Motion-robust free-running volumetric cardiovascular MRI

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Cardiovascular Research

Background:

• Free-running volumetric cardiovascular MRI (CMR) is susceptible to motion artifacts.
• Robustness to motion is crucial for accurate CMR image acquisition and analysis.
• Existing methods may not fully address outlier data caused by motion.

Purpose of the Study:

• To introduce and evaluate a novel outlier mitigation technique for free-running volumetric CMR.
• To enhance the robustness of cardiovascular MRI to motion-induced artifacts.
• To improve the reliability of quantitative measurements derived from CMR data.

Main Methods:

• The compressive recovery with outlier rejection (CORe) method models outliers as an additive variable.
• MR physics-guided group sparsity is enforced on the auxiliary variable.
• Joint estimation of the image and auxiliary variable is performed iteratively.
• CORe was compared against traditional compressed sensing (CS), robust regression (RR), and an existing outlier rejection method in simulations and real CMR datasets.

Main Results:

• CORe demonstrated superior performance over CS, RR, and existing methods in simulation studies.
• Expert evaluation confirmed CORe's effectiveness in artifact suppression and maintaining image sharpness for 3D cine CMR.
• CORe provided more reliable and consistent 4D flow measurements, particularly under motion and stress conditions.

Conclusions:

• The presented outlier rejection method, CORe, effectively suppresses motion artifacts in free-running CMR.
• CORe shows significant potential for improving image quality and quantitative analysis across various free-running CMR applications.
• This method enhances the utility of cardiovascular MRI in challenging acquisition scenarios.