The introduction of air bubbles into the systemic circulation can result in significant morbidity. Real-time monitoring of continuous heart sound in patients detected by precordial Doppler ultrasound is, thus, vital for early detection of venous air embolism (VAE) during surgery. In this study, the multiscale feature of wavelet transforms (WT's) is exploited to examine the embolic Doppler heart sound (DHS) during intravenous air injections in dogs. As both humans and dogs share similar physiological conditions, our methods and results for dogs are expected to be applicable to humans. The WT of DHS at scale 2j (j = 1, 2) selectively magnified the power of embolic, but not the normal, heart sound. Statistically, the enhanced embolic power was found to be sensitive (P < 0.01 at 0.01 ml of injected air) and correlated significantly (P < 0.0005, r = 0.83) with the volume of injected air from 0.01 to 0.10 ml. A fast detection algorithm of O(N) complexity with unit complexity constant for VAE was developed (processing speed = 8 ms per heartbeat), which confirmed the feasibility of real-time processing for both humans and dogs.
A fast detection algorithm for venous air embolism (VAE) was developed and implemented as a real-time monitor for detecting embolic heart sound and estimating embolic air volume. Its performance was evaluated under bolus injection of sub-clinical (0.01 to 0.80 ml) and continuous infusion of clinically significant (0.80 to 9.60 ml) air volumes in anaesthetized dogs. The clinically significant air emboli could be estimated based on the calibration curve obtained during sub-clinical VAE for a subject. The monitor also kept track of the cumulative embolic air volumes and alerted the anaesthetists once a predefined clinically significant embolic air volume was reached. As both humans and dogs share similar physiological conditions, our monitor for dogs are expected to be applicable to humans.
The real-time wavelet analysis of the heart sound detected by precordial Doppler ultrasound may be useful in estimating larger volumes of air emboli based on previous injections of small volumes of air in anesthetized dogs.
The wavelet analysis of the Doppler heart sound detected under controlled venous air embolism at sub-clinically and clinically significant volumes was studied in anaesthetized dogs. Signal processing with wavelet enhances the power of embolic signal and facilitates the simple detection and extraction of embolic heart beats by thresholding. The cumulative power of the extracted embolic heart beats is found to be linearly related to the volume of embolic air on the log-log scale, suggesting that it is feasible to estimate clinically significant volume of embolic air in human subjects by linearly extrapolating from sub-clinical embolic volumes.
The Doppler heart sound signals detected by the precordial Doppler ultrasound method under simulated sub-clinical and clinically significant venous air embolism were studied in anesthetized dogs. Signal processing using wavelet transform enhanced the contrast of embolic to normal signal, facilitating automatic detection and extraction of embolic signal simply by thresholding. Linear relationship of good correlation coefficient was obtained in log-log scale between the subclinical volume of injected air and the corresponding embolic signal power in all dogs. The calibration curve was found to be good estimate of the volume of embolic air during simulated clinically significant venous air embolism. Hence, we overcame the need of constant human attention for detecting venous air embolism and the lack of quantitative information on the volume of embolic air in the traditional precordial Doppler ultrasound method by the present approach.
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