Modeling sound generation in stenosed coronary arteries

Effects of high-frequency mechanical stimuli on flow related vascular cell biology

Mechanical forces related to blood pressure and flow patterns play a crucial role in vascular homeostasis. Perturbations in vascular stresses and strain resulting from changes in hemodynamic may occur in pathological conditions, leading to vascular dysfunction as well as in vascular prosthesis, arteriovenous shunt for hemodialysis and in mechanical circulation support. Turbulent-like blood flows can induce high-frequency vibrations of the vessel wall, and this stimulus has recently gained attention as potential contributors to vascular pathologies, such as development of intimal hyperplasia in arteriovenous fistula for hemodialysis. However, the biological response of vascular cells to this stimulus remains incompletely understood. This review provides an analysis of the existing literature concerning the impact of high-frequency stimuli on vascular cell morphology, function, and gene expression. Morphological and functional investigations reveal that vascular cells stimulated at frequencies higher than the normal heart rate exhibit alterations in cell shape, alignment, and proliferation, potentially leading to vessel remodeling. Furthermore, vibrations modulate endothelial and smooth muscle cells gene expression, affecting pathways related to inflammation, oxidative stress, and muscle hypertrophy. Understanding the effects of high-frequency vibrations on vascular cells is essential for unraveling the mechanisms underlying vascular diseases and identifying potential therapeutic targets. Nevertheless, there are still gaps in our understanding of the molecular pathways governing these cellular responses. Further research is necessary to elucidate these mechanisms and their therapeutic implications for vascular diseases.

Coronary Artery Disease Detected by Low Frequency Heart Sounds

OBJECTIVES

Previous studies have observed an increase in low frequency diastolic heart sounds in patients with coronary artery disease (CAD). The aim was to develop and validate a diagnostic, computerized acoustic CAD-score based on heart sounds for the non-invasive detection of CAD.

METHODS

Prospective study enrolling 463 patients referred for elective coronary angiography. Pre-procedure non-invasive recordings of heart sounds were obtained using a novel acoustic sensor. A CAD-score was defined as the power ratio between the 10-90 Hz frequency spectrum and the 90-300 Hz frequency spectrum of the mid-diastolic heart sound. Quantitative coronary angiography analysis was performed by a blinded core laboratory and patients grouped according to the results: obstructive CAD defined by the presence of at least one ≥ 50% stenosis, non-obstructive CAD as patients with a maximal stenosis in the 25-50% interval and non-CAD as no coronary lesions exceeding 25%. We excluded patients with potential confounders or incomplete data (n = 245). To avoid over-fitting the final cohort of 218 patients was randomly divided into to a training group for development (n = 127) and a validation group (n = 91).

RESULTS

In both the training and the validation group the CAD-score was significantly increased in CAD patients compared to non-CAD patients (p < 0.0001). In the validation group the area under the receiver-operating curve was 77% (95% CI 63-91%). Sensitivity was 71% (95% CI 59-82%) and specificity 64% (95% CI 45-83%).

CONCLUSION

The acoustic CAD-score is a new, inexpensive, non-invasive method to detect CAD, which may supplement clinical risk stratification and reduce the need for subsequent non-invasive and invasive testing.

Spectral analysis of heart sounds associated with coronary artery disease

Objective. The aim of this study was to find spectral differences of diagnostic interest in heart sound recordings of patients with coronary artery disease (CAD) and healthy subjects.Approach. Heart sound recordings from three studies were pooled, and patients with clear diagnostic outcomes (positive: CAD and negative: Non-CAD) were selected for further analysis. Recordings from 1146 patients (191 CAD and 955 Non-CAD) were analyzed for spectral differences between the two groups using Welch's spectral density estimate. Frequency spectra were estimated for systole and diastole segments, and time-frequency spectra were estimated for first (S1) and second (S2) heart sound segments. An ANCOVA model with terms for diagnosis, age, gender, and body mass index was used to evaluate statistical significance of the diagnosis term for each time-frequency component.Main results. Diastole and systole segments of CAD patients showed increased energy at frequencies 20-120 Hz; furthermore, this difference was statistically significant for the diastole. CAD patients showed decreased energy for the mid-S1 and mid-S2 segments and conversely increased energy before and after the valve sounds. Both S1 and S2 segments showed regions of statistically significant difference in the time-frequency spectra.Significance. Results from analysis of the diastole support findings of increased low-frequency energy from previous studies. Time-frequency components of S1 and S2 sounds showed that these two segments likely contain heretofore untapped information for risk assessment of CAD using phonocardiography; this should be considered in future works. Further development of features that build on these findings could lead to improved acoustic detection of CAD.

Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy

Coronary heart disease (CHD) is the leading cause of cardiovascular death. This study aimed to propose an effective method for mining cardiac mechano-electric coupling information and to evaluate its ability to distinguish patients with varying degrees of coronary artery stenosis (VDCAS). Five minutes of electrocardiogram and phonocardiogram signals was collected synchronously from 191 VDCAS patients to construct heartbeat interval (RRI)-systolic time interval (STI), RRI-diastolic time interval (DTI), HR-corrected QT interval (QTcI)-STI, QTcI-DTI, Tpeak-Tend interval (TpeI)-STI, TpeI-DTI, Tpe/QT interval (Tpe/QTI)-STI, and Tpe/QTI-DTI series. Then, the cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), joint distribution entropy (JDistEn), magnitude-squared coherence function, cross power spectral density, and mutual information were applied to evaluate the coupling of the series. Subsequently, support vector machine recursive feature elimination and XGBoost were utilized for feature selection and classification, respectively. Results showed that the joint analysis of XSampEn, XFuzzyEn, and JDistEn had the best ability to distinguish patients with VDCAS. The classification accuracy of severe CHD-mild-to-moderate CHD group, severe CHD-chest pain and normal coronary angiography (CPNCA) group, and mild-to-moderate CHD-CPNCA group were 0.8043, 0.7659, and 0.7500, respectively. The study indicates that the joint analysis of XSampEn, XFuzzyEn, and JDistEn can effectively capture the cardiac mechano-electric coupling information of patients with VDCAS, which can provide valuable information for clinicians to diagnose CHD.

Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals

Heart sound signals reflect valuable information about heart condition. Previous studies have suggested that the information contained in single-channel heart sound signals can be used to detect coronary artery disease (CAD). But accuracy based on single-channel heart sound signal is not satisfactory. This paper proposed a method based on multi-domain feature fusion of multi-channel heart sound signals, in which entropy features and cross entropy features are also included. A total of 36 subjects enrolled in the data collection, including 21 CAD patients and 15 non-CAD subjects. For each subject, five-channel heart sound signals were recorded synchronously for 5 min. After data segmentation and quality evaluation, 553 samples were left in the CAD group and 438 samples in the non-CAD group. The time-domain, frequency-domain, entropy, and cross entropy features were extracted. After feature selection, the optimal feature set was fed into the support vector machine for classification. The results showed that from single-channel to multi-channel, the classification accuracy has increased from 78.75% to 86.70%. After adding entropy features and cross entropy features, the classification accuracy continued to increase to 90.92%. The study indicated that the method based on multi-domain feature fusion of multi-channel heart sound signals could provide more information for CAD detection, and entropy features and cross entropy features played an important role in it.

Advanced heart sound analysis as a new prognostic marker in stable coronary artery disease

Aims

Recent technological advances enable diagnosing of obstructive coronary artery disease (CAD) from heart sound analysis with a high negative predictive value. However, the prognostic impact of this approach remains unknown. To investigate the prognostic value of heart sound analysis as two scores, the Acoustic-score and the CAD-score, in patients with suspected CAD which is treated according to standard of care.

Methods and results

Consecutive patients with angina symptoms referred for coronary computed tomography angiography (CTA) were enrolled. The Acoustic-score was developed from eight acoustic CAD-related features. This score was combined with risk factors to generate the CAD-score. A cut-off score >20 was pre-specified for both scores to indicate disease. If coronary CTA raised suspicion of obstructive CAD, patients were referred to invasive angiography and revascularized when indicated. Of 1675 enrolled patients, 1464 (87.4%) were included in this substudy. The combined primary endpoint was all-cause mortality and myocardial infarction (n = 26). Follow-up was 3.1 (2.7-3.4) years. Of patients with primary endpoints, the Acoustic-score was >20 in 25 (96%); the CAD-score was >20 in 22 (85%). In an unadjusted Cox analysis of the primary endpoints, the hazard ratio for scores >20 under current standard clinical care was 12.6 (1.7-93.2) for the Acoustic-score and 5.4 (1.9-15.7) for the CAD-score. The CAD-score contained prognostic information even after adjusting for lipid-lowering therapy initiation, stenosis at CTA, and early revascularization.

Conclusion

Heart sound analysis seems to carry prognostic information and may improve initial risk stratification of patients with suspected CAD.

Clinicaltrialsorg ID

NCT02264717.

Computational Modeling of Carotid Bruits

The sound generated by diseased carotid arteries was investigated through computational means using three-dimensional, idealized, stenosed carotid bifurcation models. Stenosis levels of 50% and 70% with axi-symmetric and asymmetric stenosis shapes were considered. The hemodynamic flow field was obtained by solving the incompressible, Navier-Stokes equations. The resulting pressure fluctuations at the vessel walls were then used as input for a linearized wave equation for the propagation of vibrations through the modeled surrounding tissue. As observed in prior studies, the sound spectra obtained at the tissue surface indicate a 'break frequency', i.e. a frequency beyond which there is a drop-off in sound spectra intensity. This frequency was found to scale with stenosis diameter and average velocity at the stenosis throat, provided the stenosis shape remained the same. This has important implications on past attempts to estimate stenosis diameter from the break frequency.

Experimental and numerical investigation on soft tissue dynamic response due to turbulence-induced arterial vibration

Peripheral arterial occlusive disease is a serious cardiovascular disorder. The arterial occlusion leads to turbulent flow and arterial sound generation on the inner vessel wall. Stenosis-induced vibro-acoustic waves propagate through the surrounding soft tissues and reach the skin surface. In this study, the feasibility of noninvasive acoustic detection of the peripheral arterial stenosis is investigated using the vibration responses by means of experimental and computational models. Latex rubber tube is used to model the artery, and it is surrounded by a tissue mimicking phantom made of bovine gelatin. Vibration responses on phantom surface are measured using laser Doppler vibrometer, and computational results are obtained performing modal analysis. Experimental findings and computational results showed well agreement in terms of spectral content and vibration amplitudes. The effects of various stenosis severities, flow rates, and phantom thicknesses on the vibration responses are investigated from diagnostic perspective. Stenosis severities greater than 70% resulted in a considerable increase in vibration amplitudes. The structural mode shapes of the tissue phantom are dominant between 0 and 100 Hz, suppressing the signals generated by the stenosis. The optimum range of frequency for acoustic stenosis detection is concluded to be between 200 and 500 Hz, particularly around 300 Hz. Graphical abstract .

Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification

OBJECTIVE

Diagnosing coronary artery disease (CAD) continues to require substantial healthcare resources. Acoustic analysis of transcutaneous heart sounds of cardiac movement and intracoronary turbulence due to obstructive coronary disease could potentially change this. The aim of this study was thus to test the diagnostic accuracy of a new portable acoustic device for detection of CAD.

METHODS

We included 1675 patients consecutively with low to intermediate likelihood of CAD who had been referred for cardiac CT angiography. If significant obstruction was suspected in any coronary segment, patients were referred to invasive angiography and fractional flow reserve (FFR) assessment. Heart sound analysis was performed in all patients. A predefined acoustic CAD-score algorithm was evaluated; subsequently, we developed and validated an updated CAD-score algorithm that included both acoustic features and clinical risk factors. Low risk is indicated by a CAD-score value ≤20.

RESULTS

Haemodynamically significant CAD assessed from FFR was present in 145 (10.0%) patients. In the entire cohort, the predefined CAD-score had a sensitivity of 63% and a specificity of 44%. In total, 50% had an updated CAD-score value ≤20. At this cut-off, sensitivity was 81% (95% CI 73% to 87%), specificity 53% (95% CI 50% to 56%), positive predictive value 16% (95% CI 13% to 18%) and negative predictive value 96% (95% CI 95% to 98%) for diagnosing haemodynamically significant CAD.

CONCLUSION

Sound-based detection of CAD enables risk stratification superior to clinical risk scores. With a negative predictive value of 96%, this new acoustic rule-out system could potentially supplement clinical assessment to guide decisions on the need for further diagnostic investigation.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov identifier NCT02264717; Results.

Flow-induced vibration analysis of constricted artery models with surrounding soft tissue

Arterial stenosis is a vascular pathology which leads to serious cardiovascular diseases. Blood flow through a constriction generates sound and vibration due to fluctuating turbulent pressures. Generated vibro-acoustic waves propagate through surrounding soft tissues and reach the skin surface and may provide valuable insight for noninvasive diagnostic purposes. Motivated by the aforementioned phenomena, vibration of constricted arteries is investigated employing computational models. The flow-induced pressure field in an artery is modeled as broadband harmonic pressure loading based on previous studies in the literature and applied on the inner artery wall. Harmonic analysis is performed for determining radial velocity responses on the outer surface of the models. Results indicate that stenosis severities higher than 70% lead to significant increase in response amplitudes, especially at high frequencies between 250 and 600 Hz. The findings agree well with experimental and theoretical results in the literature considering bending mode frequencies, amplitude scales, and mainly excited frequency ranges. It is seen that artery vibration is sensitive to the phase behavior of pressure loading but its effect becomes less significant with the presence of surrounding tissue. As the surrounding tissue thickness increases, radial velocity response amplitudes decrease but the effect of changes in tissue elastic modulus is more pronounced.

The Assessment of Stent Effectiveness Using a Wearable Beamforming MEMS Microphone Array System

Studies involving turbulent flow have been carried out in many parts of the cardiovascular system, and it has been widely reported that turbulence related to stenosis (narrowing) of arteries creates audible sounds, which may be analyzed to yield information about the nature and severity of the blockage. Results so far indicate that the high frequency content of the sounds generally increases with the degree of stenosis. In this paper, we designed and built an MEMs microphone array and a signal acquisition board to improve the detection of coronary occlusions using an approach based on the recording and analysis of isolated diastolic heart sounds associated with turbulent blood flow in occluded coronary arteries. The nonlinear dynamic analysis method based on approximate entropy has been proposed for the analysis of diastolic heart sounds from patients with single coronary occlusions, before and after stent placement procedures. The nonlinear dynamic analysis (approximate entropy) measures of the diastolic heart sounds recorded from eight patients with single coronary occlusions and two normal subjects were estimated. In addition, a spectral analysis based on the fast Fourier transform was used to estimate the energy content of the recorded signals. Results suggest the presence of high nonlinear (approximate entropy) values of diastolic heart sounds associated with coronary artery disease (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.01$ \end{document}) as well as significant differences in the energy content of the heart sound signals above and below 150 Hz (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.05$ \end{document}).

Audible Coronary Artery Stenosis

OBJECTIVE

Hemodynamically significant coronary artery stenoses generate turbulent blood flow patterns that manifest as intracoronary murmurs. This study aims to evaluate the performance of modern acoustic detection of these murmurs by acoustic signals captured from patients undergoing gold standard comparative coronary angiography.

METHODS

We prospectively studied 156 patients undergoing elective coronary angiography, excluding those with acute coronary syndrome, prior chest surgery, or significant valvular disease. Acoustic signals were captured before arterial access. Angiographic degree of stenosis in each coronary artery was graded blinded to clinical and acoustic data. Acoustic data were analyzed blinded to clinical and angiographic data, categorizing subjects as "normal," "diseased," or "inconclusive." Of 156 patients examined, 123 generated analyzable data.

RESULTS

Angiographically significant stenosis (≥50%) prevalence was 52% (18%, 23%, 11% with 1-, 2-, 3-vessel disease, respectively). Acoustic detection sensitivity and specificity for stenosis ≥50% in any vessel were 0.70 and 0.80, respectively (negative predictive value, 0.71; positive predictive value, 0.79). Acoustic detection optimally identified stenosis ≥50% with an area under the curve of 0.75. For stenosis ≥50% in major vessels only (left main, proximal-mid left anterior descending, proximal-mid circumflex, proximal-mid right coronary), prevalence was 46%; sensitivity and specificity were 0.72 and 0.76, respectively (negative predictive value, 0.76; positive predictive value, 0.72; area under the curve, 0.76).

CONCLUSIONS

Acoustic signal patterns and modern analysis techniques may be used to identify intracoronary murmurs generated by hemodynamically significant coronary artery stenoses in all major vessels. Further investigation is warranted to compare the clinical performance of this modality with current noninvasive approaches that evaluate patients at risk for atherosclerotic and obstructive coronary artery disease.

Improved Heart Sound Detection and Signal-to-Noise Estimation Using a Low-Mass Sensor

GOAL

The purpose of this paper is to improve the detection of high-frequency sounds from the heart for better identification of turbulent blood flow in partially occluded coronary arteries. This paper also describes a method for the quantitative assessment of data quality.

METHODS

A very light-weight dual accelerometer has been developed that places a small mechanical load on the chest. When used in conjunction with a novel correlation-based analysis, this dual-signal transducer provides an estimate to the signal-to-noise ratio (SNR) of the acoustic signal.

RESULTS

The new transducer has significantly better SNR properties than the traditional cardiac microphones. This improvement is due to increased sensitivity to high-frequency signals not a reduction in noise and is likely the result of reduced mechanical loading on the chest.

CONCLUSION

Substantial improvement in the detection of high-frequency heart sounds is possible as is quantitative assessment of data quality.

SIGNIFICANCE

The new transducer and analysis will lead to substantial improvements in the acoustic detection of partially occluded arteries associated with coronary artery disease. It is finally possible to obtain a measurement of the quality of heart sound signals as they are being recorded.

Acoustic Features for the Identification of Coronary Artery Disease

GOAL

Earlier studies have documented that coronary artery disease (CAD) produces weak murmurs, which might be detected through analysis of heart sounds. An electronic stethoscope with a digital signal processing unit could be a low cost and easily applied method for diagnosis of CAD. The current study is a search for heart sound features which might identify CAD.

METHODS

Nine different types of features from five overlapping frequency bands were obtained and analyzed using 435 recordings from 133 subjects.

RESULTS

New features describing an increase in low-frequency power in CAD patients were identified. The features of the different types were relatively strongly correlated. Using a quadratic discriminant function, multiple features were combined into a CAD-score. The area under the receiving operating characteristic for the CAD score was 0.73 (95% CI: 0.69-0.78).

CONCLUSION

The result confirms that there is a potential in heart sounds for the diagnosis of CAD, but that further improvements are necessary to gain clinical relevance.

Model validation for a noninvasive arterial stenosis detection problem

A current thrust in medical research is the development of a non-invasive method for detection, localization, and characterization of an arterial stenosis (a blockage or partial blockage in an artery). A method has been proposed to detect shear waves in the chest cavity which have been generated by disturbances in the blood flow resulting from a stenosis. In order to develop this methodology further, we use one-dimensional shear wave experimental data from novel acoustic phantoms to validate a corresponding viscoelastic mathematical model. We estimate model parameters which give a good fit (in a sense to be precisely defined) to the experimental data, and use asymptotic error theory to provide confidence intervals for parameter estimates. Finally, since a robust error model is necessary for accurate parameter estimates and confidence analysis, we include a comparison of absolute and relative models for measurement error.

Path length entropy analysis of diastolic heart sounds

Early detection of coronary artery disease (CAD) using the acoustic approach, a noninvasive and cost-effective method, would greatly improve the outcome of CAD patients. To detect CAD, we analyze diastolic sounds for possible CAD murmurs. We observed diastolic sounds to exhibit 1/f structure and developed a new method, path length entropy (PLE) and a scaled version (SPLE), to characterize this structure to improve CAD detection. We compare SPLE results to Hurst exponent, Sample entropy and Multiscale entropy for distinguishing between normal and CAD patients. SPLE achieved a sensitivity-specificity of 80%-81%, the best of the tested methods. However, PLE and SPLE are not sufficient to prove nonlinearity, and evaluation using surrogate data suggests that our cardiovascular sound recordings do not contain significant nonlinear properties.

Utility of an advanced digital electronic stethoscope in the diagnosis of coronary artery disease compared with coronary computed tomographic angiography

The detection of coronary artery microbruits, subaudible bruits too faint to be heard through standard auscultation, may provide an alternative means to diagnose coronary artery disease (CAD). The aim of this study was to test the accuracy of a novel digital electronic stethoscope, the Cardiac Sonospectrographic Analyzer (CSA; SonoMedica model 3.0, SonoMedica, Inc., Vienna, Virginia, United States Food and Drug Administration 510[k] cleared) to diagnose CAD compared to gold-standard diagnosis using cardiac computed tomographic (CT) angiography. In this blinded, single-site study, adults previously referred for CT imaging were selected. Patients underwent CT and CSA evaluations. CSA exams entailed recording heart sounds at 9 positions on the chest for 40 seconds at each position. An algorithm then processed these data to generate a microbruit score. The CT scans were read blinded to patients' microbruit scores. Sensitivity and specificity of the CSA in detecting CAD compared to CT imaging were estimated using standard receiver-operating characteristic curves calculated from logistic regression models. A total of 161 patients, aged 57 ± 13 years (range 22 to 85), 53% with hypertension and 40% with obesity (body mass index ≥30 kg/m(2)), completed the protocol and had evaluable CT and CSA examinations. The overall sensitivity of the CSA to identify >50% stenosis in any major epicardial coronary artery as determined by CT imaging was 89.5% (p <0.0001). Gender-specific models based on smaller sample sizes had slightly poorer results and lower specificity among men with heavy chest hair. In conclusion, the CSA showed high sensitivity and specificity for the detection of significant early CAD in an outpatient setting and represents a new noninvasive device for detecting abnormal coronary blood flow as occurs in CAD.

Acoustic source separation for the detection of coronary artery sounds

Coronary artery disease (CAD) is the leading cause of death in the United States, being responsible for more than 20% of all deaths in the country. This is in large part due to the difficulty of diagnostic screening for CAD. Phonoangiography seeks to detect CAD via the acoustic signature associated with turbulent flow near an abnormally constricted, or stenosed, region. However, the usefulness of the technique is severely hindered by the low strength of the CAD signal compared to the background noise within the chest. In this work, acoustic finite element analysis (FEA) was performed on physiologically accurate chest geometries to demonstrate the feasibility of an original acoustic source separation methodology for isolating coronary sounds. This approach is based upon pseudoinversion of mixing matrices determined through a combination of experiment and computation. This allows calculation of the sound emitted by the coronary arteries based upon measurements of the acoustic velocity on the chest surface. This work demonstrates the feasibility of such a technique computationally and examines the vulnerability of the proposed approach to measurement errors.

Acoustical detection of venous stenosis in hemodialysis patients using principal component analysis

In this paper, a feature extraction method based on principal component analysis was developed for classification of the vascular access's condition in hemodialysis patients. The assessment of the method was carried out by discriminating between before and after angioplasty sound recordings as well as before angioplasty and reference recordings. The results showed that when before and after angioplasty recordings were compared by patient, the classification agreed with the result of angioplasty procedure. When all the available before and after angioplasty recordings were compared, it was still possible to discriminate them at a good rate. On the other hand, when the reference recordings substituted the after angioplasty recordings, almost a perfect discrimination was achieved.

Acoustic detection of coronary artery disease

Coronary artery disease (CAD) occurs when the arteries to the heart (the coronary arteries) become blocked by deposition of plaque, depriving the heart of oxygen-bearing blood. This disease is arguably the most important fatal disease in industrialized countries, causing one-third to one-half of all deaths in persons between the ages of 35 and 64 in the United States. Despite the fact that early detection of CAD allows for successful and cost-effective treatment of the disease, only 20% of CAD cases are diagnosed prior to a heart attack. The development of a definitive, noninvasive test for detection of coronary blockages is one of the holy grails of diagnostic cardiology. One promising approach to detecting coronary blockages noninvasively is based on identifying acoustic signatures generated by turbulent blood flow through partially occluded coronary arteries. In fact, no other approach to the detection of CAD promises to be as inexpensive, simple to perform, and risk free as the acoustic-based approach. Although sounds associated with partially blocked arteries are easy to identify in more superficial vessels such as the carotids, sounds from coronary arteries are very faint and surrounded by noise such as the very loud valve sounds. To detect these very weak signals requires sophisticated signal processing techniques. This review describes the work that has been done in this area since the 1980s and discusses future directions that may fulfill the promise of the acoustic approach to detecting coronary artery disease.

Vibration mode imaging

A new method for imaging the vibration mode of an object is investigated. The radiation force of ultrasound is used to scan the object at a resonant frequency of the object. The vibration of the object is measured by laser and the resulting acoustic emission from the object is measured by a hydrophone. It is shown that the measured signal is proportional to the value of the mode shape at the focal point of the ultrasound beam. Experimental studies are carried out on a mechanical heart valve and arterial phantoms. The mode images on the valve are made by the hydrophone measurement and confirmed by finite-element method simulations. Compared with conventional B-scan imaging on arterial phantoms, the mode imaging can show not only the interface of the artery and the gelatin, but also the vibration modes of the artery. The images taken on the phantom surface suggest that an image of an interior artery can be made by vibration measurements on the surface of the body. However, the image of the artery can be improved if the vibration of the artery is measured directly. Imaging of the structure in the gelatin or tissue can be enhanced by small bubbles and contrast agents.

Acoustic radiation from a fluid-filled, subsurface vascular tube with internal turbulent flow due to a constriction

The vibration of a thin-walled cylindrical, compliant viscoelastic tube with internal turbulent flow due to an axisymmetric constriction is studied theoretically and experimentally. Vibration of the tube is considered with internal fluid coupling only, and with coupling to internal-flowing fluid and external stagnant fluid or external tissue-like viscoelastic material. The theoretical analysis includes the adaptation of a model for turbulence in the internal fluid and its vibratory excitation of and interaction with the tube wall and surrounding viscoelastic medium. Analytical predictions are compared with experimental measurements conducted on a flow model system using laser Doppler vibrometry to measure tube vibration and the vibration of the surrounding viscoelastic medium. Fluid pressure within the tube was measured with miniature hydrophones. Discrepancies between theory and experiment, as well as the coupled nature of the fluid-structure interaction, are described. This study is relevant to and may lead to further insight into the patency and mechanisms of vascular failure, as well as diagnostic techniques utilizing noninvasive acoustic measurements.

Computerised analysis of auscultatory sounds associated with vascular patency of haemodialysis access

Vascular access for renal dialysis is a lifeline for about 120 000 individuals in the United States. Stethoscope auscultation of vascular sounds has some utility in the assessment of access patency, yet can be highly skill-dependent. The objective of the study was to identify acoustic parameters that are related to changes in vascular access patency. The underlying hypothesis is that stenoses of haemodialysis access vessels or grafts cause vascular sound changes that are detectable using computerised data acquisition and analysis. Eleven patients participated in the study. Their vascular sounds were recorded before and after angiography, which was accompanied by angioplasty in most patients. The sounds were acquired using two electronic stethoscopes and then digitised and analysed on a personal computer. Vessel stenosis changes were found to be associated with changes in acoustic amplitude and/or spectral energy distribution. Certain acoustic parameters correlated well (correlation coefficient = 0.98, p < 0.0001) with the change in the degree of stenosis, suggesting that stenosis severity may be predictable from these parameters. Parameters also appeared to be sensitive to modest diameter changes (> 20%), (p < 0.005, Wilcoxon rank sum test). These results suggest that computerised analysis of vascular sounds may be useful in vessel patency surveillance. Further testing using longitudinal studies may be warranted.

Beamformed nearfield imaging of a simulated coronary artery containing a stenosis

This paper is concerned with the potential for the detection and location of an artery containing a partial blockage by exploiting the space-time properties of the shear wave field in the surrounding elastic soft tissue. As a demonstration of feasibility, an array of piezoelectric film vibration sensors is placed on the free surface of a urethane mold that contains a surgical tube. Inside the surgical tube is a nylon constriction that inhibits the water flowing through the tube. A turbulent field develops in and downstream from the blockage, creating a randomly fluctuating pressure on the inner wall of the tube. This force produces shear and compressional wave energy in the urethane. After the array is used to sample the dominant shear wave space-time energy field at low frequencies, a nearfield (i.e., focused) beamforming process then images the energy distribution in the three-dimensional solid. Experiments and numerical simulations are included to demonstrate the potential of this noninvasive procedure for the early identification of vascular blockages-the typical precursor of serious arterial disease in the human heart.

Physical mechanisms involved in the genesis of temporomandibular joint sounds

Several different mechanisms are potentially capable of generating sounds in the temporomandibular joint (TMJ). These include impact, sliding and stick-slip friction, fluid dynamic effects and the release of elastic strain energy. It is the aim of this paper to provide a framework with which to separate sounds resulting from the different underlying causes. Each mechanism is described and its relevance to TMJ sounds and clinical significance discussed. Since it is not possible to observe these mechanisms in vivo the arguments are based mainly on analogies which are used to make predictions of the characteristic acoustic signatures of the sounds produced by these different mechanisms. In particular the changes in the characteristics of the sounds as parameters such as mandibular speed and loading are stressed. It is suggested that single short duration sounds (clicks) are due to impact, multiple short duration sounds (creaks) to stick-slip friction and defects of form and long duration sounds (crepitus) to simple sliding friction. Several other mechanisms which have no obvious clinical significance but which are capable of producing similar sounds are also described and methods of distinguishing them from the sounds that do have clinical implications are discussed.

Investigating the effects of vasodilator drugs on the turbulent sound caused by femoral artery stenosis using short-term Fourier and wavelet transform methods

In this study, the effects of vasodilator drugs on the turbulent sound generation mechanisms during femoral artery stenoses were investigated using the wavelet analysis of the turbulent sounds to characterize these sounds before and after the injection of vasodilator drugs. Results showed that the injection of drugs drastically improved the diagnostic performance of the turbulent sounds in detecting stenoses by increasing the signal-to-noise ratio of the sounds. Results also suggested that the sound above 250 Hz was drastically increased in response to the injection of the vasodilator drug for the partially occluded cases. The turbulence sounds caused by partially occluded femoral arteries are directly related to the slope of baseline of blood flow and to the velocity of the flow. For the 0% occlusion case, initially, sounds were produced with the injection of drugs. However, the sounds totally disappeared when the slope of average blood flow was zero. These results show that the diagnostic performance of diastolic heart sounds associated with occluded arteries can be improved by using vasodilator drugs, which increase the acoustic energy in the first and second wavelet bandwidths due to the turbulence. The short-term Fourier transform (STFT) method was also applied to the same data base. Results using the STFT showed somewhat similar power distributions in that the acoustical power above 250 Hz was increased after the injection of drugs for the occluded cases. However, the WT method provided better time-frequency resolution than the STFT method, showing details of the change in the frequency characteristics with respect to time after the injection of drug.

Dynamics of the sounds caused by partially occluded femoral arteries in dogs

Previous studies have indicated that partially occluded arteries produce sounds due to turbulence. If these sounds from the coronary arteries could be detected externally, they would provide a simple approach to the detection of coronary artery disease. To confirm the hypothesis that coronary stenosis produces detectable acoustic correlates, sounds caused by a controlled occlusion of the femoral artery of dogs were detected and analyzed using both the fast Fourier transform (FFT) and the autoregressive (AR) methods. The femoral artery was chosen, since its size and flow approximate those of coronary arteries in humans. The poles of the AR spectra and the power ratios of different sections of the FFT and AR spectra were used to differentiate the degree of the stenosis. The results showed that high frequency acoustical power between 200 and 800 Hz is associated with the turbulence produced by the partially occluded femoral arteries of the dogs. Using the AR method, high acoustic power above 200 Hz increased when the degree of the occlusions increased. The poles and power ratios of the AR spectra differed according to the degree of stenosis. However, the high frequency acoustical power above 200 Hz did not increase above the 85% occlusion.

Noninvasive acoustical detection of coronary artery disease: a comparative study of signal processing methods

Previous studies have indicated heart sounds may contain information useful in the detection of occluded coronary arteries. During diastole, coronary blood flow is maximum, and the sounds associated with turbulent blood flow through partially occluded coronary arteries should be detectable. In order to detect such sounds, recordings of diastolic heart sound segments were analyzed by using four signal processing techniques; the Fast Fourier Transform (FFT), the Autoregressive (AR), the Autoregressive Moving Average (ARMA), and the Minimum-Norm (Eigen-vector) methods. To further enhance the diastolic heart sounds and reduce background noise, an Adaptive filter was used as a preprocessor. The power ratios of the FFT method and the poles of the AR, ARMA, and Eigen-vector methods were used to diagnose patients as diseased or normal arteries using a blind protocol without prior knowledge of the actual disease states of the patients to guard against human bias. Results showed that normal and abnormal records were correctly distinguished in 56 of 80 cases using the Fast Fourier Transform (FFT), in 63 of 80 cases using the AR, in 62 of 80 cases using the ARMA method, and in 67 of 80 cases using the Eigenvector method. Among all four methods, the Eigenvector methods showed the best diagnostic performance when compared with the FFT, AR, and ARMA methods. These results confirm that high frequency acoustic energy between 300 and 800 Hz is associated with coronary stenosis.

Noninvasive characterization of the sound pattern caused by coronary artery stenosis using FTF/FAEST zero tracking filters: normal/abnormal study

In this article, a new approach has been proposed to investigate the extraction of useful information from diastolic heart sounds caused by partially occluded coronary arteries. This method, which estimates and tracks the zeros (poles) of the diastolic heart sounds directly, takes advantage of the FTF/FAEST (Fast Transversal Filters/Fast a Posteriori Error Sequential) technique which possesses the fast convergence property of the Recursive Least Square (RLS) method and the computational simplicity of the Least Mean Square (LMS) method. In previous studies, the main assumption was that the diastolic heart sounds were a stationary process. Since the production of the heart sounds were a stationary process. Since the production of the heart sounds is not a stationary process, a new approach that performs well not only for stationary but also for nonstationary processes can be required. This requirement can be satisfied by the adaptive FTF/FAEST zero tracking method which provides fast and stable convergence as well as computational efficiency since the adaptive FTF/FAEST zero tracking method is based on the exact minimization of least squares criteria and the filter weights of this method are optimal at each time instant. The zero trajectories of the diastolic heart sounds were used to diagnose patients as diseased or normal. Results showed that the normal and abnormal records were incorrectly distinguished in only 6 of 35 cases using a blind protocol where analysis was done without knowledge of the actual disease states of the patients. The most discriminant time region of the zero trajectories of the diastolic heart sounds associated with coronary artery disease was between 200 and 300 msec after the second heart sound during the diastolic period.

Accelerometer type cardiac transducer for detection of low-level heart sounds

New applications in phonocardiography require transducers with high sensitivity, low noise, and extended frequency range. This paper compares several different cardiac transducers and describes the development of a low-mass, accelerometer type cardiac transducer which fulfills these objectives. The accelerometer weighs approximately 5 g and has a theoretical sensitivity of 125 mV/g in the frequency range 200-800 Hz. The basic design allows for easy modification of sensitivity and resonant frequency. This transducer has been effective in detecting sounds associated with turbulent blood flow in partially occluded coronary arteries.