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The average pixel intensity method and outcome of mitral regurgitation in mitral valve prolapse

  • Kamoen, Victor
  • El Haddad, Milad
  • De Backer, Tine
  • De Buyzere, Marc
  • Timmermans, Frank
Publication Date
Jan 01, 2020
DOI: 10.1016/j.echo.2019.07.021
Ghent University Institutional Archive
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Background: Mitral regurgitation (MR) is a frequent consequence of mitral valve prolapse (MVP). However, the echocardiographic grading of MR is challenging, and the recommended grading parameters have several limitations. The authors developed a novel echocardiographic parameter to grade MR, the average pixel intensity (API) method, on the basis of pixel intensity analysis of the continuous-wave Doppler signal. Methods: Transthoracic echocardiography was performed prospectively in consecutive patients with MVP (N = 149). MR was quantitatively assessed using the API method, vena contracta width, effective regurgitant orifice area, and regurgitant volume. The primary clinical events were cardiovascular mortality, mitral valve surgery, percutaneous mitral intervention, and heart failure hospitalization. Results: The API method was feasible in 90% of all patients with MVP, which was significantly higher than vena contracta width, effective regurgitant orifice area, and regurgitant volume. During a median follow-up period of 17 months, 44 patients (32%) had major adverse cardiac events, and the majority of events occurred in the holosystolic MVP subgroup. The degree of MR severity by the API method was highly significant for the prediction of events. An API cutoff of 111 arbitrary units was defined as "severe" MR due to MVP, with overall superior sensitivity and specificity compared with cutoffs for established MR grading parameters. In patients who did not have major adverse cardiac events during the follow-up period (n = 92), no significant changes in measures of MR severity were found on follow-up echocardiography. Conclusions: The API method is predictive of clinical events and outcomes in MR due to MVP. Therefore, the API method may be considered for grading the severity of MR due to MVP in clinical practice.

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