Sébastien Ménigot

New Estimators and Guidelines for Better Use of Fetal Heart Rate Estimators with Doppler Ultrasound Devices

Characterizing fetal wellbeing with a Doppler ultrasound device requires computation of a score based on fetal parameters. In order to analyze the parameters derived from the fetal heart rate correctly, an accuracy of 0.25 beats per minute is needed. Simultaneously with the lowest false negative rate and the highest sensitivity, we investigated whether various Doppler techniques ensure this accuracy. We found that the accuracy was ensured if directional Doppler signals and autocorrelation estimation were used. Our best estimator provided sensitivity of 95.5%, corresponding to an improvement of 14% compared to the standard estimator.

Optimization of contrast-to-tissue ratio by frequency adaptation in pulse inversion imaging

Contrast imaging has significantly improved clinical diagnosis by increasing the contrast-to-tissue ratio after microbubble injection. Pulse inversion imaging is the most commonly used contrast imaging technique because it greatly increases the contrast-to-tissue ratio by extracting microbubble nonlinearities. The main purpose of our study was to propose an automatic technique providing the best contrast- to-tissue ratio throughout the experiment. For reasons of simplicity, we proposed maximizing the contrast-to-tissue ratio with an appropriate choice of the transmit frequency. The contrast-to-tissue ratio was maximized by a closed-loop system including the pulse inversion technique. An algorithm based on gradient descent provided iterative determination of the optimal transmit frequency. The optimization method converged quickly after six iterations. This optimal control method is easy to implement and it optimizes the contrast-to-tissue ratio by adaptively selecting the transmit frequency.

Contrast improvement in sub- and ultraharmonic ultrasound contrast imaging by combining several hammerstein models.

Sub- and ultraharmonic (SUH) ultrasound contrast imaging is an alternative modality to the second harmonic imaging, since, in specific conditions it could produce high quality echographic images. This modality enables the contrast enhancement of echographic images by using SUH present in the contrast agent response but absent from the nonperfused tissue. For a better access to the components generated by the ultrasound contrast agents, nonlinear techniques based on Hammerstein model are preferred. As the major limitation of Hammerstein model is its capacity of modeling harmonic components only, in this work we propose two methods allowing to model SUH. These new methods use several Hammerstein models to identify contrast agent signals having SUH components and to separate these components from harmonic components. The application of the proposed methods for modeling simulated contrast agent signals shows their efficiency in modeling these signals and in separating SUH components. The achieved gain with respect to the standard Hammerstein model was 26.8 dB and 22.8 dB for the two proposed methods, respectively.

Automatic Optimal Input Command for Linearization of cMUT Output by a Temporal Target

Capacitive micromachined ultrasonic transducers (cMUTs) are a promising alternative to the piezoelectric transducer. However, their native nonlinear behavior is a limitation for their use in medical ultrasound applications. Several methods based on the pre-compensation of a preselected input voltage have been proposed to cancel out the harmonic components generated. Unfortunately, these existing pre-compensation methods have two major flaws. The first is that the pre-compensation procedure is not generally automatic, and the second is that they can only reduce the second harmonic component. This can, therefore, limit their use for some imaging methods, which require a broader bandwidth, e.g., to receive the third harmonic component. In this study, we generalized the presetting methods to reduce all nonlinearities in the cMUT output. Our automatic pre-compensation method can work whatever the excitation waveform. The precompensation method is based on the nonlinear modeling of harmonic components from a Volterra decomposition in which the parameters are evaluated by using a Nelder-Mead algorithm. To validate the feasibility of this approach, the method was applied to an element of a linear array with several types of excitation often encountered in encoded ultrasound imaging. The results showed that the nonlinear components were reduced by up to 21.2 dB.

Improvement of the power response in contrast imaging with transmit frequency optimization

Conventionnal ultrasound contrast imaging systems use a fixed transmit frequency. However it is known that the insonified medium (microbubbles) is time-varying and therefore an adapted time-varying excitation is expected. We suggest an adaptive imaging technique which selects the optimal transmit frequency that maximizes the contrast tissue ratio (CTR). Two algorithms have been proposed to find an US excitation for which the frequency has been optimal with microbubbles. Simulations were carried out for encapsulated microbubbles of 2 ¿m-radius by considering the modified Rayleigh-Plesset equation for a 2.25 MHz transmitted frequency and for various pressure levels (20 kPa up to 420 kPa). In vitro experiments have been carried out using a 2.25 MHz transducer and using a programmable waveform generator. Responses of a 1/2000 blood mimicking fluid-diluted solution of Sonovue¿ were measured by a 3.5 MHz transducer. We show through simulations that our adaptive imaging technique allows to reduce the transmit maximal pressure. As for in vitro experiments the CTR can reach 10 dB. By proposing a close loop system whose frequency adapts itself with the perfused media, throughout the examination, the optimization system adapt itself to the remaining bubbles population thus allowing an increase of the 30% examination duration.

Optimization of Contrast-to-Tissue Ratio by Adaptation of Transmitted Ternary Signal in Ultrasound Pulse Inversion Imaging

Ultrasound contrast imaging has provided more accurate medical diagnoses thanks to the development of innovating modalities like the pulse inversion imaging. However, this latter modality that improves the contrast-to-tissue ratio (CTR) is not optimal, since the frequency is manually chosen jointly with the probe. However, an optimal choice of this command is possible, but it requires precise information about the transducer and the medium which can be experimentally difficult to obtain, even inaccessible. It turns out that the optimization can become more complex by taking into account the kind of generators, since the generators of electrical signals in a conventional ultrasound scanner can be unipolar, bipolar, or tripolar. Our aim was to seek the ternary command which maximized the CTR. By combining a genetic algorithm and a closed loop, the system automatically proposed the optimal ternary command. In simulation, the gain compared with the usual ternary signal could reach about 3.9 dB. Another interesting finding was that, in contrast to what is generally accepted, the optimal command was not a fixed-frequency signal but had harmonic components.

A general framework for modeling sub- and ultraharmonics of ultrasound contrast agent signals with MISO volterra series.

Sub- and ultraharmonics generation by ultrasound contrast agents makes possible sub- and ultraharmonics imaging to enhance the contrast of ultrasound images and overcome the limitations of harmonic imaging. In order to separate different frequency components of ultrasound contrast agents signals, nonlinear models like single-input single-output (SISO) Volterra model are used. One important limitation of this model is its incapacity to model sub- and ultraharmonic components. Many attempts are made to model sub- and ultraharmonics using Volterra model. It led to the design of mutiple-input singe-output (MISO) Volterra model instead of SISO Volterra model. The key idea of MISO modeling was to decompose the input signal of the nonlinear system into periodic subsignals at the subharmonic frequency. In this paper, sub- and ultraharmonics modeling with MISO Volterra model is presented in a general framework that details and explains the required conditions to optimally model sub- and ultraharmonics. A new decomposition of the input signal in periodic orthogonal basis functions is presented. Results of application of different MISO Volterra methods to model simulated ultrasound contrast agents signals show its efficiency in sub- and ultraharmonics imaging.

Detection of Doppler Microembolic Signals Using High Order Statistics

Robust detection of the smallest circulating cerebral microemboli is an efficient way of preventing strokes, which is second cause of mortality worldwide. Transcranial Doppler ultrasound is widely considered the most convenient system for the detection of microemboli. The most common standard detection is achieved through the Doppler energy signal and depends on an empirically set constant threshold. On the other hand, in the past few years, higher order statistics have been an extensive field of research as they represent descriptive statistics that can be used to detect signal outliers. In this study, we propose new types of microembolic detectors based on the windowed calculation of the third moment skewness and fourth moment kurtosis of the energy signal. During energy embolus-free periods the distribution of the energy is not altered and the skewness and kurtosis signals do not exhibit any peak values. In the presence of emboli, the energy distribution is distorted and the skewness and kurtosis signals exhibit peaks, corresponding to the latter emboli. Applied on real signals, the detection of microemboli through the skewness and kurtosis signals outperformed the detection through standard methods. The sensitivities and specificities reached 78% and 91% and 80% and 90% for the skewness and kurtosis detectors, respectively.

Analysis of index modulation of doppler microembolic signals part II: in vitro discrimination.

The purpose of this study was to validate through experiments that frequency modulation (FM) of microembolic signatures was principally due to the radiation force. Several experiments were required to prove that such a frequency modulation originates from microdisplacements induced by the radiation force acting on microbubbles. The first experiment was performed to verify that the diffraction effects due to the presence of a skull did not disturb the acoustic field appreciably and to validate that a radiation force in the brain was sufficient to create a detectable microdisplacement. A second in vitro experiment using a single gate transcranial Doppler (TCD) system was conducted to show discrimination feasibility and to check that microembolic frequency modulation signatures (FMS) and frequency modulation index (FMI) were the same as those observed in vivo and those calculated by simulation. A final in vitro experiment was performed using a multigate multichannel TCD system to confirm the second experiment by directly measuring the microdisplacement induced by the radiation force. A new parameter, to be known as the position modulation index (PMI), is proposed. We showed that the radiation force is sufficient to induce detectable microdisplacements despite the presence of the skull. We also showed that the diffraction effects due to the skull induced a decrease in the ultrasound beam of 7.6 dB. Finally, we showed by using FMI and PMI that it is possible to discriminate gaseous from formed elements (<100 microns) despite the presence of the skull. The discrimination based on the FMI is an off-line technique allowing the analysis of standard TCD recordings. However, discrimination based on the PMI requires recordings obtained exclusively from a multi-gate system.

Analysis of index modulation in microembolic Doppler signals part I: radiation force as a new hypothesis-simulations.

The purpose of this study was to reveal the cause of frequency modulation (FM) present in microembolic Doppler ultrasound signals. This novel explanation should help the development of sensitive microembolus discrimination techniques. We suggest that the frequency modulation detected is caused by the ultrasonic radiation force (URF) acting directly on microemboli. The frequency modulation and the imposed displacement were calculated using a numerical dynamic model. By setting simulation parameters with practical values, it was possible to reproduce most microembolic frequency modulation signatures. The most interesting findings in this study were that: (1) the ultrasound radiation force acting on a gaseous microembolus and its corresponding cumulative displacement were far higher than those obtained for a solid microembolus, and that is encouraging for discrimination purposes; and 2) the calculated frequency modulation indices (FMIs) (≈20 kHz) were in good agreement with literature results. By taking into account the URF, the flow pulsatility, the beam-to-flow angle and both the velocity and the ultrasound beam profiles, it was possible to explain all erratic FM signatures of a microbubble. Finally, by measuring FMI from simulated Doppler signals and by using a constant threshold of 1 KHz, it was possible to discriminate gaseous from solid microemboli with ease.