Coronary Artery Disease Detected by Low Frequency Heart Sounds

Schmidt, Samuel; Madsen, Lene Helleskov; Hansen, John H. L.; Zimmermann, H.; Kelbæk, Henning; Winter, Sabrina De; Hammershøi, Dorte; Toft, Egon; Struijk, Johannes; Clemmensen, Peter

doi:10.1007/s13239-022-00622-6

Cited by 7 publications

(10 citation statements)

References 27 publications

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“…Moreover, CAD can occur at very low frequencies, which might have been the cause of more selections from the range of 18-70. 45 Feature analysis. Figure 8 shows the most important selected physiological and statistical features in the unbalanced and balanced conditions of the dataset.…”

Section: Resultsmentioning

confidence: 99%

Effective features extraction by analyzing heart sound for identifying cardiovascular diseases related to COVID-19: A diagnostic model

Sabouri

Ghadimi

Kiani-Sarkaleh

et al. 2022

Proc Inst Mech Eng H

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Incidence and exacerbation of some of the cardiovascular diseases in the presence of the coronavirus will lead to an increase in the mortality rate among patients. Therefore, early diagnosis of such diseases is critical, especially during the COVID-19 pandemic (mild COVID-19 infection). Thus, for diagnosing the heart diseases related to the COVID-19, an automatic, non-invasive, and inexpensive method based on the heart sound processing approach is proposed. In the present study, a set of features related to the nature of heart signals is defined and extracted. The investigated features included morphological and statistical features in the heart sound frequencies. By extracting and selecting a set of effective features related to the mentioned diseases, and avoiding to use different segmentation and filtering techniques, dependence on a limited dataset and specific sampling procedures has been eliminated. Different classifiers with various kernels are applied for diagnosis in data unbalanced and balanced conditions. The results showed 93.15% accuracy and 93.72% F1-score using 60 effective features in data balanced conditions. The identification system using the extracted features from Azad dataset is able to achieve the desired results in a generalized dataset. In this way, in the shortest possible sampling time, the present system provided an effective and generalizable method and a practical model for diagnosing important cardiovascular diseases in the presence of coronavirus in the COVID-19 pandemic.

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Section: Resultsmentioning

confidence: 99%

Effective features extraction by analyzing heart sound for identifying cardiovascular diseases related to COVID-19: A diagnostic model

Sabouri

Ghadimi

Kiani-Sarkaleh

et al. 2022

Proc Inst Mech Eng H

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“…Third, the effects of changes in participants' hemodynamic factors (including heart rate and blood pressure) on the accuracy and reproducibility of the test results during the heart sounds collection process remains to be determined. Fourth, no reports have evaluated the overall diagnostic performance of the acoustic method for one-vessel and multi-vessel lesions, different vessels, or lesions in different segments of the same vessel [11,24]. Although our study initially evaluated the sensitivity of the acoustic analysis method for single-vessel and multi-vessel lesions, we did not assess overall diagnostic performance in different lesion types.…”

Section: Discussionmentioning

confidence: 98%

Diagnosis of Coronary Artery Disease by Acoustic Analysis of Turbulent Murmur Caused by Coronary Artery Stenosis: A Single Center Study from China

Zhao

Huang

Xiao

et al. 2023

CVIA

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Aim: Intracoronary murmur results from turbulent flow due to coronary artery narrowing. This study evaluated the diagnostic performance of a method for acoustic analysis of turbulent murmur caused by coronary artery stenosis in coronary artery disease (CAD) in Chinese populations. Method: Patients admitted to the cardiovascular department of the Sixth Medical Center of the Chinese People’s Liberation Army General Hospital between September 2021 and June 2022 for elective coronary angiography were prospectively enrolled. A digital electronic stethoscope was used to record heart sounds before angiography. Quantitative coronary angiography (QCA) served as the “gold standard” for CAD diagnosis to evaluate the diagnostic performance of the acoustic analysis method for CAD. Results: A total of 452 patients had complete QCA and heart sound data. The final interpretation results of the acoustic analysis method indicated 310 disease cases and 142 normal results. Increasing the cut-off values of coronary artery diameter stenosis from 30% to 50%, 70%, and 90% increased the sensitivity and NPV of the acoustic analysis method; the sensitivity was 75.6%, 81.9%, 83.3%, and 85.7%, respectively; the NPV was 33.1%, 57.0%, 69.7%, and 88.0%, respectively; the specificity and PPV decreased (specificity of 75.8%, 70.4%, 51.0%, and 37.5%, respectively; PPV of 95.2%, 89.0%, 69.4%, and 32.9%, respectively); and the AUC values were 0.757, 0.762, 0.672, and 0.616, respectively. The sensitivity of the acoustic analysis method for one-vessel disease was 86.6% when the cut-off value was 50%. The sensitivity for identifying left anterior descending coronary artery lesions was best, at 90.7%. The sensitivity for identifying isolated coronary artery branch lesions was 66.7%, whereas the sensitivity for identifying three-vessel disease in multi-vessel coronary artery lesions was better, at 82.9%. Conclusion: Acoustic analysis of turbulent murmur caused by coronary artery stenosis for diagnosis of CAD may have favorable performance in the Chinese population. This method has good performance in CAD diagnosis with a cut-off coronary artery diameter for stenosis of 50%.

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“…Acoustic detection of coronary stenosis is a method that can be used as an exclusion diagnostic tool for obstructive CAD. Acoustic detection of coronary stenosis is a noninvasive and X-ray-free technology based on the turbulent blood ow in the coronary arteries caused by stenosis [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Clinical utility of the acoustic detection of coronary stenosis as an early rule-out criterion: a blinded, prospective, monocentric study versus standard care

Birkemeyer¹,

Wittenberg

Müller

et al. 2023

Preprint

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Background: The CADScor®System is a noninvasive and radiation-free technology that searches for stenosis induced by turbulent coronary blood flow. A CADSscore represents the acoustic detection results of coronary stenoses. We assessed consecutive patients with stable symptoms without known coronary artery disease (CAD) to define a low risk for obstructive CAD based on a low CAD score than a standard approach of clinical assessment using noninvasive and invasive diagnostic measurements. Methods: Overall, 214 consecutive patients aged ˃40 years in a German cardiological outpatient unit were included. Patients underwent an initial clinical assessment, a double-blinded CAD score, standard examinations, and a national guidance-based diagnostic cascade. They underwent a 6-month telephone follow-up to capture future CAD events. A CAD score of ≤20 was defined as low risk. Results: Overall, 196 patients completed the planned diagnostic workup after their initial visit, and 187 had a valid CAD score. All 196 patients underwent an electrocardiogram (ECG) and echocardiography, and 178 patients underwent a stress ECG. According to the initial standard evaluation, 41 patients were considered to be low-risk without further diagnosis. A CAD score of ≤20 was found in 51 patients. According to clinical standards, 85 and 77 patients underwent noninvasive testing and invasive angiography, respectively. The obstructive CAD was invasively diagnosed in 25 patients, of whom 4 had a CAD score of ≤20. No additional CAD was detected at the 6-month follow-up. Overall, 41 of the 165 noninvasive and invasive diagnostic procedures could have been avoided with a CAD score of ≤20 as the exclusion criterion for further diagnosis after the standard initial diagnosis. Furthermore, 10 of the 52 invasive procedures without evidence of obstructive CAD could have been prevented. Conclusions: The obstructive CAD was confirmed in 12.8% of patients with stable symptoms and suspected CAD. Therefore, advanced noninvasive testing was mainly used for further CAD exclusion. The diagnostic yield of invasive angiography was low, and approximately a quarter of further diagnostic procedures could have been avoided with the CAD score, which showed an acceptable false-negative rate compared with the standard diagnostic tools. Trial registration: Deutsches Register Klinischer Studien (DRKS): DRKS00016986 (22/03/2019)

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Coronary Artery Disease Detected by Low Frequency Heart Sounds

Cited by 7 publications

References 27 publications

Effective features extraction by analyzing heart sound for identifying cardiovascular diseases related to COVID-19: A diagnostic model

Effective features extraction by analyzing heart sound for identifying cardiovascular diseases related to COVID-19: A diagnostic model

Diagnosis of Coronary Artery Disease by Acoustic Analysis of Turbulent Murmur Caused by Coronary Artery Stenosis: A Single Center Study from China

Clinical utility of the acoustic detection of coronary stenosis as an early rule-out criterion: a blinded, prospective, monocentric study versus standard care

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