Ann Thorac Surg 2006;81:34-41
© 2006 The Society of Thoracic Surgeons
Original article: Cardiovascular
Intraoperative and Postoperative Evaluation of Cavitation in Mechanical Heart Valve Patients
Tina S. Andersen, MD,
Peter Johansen, PhD,
Bekka O. Christensen, MD,
Peter K. Paulsen, DMSc,
Hans Nygaard, DMSc,
J. Michael Hasenkam, DMSc
*
Department of Cardiothoracic and Vascular Surgery, Aarhus University Hospital, Skejby Sygehus, Aarhus, Denmark
Accepted for publication June 7, 2005.
* Address correspondence to Dr Hasenkam, Department of Cardiothoracic and Vascular Surgery, Aarhus University Hospital, Skejby Sygehus, Brendstrupgaardsvej, 8200 Aarhus N, Denmark (Email: hasenkam{at}ki.au.dk).
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Abstract
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BACKGROUND: Cavitation has been claimed partly responsible for the increased risk of thromboembolic complications, hemolysis, and fatal valve failure seen in mechanical heart valve patients. In vivo studies have investigated cavitation using high-pass filtering of the high-frequency pressure fluctuations with the root mean square values as an assessment of intensities. In vitro studies have shown that this well-known method may not be ideal owing to loss of data as a consequence of filtering, and because it requires a priori knowledge of the valve resonance pattern. Therefore, a new method has been developed, which decomposes the signal into nondeterministic (cavitation) and deterministic (valve resonance) signal components, and hence decreases data loss. This study aimed to evaluate cavitation in patients with mechanical, biological, and native heart valves both intraoperatively and postoperatively using the new method.
METHODS: High-frequency pressure fluctuations were measured by a hydrophone intraoperatively and postoperatively in 14 patients with mechanical valves, 10 patients with normal aortic valves, and 5 patients with bioprosthesis. The total signal energy was evaluated as nondeterministic and deterministic energies.
RESULTS: Nondeterministic energies were verified both intraoperatively and postoperatively in all patients who had a mechanical valve; this finding confirms the cavitation potential of mechanical valves. None of the data recorded in patients with bioprosthetic or native valves contained nondeterministic energy.
CONCLUSIONS: The study confirms the presence of cavitation in mechanical heart valve patients using the nondeterministic energy of high-frequency pressure fluctuations as a quantitative measure of cavitation both intraoperatively and postoperatively.
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Introduction
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Patients with mechanical heart valves have greater risk of thromboembolic complications and anticoagulant-related bleedings than patients with biological counterparts. A possible explanation for this difference could be cavitation. In vitro studies using high-speed visualization techniques in transparent fluids have shown this phenomenon to occur in the vicinity of the mechanical valves, but not in biological valves, or native valves [1, 2]. Cavitation bubble implosion release significant amount of energy that may impinge on the vessel wall [2], nearby blood cells, or the valve material and cause severe damage to these structures [3].
Cavitation could explain the microcracking and erosions found at explanted mechanical heart valves [4], and may also explain some of the clinical reports on valve failure and leaflet escape [5]. This kind of damage is also known from ship propellers, dam outlets, and steel turbines where cavitation is a well-known phenomenon that has significant damage potential [6]. Therefore, cavitation could be a significant contributor to the observed differences in thrombogenicity between mechanical and biological prostheses [7–9]. The destruction of the blood cells mediated by cavitation bubble implosion can activate the coagulation cascade where especially the release of tissue factor has been found to be an important initiator for thromboembolic complications [10].
The visualization methods used in vitro (for example, Graf and associates [2]) are obviously not applicable in vivo. Therefore, Garrison and coworkers [11] developed a method based on the property that noise generation at cavitation implosion can be measured acoustically as high-frequency pressure fluctuations (HFPF). They found that the acoustic signal was composed of the valve-closing sound (less than 35 kHz) and transient pressure spikes (above 35 kHz) that corresponded with cavitation bubble formation and implosion visualized in vitro. Therefore, these investigators [11] high-pass (HP) filtered the signal at 35 kHz to extract the valve-closing sound from the cavitation signal. They also found a correlation between the root mean square of the HP-filtered signal and hemolysis. Their method was subsequently used in other studies (for example, Paulsen and colleagues [7], Andersen and colleagues [8], and Zapanta and associates [12]). However, we recently found that the different valve designs had different closing-sound characteristics [13], which for some valve types showed frequencies above the previously used 35 kHz [11]. Therefore, HP-filtering of the data requires a valve-dependent cut-off frequency to ensure that the closing sound is removed completely and to ensure that some of the cavitation signal is not filtered away. Recently, we developed a signal analysis method [14] to distinguish between the cavitation signal components and the closing sound without using a HP filter. The method is based on the cavitation bubble implosion creating random or nondeterministic pressure fluctuations [15]. By comparing the previously used HP-filtered root mean square values [11] to the nondeterministic energy extraction, we found a high correlation between the two methods. Hence, using the nondeterministic energy extraction method, an alternative method has been developed where bandwidth limitation is avoided and knowledge of the valve-dependant cut-off frequency is not needed. The method has been tested in animal studies [16], which support the use of this method as an alternative to the previously used method.
From a practical clinical point of view, it would be ideal if cavitation could be assessed by noninvasive means. Therefore, we have also developed a new transducer design that enables recordings of HFPF on the precordial skin.
We hypothesize that the nondeterministic energy can be used in humans as a quantitative measure of cavitation both intraoperatively and postoperatively.
The aim of this study was to evaluate cavitation intensities in mechanical heart valve patients intraoperatively and postoperatively using the nondeterministic characteristics of the HFPF generated during valve closure compared with biological and native heart valves.
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Patients and Methods
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The study comprised 29 patients (22 men and 7 women; average age 67 years). The patients were divided into three subgroups: (1) 14 with aortic St. Jude Medical valves; (2) 5 with aortic Carpentier-Edwards pericardial bioprosthesis; and (3) 10 who underwent coronary artery bypass surgery (CABG). Preoperatively all CABG patients had normal aortic and mitral valves verified by echocardiography. Inclusion criteria were age greater than 18 years, patient scheduled for elective heart valve surgery or CABG, and patient giving consent (oral and written). Exclusion criteria were hemodynamic unstability, implantation of composite grafts required, implantation of double valve prostheses, and coronary bypass surgery performed as a beating-heart procedure.
The HFPF was measured intraoperatively and postoperatively using a miniature hydrophone (type 8103; Brüel & Kjær, Nærum, Denmark) with an upper frequency limit of 150 kHz. The hydrophone was connected to a preamplifier (type 2635; Brüel & Kjær) with a built-in HP filter at 20 Hz. Data were stored on a computer equipped with a data acquisition card (AT-MIO16-E2; National Instruments, Austin, Texas) at a sampling rate of 500 kHz. Data acquisition and off-line signal analysis were accomplished using a custom-made program developed in LabVIEW 6.0i (National Instruments). The recorded signals were visualized on-line using an oscilloscope (type PM 3305; Phillips, Einthoven, Holland).
The intraoperative measurements were performed when the patient had been hemodynamically stable for at least 2 minutes after being weaned from cardiopulmonary bypass. The sterilized hydrophone was placed near the aortic annulus at the low aortic–left atrial junction, and data were acquired for approximately 30 seconds, while registering blood pressure, heart rate, cardiac output, blood gases (pO2 and pCO2). Ejection fractions were registered from the preoperatively performed echocardiography.
On the fourth postoperative day, the hydrophone was placed in a custom-made water-filled chamber and placed on the precordium in the left fourth intercostal space close to the sternum. This location has previously been shown to be the optimal position for mechanical aortic heart valve sound recordings [17]. The measurements were performed with the patients in supine position. Arterial blood pressure brachial cuff and pulse were recorded.
As the aim was primarily to reconfirm the findings obtained by Paulsen and colleagues [7] and additionally to investigate whether it was possible to perform noninvasive measurements, a preoperative measurement was not performed.
The study was approved by the local Ethical Committee and complied with the Helsinki II declaration.
Data Analysis
The intraoperative data were analyzed for all 29. Postoperative data were not obtained for all the included patients owing to equipment failure (2 for mechanical and 2 for native valves), and postoperative complications, namely, confusion and intensive care unit admission (2 for mechanical, 1 for bioprosthetic, and 1 for native valves). Therefore, postoperative data were analyzed for only 21 patients (10 mechanical, 4 biological, and 7 native valves). This group comprised 15 men and 6 women (average age 66 years). Thirty seconds of continuous recorded data were analyzed off-line using LabVIEW 6.0i (National Instruments). Cavitation was quantified based on recorded pressure signatures and the method developed by Johansen and associates [14], which entails separation of the HFPF signal into deterministic and nondeterministic components. Motivated by the assumption that the acoustic signal from cavitation is stochastic (random) [15], the nondeterministic component should primarily contain signal originating from cavitation, and the deterministic component originating primarily from the valve-closing sound. The method first calculates the ensemble averaged component in a time domain of 30 consecutive closing sounds. Because each closing sound is within a very short time window, it is necessary to exactly line up the data before averaging. This lining up is done by cross correlating every heart cycle with a chosen template. Using the time variable in the cross correlation enables temporal line up with reference to the chosen template. When the ensemble averaged time domain signal is calculated, the energy density spectrum is deduced to derive the deterministic signal energy, which originates from the valve-closing sound. The next step is calculating the mean energy density spectrum from each single closing event. The energy is calculated in the same way as for the ensemble averaged signal. That leads to the total signal energy, which is the sum of the deterministic and nondeterministic energy. By subtracting the deterministic energy from the total energy, the nondeterministic (approximate cavitation parameter) energy can be deduced.
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Results
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In all the mechanical heart valve measurements, both intraoperative and postoperative HFPF were found. The total energy content in the intraoperatively recorded signal for one mechanical heart valve is shown in Figure 1. It is seen that the signal contains a considerable amount of energy within the hydrophone's frequency range (20 Hz to 150 kHz). The total energy consists of the nondeterministic energy (Fig 2A) and the deterministic energy (Fig 2B). The Figures show that the signal comprise nondeterministic energy in the entire frequency range. The deterministic energy mostly dominates frequencies below 75 kHz with a gradual decrease in upper frequency energy and energies with generally lower amplitude compared with the nondeterministic energy.
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Fig 1. The total energy content in the signal recorded intraoperatively in a mechanical heart valve patient with frequencies (Hz) on the x-axis and signal energy density (Pa2 . s) on the y-axis. The graph on the left shows logarithmic scale and the graph on the right shows linear scale.
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Fig 2. The (A) nondeterministic and (B) deterministic content in the signal recorded intraoperatively in a mechanical heart valve patient with frequencies (Hz) on the x-axis and signal energy density (Pa2 . s) on the y-axis. The graph on the left shows logarithmic scale and the graph on the right shows linear scale.
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In Figure 3, the total energy content for the same mechanical valve is shown postoperatively. Figure 4
shows the nondeterministic (Fig 4A) and the deterministic (Fig 4B) energies contained in the signal. The signal contains a greater amount of nondeterministic than deterministic energy in the high frequencies. The nondeterministic energy representative for cavitation ranges interoperatively (Fig 5) from approximately 345 Pa2 to approximately 16,090 Pa2, with a median value of 6720 Pa2. The postoperative nondeterministic (Fig 5) energy varied between 1.33 Pa2 and 39.3 Pa2, with a median value of 6.22 Pa2. None of the data obtained from bioprosthetic or native valves contained HFPF either intraoperatively or postoperatively. The intraoperative noise floor for the two control groups (Fig 5) was between 0.77 Pa2 and 10.76 Pa2, with a median value of 2.40 Pa2 for bioprosthetic valves; and between 0.76 Pa2 and 6.92 Pa2, with a median value of 2.80 Pa2 for native valves. The postoperative (Fig 5) noise floor was between 0.006 Pa2 and 0.15 Pa2, with a median value of 0.06 Pa2 for bioprosthetic valves; and between 0.004 Pa2 and 0.01 Pa2, with a median value of 0.008 Pa2 for native valves.
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Fig 3. The total energy content in the signal recorded postoperatively in a mechanical heart valve patient with frequencies (Hz) on the x-axis and signal energy density (Pa2 . s) on the y-axis. The graph on the left shows logarithmic scale and the graph on the right shows linear scale.
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Fig 4. The (A) nondeterministic and (B) deterministic content in the signal recorded intraoperatively in a mechanical heart valve patient with frequencies (Hz) on the x-axis and signal energy density (Pa2 . s) on the y-axis. The graph on the left shows logarithmic scale and the graph on the right shows linear scale.
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Fig 5. The nondeterministic energy with intervals for the three groups in a logarithmic scale is shown. (A) Intraoperative measurements, n = 29. (B) Postoperative measurements, n = 21. (E-nondet. = nondeterministic energy; St.J = St. Jude Medical; C-E = Carpentier-Edwards bioprosthesis; Nat = native valves.)
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Hemodynamic parameters (cardiac output, heart rate, pO2, pCO2, blood pressure, and ejection fraction) are shown in Tables 1 and 2. 
No apparent relation was found between nondeterministic energies and cardiac output, heart rate, pO2, pCO2, blood pressure, or ejection fraction; blood pressure and heart rate in the postoperative data collection setting did not show any relation either. Valve sizes were compared against the intraoperative nondeterministic and deterministic values for the mechanical valves, but no clear relation was found.
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Comment
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Thromboembolic complications in mechanical heart valve patients are the most frequent cause of complications for heart valve replacement. Especially young patients with a long life expectancy may face significant additive risk over several years; therefore, cavitation as a potential contributor to thromboembolism should be investigated. Samboe and colleagues [10] showed that thromboembolic complication may be caused by release of tissue factor. Our own studies have supported these findings by demonstrating hypercoagulability caused by cavitation [16]. As cavitation bubble implosion is known to release high energies, it may be assumed that the energies will be able to destroy the blood components and hence activate the coagulation cascade. Therefore, it seems plausible that thromboembolic complications in mechanical heart valve patients can—at least partially—be attributed to cavitation.
Using the deterministic/nondeterministic decomposition method to separate the closing sound from cavitation has the advantage that it does not require valve specific HP filtering, as in the previously used method [11, 13]. Furthermore, there is no bandwidth limitation introduced as a consequence of filtering.
The present study verified that the signal recorded in all mechanical heart valve patients contained nondeterministic energies in the entire frequency range and only deterministic energies in the lower frequency ranges. This finding is in accordance with previous studies where the valve-closing sound has been found to be present in the lower frequencies; therefore, these findings support that the deterministic energies can be used as an expression of the valve-closing sound in vivo, and the nondeterministic energies used for cavitation monitoring. The HP-filtered HFPF and the nondeterministic energy are not a definite proof of cavitation. However, in vitro studies [1] have since demonstrated that root mean square values of HFPF are a good assessment of cavitation intensities assessed by high-speed visualization techniques. They support our assumption that nondeterministic energies are an expression of cavitation.
In Figures 1 and 2, it is seen that the intraoperative measurements appear to pick up signal at higher frequencies than the postoperative measurements (Figs 3 and 4), and the difference between the median values in the two setups indicate a difference in magnitude of the recorded signal. However, it was expected that an attenuation of the higher frequencies would take place in the postoperative situation, as tissue and bone situated between the transducer and the valve entail low-pass filtering of the signal [19–21]. Anyway, this method still seems capable of detecting pressure fluctuations with an acceptable signal-to-noise ratio at frequencies close to 150 kHz in the postoperative measurements. Furthermore, HFPF in the two setups seems to correlate across the three groups of patients investigated, and that may support that it is the same energies we measured intraoperatively as postoperatively.
This study aimed to evaluate a method capable of separating the valve-closing sound from the cavitation signal in HFPF, which as shown in previous studies only is present at mechanical heart valves. When using the method on our control data, it should be observed that the signal comprises no acoustic signal containing the closing sound component originating from a rigid geometrical structure. Therefore, these data cannot be directly compared. Using the method on these data may show a signal with nondeterministic energies due to turbulence and low-frequency vibration in the tissue. Looking at the data obtained from our two control groups, none of the signals contained HFPF; and it is therefore assumed that these valves produce no cavitation or closing sound, which also is in accordance with previous findings in studies with bioprosthetic valves [7, 8].
In Tables 1 and 2, all the measurements registered for all the patients included in the intraoperative group are shown. When comparing valve sizes, no apparent correlation were found, although it must be expected that the larger valves generate more cavitation than the smaller valves as shown in vitro [22–24]. The reason for this discrepancy is most likely that the study material is too small to illustrate this aspect. Likewise, in vitro studies [1, 25, 26] have previously indicated a correlation between closing velocity and cavitation intensity, but no apparent correlation was found in this study. In vitro studies have shown a relation between the ratio of ventricular pressure change to time change (dp/dt) and cavitation, where cavitation intensity increases with dp/dt without any specific cavitation threshold [27]. Experimental animal studies [28] have shown that during exercise, more extensive damage had been found at the explanted valves than in valves not exposed to exercise conditions, so it may be assumed that there is a possibility for higher cavitation intensities in patients during exercise. That might be a particular concern for younger patients with high exercise levels.
With regard to the remaining hemodynamic parameters, no clear relation was found.
Table 1 shows that there is a 4.5 times spread between the patient with the highest nondeterministic energy and the one with the lowest. Since all the patients had the same valve type implanted, it may be assumed that this difference could be attributed to the different amount of cavitation generated. It would have been interesting to be able to evaluate cavitation intensities under different left ventricular pressure dp/dt conditions, but this was not considered feasible either intraoperatively or postoperatively. The method most likely has its strength in monitoring cavitation intensities in the individual patient and not as a comparison between patients.
We have earlier carried out in vitro studies showing that cavitation may generate frequency components above 150 kHz, which is the upper frequency limit of the transducer used in this study [14]. Such high-frequency components could not be detected with the hydrophone used in the present study.
This study only comprised patients who had the St. Jude Medical aortic valves implanted; however, the used methodology could also have been applied to patients implanted with a mechanical heart valve in the mitral position, and a study that examines different types of mechanical heart valves in different positions is needed. Recently, an in vitro study has shown that some valve types are more likely to produce cavitation than other models [14].
Figures 2 and 4 shows that both intraoperative and postoperative measurements contain nondeterministic signal components as an indication of cavitation; and Figure 5 shows the differences between the mechanical, bioprosthetic, and native valves with respect to energy contained in the signal. The low values found in the two control groups express the noise floor. The type of noise observed is primarily noncorrelated, and therefore contributes to the nondeterministic energy. However, the energy in the noise is several orders of magnitude lower than that of the signal of interest.
It is shown (Figs 1 and 2) that the main part of the signal recorded at mechanical heart valves consists of nondeterministic energy. It is also seen that the signal contain both deterministic and nondeterministic energy in most of the frequency range of the hydrophone, suggesting that the two components overlap in frequency range. This finding further supports that parts of the cavitation signal will be lost if a HP filter is used, and parts of the closing sound will be included in the cavitation signal using that method.
The nondeterministic energy can not be used as the irrefutable fingerprint of cavitation, but can be assumed to be a good indicator of cavitation intensities compared with the knowledge achieved from previous studies. Whether the signal contains other components is difficult to say, but factors such as turbulence could be a contributor due to its stochastic nature. Owing to the time window we used and the frequency composition of turbulence (< 1,000 Hz), it is believed that turbulence is an insignificant contributor to bias for these measurements.
It is believed that it is possible to develop this method of noninvasive assessment of cavitation further and thereby create a standardized postoperative setup that can be used for routine investigation of mechanical heart valve patients.
Methods based on detecting and evaluating cavitation using HFPF seem promising, but they still require further investigation.
In summary, high-frequency pressure fluctuations recorded during valve closure comprised nondeterministic energy both intraoperatively and postoperatively in mechanical heart valve patients, but not in patients with bioprosthetic or native valves. This finding indicates that cavitation only occurs at mechanical valves, and therefore contributes to the explanation of the differences in thrombogenicity among mechanical, bioprosthetic, and native heart valves. This study supports that the nondeterministic method can be used as an alternative method in cavitation research both intraoperatively and postoperatively with a minimal loss of information and no need of a priori knowledge of the valve characteristics [18].
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Acknowledgments
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We wish to thank the Danish Heart Foundation (Grant 00-2-3-45A-22853) for financial support. We also thank the surgeons and other personnel at the Department of Cardiothoracic and Vascular Surgery, Skejby Sygehus, for their kind help during our measurements.
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References
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Abstract
Introduction
