Related Experiment Video

Updated: Jun 19, 2026

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
11:04

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

Published on: September 1, 2014

Past, Present, and Future of Evaluating Diastolic Function

Sherif F Nagueh1

  • 1Department of Cardiology, Methodist DeBakey Heart and Vascular Center, Houston, TX.

Circulation. Cardiovascular Imaging
|June 18, 2026
PubMed

Insights

Diagnosing diastolic dysfunction and heart failure with preserved ejection fraction is evolving. New echocardiography methods and artificial intelligence show promise for more accurate assessments beyond current guidelines.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence in Medicine

Background:

  • Left ventricular diastolic function assessment has transitioned from invasive pressure measurements to primarily echocardiography.
  • Current diagnostic methods involve mitral inflow, tissue Doppler, tricuspid regurgitation, pulmonary vein flow, left atrial size/function, and estimated right atrial pressure.
  • The 2025 American Society of Echocardiography guidelines offer an algorithm for mean left atrial pressure estimation, validated in a large multicenter study.

Purpose of the Study:

  • To review current and emerging methods for assessing left ventricular diastolic function.
  • To evaluate the diagnostic value of updated echocardiographic algorithms for heart failure with preserved ejection fraction.
  • To explore the role of artificial intelligence in diagnosing diastolic dysfunction and heart failure with preserved ejection fraction.

Main Methods:

  • Review of current echocardiographic parameters for diastolic function assessment.
  • Validation of a new algorithm for mean left atrial pressure estimation against invasive methods and clinical scores.
  • Exploration of novel techniques like shear wave propagation velocity, left atrial conduit volume, and valve opening timing.
  • Application of artificial intelligence, including rule-based algorithms and deep learning neural networks.

Main Results:

  • The validated algorithm for mean left atrial pressure estimation demonstrated incremental value in diagnosing heart failure with preserved ejection fraction.
  • Newer echocardiographic approaches show promise for studying diastolic function.
  • Artificial intelligence models are being developed for diagnosing and grading diastolic dysfunction and heart failure with preserved ejection fraction.

Conclusions:

  • Echocardiography remains central to diastolic function assessment, with ongoing advancements improving accuracy.
  • Validated algorithms and novel imaging techniques enhance the diagnosis of diastolic dysfunction and heart failure with preserved ejection fraction.
  • Artificial intelligence holds significant potential to further refine the diagnosis and management of these conditions.

Keywords:
atrial pressureechocardiographyheart failurepulmonary arterypulmonary veins

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