Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Cardiovascular Research

Background:

• Phase velocity magnetic resonance imaging (MRI) offers potential for tracking myocardial motion during the cardiac cycle.
• Phase contrast MR imaging captures velocity data, enabling pixel-level tissue motion analysis.

Purpose of the Study:

• To detail three algorithms for motion tracking using phase contrast MRI velocity maps.
• To evaluate algorithm performance using simulated, phantom, and in vivo data.
• To address practical challenges in motion tracking, including noise, phase errors, and tissue deformation.

Main Methods:

• Development and detailed presentation of three distinct motion tracking algorithms.
• Utilized simulated and phantom data to test algorithm robustness against noise and phase errors.
• Assessed the impact of tissue expansion/contraction, dimensionality (2D vs. 3D), and small motion errors.

Main Results:

• Examined the influence of noise and phase errors on each tracking algorithm.
• Investigated issues related to tissue expansion, contraction, and motion relative to pixel size.
• Demonstrated the efficacy of the optimal algorithm in measuring left ventricular circumferential shortening in a canine model.

Conclusions:

• The study provides robust algorithms for phase contrast MRI-based myocardial motion tracking.
• The developed methods address key challenges in accurately quantifying cardiac motion.
• The best algorithm shows promise for assessing myocardial function, particularly in post-infarct scenarios.