the best performance using in vivo data, producing the least number of incorrectly segmented beats and 8.2% more correctly segmented beats than the next best performing method. The ability of the proposed methods to reliably extract timing indices for cardiac cycles across a range of signal quality is of particular significance for research and monitoring applications.Ultrafast power Doppler imaging based on coherent compounding (UPDI-CC) has become a promising technique for microvascular imaging due to its high sensitivity to slow blood flows. However, since this method utilizes a limited number of plane-wave or diverging-wave transmissions for high-frame-rate imaging, it suffers from degraded image quality because of the low contrast resolution. In this article, an ultrafast power Doppler imaging method based on a nonlinear compounding framework, called frame-multiply-and-sum (UPDI-FMAS), is proposed to improve contrast resolution. In UPDI-FMAS, unlike conventional channel-domain delay-multiply-and-sum (DMAS) beamforming, the signal coherence is estimated based on autocorrelation function over plane-wave angle frames. To avoid phase distortion of blood flow signals during the autocorrelation process, clutter filtering is preferentially applied to individual beamformed plane-wave data set. Therefore, only coherent blood flow signals are emphasized, while incoherent background noise is suppressed.
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