Methods for robust in vivo strain estimation in the carotid artery

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Cardiovascular Research

Background:

• Carotid artery plaque rupture is a major cause of stroke.
• Current imaging methods have limitations in characterizing plaque stability.
• Accurate assessment of plaque biomechanics is crucial for risk stratification.

Purpose of the Study:

• To develop and validate advanced algorithms for non-invasive carotid strain imaging.
• To improve the accuracy and robustness of displacement and strain estimation.
• To characterize plaque features indicative of instability using 2D strain tensor analysis.

Main Methods:

• Hierarchical block-matching motion tracking with Bayesian regularization and subsample interpolation.
• Modified least-squares strain estimation to handle noisy displacement and boundary discontinuities.
• Dynamic frame skip criterion for optimal data processing during the cardiac cycle.
• Accumulation algorithms for displacement and strain over the cardiac cycle.
• Novel visualization methods for the full 2D strain tensor.

Main Results:

• The developed algorithms provide robust and precise estimation of displacements and strain.
• Strain imaging successfully identified high-risk plaque features, including soft composition, unstable morphology, and abnormal hemodynamics.
• Specific strain patterns (e.g., maximum absolute principal strain > 0.2) correlated with vulnerable plaque characteristics near calcifications and turbulent flow.
• Correlation observed between plaque protrusion, low echogenicity, and high strain values.

Conclusions:

• Non-invasive carotid strain imaging, utilizing advanced motion tracking and estimation algorithms, is a promising tool.
• This technique can detect and characterize features of unstable carotid plaque, potentially improving stroke risk assessment.
• Further validation may establish strain imaging as a valuable component of carotid artery disease management.