Insights into functional mitral regurgitation using the average pixel intensity method

Victor Kamoen1, Milad El Haddad2, Tine De Backer2

  • 1Department of Cardiology, Heart Center, Ghent University Hospital, Cornelis Heymanslaan 10, 10-K12, 9000, Ghent, Belgium. victor.kamoen@ugent.be.

Insights

The average pixel intensity (API) method effectively grades functional mitral regurgitation (FMR) with high applicability. This fast, feasible parameter correlates with FMR severity and complements current assessments.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Echocardiography

Background:

  • Functional mitral regurgitation (FMR) assessment is complex.
  • Existing methods like vena contracta width (VCW) and proximal isovelocity surface area (PISA) have limitations in applicability.
  • The average pixel intensity (API) method was previously validated for general mitral regurgitation (MR).

Purpose of the Study:

  • To investigate the feasibility and added value of the API method specifically for grading functional mitral regurgitation (FMR).
  • To compare the applicability and correlation of the API method with guideline-recommended parameters in FMR patients.

Main Methods:

  • 283 patients with pure FMR underwent transthoracic echocardiography.
  • Mitral regurgitation (MR) was assessed using the API method, color Doppler, VCW, and PISA-based methods.
  • API dynamics during MR were analyzed and correlated with FMR severity and clinical parameters.

Main Results:

  • The API method demonstrated 98% applicability in FMR patients, significantly higher than VCW (84%) and PISA (75%).
  • API showed significant correlations with FMR severity, ejection fraction, chamber dimensions, pulmonary pressures, and NYHA class.
  • An optimal API cut-off of 125 au was identified for severe FMR, consistent with degenerative MR (DMR) cut-offs.

Conclusions:

  • The API method is a feasible, fast, and easy-to-use parameter for grading FMR.
  • API can complement multiparametric assessments in clinical practice for FMR.
  • The consistent severity cut-off across FMR and DMR suggests a robust grading capability of the API method.

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