TY - JOUR
T1 - Employment of artificial intelligence for an unbiased evaluation regarding the recovery of right ventricular function after mitral valve transcatheter edge-to-edge repair
AU - Fortmeier, Vera
AU - Hesse, Amelie
AU - Trenkwalder, Teresa
AU - Tokodi, Márton
AU - Kovács, Attila
AU - Rippen, Elena
AU - Tervooren, Jule
AU - Fett, Michelle
AU - Harmsen, Gerhard
AU - Yuasa, Shinsuke
AU - Kühlein, Moritz
AU - Covarrubias, Héctor Alfonso Alvarez
AU - von Scheidt, Moritz
AU - Roski, Ferdinand
AU - Gerçek, Muhammed
AU - Schuster, Tibor
AU - Mayr, N. Patrick
AU - Xhepa, Erion
AU - Laugwitz, Karl Ludwig
AU - Joner, Michael
AU - Rudolph, Volker
AU - Lachmann, Mark
N1 - Publisher Copyright:
© 2025 The Author(s). European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.
PY - 2025
Y1 - 2025
N2 - Aims: Long-standing severe mitral regurgitation (MR) leads to left atrial (LA) enlargement, elevated pulmonary artery pressures, and ultimately right heart failure. While mitral valve transcatheter edge-to-edge repair (M-TEER) alleviates left-sided volume overload, its impact on right ventricular (RV) recovery is unclear. This study aims to use both conventional echocardiography and artificial intelligence to assess the recovery of RV function in patients undergoing M-TEER for severe MR. Methods and results: The change in RV function from baseline to 3-month follow-up was analysed in a dual-centre registry of patients undergoing M-TEER for severe MR. RV function was conventionally assessed by measuring the tricuspid annular plane systolic excursion (TAPSE). Additionally, RV function was evaluated using a deep learning model that predicts RV ejection fraction (RVEF) based on two-dimensional apical four-chamber view echocardiographic videos. Among the 851 patients who underwent M-TEER, the 1-year survival rate was 86.8%. M-TEER resulted in a significant reduction in both LA volume and estimated systolic pulmonary artery pressure (sPAP) levels (median LA volume: from 123 ml [interquartile range, IQR 92–169 ml] to 104 ml [IQR 78–142 ml], p < 0.001; median sPAP: from 46 mmHg [IQR 35–58 mmHg] to 41 mmHg [IQR 32–54 mmHg], p = 0.036). In contrast, TAPSE remained unchanged (median: from 17 mm [IQR 14–21 mm] to 18 mm [IQR 15–21 mm], p = 0.603). The deep learning model confirmed this finding, showing no significant change in predicted RVEF after M-TEER (median: from 43.1% [IQR 39.1–47.4%] to 43.2% [IQR 39.2–47.2%], p = 0.475). Conclusions: While M-TEER improves left-sided haemodynamics, it does not lead to significant RV function recovery, as confirmed by both conventional echocardiography and artificial intelligence. This finding underscores the importance of treating patients before irreversible right heart damage occurs.
AB - Aims: Long-standing severe mitral regurgitation (MR) leads to left atrial (LA) enlargement, elevated pulmonary artery pressures, and ultimately right heart failure. While mitral valve transcatheter edge-to-edge repair (M-TEER) alleviates left-sided volume overload, its impact on right ventricular (RV) recovery is unclear. This study aims to use both conventional echocardiography and artificial intelligence to assess the recovery of RV function in patients undergoing M-TEER for severe MR. Methods and results: The change in RV function from baseline to 3-month follow-up was analysed in a dual-centre registry of patients undergoing M-TEER for severe MR. RV function was conventionally assessed by measuring the tricuspid annular plane systolic excursion (TAPSE). Additionally, RV function was evaluated using a deep learning model that predicts RV ejection fraction (RVEF) based on two-dimensional apical four-chamber view echocardiographic videos. Among the 851 patients who underwent M-TEER, the 1-year survival rate was 86.8%. M-TEER resulted in a significant reduction in both LA volume and estimated systolic pulmonary artery pressure (sPAP) levels (median LA volume: from 123 ml [interquartile range, IQR 92–169 ml] to 104 ml [IQR 78–142 ml], p < 0.001; median sPAP: from 46 mmHg [IQR 35–58 mmHg] to 41 mmHg [IQR 32–54 mmHg], p = 0.036). In contrast, TAPSE remained unchanged (median: from 17 mm [IQR 14–21 mm] to 18 mm [IQR 15–21 mm], p = 0.603). The deep learning model confirmed this finding, showing no significant change in predicted RVEF after M-TEER (median: from 43.1% [IQR 39.1–47.4%] to 43.2% [IQR 39.2–47.2%], p = 0.475). Conclusions: While M-TEER improves left-sided haemodynamics, it does not lead to significant RV function recovery, as confirmed by both conventional echocardiography and artificial intelligence. This finding underscores the importance of treating patients before irreversible right heart damage occurs.
KW - Deep learning
KW - Echocardiography
KW - Mitral regurgitation
KW - Right ventricular dysfunction
KW - Transcatheter edge-to-edge repair
UR - http://www.scopus.com/inward/record.url?scp=105007870744&partnerID=8YFLogxK
U2 - 10.1002/ejhf.3705
DO - 10.1002/ejhf.3705
M3 - Article
AN - SCOPUS:105007870744
SN - 1388-9842
JO - European Journal of Heart Failure
JF - European Journal of Heart Failure
ER -