title: Ultrasound phonocardiography for detecting thrombotic formations on bileaflet mechanical heart valves.
abstract: OBJECTIVE
  The main disadvantage of a mechanical heart valve (MHV) is thrombosis, a serious complication that is associated with high morbidity and mortality. The early detection of thrombotic formations is crucial for a prompt diagnosis and correct therapy before critical symptoms appear in patients. The present study describes the in-vitro assessment of thrombotic deposits by ultrasound phonocardiography on five commercially available bileaflet MHVs.
  
  
  METHODS
  The closing sounds produced by bileaflet MHVs were acquired in the frequency range from 6 to 55 kHz. The corresponding power spectra were calculated and then analyzed by an artificial neural network (ANN) trained to classify the presence of simulated thrombotic formations of different weight and shape. Simulations were performed in a Sheffield pulse duplicator under different hydrodynamic regimes.
  
  
  RESULTS
  Classification performances of the ANN depend on the range of frequency considered: better performances (up to 100% correct classification) are achieved when the entire spectrum is considered, rather than the audible (down to 87%) and ultrasound (down to 61%) regions, separately.
  
  
  CONCLUSIONS
  Good and very good classification performances are achieved in vitro when phonocardiography is applied to detect and analyze the closing sounds produced by MHVs. Interestingly, extension of the analysis to the ultrasound region can improve classification efficiency. This finding allows the consideration of potential clinical applications of the proposed method to assign an MHV recipient to a risk class, thus enabling a prompt diagnosis.
authors.affiliation: Department of Industrial Engineering, University of Padua, Padua, Italy.
authors.forename: Giacomo
authors.initials: G
authors.lastname: Melan
authors.affiliation: Department of Industrial Engineering, University of Padua, Padua, Italy.
authors.forename: Angela
authors.initials: A
authors.lastname: Bellato
authors.affiliation: Department of Civil, Environmental and Architectural Engineering, University of Padua, Padua.
authors.forename: Francesca Maria
authors.initials: FM
authors.lastname: Susin
authors.affiliation: Cardiovascular Surgery, University of Padua School of Medicine, Padua, Italy.
authors.forename: Tomaso
authors.initials: T
authors.lastname: Bottio
authors.affiliation: Cardiovascular Surgery, University of Padua School of Medicine, Padua, Italy.
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Tarzia
authors.affiliation: Clinical Cardiology, Department of Cardiologic, Thoracic and Vascular Sciences, University of Padua School of Medicine, Padua, Italy.
authors.forename: Vittorio
authors.initials: V
authors.lastname: Pengo
authors.affiliation: Cardiovascular Surgery, University of Padua School of Medicine, Padua, Italy.
authors.forename: Gino
authors.initials: G
authors.lastname: Gerosa
authors.affiliation: Department of Industrial Engineering, University of Padua, Padua, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Bagno
mesh_terms: D003198:Computer Simulation; D042241:Early Diagnosis; D006349:Heart Valve Diseases / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology; D006350:Heart Valve Prosthesis / Q000009:adverse effects*; D057446:Hydrodynamics; D008422:Materials Testing; D008955:Models, Cardiovascular; D016571:Neural Networks, Computer; D010701:Phonocardiography / Q000379:methods*; D011237:Predictive Value of Tests; D011474:Prosthesis Design; D012815:Signal Processing, Computer-Assisted; D013927:Thrombosis / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology; D014465:Ultrasonics