Automated quantification of mitral valve tenting volume in functional mitral regurgitation by three‐dimensional echocardiography. Issue 7 (12th June 2020)

• Record Type: Journal Article
• Authors: Hübscher, Anne; Schwerg, Marius; Hoffmann, Saskia; Baldenhofer, Gerd; Heupel, Christian; Jasaityte, Ruta; Kruck, Sebastian; Stangl, Karl; Dreger, Henryk; Knebel, Fabian
• Is Part Of: Echocardiography. Volume 37:Issue 7(2020)
• Page Start: 1043
• Page End: 1048
• Publication Date: 2020-06-12
• Subjects: mitral regurgitation -- three‐dimensional echocardiography; Echocardiography -- Periodicals; Echocardiography -- Periodicals; 616.1207543
• DOI: 10.1111/echo.14759
• Languages: English
• ISSNs: 0742-2822

Abstract

Abstract: Background: Tenting of the mitral leaflets is a major pathophysiological factor contributing to functional mitral regurgitation (FMR). A novel software tool allows automated quantification of the tenting volume (TnV) by 3D transesophageal echocardiography (TEE). The aims of this study are to investigate the correlations of biometric patient characteristics with the TnV and whether a threshold value for the diagnosis of a moderate or severe FMR can be calculated for the TnV. Methods: This explorative and hypothesis‐generating study analyzed the TnV of the mitral valve obtained by clinically indicated TEE. The mid‐systolic, threefold calculated and averaged TnV from 80 patients with no or mild FMR and 27 patients with moderate or severe FMR was determined using the TomTec 4D MV Assessment tool. Results: The TnV correlated significantly with the body size ( r = 0.341), the weight ( r = 0.272), and the body surface area ( r = 0.320). After the adjustment to the body size, a threshold value of 1.25 cm 3 /m was determined for the TnV by using a receiver‐operating characteristic curve. This value distinguished moderate to severe from none to mild FMR with a sensitivity of 85% and a specificity of 71%. The intra‐observer variability and inter‐observer variability were determined to be 0.96 and 0.85, respectively. Conclusions: Automated assessment of TnV has the potential to support the diagnostic evaluation of FMR. Further studies are needed to validate this result, detect additional factors influencing the size of the TnV, and determine further thresholds for any degree of FMR.