-
The Medical Clinics of North America Sep 2016Valvular heart disease is a common condition in today's patient population. Accurate characterization of vital cardiac structures has become crucial to early diagnosis... (Review)
Review
Valvular heart disease is a common condition in today's patient population. Accurate characterization of vital cardiac structures has become crucial to early diagnosis and varied treatment options. The advent of ultrasound technology has had a large impact in cardiovascular medicine, particularly in the assessment of valvular heart disease. Today its versatility and availability have allowed it to become one of the most frequently ordered imaging tests for cardiovascular indications. Despite the tremendous evidence that suggests that clinical examinations are still standard of care, a large volume of referrals for echocardiograms suggests differently.
Topics: Echocardiography; Heart Murmurs; Heart Valve Diseases; Humans; Physical Examination; Practice Guidelines as Topic
PubMed: 27542419
DOI: 10.1016/j.mcna.2016.04.005 -
Pediatric Clinics of North America Feb 1998This review article outlines the significance and defines the skills important for the diagnosis and recognition of common innocent cardiac murmurs in childhood. The... (Review)
Review
This review article outlines the significance and defines the skills important for the diagnosis and recognition of common innocent cardiac murmurs in childhood. The origin of heart sounds and murmurs is reviewed, and an approach to pediatric murmur evaluation is presented. The seven innocent murmurs of childhood and adolescence are reviewed in detail. Further diagnostic evaluation and referral is dependent on the comfort factor and experience in recognition and correct characterization of these murmurs.
Topics: Child; Heart Auscultation; Heart Murmurs; Heart Sounds; Humans; Referral and Consultation
PubMed: 9491089
DOI: 10.1016/s0031-3955(05)70585-x -
Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning.Artificial Intelligence in Medicine Jul 2024To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and pathologic murmurs.
OBJECTIVE
To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and pathologic murmurs.
METHODS
We prospectively enrolled children under age 18 being evaluated by the Division of Pediatric Cardiology. Parents provided consent for a deidentified recording of their child's heart sounds with a digital stethoscope. Innocent murmurs were validated by a pediatric cardiologist and pathologic murmurs were validated by echocardiogram. To augment our collection of normal heart sounds, we utilized a public database of pediatric heart sound recordings (Oliveira, 2022). We propose two novel approaches for this audio classification task. We train a vision transformer on either Markov transition field or Gramian angular field image representations of the frequency spectrum. We benchmark our results against a ResNet-50 CNN trained on spectrogram images.
RESULTS
Our final dataset consisted of 366 normal heart sounds, 175 innocent murmurs, and 216 pathologic murmurs. Innocent murmurs collected include Still's murmur, venous hum, and flow murmurs. Pathologic murmurs included ventricular septal defect, tetralogy of Fallot, aortic regurgitation, aortic stenosis, pulmonary stenosis, mitral regurgitation and stenosis, and tricuspid regurgitation. We find that the Vision Transformer consistently outperforms the ResNet-50 on all three image representations, and that the Gramian angular field is the superior image representation for pediatric heart sounds. We calculated a one-vs-rest multi-class ROC curve for each of the three classes. Our best model achieves an area under the curve (AUC) value of 0.92 ± 0.05, 0.83 ± 0.04, and 0.88 ± 0.04 for identifying normal heart sounds, innocent murmurs, and pathologic murmurs, respectively.
CONCLUSION
We present two novel methods for pediatric heart sound classification, which outperforms the current standard of using a convolutional neural network trained on spectrogram images. To our knowledge, we are the first to demonstrate multi-class classification of pediatric murmurs. Multiclass output affords a more explainable and interpretable model, which can facilitate further model improvement in the downstream model development cycle and enhance clinician trust and therefore adoption.
Topics: Humans; Deep Learning; Heart Murmurs; Child; Child, Preschool; Infant; Adolescent; Prospective Studies; Heart Sounds; Female; Male; Algorithms; Diagnosis, Differential; Heart Auscultation
PubMed: 38723434
DOI: 10.1016/j.artmed.2024.102867 -
Annals of Internal Medicine Mar 1955
Topics: Cell Differentiation; Heart Murmurs; Heart Sounds; Mitral Valve Stenosis
PubMed: 14350484
DOI: 10.7326/0003-4819-42-3-644 -
American Heart Journal Feb 1968
Topics: Adult; Cineangiography; Diastole; Electrocardiography; Evaluation Studies as Topic; Female; Heart; Heart Auscultation; Heart Murmurs; Humans; Manometry; Mitral Valve Stenosis; Phonocardiography; Pulmonary Valve Insufficiency; Rheumatic Heart Disease
PubMed: 4951312
DOI: 10.1016/s0002-8703(68)90059-8 -
American Heart Journal May 1952
Topics: Cardiovascular Abnormalities; Cardiovascular System; Heart Defects, Congenital; Heart Murmurs; Heart Sounds; Humans; Lutembacher Syndrome
PubMed: 14923611
DOI: 10.1016/0002-8703(52)90044-6 -
American Practitioner and Digest of... Jan 1948
Topics: Heart; Heart Murmurs; Humans; Sound
PubMed: 18919965
DOI: No ID Found -
Clinical Pediatrics Aug 1983Three newborn infants were observed to have murmurs restricted to diastole. None was considered ill, and none has exhibited symptoms or findings of cardiopulmonary...
Three newborn infants were observed to have murmurs restricted to diastole. None was considered ill, and none has exhibited symptoms or findings of cardiopulmonary disease throughout follow-up. Localization of the diastolic timing and absence of a significant systolic component of the murmur were confirmed by phonocardiography. The transient nature of the finding was established by serial phonocardiography. Essentially normal cardiac anatomy was determined by routine chest radiograms, electrocardiograms, and echocardiography in both M and two-dimensional modes. Suggestive evidence for left-to-right shunting was present in each case. Invasive studies were not performed. An anatomic cause for the diastolic murmur was not discovered, suggesting it could be related to the ductus arteriosus or mild pulmonary insufficiency.
Topics: Diastole; Echocardiography; Electrocardiography; Female; Heart Auscultation; Heart Murmurs; Humans; Infant, Newborn; Myocardial Contraction; Phonocardiography; Time Factors
PubMed: 6861423
DOI: 10.1177/000992288302200805 -
Texas Reports on Biology and Medicine 1946
Topics: Heart; Heart Murmurs; Humans
PubMed: 20990202
DOI: No ID Found -
The Nurse Practitioner Mar 2011The ability of the NP to discern pediatric heart murmurs is critical for accurate assessment of etiology, appropriate diagnostic testing, and prudent referral when... (Review)
Review
The ability of the NP to discern pediatric heart murmurs is critical for accurate assessment of etiology, appropriate diagnostic testing, and prudent referral when indicated. This review includes an overview of cardiac assessment, distinguishing features of innocent and pathologic murmurs, differential diagnosis of murmurs, and current referral recommendations.
Topics: Child; Education, Nursing, Continuing; Heart Murmurs; Humans; Nurse Practitioners; Primary Health Care; Referral and Consultation
PubMed: 21307802
DOI: 10.1097/01.NPR.0000393968.36683.f0