A 3D scaling law for supravalvular aortic stenosis suited for stethoscopic auscultations

In this study a frequency scaling law for 3D anatomically representative supravalvular aortic stenosis (SVAS) cases is proposed. The law is uncovered for stethoscopy's preferred auscultation range (70-120 Hz). LES simulations are performed on the CFD solver Fluent, leveraging Simulia's Living Heart Human Model (LHHM), modified to feature hourglass stenoses that range between 30 to 80 percent (mild to severe) in addition to the descending aorta. For physiological hemodynamic boundary conditions the Windkessel model is implemented via a UDF subroutine. The flow-generated acoustic signal is then extracted using the FW-H model and analyzed using FFT. A preferred receiver location that matches clinical practice is confirmed (right intercostal space) and a correlation between the degree of stenosis and a corresponding acoustic frequency is obtained. Five clinical auscultation signals are tested against the scaling law, with the findings interpreted in relation to the NHS classification of stenosis and to the assessments of experienced cardiologists. The scaling law is thus shown to succeed as a potential quantitative decision-support tool for clinicians, enabling them to reliably interpret stethoscopic auscultations for all degrees of stenosis, which is especially useful for moderate degrees of SVAS. Computational investigation of more complex stenotic cases would enhance the clinical relevance of this proposed scaling law, and will be explored in future research.

A CFD-FFT approach to hemoacoustics that enables degree of stenosis prediction from stethoscopic signals

In this paper, we identify a new (acoustic) frequency-stenosis relation whose frequencies lie within the recommended auscultation threshold of stethoscopy (< 120 Hz). We show that this relation can be used to extend the application of phonoangiography (quantifying the degree of stenosis from bruits) to widely accessible stethoscopes. The relation is successfully identified from an analysis restricted to the acoustic signature of the von Karman vortex street, which we automatically single out by means of a metric we propose that is based on an area-weighted average of the Q-criterion for the post-stenotic region. Specifically, we perform CFD simulations on internal flow geometries that represent stenotic blood vessels of different severities. We then extract their emitted acoustic signals using the Ffowcs Williams-Hawkings equation, which we subtract from a clean signal (stenosis free) at the same heart rate. Next, we transform this differential signal to the frequency domain and carefully classify its acoustic signatures per six (stenosis-)invariant flow phases of a cardiac cycle that are newly identified in this paper. We then automatically restrict our acoustic analysis to the sounds emitted by the von Karman vortex street (phase 4) by means of our Q-criterion-based metric. Our analysis of its acoustic signature reveals a strong linear relationship between the degree of stenosis and its dominant frequency, which differs considerably from the break frequency and the heart rate (known dominant frequencies in the literature). Applying our new relation to available stethoscopic data, we find that its predictions are consistent with clinical assessment. Our finding of this linear correlation is also unlike prevalent scaling laws in the literature, which feature a small exponent (i.e., low stenosis percentage sensitivity over much of the clinical range). They hence can only distinguish mild, moderate, and severe cases. Conversely, our linear law can identify variations in the degree of stenosis sensitively and accurately for the full clinical range, thus significantly improving the utility of the relevant scaling laws... Future research will investigate incorporating the vibroacoustic role of adjacent organs to expand the clinical applicability of our findings. Extending our approach to more complex 3D stenotic morphologies and including the vibroacoustic role of surrounding organs will be explored in future research to advance the clinical reach of our findings.

Evaluation of a new smartphone-based digital stethoscope featuring phonocardiography and electrocardiography in dogs and cats

This study assessed a new smartphone-based digital stethoscope (DS) featuring simultaneous phonocardiographic and one-lead electrocardiogram (ECG) recording in dogs and cats. The audio files and ECG traces obtained by the device were compared with conventional auscultation and standard ECG. A total of 99 dogs and nine cats were prospectively included. All cases underwent conventional auscultation using an acoustic stethoscope, standard six-lead ECG, standard echocardiography and recordings with the DS. All the audio recordings, phonocardiographic files and ECG traces were then blind reviewed by an expert operator. The agreement between methods was assessed using Cohen's kappa and the Bland-Altman test. Audio recordings were considered interpretable in 90% animals. Substantial agreement was found in the diagnosis of heart murmur (κ = 0.691) and gallop sound (k = 0.740). In nine animals with an echocardiographic diagnosis of heart disease, only the DS detected a heart murmur or gallop sound. ECG traces recorded with the new device were deemed interpretable in 88 % animals. Diagnosis of heart rhythm showed moderate agreement in the identification of atrial fibrillation (k = 0.596). The detection of ventricular premature complexes and bundle branch blocks revealed an almost perfect agreement (k = 1). Overall, the DS showed a good diagnostic accuracy in detecting heart murmurs, gallop sounds, ventricular premature complexes and bundle branch blocks. A clinically relevant overdiagnosis of atrial fibrillation was found but without evidence of false negatives. The DS could represent a useful screening tool for heart sound abnormalities and cardiac arrhythmias..

Association between phonocardiography and echocardiography in heart failure patients with preserved ejection fraction

Aims

Heart failure with preserved ejection fraction (HFpEF) is associated with stiffened myocardium and elevated filling pressure that may be captured by heart sound (HS). We investigated the relationship between phonocardiography (PCG) and echocardiography in symptomatic patients suspected of HFpEF.

Methods and results

Consecutive symptomatic patients with sinus rhythm and left ventricular ejection fraction >45% were enrolled. Echocardiography was performed to evaluate the patients' diastolic function, accompanied by PCG measurements. Phonocardiography features including HS amplitude, frequency, and timing intervals were calculated, and their abilities to differentiate the ratio between early mitral inflow velocity and early diastolic mitral annular velocity (E/e') were investigated. Of 45 patients, variable ratio matching was applied to obtain two groups of patients with similar characteristics but different E/e'. Patients with a higher E/e' showed higher first and second HS frequencies and more fourth HS and longer systolic time intervals. The interval from QRS onset to first HS was the best feature for the prediction of E/e' > 9 [area under the curve (AUC): 0.72 (0.51-0.88)] in the matched patients. In comparison, N-terminal pro-brain natriuretic peptide (NT-proBNP) showed an AUC of 0.67 (0.46-0.85), a value not better than any PCG feature (P > 0.05).

Conclusion

Phonocardiography features stratify E/e' in symptomatic patients suspected of HFpEF with a diagnostic performance similar to NT-proBNP. Heart sound may serve as a simple non-invasive tool for evaluating HFpEF patients.

Improved pre-test likelihood estimation of coronary artery disease using phonocardiography

Aims

Current early risk stratification of coronary artery disease (CAD) consists of pre-test probability scoring such as the 2019 ESC guidelines on chronic coronary syndromes (ESC2019), which has low specificity and thus rule-out capacity. A newer clinical risk factor model (risk factor-weighted clinical likelihood, RF-CL) showed significantly improved rule-out capacity over the ESC2019 model. The aim of the current study was to investigate if the addition of acoustic features to the RF-CL model could improve the rule-out potential of the best performing clinical risk factor models.

Methods and results

Four studies with heart sound recordings from 2222 patients were pooled and distributed into two data sets: training and test. From a feature bank of 40 acoustic features, a forward-selection technique was used to select three features that were added to the RF-CL model. Using a cutoff of 5% predicted risk of CAD, the developed acoustic-weighted clinical likelihood (A-CL) model showed significantly (P < 0.05) higher specificity of 48.6% than the RF-CL model (specificity of 41.5%) and ESC 2019 model (specificity of 6.9%) while having the same sensitivity of 84.9% as the RF-CL model. Area under the curve of the receiver operating characteristic for the three models was 72.5% for ESC2019, 76.7% for RF-CL, and 79.5% for A-CL.

Conclusion

The proposed A-CL model offers significantly improved rule-out capacity over the ESC2019 model and showed better overall performance than the RF-CL model. The addition of acoustic features to the RF-CL model was shown to significantly improve early risk stratification of symptomatic patients suspected of having stable CAD.

Simple Phonocardiography with the Ankle-Brachial Index Measurement System as a Tool for Detecting Fourth Heart Sounds of Hypertrophic Cardiomyopathy

Conventional phonocardiography is useful for objective assessment of cardiac auscultation, but its availability is limited. More recently, an ankle-brachial index (ABI) measurement system equipped with simple phonocardiography has become widely used for diagnosing peripheral artery disease, however, whether this simple phonocardiography can be an alternative to conventional phonocardiography remains unclear.This retrospective study consisted of 48 patients with hypertrophic cardiomyopathy (HCM) and 107 controls. The presence of the fourth sound (S4) was assessed by conventional phonocardiography, in addition to apexcardiography and auscultation, in all patients with HCM. S4 was also estimated by the ABI measurement system with the phonocardiographic microphone on the sternum (the standard method) or at the apex (the apex method) in HCM patients and controls.S4 on conventional phonocardiography was detected in 42 of 48 patients (88%) with HCM. Auscultation for the detection of S4 had a sensitivity of 0.78, specificity of 0.57, and accuracy of 0.75. These diagnostic values were generally superior to those of the standard method using the ABI measurement system, whereas the apex method using the ABI measurement system had better diagnostic values, with an excellent specificity of 1.0, sensitivity of 0.77, and accuracy of 0.80. No significant differences were observed in low ABI defined as < 0.9.Simple phonocardiography equipped with the ABI measurement system may be an alternative to conventional phonocardiography for the detection of S4 in patients with HCM when the phonocardiographic microphone is moved from the sternum to the apex.

Unsupervised detection and classification of heartbeats using the dissimilarity matrix in PCG signals

BACKGROUND AND OBJECTIVE

Auscultation is the first technique applied to the early diagnose of any cardiovascular disease (CVD) in rural areas and poor-resources countries because of its low cost and non-invasiveness. However, it highly depends on the physician's expertise to recognize specific heart sounds heard through the stethoscope. The analysis of phonocardiogram (PCG) signals attempts to segment each cardiac cycle into the four cardiac states (S1, systole, S2 and diastole) in order to develop automatic systems applied to an efficient and reliable detection and classification of heartbeats. In this work, we propose an unsupervised approach, based on time-frequency characteristics shown by cardiac sounds, to detect and classify heartbeats S1 and S2.

METHODS

The proposed system consists of a two-stage cascade. The first stage performs a rough heartbeat detection while the second stage refines the previous one, improving the temporal localization and also classifying the heartbeats into types S1 and S2. The first contribution is a novel approach that combines the dissimilarity matrix with the frame-level spectral divergence to locate heartbeats using the repetitiveness shown by the heart sounds and the temporal relationships between the intervals defined by the events S1/S2 and non-S1/S2 (systole and diastole). The second contribution is a verification-correction-classification process based on a sliding window that allows the preservation of the temporal structure of the cardiac cycle in order to be applied in the heart sound classification. The proposed method has been assessed using the open access databases PASCAL, CirCor DigiScope Phonocardiogram and an additional sound mixing procedure considering both Additive White Gaussian Noise (AWGN) and different kinds of clinical ambient noises from a commercial database.

RESULTS

The proposed method outperforms the detection and classification performance of other recent state-of-the-art methods. Although our proposal achieves the best average accuracy for PCG signals without cardiac abnormalities, 99.4% in heartbeat detection and 97.2% in heartbeat classification, its worst average accuracy is always above 92% for PCG signals with cardiac abnormalities, signifying an improvement in heartbeat detection/classification above 10% compared to the other state-of-the-art methods evaluated.

CONCLUSIONS

The proposed method provides the best detection/classification performance in realistic scenarios where the presence of cardiac anomalies as well as different types of clinical environmental noises are active in the PCG signal. Of note, the promising modelling of the temporal structures of the heart provided by the dissimilarity matrix together with the frame-level spectral divergence, as well as the removal of a significant number of spurious heart events and recovery of missing heart events, both corrected by the proposed verification-correction-classification algorithm, suggest that our proposal is a successful tool to be applied in heart segmentation.

Prospective validation of an acoustic-based system for the detection of obstructive coronary artery disease in a high-prevalence population

Recent guidelines recommend a risk-adjusted, non-invasive work-up in patients presenting with chest discomfort to exclude coronary artery disease (CAD). However, a risk-adjusted diagnostic approach remains challenging in clinical practice. An acoustic detection device for analyzing micro-bruits induced by stenosis-generated turbulence in the coronary circulation has shown potential for ruling out CAD in patients with low-to-intermediate likelihood. We examined the diagnostic value of this acoustic detection system in a high-prevalence cohort. In total, 226 patients scheduled for clinically indicated invasive coronary angiography (ICA) were prospectively enrolled at two centers and examined using a portable, acoustic detection system. The acoustic analysis was performed in double-blinded fashion prior to quantitative ICA and following percutaneous coronary intervention (PCI). An acoustic detection result (CAD score) was obtained in 94% of all patients. The mean baseline CAD score was 41.2 ± 11.9 in patients with obstructive CAD and 33.8 ± 13.4 in patients without obstructive CAD (p < 0.001). ROC analysis revealed an AUC of 0.661 (95% CI 0.584-0.737). Sensitivity was 97.6% (95% confidence interval (CI) 91.5-99.7%), specificity was 14.5% (CI 9.0-21.7%), negative predictive value was 90.5% (CI 69.6-98.8%), and positive predictive value was 41.7% (CI 34.6-49.0%). Following PCI, the mean CAD score decreased from 40.5 ± 11.2 to 38.3 ± 13.7 (p = 0.039). Using an acoustic detection device identified individuals with CAD in a high-prevalence cohort with high sensitivity but relatively low specificity. The negative predictive value was within the predicted range and may be of value for a fast rule-out of obstructive CAD even in a high-prevalence population.

Onset of new diastolic murmur as a sign of bioprosthetic valve dysfunction: A case report

The diagnosis of prosthetic valve dysfunction remains challenging because visualization is limited due to artifacts on echocardiography. We herein report a case of bioprosthetic valve dysfunction, in which cardiac auscultation was useful as an initial clue to the diagnosis. An 81-year-old man, who had undergone bioprosthetic aortic valve replacement due to aortic stenosis 10 years earlier, presented to the emergency department with chest discomfort. Cardiac auscultation revealed a newly developed diastolic murmur, although no diastolic murmurs were previously detected on auscultation or phonocardiography. There were no notable changes in electrocardiography, chest radiograph, laboratory tests, or echocardiography except for trivial aortic regurgitation. His hemodynamic status progressively deteriorated due to prosthetic valve dysfunction, which was later confirmed on echocardiography, and aortic valve re-replacement was semi-urgently performed with success. The diastolic murmurs disappeared after surgery. <Learning objective: This case once again highlights the importance of cardiac auscultation for diagnosis even with the use of advanced imaging technology.>.

Non-invasive fetal monitoring using electrocardiography and phonocardiography: A preliminary study

BACKGROUND

Continuous fetal monitoring is commonly used during pregnancy and labor to assess fetal wellbeing. The most often used technology is cardiotocography (CTG), but this technique has major drawbacks in clinical use.

OBJECTIVES

Our aim is to test a non-invasive multimodal technique of fetal monitoring using phonocardiography (PCG) and electrocardiography (ECG) and to evaluate its feasibility in clinical practice, by comparison with CTG.

METHODS

This prospective open label study took place in a French university hospital. PCG and ECG signals were recorded using abdominal and thoracic sensors from antepartum women during the second half of pregnancy, simultaneously with CTG recording. Signals were then processed to extract fetal PCG and ECG and estimate fetal heart rate (FHR).

RESULTS

A total of 9 sets of recordings were evaluated. Very accurate fetal ECG and fetal PCG signals were recorded, enabling us to obtain FHR for several subjects. The FHR calculated from ECG was highly correlated with the FHR from the CTG reference (from 74% to 84% of correlation).

CONCLUSION

This work with preliminary signal processing algorithms proves the feasibility of the approach and constitutes the beginnings of a unique database that is needed to improve and validate the signal processing algorithms.

Third and Fourth Heart Sounds and Myocardial Fibrosis in Hypertrophic Cardiomyopathy

BACKGROUND

The 4th heart sound (S4) is commonly heard in patients with hypertrophic cardiomyopathy (HCM). The 3rd heart sound (S3) is also audible in HCM patients regardless of the presence or absence of heart failure. These extra heart sounds may be associated with myocardial fibrosis because myocardial fibrosis has been suggested to affect left ventricular compliance.Methods and Results:The present retrospective study evaluated 53 consecutive HCM patients with sinus rhythm who had no symptoms of heart failure and underwent an initial assessment including phonocardiography, echocardiography, and late gadolinium enhancement (LGE) magnetic resonance imaging (MRI). S3 was detected on phonocardiography in 13% of all patients, and S4 was recorded in 75% of patients. Patients with S3 had a higher incidence of LGE and larger LGE volumes (86% and 11.5±2.4 g/cm, respectively) than patients without S3 (33% and 2.5±0.8 g/cm, respectively; P=0.02 and P=0.002). The presence of S4 was not associated with MRI findings, including the incidence of LGE and LGE volume. The diagnostic value of S3 for the detection of LGE was highly specific (97%), with a low sensitivity (29%).

CONCLUSIONS

Myocardial fibrosis, as assessed by LGE, was associated with S3 but not with S4 in patients with HCM. These results may contribute to the risk stratification of patients with HCM.

Phonographic detection of mechanical heart valve thrombosis

The formation of thrombotic deposits affects the functionality of mechanical prosthetic heart valves; as a consequence, mechanical valves thrombosis needs early diagnosis to prevent thromboembolic events. This paper compares the acoustic signals produced by two commercial bileaflet mechanical heart valves in the closing phase to detect the presence of thrombi. The closing sounds were recorded in vitro by means of a phonocardiographic device under different hydrodynamic conditions. Thrombotic deposits of different weight and shape were applied onto the valve leaflet and the annular housing, until the movement of one leaflet was completely blocked. From the acoustic signals, the corresponding spectra were calculated and four diagnostic frequency bands were identified: their comparison allowed detecting malfunctioning valves because of the presence of thrombotic formations.

Initial Field Test of a Cloud-Based Cardiac Auscultation System to Determine Murmur Etiology in Rural China

A system for collection, distribution, and long distant, asynchronous interpretation of cardiac auscultation has been developed and field-tested in rural China. We initiated a proof-of-concept test as a critical component of design of a system to allow rural physicians with little experience in evaluation of congenital heart disease (CHD) to obtain assistance in diagnosis and management of children with significant heart disease. The project tested the hypothesis that acceptable screening of heart murmurs could be accomplished using a digital stethoscope and internet cloud transmittal to deliver phonocardiograms to an experienced observer. Of the 7993 children who underwent school-based screening in the Menghai District of Yunnan Province, Peoples Republic of China, 149 had a murmur noted by a screener. They had digital heart sounds and phonocardiograms collected with the HeartLink tele auscultation system, and underwent echocardiography by a cardiology resident from the First Affiliated Hospital of Kunming Medical University. The digital phonocardiograms, stored on a cloud server, were later remotely reviewed by a board-certified American pediatric cardiologist. Fourteen of these subjects were found to have CHD confirmed by echocardiogram. Using the HeartLink system, the pediatric cardiologist identified 11 of the 14 subjects with pathological murmurs, and missed three subjects with atrial septal defects, which were incorrectly identified as venous hum or Still's murmur. In addition, ten subjects were recorded as having pathological murmurs, when no CHD was confirmed by echocardiography during the field study. The overall test accuracy was 91% with 78.5% sensitivity and 92.6% specificity. This proof-of-concept study demonstrated the feasibility of differentiating pathologic murmurs due to CHD from normal functional heart murmurs with the HeartLink system. This field study is an initial step to develop a cost-effective CHD screening strategy in low-resource settings with a shortage of trained medical professionals and pediatric heart programs.

Heart monitoring systems--a review

To diagnose health status of the heart, heart monitoring systems use heart signals produced during each cardiac cycle. Many types of signals are acquired to analyze heart functionality and hence several heart monitoring systems such as phonocardiography, electrocardiography, photoplethysmography and seismocardiography are used in practice. Recently, focus on the at-home monitoring of the heart is increasing for long term monitoring, which minimizes risks associated with the patients diagnosed with cardiovascular diseases. It leads to increasing research interest in portable systems having features such as signal transmission capability, unobtrusiveness, and low power consumption. In this paper we intend to provide a detailed review of recent advancements of such heart monitoring systems. We introduce the heart monitoring system in five modules: (1) body sensors, (2) signal conditioning, (3) analog to digital converter (ADC) and compression, (4) wireless transmission, and (5) analysis and classification. In each module, we provide a brief introduction about the function of the module, recent developments, and their limitation and challenges.

Spectral analysis of the heart sounds in children with and without pulmonary artery hypertension

BACKGROUND

Pulmonary artery hypertension (PAH) is difficult to recognize clinically. Digital stethoscopes offer an opportunity to re-evaluate the diagnosis of PAH. We hypothesized that spectral analysis of heart sound frequencies using recordings from a digital stethoscope would differ between children with and without PAH.

METHODS

We recorded heart sounds using a digital stethoscope from 27 subjects (12 males) with a median age of 7 years (3 months to 19 years) undergoing simultaneous cardiac catheterization. 13 subjects had a mean pulmonary artery pressure (mPAp)<25 mm Hg (8-24 mm Hg). 14 subjects had a mPAp≥25 mm Hg (25-97 mm Hg). We applied the fast Fourier transform, power spectral analysis, separability testing, and linear discriminant analysis with leave-one-out cross-validation to the heart sounds recorded from the cardiac apex and 2nd left intercostal space (LICS) to examine the frequency domain. The significance of the results was determined using a t-test and rank-sum test.

RESULTS

The relative power of the frequencies 21-22 Hz of the heart sounds recorded at the 2nd LICS was decreased significantly in subjects mPAp≥25 mm Hg versus<25 mm Hg.

CONCLUSIONS

Heart sound signals of patients with PAH contain significantly less relative power in the band 21-22 Hz compared to subjects with normal PAp. Information contained in the frequency domain may be useful in diagnosing PAH and aid the development of auscultation based techniques for diagnosing PAH. In the future, utilizing the diagnostic information contained in heart sounds recordings may require analysis of both the time and frequency domains.

Heart sounds are altered by open cardiac surgery

BACKGROUND AND OBJECTIVE

Patients have reported that they perceive their own heart sounds differently after open cardiac surgery than before the surgery. The present study was designed to investigate whether changes in heart sounds can be quantitatively measured.

METHOD

Heart sounds were recorded from 57 patients undergoing coronary artery bypass graft (CABG) surgery and from a control group of 10 subjects. The so-called Hjorth descriptors and the main frequency peak were compared before and after surgery to determine whether the characteristics of the heart sounds had changed.

RESULTS

At a group level, the first heart sound was found to be significantly different after CABG surgery. Generally, the heart sounds shifted toward a lower frequency after surgery in the CABG group. No significant changes were found in the control group.

CONCLUSIONS

Heart sounds are altered after CABG surgery. The changes are objectively quantifiable and may also be subjectively perceived by the patients.