title: An automated four-point scale scoring of segmental wall motion in echocardiography using quantified parametric images.
abstract: The aim of this paper is to develop an automated method which operates on echocardiographic dynamic loops for classifying the left ventricular regional wall motion (RWM) in a four-point scale. A non-selected group of 37 patients (2 and 4 chamber views) was studied. Each view was segmented according to the standardized segmentation using three manually positioned anatomical landmarks (the apex and the angles of the mitral annulus). The segmented data were analyzed by two independent experienced echocardiographists and the consensual RWM scores were used as a reference for comparisons. A fast and automatic parametric imaging method was used to compute and display as static color-coded parametric images both temporal and motion information contained in left ventricular dynamic echocardiograms. The amplitude and time parametric images were provided to a cardiologist for visual analysis of RWM and used for RWM quantification. A cross-validation method was applied to the segmental quantitative indices for classifying RWM in a four-point scale. A total of 518 segments were analyzed. Comparison between visual interpretation of parametric images and the reference reading resulted in an absolute agreement (Aa) of 66% and a relative agreement (Ra) of 96% and kappa (κ) coefficient of 0.61. Comparison of the automated RWM scoring against the same reference provided Aa = 64%, Ra = 96% and κ = 0.64 on the validation subset. Finally, linear regression analysis between the global quantitative index and global reference scores as well as ejection fraction resulted in correlations of 0.85 and 0.79. A new automated four-point scale scoring of RWM was developed and tested in a non-selected database. Its comparison against a consensual visual reading of dynamic echocardiograms showed its ability to classify RWM abnormalities.
authors.affiliation: INSERM U 678, University Pierre et Marie Curie, CHU Pitié-Salpêtrière. 91, Boulevard de l'Hôpital, 75634 Paris Cedex 13, France. Nadjia.Kachenoura@imed.jussieu.fr
authors.forename: N
authors.initials: N
authors.lastname: Kachenoura
authors.forename: A
authors.initials: A
authors.lastname: Delouche
authors.forename: C
authors.initials: C
authors.lastname: Ruiz Dominguez
authors.forename: O
authors.initials: O
authors.lastname: Nardi
authors.forename: F
authors.initials: F
authors.lastname: Frouin
authors.forename: B
authors.initials: B
authors.lastname: Diebold
mesh_terms: D001331:Automation; D004452:Echocardiography / Q000379:methods*; D004699:Endocardium / Q000503:physiopathology; D005260:Female; D006352:Heart Ventricles / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009068:Movement; D017202:Myocardial Ischemia / Q000000981:diagnostic imaging / Q000503:physiopathology; D013318:Stroke Volume; D013997:Time Factors