Chest ACCP Member Benefits
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Guest Access | Sign In via User Name/Password
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF) Free
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Article Archive
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (9)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kim, D.
Right arrow Articles by Tavel, M. E.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kim, D.
Right arrow Articles by Tavel, M. E.
(Chest. 2003;124:1638-1644.)
© 2003 American College of Chest Physicians

Assessment of Severity of Aortic Stenosis Through Time-Frequency Analysis of Murmur*

Dosik Kim, MD and Morton E. Tavel, MD, FCCP

* From the Department of Internal Medicine, St. Vincent Hospital, Indianapolis, IN.

Correspondence to: Morton Tavel, MD, FCCP, 8333 Naab Rd, Suite 400, Indianapolis, IN 46260; e-mail: Mtavel6986{at}aol.com


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study objective: The accurate and inexpensive noninvasive assessment of the presence and severity of aortic stenosis remains a challenge. In this study, we performed spectral analysis on the murmurs of a group of patients with this disease in order to assess its severity.

Design: An electronic stethoscope was used to generate a spectral analysis of murmurs in patients with aortic stenosis. The durations of the spectra at different frequencies (ie, 200, 250, and 300 Hz) were correlated to the Doppler echocardiogram-derived mean and peak pressure gradients. Heart murmurs from the patients were recorded, and the spectra of the recordings were produced via fast-Fourier transformation. The duration of the spectra above the three given frequencies was then measured.

Patients: Forty-one patients (age range, 45 to 94 years; mean age, 68 years) met the inclusion criteria, which included a minimum ejection fraction of 40% and no other significant systolic murmur or coexistent valve disease.

Results: The peak pressure gradient measured via Doppler echocardiogram ranged from 15.3 to 185 mm Hg with the mean of 63 mm Hg. The duration of the spectra of > 300 Hz correlated best with the peak pressure gradient measured using the Doppler echocardiogram. An exponential regression model was created showing a significant correlation coefficient of r = 0.86 (p < 0.0001).

Conclusions: This study demonstrated a good correlation between the duration of spectra at 300 Hz and the Doppler derived peak pressure gradient. This simple and inexpensive technique may prove to be valuable in the evaluation and monitoring of patients with suspected and proven aortic stenosis.


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Aortic stenosis is a common disease that requires close monitoring of patients’ hemodynamics. Although cardiac catheterization remains the most accurate method of diagnosing and assessing aortic stenosis, its cost and invasiveness make it an inappropriate test for serial monitoring of aortic stenosis severity. Doppler echocardiograms have been shown to accurately assess the severity of stenotic lesions by measuring jet velocities distal to the stenotic valve. However, the use of Doppler echocardiograms is not without problems. They are expensive and require a well-trained technician as well as a trained cardiologist for accurate assessment.1

In the past, investigators have sought to employ other noninvasive techniques to evaluate aortic stenosis.2 3 4 5 6 7 8 9 10 Since a harsh systolic murmur is the mostconstant clinical sign of aortic stenosis, inherent characteristics of the murmur including frequency, pitch, timing, and quality have been studied.11 12 13 A previous study3 that utilized spectral analyses for the assessment of severity has shown that dominant frequencies contained within the heart murmur are related to instantaneous jet velocities distal to the obstruction in stenotic cardiac lesions. Other investigators have used frequency analysis to estimate the severity of aortic stenosis. They have shown that the ratio of the higher frequency predictive area and the lower frequency control area under the frequency analysis curve correlate well with the peak systolic difference of aortic stenosis patients.6 7

These studies, however, require a precise and complicated setup to record high-quality sound. They also require that the filtering effect of the chest wall be minimized beyond what is practical. These difficulties make the methods in earlier studies difficult to reproduce and unsuitable for current practice settings where expedient and accurate results are required.

With advances in technology have come electronic forms of one of the most revered tools of clinicians, the stethoscope. These devices are able to combine ease of use with a seamless integration with computer technology. In this study, we have utilized a simple electronic stethoscope and a computer to generate a spectral display of the murmur. The duration of the murmur spectra then was measured across different frequencies. We sought to correlate the measured duration with our most accurate noninvasive tool, the Doppler echocardiogram, in order to test the hypothesis that the duration of the murmur spectra above a given frequency will correlate with Doppler echocardiogram-derived indexes, the peak and mean transvalvular pressure gradient.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Subject
Forty-one subjects with aortic stenosis were selected using criteria approved by the Institutional Review Board of St. Vincent Hospitals (Indianapolis, IN). Informed consent was obtained from each patient prior to participation. Inclusion criteria included a confirmed diagnosis of aortic stenosis via Doppler echocardiogram (the peak and mean pressure gradients across the stenotic aortic valve were calculated using a modified Bernoulli equation14 15 16 17 ). Integrating the time-velocity area, squaring this value, and then multiplying by four derived the mean gradient. The subjects included no other coexistent valvular disease, no other significant systolic murmur, and a near-normal ejection fraction (ie, > 40%) by echocardiogram performed within 3 months of study entry. Subjects with a history of myocardial infarction or coronary artery disease who met the above criteria were included in the study.

Recording Procedure
A quiet room was prepared for our recordings. We placed patients in the supine position and an initial evaluation was performed using a standard acoustic stethoscope. Then, the electronic stethoscope chest piece was used in the following four positions: right upper sternal border; left upper sternal border; left lower sternal border; and near the fifth intercostal space at the left midclavicular line.

The location of the chest piece was not necessarily determined by precise anatomic landmarks. Instead, traditional auscultation techniques were used to capture the loudest and clearest heart sound possible. The spectral analysis was performed on sounds obtained from a single area in each subject (ie, the location of maximum murmur intensity as assessed by auditory impression). In almost all instances, this area was the right upper sternal border. The bell chest piece was used in all of the recordings. Sounds from each of the four areas were recorded for 10 to 30 s.

Equipment
Recordings were made using an electronic stethoscope (eStation; Toronto, ON, Canada) connected to a portable computer (Dell Computer Corp; Round Rock, TX) with the signal processed through the computer’s sound card.

Spectral Analysis
Recordings were analyzed (Cool Edit 2000; Syntrillium Software Corp; San Jose, CA), and the initial signal was processed (eStation) and routed to the computer, where it was converted into a format compatible with the analysis software. When signal clarity appeared to be suboptimal, a digital filter was used to suppress frequencies of < 150 Hz in order to clarify those at > 200 Hz. The recorded file was viewed in a waveform mode to determine the location of S1 (Fig 1 ). The localization of these sounds was necessary in order to exclude them from the subsequent frequency analysis.



View larger version (87K):
[in this window]
[in a new window]
[Download PPT slide]
  		Figure 1.. An example of a waveform (oscilloscopic) view.

 
All sound then was transformed to a spectral image using a fast Fourier transformation technique (Cool Edit 2000). Once the signal clarity was satisfactory, the spectra were printed (Deskjet 970 color printer; Hewlett-Packard; Palo Alto, CA) for actual measurements. Each spectrum was evaluated, and the duration of the signal at 200, 250, and 300 Hz was measured using a caliper (Fig 2 ). This measurement was compared to the reference time line for conversion into milliseconds.



View larger version (111K):
[in this window]
[in a new window]
[Download PPT slide]
  		Figure 2.. A spectral image of an aortic stenosis murmur. Blue lines indicate the frequency level in Hz (y-axis). The measured distance was compared to the time line in milliseconds (x-axis) in order to determine the actual duration of the murmur at > 300 Hz.

 
Data Analysis
The duration of a spectrum above each of three given frequencies was compared to the peak and mean transvalvular pressure gradient obtained by the Doppler echocardiogram.

Statistical Analysis
The measured duration and the peak and mean transvalvular pressure gradient obtained through Doppler echocardiogram were correlated using an exponential regression model. The regression model expressing the best correlation was obtained through a computer program (Excel; Microsoft; Redmond, WA) that calculates an exponential curve that fits the data and returns an array of values that best describe that curve.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Population
Forty-one subjects (24 men and 17 women; mean age, 68 years; age range, 45 to 94 years) were examined (Table 1 ).


View this table:
[in this window]
[in a new window]

  		Table 1.. Patient Characteristics*

 
Doppler Echocardiogram-Derived Measurements
The peak pressure gradients ranged from 15.3 to 185 mm Hg (mean gradient, 62.97 mm Hg). The mean pressure gradient ranged from 2.4 to 105 mm Hg (mean, 35.4 mm Hg).

Data Correlation and Statistical Analysis
After the recorded murmurs were converted into spectral analytical images, the durations were measured at three different frequencies (200, 250, and 300 Hz). The measured durations were correlated with the peak and mean pressure gradients.

The Doppler echocardiogram-derived peak pressure gradient correlated the best with the following r values: 200 Hz, r = 0.80 (p < 0.001); 250 Hz, r = 0.83 (p < 0.001); and 300 Hz, r = 0.86 (p < 0.001) [Table 2 ]. Figure 3 presents the relationship between the peak pressure gradient and signal duration at 300 Hz.


View this table:
[in this window]
[in a new window]

  		Table 2.. Correlation Coefficient at Different Frequencies*

 


View larger version (27K):
[in this window]
[in a new window]
[Download PPT slide]
  		Figure 3.. Measured time duration at 300 Hz plotted against the Doppler echocardiogram-derived transvalvular peak pressure gradient. The line indicates the exponential regression curve.

 
The Doppler echocardiogram-derived mean pressure gradient also correlated well, although not as strongly as with the peak pressure gradient. The correlation results were as follows: 200 Hz, r = 0.71 (p < 0.001); 250 Hz, r = 0.72 (p < 0.001); and 300 Hz, r = 0.80 (p < 0.001) [Table 2 ].


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Previous studies18 19 have demonstrated that increasing severity of aortic stenosis prolongs the total duration of left ventricular ejection and also causes the systolic murmur to contain a greater proportion of higher frequency component waves. We hypothesized that combining elements of both ejection duration and frequency content may provide an enhanced means with which to assess stenosis severity. Our method extends the findings that have resulted from earlier attempts to quantify relative proportions of higher frequency murmur components6 7 and may prove more convenient to apply. Although appearing to correlate with peak flow velocities, peak frequency content is difficult to assess with current spectral techniques. Moreover, many subjects within this study, especially those with mild stenosis, possessed attenuated spectral patterns of > 300 Hz, which were not amenable to satisfactory analysis.

Our data showed good correlation between the Doppler echocardiogram-derived peak transvalvular pressure gradient and the duration of the murmur spectra at all three frequencies. Peak pressure gradients correlated best with our measured data for several likely reasons. As the transvalvular pressure gradient increases, the time it takes to eject a given volume also increases. This is reflected as the increase in duration of the systolic murmur. Since we measured the duration of the murmur at a given frequency, the relationship between the Doppler echocardiogram-derived transvalvular gradient and the duration of its spectral content is predictable.

Clinicians have long been able to gain an impression of the severity of aortic stenosis simply by judging the auditory duration of a given murmur. Frequency analysis can complement this evaluation, because it quantifies a specific characteristic of the harsh systolic murmur, which is beyond the capability of human hearing. The spectral recording provides a visual display of the duration and frequency at the same time. Of the three frequencies we studied, the measured duration of spectra at 300 Hz had the greatest correlation with the Doppler echocardiogram-measured peak transvalvular gradient. The r value progressively declined as the analyzed frequency reference level became lower. In reviewing the spectral images further, we found that there was less variation between subjects at lower frequency levels. The cause for the apparent reduction of accuracy in this group is uncertain. It may have been partially attributable to difficulty in separating portions of the S1 from the early part of the murmur at lower frequency levels.

The mean transvalvular pressure gradient also correlated best with the measured duration at 300 Hz. However, the overall correlation was not as strong as the correlation with the peak transvalvular pressure gradient.

The high correlation between the measured duration at 300 Hz and the Doppler echocardiogram-derived peak transvalvular pressure gradient should be clinically useful. For example, a physician who sees a patient and discovers a new systolic murmur may use this simple technique to assess initially the presence and severity of aortic stenosis. A patient with known aortic stenosis may be observed periodically by monitoring the change in spectral duration. A significant increase in the duration of the murmur may signal increasing aortic stenosis severity, thus prompting a more thorough investigation. Similarly, since it is known that a significant decrease in left ventricular function results in a reduction of murmur intensity, a drop in murmur duration also may suggest that a further evaluation is needed.

This method employs a simple setup that consists of an electronic stethoscope and a standard desktop or laptop computer, which contains readily available and inexpensive software. In addition to being simple, this method requires little time and expertise and allows for the rapid analysis of murmurs at the recording site. Alternatively, the sounds can be quickly transmitted telephonically to distant sites for analysis. Unlike previous studies, this setup is easily adaptable to the everyday clinical setting. Electronic stethoscopes are relatively inexpensive and widely available, as are computers. The software used to convert the murmur to spectral images and to measure the murmur duration is inexpensive and easily obtained. Furthermore, even though our data collection required a physical link between the electronic stethoscope and the computer, a wireless means of transferring data between the electronic stethoscope and the computer has since become available. It is also worth noting that, during the recording sessions, none of the recordings took longer than approximately 5 min, and no special preparation was needed to obtain useful recordings.

Limitations and Further Studies
Although our data showed a high level of correlation with the Doppler echocardiogram-derived indexes, we found several limitations of our study. The most obvious is that the Doppler echocardiogram, despite being the "gold standard" of noninvasive diagnostic techniques for aortic stenosis, represents a derived estimate of severity. Thus, our technique also possesses the same limitations as those of the Doppler echocardiogram-derived indexes.

In addition, we made no attempts to distinguish between innocent ejection murmurs and those attributable to aortic stenosis. However, our preliminary observations suggest that murmurs of the former group, as in the example of very mild stenosis, demonstrate the absence of sustained high frequencies.20 21

In performing a visual analysis of spectral displays, some difficulty was encountered in locating the end points of the S1. Depending on where one designates the S1, the measured duration of the murmur may be influenced, since the murmur of aortic stenosis in the spectral image begins at or near the terminal section of S1. Therefore, considerable care must be exercised in identifying these points.

We also did not include other patients with significant concomitant valvular disease such as tricuspid or mitral regurgitation. The effects of the murmurs created by other valvular diseases remain to be studied.

The effect of significantly decreased left ventricular function on an observed correlation also requires study in order to make this technique applicable to those who have previously manifested reduced systolic function and/or cardiac decompensation.

In order to make our setup and technique more adaptable to the clinical setting, an immediate conversion of the recording to a spectral image, and perhaps the nearly instantaneous calculation of estimated pressure gradient, are needed. Currently, there are many devices under development that can display a spectral image of a murmur almost instantaneously. Further development and refinement will definitely simplify and increase the likelihood of its use in today’s busy clinical practices.

In conclusion, our study showed a high level of correlation between a murmur duration of > 300 Hz and both the peak and mean Doppler echocardiogram-derived transvalvular aortic pressure gradient. Thus, we believe that this may be developed as a simple and effective diagnostic tool with which to assess and monitor the severity of valvular aortic stenosis.


   Acknowledgements
 
The authors are indebted to Hart Katz, MD, PhD, and Mark Smith, MS, for their assistance in the technical and statistical aspects of this project.


   Footnotes
 
This project was funded partially by the St. Vincent Hospital Foundation, Indianapolis, IN.

Received for publication May 9, 2002. Accepted for publication March 20, 2003.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Otto, CM, Pearlman, AS (1998) Doppler echocardiography in adults with symptomatic aortic stenosis: diagnostic utility and cost-effectiveness. Arch Intern Med 148,2553-2560
  2. Bonner, AJ, Jr, Sacks, HN, Tavel, ME Assessing the severity of aortic stenosis by phonocardiography and external carotid pulse recordings. Circulation 1973;48,247-252[Abstract/Free Full Text]
  3. Donnerstein, RL Continuous spectral analysis of heart murmurs for evaluating stenotic cardiac lesion. Am J Cardiol 1989;64,625-630[CrossRef][ISI][Medline]
  4. Hans, N, Thuesen, L, Hasenkam, JM, et al Assessing the severity of aortic valve stenosis by spectral analysis of cardiac murmurs (spectral vibrocardiography): Part I. Technical aspects. J Heart Valve Dis 1993;2,454-467[Medline]
  5. Hans, N, Thuesen, L, Terp, K, et al Assessing the severity of aortic valve stenosis by spectral analysis of cardiac murmurs (spectral vibrocardiography): Part II. Clinical aspect. J Heart Valve Dis 1993;2,468-475[Medline]
  6. Johnson, GR, Adolph, RJ, Campbell, DJ Estimation of the severity of aortic valve stenosis by frequency analysis of the murmur. J Am Coll Cardiol 1983;1,1315-1323[ISI][Medline]
  7. Johnson, GR, Myers, GS, Lees, RS Evaluation of aortic stenosis by spectral analysis of the murmur. J Am Coll Cardiol 1985;6,55-63[Abstract]
  8. Masso, N, Nakamura, T, Hultgren, HN, et al Noninvasive evaluation of the severity of aortic stenosis. Chest 1987;97,682-687
  9. Munt, B, Legget, ME, Kraft, CD, et al Physical examination in valvular aortic stenosis: correlation with stenosis severity and prediction of clinical outcome. Am Heart J 1999;137,298-306[CrossRef][ISI][Medline]
  10. Rama, BN, Mohiuddin, SM, Esterbrooks, DJ, et al Correlation of intensity of aortic stenosis murmur by auscultation with echocardiographically determined transvalvular gradients and valve area. J Noninvasive Cardiol 1999;3,25-31
  11. Tavel, ME Frequency content of systolic murmurs: an answer to the riddle of aortic stenosis [editorial]? J Am Coll Cardiol 1985;6,64-65
  12. Tavel, ME Clinical phonocardiography and external pulse recording 4th ed. 1967,139-188 Year Book Medical Publishers. Chicago, IL:
  13. Vollenhoven, VE, Rotterdam, VA, Dorenbos, T Frequency analysis of heart murmurs. Med Biol Eng 1968;7,227-232
  14. Hatle, L, Brubakk, A, Tromsdal, A, et al Noninvasive assessment of pressure drop in mitral stenosis by Doppler ultrasound. Br Heart J 1978;40,131-140[Abstract/Free Full Text]
  15. Hatle, L, Tromsdal, A, Angelsen, B Non-invasive assessment of aortic stenosis by Doppler ultrasound. Br Heart J 1980;43,284-292[Abstract/Free Full Text]
  16. Requarth, JA, Goldberg, SJ, Vasko, SD, et al In vitro verification of Doppler prediction of transvalve pressure gradient and orifice area in stenosis. Am J Cardiol 1984;53,1369-1373[CrossRef][ISI][Medline]
  17. Stamm, BR, Martin, RP Quantification of pressure gradients across stenotic valves by Doppler ultrasound. J Am Coll Cardiol 1983;2,707-718[Abstract]
  18. Robinson, B The carotid pulse: I. Diagnosis of aortic stenosis by external carotid recording. Br Heart J 1963;25,51-60[Free Full Text]
  19. Robinson, B The carotid pulse: II. Relation of external recordings to carotid, aortic, and brachial pulses. Br Heart J 1963;25,61-68[Free Full Text]
  20. Balster, DA, Chan, DP, Rowland, DG, et al Digital acoustic analysis of precordial innocent versus ventricular septal defect murmurs in children. Am J Cardiol 1997;79,1552-1555[CrossRef][ISI][Medline]
  21. Donnerstein, RL, Thomsen, VS Hemodynamic and anatomic factors affecting the frequency content of Still’s innocent murmur. Am J Cardiol 1994;74,508-510[CrossRef][ISI][Medline]



This article has been cited by other articles:


Home page
 BMJHome page
Minerva
BMJ, January 3, 2004; 328(7430): 58 - 58.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF) Free
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Article Archive
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (9)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kim, D.
Right arrow Articles by Tavel, M. E.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kim, D.
Right arrow Articles by Tavel, M. E.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS