title: Three-dimensional left ventricular segmentation from magnetic resonance imaging for patient-specific modelling purposes.
abstract: OBJECTIVE
  To propose a nearly automated left ventricular (LV) three-dimensional (3D) surface segmentation procedure, based on active shape modelling (ASM) and built on a database of 3D echocardiographic (3DE) LV surfaces, for cardiac magnetic resonance (CMR) images, and to test its accuracy for LV volumes computation compared with 'gold standard' manual tracings and discs-summation method.
  
  
  RESULTS
  The ASM was created based on segmented LV surfaces (4D LV analysis, Tomtec) from 3DE datasets of 205 patients. Then, it was applied to the cardiac magnetic resonance imaging short-axis (SAX) images stack of 12 consecutive patients. After proper realignment using two- and four-chambers CMR long-axis views both as reference and for initializing LV apex and base (six points in total), the ASM was iteratively and automatically updated to match the information of all the SAX planes contemporaneously, resulting in an endocardial LV 3D mesh from which volume was directly derived. The same CMR images were analysed by an experienced cardiologist to derive end-diastolic and end-systolic volumes. Linear correlation and Bland-Altman analyses were applied vs. the manual 'gold standard'. Active shape modelling results showed high correlations with manual values both for LV volumes (r(2) > 0.98) and ejection fraction (EF) (r(2) > 0.90), non-significant biases and narrow limits of agreement.
  
  
  CONCLUSIONS
  The proposed method resulted in accurate detection of 3D LV endocardial surfaces, which lead to fast and reliable measurements of LV volumes and EF when compared with manual tracing of CMR SAX images. The segmented 3D mesh, including a realistic LV apex and base, could constitute a novel starting point for more realistic patient-specific finite element modelling.
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza L. da Vinci, 32, 20133 Milan, Italy enrico.caiani@polimi.it.
authors.forename: Enrico G
authors.initials: EG
authors.lastname: Caiani
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza L. da Vinci, 32, 20133 Milan, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Colombo
authors.affiliation: IRCCS Centro Cardiologico Monzino, 20138 Milan, Italy.
authors.forename: Mauro
authors.initials: M
authors.lastname: Pepi
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza L. da Vinci, 32, 20133 Milan, Italy Center for Computational Medicine in Cardiology, Universitá della Svizzera Italiana, 6900 Lugano, Switzerland.
authors.forename: Concetta
authors.initials: C
authors.lastname: Piazzese
authors.affiliation: Noninvasive imaging Laboratories, University of Chicago Medical Center, 60637 Chicago, USA.
authors.forename: Francesco
authors.initials: F
authors.lastname: Maffessanti
authors.affiliation: Noninvasive imaging Laboratories, University of Chicago Medical Center, 60637 Chicago, USA.
authors.forename: Roberto M
authors.initials: RM
authors.lastname: Lang
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza L. da Vinci, 32, 20133 Milan, Italy IRCCS Centro Cardiologico Monzino, 20138 Milan, Italy.
authors.forename: Maria Chiara
authors.initials: MC
authors.lastname: Carminati
mesh_terms: D000465:Algorithms; D001331:Automation; D003196:Computer Graphics; D003198:Computer Simulation; D005240:Feasibility Studies; D006331:Heart Diseases / Q000473:pathology* / Q000503:physiopathology; D006352:Heart Ventricles / Q000473:pathology* / Q000503:physiopathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008955:Models, Cardiovascular; D010865:Pilot Projects; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012189:Retrospective Studies; D016277:Ventricular Function, Left
keywords: Active shape models; Cardiac magnetic resonance imaging; Image segmentation; Left ventricular volume; Patient-specific modelling