title: Semi-automated segmentation and quantification of mitral annulus and leaflets from transesophageal 3-D echocardiographic images.
abstract: Quantification of three-dimensional (3-D) morphology of the mitral valve (MV) using real-time 3-D transesophageal echocardiography (RT3-D TEE) has proved to be a valuable tool for the assessment of MV pathologies, but of limited use in clinical practice because it relies on user-intensive approaches. This study presents a new algorithm for the segmentation and morphologic quantification of the mitral annulus (MA) and mitral leaflets (ML) in closed valve configuration from RT3-D TEE volumes. Following initialization, the MA and the ML and the coaptation line (CL) are automatically obtained in 3-D. Validation with manual tracings was performed on 33 patients, resulting in segmentation errors in the order of 0.7 mm and 0.6 mm for the MA and ML segmentation, in addition to good intra- and inter-observer reproducibility (coefficients of variation below 12% and 15%, respectively). The ability of the algorithm to assess different MV pathologies as well as repaired valves with implanted annular rings was also explored. The reported performance of the proposed fast, semi-automated MA and ML quantification makes it promising for future applications in clinical settings such as the operating room, where obtaining results in short time is important.
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.
authors.forename: Miguel
authors.initials: M
authors.lastname: Sotaquira
authors.affiliation: Centro Cardiologico Monzino IRCCS, Milan, Italy.
authors.forename: Mauro
authors.initials: M
authors.lastname: Pepi
authors.affiliation: Centro Cardiologico Monzino IRCCS, Milan, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Fusini
authors.affiliation: Centro Cardiologico Monzino IRCCS, Milan, Italy; Noninvasive Cardiac Imaging Laboratory, University of Chicago, Chicago, IL, USA.
authors.forename: Francesco
authors.initials: F
authors.lastname: Maffessanti
authors.affiliation: Noninvasive Cardiac Imaging Laboratory, University of Chicago, Chicago, IL, USA.
authors.forename: Roberto M
authors.initials: RM
authors.lastname: Lang
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy. Electronic address: enrico.caiani@polimi.it.
authors.forename: Enrico G
authors.initials: EG
authors.lastname: Caiani
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019560:Echocardiography, Three-Dimensional / Q000379:methods*; D017548:Echocardiography, Transesophageal / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008943:Mitral Valve / Q000000981:diagnostic imaging*; D008944:Mitral Valve Insufficiency / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Block-matching; Echocardiography; Graph-based segmentation; Mitral annulus; Mitral leaflets; Mitral valve; Mitral valve quantification