RF signals provide additional information on embolic events recorded during TCD monitoring

An automated microemboli detection and classification system using backscatter RF signals and differential evolution

Embolic phenomena, whether air or particulate emboli, can induce immediate damages like heart attack or ischemic stroke. Embolus composition (gaseous or particulate matter) is vital in predicting clinically significant complications. Embolus detection using Doppler methods have shown their limits to differentiate solid and gaseous embolus. Radio-frequency (RF) ultrasound signals backscattered by the emboli contain additional information on the embolus in comparison to the traditionally used Doppler signals. Gaseous bubbles show a nonlinear behavior under specific conditions of the ultrasound excitation wave, this nonlinear behavior is exploited to differentiate solid from gaseous microemboli. In order to verify the usefulness of RF ultrasound signal processing in the detection and classification of microemboli, an in vitro set-up is developed. Sonovue micro bubbles are exploited to mimic the acoustic behavior of gaseous emboli. They are injected at two different concentrations (0.025 and 0.05 µl/ml) in a nonrecirculating flow phantom containing a tube of 0.8 mm in diameter. The tissue mimicking material surrounding the tube is chosen to imitate the acoustic behavior of solid emboli. Both gaseous and solid emboli are imaged using an Anthares ultrasound scanner with a probe emitting at a transmit frequency of 1.82 MHz and at two mechanical indices (MI) 0.2 and 0.6. We propose in this experimental study to exploit discrete wavelet transform and a dimensionality reduction algorithm based on differential evolution technique in the analysis and the characterization of the backscattered RF ultrasound signals from the emboli. Several features are evaluated from the detail coefficients. It should be noted that the features used in this study are the same used in the paper by Aydin et al. These all features are used as inputs to the classification models without using feature selection method. Then we perform feature selection using differential evolution algorithm with support vector machines classifier. The experimental results show clearly that our proposed method achieves better average classification rates compared to the results obtained in a previous study using also the same backscatter RF signals.

Optoelectronic system for the determination of blood volume in pneumatic heart assist devices

BACKGROUND

The following article describes the concept of optical measurement of blood volume in ventricular assist devices (VAD's) of the pulsatile type. The paper presents the current state of art in blood volume measurements of such devices and introduces a newly developed solution in the optic domain. The objective of the research is to overcome the disadvantages of the previously developed acoustic method-the requirement of additional sensor chamber.

METHODS

The idea of a compact measurement system has been introduced, followed by laboratory measurements. Static tests of the system have been presented, followed by dynamic measurements on a physical model of the human ventricular system. The results involving the measurements of blood chamber volume acquired by means of an optical system have been compared with the results acquired by means of the Transonic T410 ultrasound flow rate sensor (11PLX transducer, uncertainty ±5 %).

RESULTS

Preliminary dynamic measurements conducted on the physical model of the human cardiovascular system show that the proposed optical measurement system may be used to measure the transient blood chamber volumes of pulsatile VAD's with the uncertainties (standard mean deviation) lower than 10 %.

CONCLUSIONS

The results show that the noninvasive measurements of the temporary blood chamber volume in the POLVAD prosthesis with the use of the developed optical system allows us to carry out accurate static and dynamic measurements.

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.

Quantification of embolic showers using radio-frequency based TCD analysis

During cardiac surgery and cardiology interventions, microemboli may be generated and disperse in the systemic circulation. The amount of microemboli that ends up in cerebral blood vessels is associated with postoperative neurologic complications. During cardiac surgery a large amount of cerebral microemboli can occur at once and create so-called "cerebral embolic showers." To correlate postoperative neurologic outcome to cerebral embolic load, a quantitative evaluation of these embolic showers is necessary. The standard monitoring technology to visualize cerebral microemboli is transcranial Doppler (TCD). Although the conventional TCD systems are equipped with software claiming to detect microembolic signals, none of the existing TCD systems is capable of an accurate estimation of the number of cerebral microemboli in embolic showers. In this study, an algorithm with a high temporal resolution, based on the radiofrequency (RF) signal of a TCD system, has been designed to quantify these showers. Evaluation by three independent observers of a training set demonstrates that the proposed method has a sensitivity of at least one order of magnitude better than the automatic detection algorithm on the existing Doppler device used. RF-based emboli detection can possibly become a standard addition to conventional Doppler methods, considering that accurate estimation of the embolic load supports quantification of neurologic risk during various surgical procedures.

Coded excitation in TCD ultrasound systems to improve axial resolution

The radiofrequency (RF) signal from a transcranial Doppler (TCD) ultrasound system allows us to track the motion of an embolus in a 2-D space of time and depth. The technique is limited by the narrow bandwidth (long duration) of the transmitted pulse because this provides poor axial resolution. This study aimed to assess whether implementing coded excitation and pulse compression in a TCD system would be a feasible means of increasing the bandwidth and hence improving the axial resolution, without the need for reducing the pulse length and increasing peak power levels. Embolic signals were collected in vitro from a flow phantom using a TCD system, which alternately transmitted coded and noncoded pulses. This allowed the same event to be investigated using the two different types of processing. Quantitative and qualitative measures were used to compare the two processing methods. The in vitro results were promising. They showed that the axial resolution could be improved, on average, by a factor of 6.6, using a pulse length of 13 micros and a chirp bandwidth of 0.8 MHz. This was reduced to a factor of 6 when a temporal bone sample was placed between the transducer and the flow phantom. Qualitatively the journey of an embolus was easier to track using the pulse compressed signal. Sonograms could be generated from smaller receive gates using the pulse compressed signal while still achieving an adequate signal-to-noise ratio. We found that it is both feasible and beneficial to implement coded excitation and pulse compression in a TCD system.

Automatic detection of emboli in the TCD RF signal using principal component analysis

The transcranial Doppler (TCD) radio-frequency (RF) signal can provide additional information on events recorded during ultrasonic monitoring. Embolic signals appear as uniform and predictable shapes within the RF signal, enabling pattern recognition and image processing techniques to be used for their automated detection. This paper uses principal component analysis (PCA) to characterise the typical variation in embolic signal shape, within the RF signal, using training sets of in vitro and in vivo data. PCA techniques are then utilised to discriminate between previously unseen embolic and artifact signals. Although the results of this study show that the algorithms described in this paper do not yet have the accuracy required for their use in a clinical setting, it does demonstrate that this novel technique has the potential to be developed further.