Tracking myocardial deformation using phase contrast MR velocity fields: a stochastic approach.

Area of Science:

• Cardiovascular imaging
• Biomedical engineering
• Medical physics

Background:

• Phase contrast magnetic resonance (MR) velocity data can track cardiac motion.
• Existing methods struggle with noisy velocity data near left-ventricular (LV) borders.
• LV motion and deformation estimation is crucial for diagnosing cardiac conditions.

Purpose of the Study:

• To develop an improved method for tracking left-ventricular (LV) myocardium deformation.
• To overcome limitations of noisy velocity data in 2-D MR phase contrast imaging.
• To integrate boundary contour information with velocity data for more accurate motion tracking.

Main Methods:

• A novel approach combines LV endocardial and epicardial contours with 2-D MR phase contrast velocity data.
• A deforming mesh is tracked over the cardiac cycle, guided by a Kalman filter.
• The Kalman filter balances velocity/contour data with a smooth cyclic cardiac motion model.

Main Results:

• Simulated data showed an average tracking error of 1.8% of total path length.
• Phantom data yielded an average error of 4.4% of total path length.
• The new approach demonstrated improvements over methods using velocity data alone.

Conclusions:

• The proposed method enhances the accuracy of LV myocardium deformation tracking.
• Integrating boundary constraints and Kalman filtering effectively handles noisy velocity data.
• This technique shows promise for improved in vivo and 3-D cardiac motion analysis.