OBJECTIVES: The complexity of the mitral valve (MV) anatomy and function is not yet fully understood. Assessing the dynamic movement and interaction of MV components to define MV physiology during the complete cardiac cycle remains a challenge. We herein describe a novel semi-automated 4D MV model. METHODS: The model applies quantitative analysis of the MV over a complete cardiac cycle based on real-time 3D transoesophageal echocardiography (RT3DE) data. RT3DE data of MVs were acquired for 18 patients. The MV annulus and leaflets were semi-automatically reconstructed. Dimensions of the mitral annulus (anteroposterior and anterolateral-posteromedial diameter, annular circumference, annular area) and leaflets (MV orifice area, intercommissural distance) were acquired. Variability and reproducibility (intraclass correlation coefficient, ICC) for interobserver and intraobserver comparison were quantified at 4 time points during the cardiac cycle (mid-systole, end-systole, mid-diastole and end-diastole). RESULTS: Mitral annular dimensions provided highly reliable and reproducible measurements throughout the cardiac cycle for interobserver (variability range, 0.5-1.5%; ICC range, 0.895-0.987) and intraobserver (variability range, 0.5-1.6%; ICC range, 0.827-0.980) comparison, respectively. MV leaflet parameters showed a high reliability in the diastolic phase (variability range, 0.6-9.1%; ICC range, 0.750-0.986), whereas MV leaflet dimensions showed a high variability and lower correlation in the systolic phase (variability range, 0.6-22.4%; ICC range, 0.446-0.915) compared with the diastolic phase. CONCLUSIONS: This 4D model provides detailed morphological reconstruction as well as sophisticated quantification of the complex MV structure and dynamics throughout the cardiac cycle with a precision not yet described.
OBJECTIVES: The complexity of the mitral valve (MV) anatomy and function is not yet fully understood. Assessing the dynamic movement and interaction of MV components to define MV physiology during the complete cardiac cycle remains a challenge. We herein describe a novel semi-automated 4D MV model. METHODS: The model applies quantitative analysis of the MV over a complete cardiac cycle based on real-time 3D transoesophageal echocardiography (RT3DE) data. RT3DE data of MVs were acquired for 18 patients. The MV annulus and leaflets were semi-automatically reconstructed. Dimensions of the mitral annulus (anteroposterior and anterolateral-posteromedial diameter, annular circumference, annular area) and leaflets (MV orifice area, intercommissural distance) were acquired. Variability and reproducibility (intraclass correlation coefficient, ICC) for interobserver and intraobserver comparison were quantified at 4 time points during the cardiac cycle (mid-systole, end-systole, mid-diastole and end-diastole). RESULTS: Mitral annular dimensions provided highly reliable and reproducible measurements throughout the cardiac cycle for interobserver (variability range, 0.5-1.5%; ICC range, 0.895-0.987) and intraobserver (variability range, 0.5-1.6%; ICC range, 0.827-0.980) comparison, respectively. MV leaflet parameters showed a high reliability in the diastolic phase (variability range, 0.6-9.1%; ICC range, 0.750-0.986), whereas MV leaflet dimensions showed a high variability and lower correlation in the systolic phase (variability range, 0.6-22.4%; ICC range, 0.446-0.915) compared with the diastolic phase. CONCLUSIONS: This 4D model provides detailed morphological reconstruction as well as sophisticated quantification of the complex MV structure and dynamics throughout the cardiac cycle with a precision not yet described.
Authors: Iolanda Aquila; Ariana González; Covadonga Fernández-Golfín; Luis Miguel Rincón; Eduardo Casas; Ana García; Rocio Hinojar; José Julio Jiménez-Nacher; José Luis Zamorano Journal: Cardiovasc Ultrasound Date: 2016-05-17 Impact factor: 2.062
Authors: Iolanda Aquila; Covadonga Fernández-Golfín; Luis Miguel Rincon; Ariana González; Ana García Martín; Rocio Hinojar; Jose Julio Jimenez Nacher; Ciro Indolfi; Jose Luis Zamorano Journal: Medicine (Baltimore) Date: 2016-12 Impact factor: 1.817