title: Accurate and Standardized Coronary Wave Intensity Analysis.
abstract: Coronary wave intensity analysis (cWIA) has increasingly been applied in the clinical research setting to distinguish between the proximal and distal mechanical influences on coronary blood flow. Recently, a cWIA-derived clinical index demonstrated prognostic value in predicting functional recovery postmyocardial infarction. Nevertheless, the known operator dependence of the cWIA metrics currently hampers its routine application in clinical practice. Specifically, it was recently demonstrated that the cWIA metrics are highly dependent on the chosen Savitzky-Golay filter parameters used to smooth the acquired traces. Therefore, a novel method to make cWIA standardized and automatic was proposed and evaluated in vivo.
  
  
  
  The novel approach combines an adaptive Savitzky-Golay filter with high-order central finite differencing after ensemble-averaging the acquired waveforms. Its accuracy was assessed using in vivo human data. The proposed approach was then modified to automatically perform beat wise cWIA. Finally, the feasibility (accuracy and robustness) of the method was evaluated.
  
  
  
  The automatic cWIA algorithm provided satisfactory accuracy under a wide range of noise scenarios (≤10% and ≤20% error in the estimation of wave areas and peaks, respectively). These results were confirmed when beat-by-beat cWIA was performed.
  
  
  
  An accurate, standardized, and automated cWIA was developed. Moreover, the feasibility of beat wise cWIA was demonstrated for the first time.
  
  
  
  The proposed algorithm provides practitioners with a standardized technique that could broaden the application of cWIA in the clinical practice as enabling multicenter trials. Furthermore, the demonstrated potential of beatwise cWIA opens the possibility investigating the coronary physiology in real time.
authors.affiliation: Division of Imaging Science and Biomedical EngineeringKing's College London.
authors.forename: Simone
authors.initials: S
authors.lastname: Rivolo
authors.affiliation: Cardiovascular Division, King's College London.
authors.forename: Tiffany
authors.initials: T
authors.lastname: Patterson
authors.affiliation: Cardiovascular Division, King's College London.
authors.forename: Kaleab N
authors.initials: KN
authors.lastname: Asrress
authors.affiliation: Cardiovascular Division, King's College London.
authors.forename: Michael
authors.initials: M
authors.lastname: Marber
authors.affiliation: Cardiovascular Division, King's College London.
authors.forename: Simon
authors.initials: S
authors.lastname: Redwood
authors.affiliation: Faculty of EngineeringThe University of Auckland.
authors.forename: Nicolas P
authors.initials: NP
authors.lastname: Smith
authors.affiliation: Division of Imaging Science and Biomedical EngineeringKing's College London.
authors.forename: Jack
authors.initials: J
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity / Q000502:physiology*; D003326:Coronary Circulation / Q000502:physiology*; D003331:Coronary Vessels / Q000502:physiology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods* / Q000592:standards; D006801:Humans; D063177:Pulse Wave Analysis / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity