Deep Learning-Based Automated Pressure-Strain Loop Analysis

Condition(s) studied

Investigational drug(s) / intervention(s)

Sustained Isometric Handgrip Exercise: Participants perform sustained isometric handgrip at around 30 % of maximal voluntary contraction for 5 minutes during echocardiography.

Semi-Supine Bicycle Exercise: Participants perform graded semi-supine bicycle exercise during echocardiography.

Study summary

Noninvasive left ventricular pressure-strain loop analysis estimates myocardial work from longitudinal strain, brachial systolic blood pressure, and cardiac valve-event timing. It provides global work index, constructive work, wasted work, and work efficiency.

This study evaluates a deep-learning method that automates myocardial work and loop-shape analysis. The method may reduce analysis time, improve reproducibility, and identify patterns associated with heart failure.

Eligibility

Primary outcome measure(s)

• Echocardiographic Acquisition Success — During one study visit: at rest, during the handgrip and bicycle test.
  Percentage of acquired examinations successfully processed by the deep-learning pipeline to generate myocardial work indices, assessed separately at rest, during handgrip, and during bicycle exercise.

Trial sites (1)

More Norwegian University of Science and Technology trials in Norway

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