Spline-based cardiac motion tracking using velocity-encoded magnetic resonance imaging

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Cardiovascular Research

Background:

• Cardiac motion and deformation tracking are crucial for diagnosing heart conditions.
• Velocity-encoded magnetic resonance imaging (VE-MRI) offers a method for assessing cardiac dynamics.
• Existing methods require refinement for improved accuracy and robustness.

Purpose of the Study:

• To improve cardiac motion and deformation tracking using VE-MRI.
• To evaluate the efficacy of different spatial elements in a spatiotemporal motion model.
• To investigate the complementary role of optical flow in noisy VE-MRI data.

Main Methods:

• Fitting a spatiotemporal motion model to VE-MRI velocity data.
• Investigating various spatial elements for motion modeling using phantom and human subject data.
• Employing Horn-Schunk optical flow estimation to supplement noisy VE-MRI regions.

Main Results:

• Good motion tracking accuracy achieved in phantoms with carefully selected spatial elements.
• Optical flow can mitigate some measurement artifacts but may underestimate deformation magnitude.
• Quantitative performance of different spatial elements was similar in human subjects, though qualitative differences were observed.

Conclusions:

• A refined spatiotemporal motion model can accurately track cardiac motion using VE-MRI.
• The choice of spatial elements significantly impacts accuracy, especially in controlled phantom settings.
• Optical flow serves as a useful adjunct for improving VE-MRI data quality in challenging regions.