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Background: Quantitative analysis of mitral valve morphology with three-dimensional (3D) transesophageal echocardiography (TEE) provides anatomic information that can assist clinical decision-making. However, routine use of mitral valve quantification has been hindered by tedious workflow and high operator-dependence. The purpose of this paper was to evaluate the feasibility, accuracy and efficiency of a novel computer-learning algorithm using anatomical intelligence in ultrasound (AIUS) to automatically detect and quantitatively assess the mitral valve anatomy., Methods: A novice operator used AIUS to quantitatively assess mitral valve anatomy on the 3D TEE images of 55 patients (33 with mitral valve prolapse, 11 with functional mitral regurgitation, and 11 normal valves). The results were compared to that of manual mitral valve quantification by an experienced 3D echocardiographer and, in the 24 patients who underwent mitral valve repair, the surgical findings. Time consumption and reproducibility of AIUS were compared to the manual method., Results: AIUS mitral valve quantification was feasible in 52 patients (95%). There were excellent agreements between AIUS and expert manual quantification for all mitral valve anatomic parameters (r=0.85-0.99, p<0.05). AIUS accurately classified surgically defined location of prolapse in 139 of 144 segments analyzed (97%). AIUS improved the intra- [intraclass-correlation coefficient (ICC)=0.91-0.99] and inter-observer (ICC=0.86-0.98) variability of novice users, surpassing the manual approach (intra-observer ICC=0.32-0.95; inter-observer ICC=0.45-0.93), yet requiring significantly less time (144±24s vs. 770±89s, p<0.0001)., Conclusion: Anatomic intelligence in 3D TEE image can provide accurate, reproducible, and rapid quantification of the mitral valve anatomy., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

The mitral valve (MV) has complex 3-dimensional (3D) morphology and motion. Advance in real-time 3D echocardiography (RT3DE) has revolutionized clinical imaging of the MV by providing clinicians with realistic visualization of the valve. Thus far, RT3DE of the MV structure and dynamics has adopted an approach that depends largely on subjective and qualitative interpretation of the 3D images of the valve, rather than objective and reproducible measurement. RT3DE combined with image-processing computer techniques provides precise segmentation and reliable quantification of the complex 3D morphology and rapid motion of the MV. This new approach to imaging may provide additional quantitative descriptions that are useful in diagnostic and therapeutic decision-making. Quantitative analysis of the MV using RT3DE has increased our understanding of the pathologic mechanism of degenerative, ischemic, functional, and rheumatic MV disease. Most recently, 3D morphologic quantification has entered into clinical use to provide more accurate diagnosis of MV disease and for planning surgery and transcatheter interventions. Current limitations of this quantitative approach to MV imaging include labor-intensiveness during image segmentation and lack of a clear definition of the clinical significance of many of the morphologic parameters. This review summarizes the current development and applications of quantitative analysis of the MV morphology using RT3DE.