Magnetic resonance derived myocardial strain assessment using feature tracking

Area of Science:

• Cardiovascular Imaging
• Medical Image Analysis
• Biomedical Engineering

Background:

• Myocardial strain is a sensitive indicator of cardiac contractile dysfunction, often preceding ejection fraction (EF) changes.
• Current cardiac magnetic resonance imaging (CMR) techniques for strain analysis are time-consuming and challenging for clinical implementation.
• Feature tracking offers a potential solution for automated, robust, and efficient quantitative analysis of medical images.

Purpose of the Study:

• To develop and validate an accurate and practical method for measuring myocardial tissue parameters, such as strain, using CMR.
• To assess the potential of feature tracking technology for automating quantitative analysis in CMR, reducing time consumption.
• To establish a method suitable for clinical practice, offering a more sensitive marker for early contractile dysfunction detection.

Main Methods:

• An automated or manual single-phase input initializes the system for tracking anatomical structure displacements over time.
• The feature tracking method does not require pre-manipulation of images, such as tagging, simplifying the workflow.
• The system tracks individual patterns representing anatomical structures to quantify motion and deformation.

Main Results:

• The developed method demonstrates high suitability for tracking muscular tissue, enabling quantitative analysis of myocardial motion.
• The technique allows for the quantitative elaboration of both myocardium and blood flow dynamics.
• The feature tracking approach provides robust and time-efficient quantification of displacement, velocity, and deformation parameters.

Conclusions:

• This novel feature tracking method provides a robust and time-saving procedure for quantifying myocardial and blood parameters from standard CMR sequences.
• The method's efficiency and accuracy make it suitable for implementation in routine clinical practice.
• It offers a valuable tool for the early and sensitive detection of cardiac contractile dysfunction.