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Related Experiment Video

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Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

Adaptive postprocessing techniques for myocardial tissue tracking with displacement-encoded MR imaging.

Han Wen1, Keith A Marsolo, Eric E Bennett

  • 1National Heart, Lung and Blood Institute, National Institutes of Health, Bldg 10, B1D416, 10 Center Dr, Bethesda, MD 20892, USA. wenh@nhlbi.nih.gov

Radiology
|December 22, 2007
PubMed
Summary
This summary is machine-generated.

Adaptive postprocessing techniques significantly improved myocardial function evaluation using displacement-encoded magnetic resonance (MR) imaging. These methods reduced phase-unwrapping failures and enhanced the detection of abnormal wall motion in patients.

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Area of Science:

  • Cardiovascular imaging
  • Medical physics
  • Biomedical engineering

Background:

  • Myocardial function assessment is crucial for diagnosing cardiac diseases.
  • Displacement-encoded magnetic resonance (MR) imaging offers detailed insights into myocardial mechanics.
  • Current postprocessing techniques can limit the accuracy and reliability of MR imaging analysis.

Purpose of the Study:

  • To prospectively evaluate the impact of adaptive postprocessing techniques on myocardial function assessment using displacement-encoded MR imaging.
  • To compare the sensitivity for detecting abnormal wall motion against two-dimensional echocardiography.
  • To determine if adaptive techniques improve the accuracy and reduce variability in strain measurements.

Main Methods:

  • Prospective study involving 16 patients and 12 healthy volunteers.
  • Breath-hold displacement-encoded MR imaging was performed.
  • Adaptive phase-unwrapping and spatial filtering were compared to conventional methods.

Main Results:

  • Adaptive techniques reduced phase-unwrapping failure rates from 18.9% to 0.6% (P < .001).
  • Variability in segmental strain measurements among healthy volunteers decreased significantly (P < .001 to P = .02).
  • Sensitivity for detecting abnormal segments in patients increased from 82.5% to 87.7% (P = .034).

Conclusions:

  • Adaptive postprocessing techniques enhance the reliability of displacement-encoded cardiac MR imaging.
  • These methods improve the semiautomated analysis of cardiac images.
  • The adaptive approach increases the sensitivity for detecting abnormal myocardial wall motion.