Motion corrected compressed sensing for free-breathing dynamic cardiac MRI

Area of Science:

• Medical Imaging
• Biophysics
• Computer-Aided Diagnosis

Background:

• Compressed sensing (CS) accelerates MRI by reconstructing images from undersampled data.
• Motion artifacts degrade image quality in accelerated MRI, limiting clinical applications.
• Existing joint CS and motion correction methods are limited to affine deformations.

Purpose of the Study:

• To develop a novel compressed sensing (CS) framework for free-breathing dynamic cardiac MRI.
• To incorporate general motion correction directly into the CS reconstruction process.
• To enable reconstruction of high-quality cardiac CINE MRI with accelerated acquisition.

Main Methods:

• A novel motion-corrected CS framework was developed for free-breathing dynamic cardiac MRI.
• The framework integrates general motion correction (affine and nonrigid) into the CS reconstruction.
• Applied to 2D respiratory self-gated free-breathing cardiac CINE MRI using golden angle radial acquisition.

Main Results:

• The proposed framework successfully corrects for arbitrary affine or nonrigid motion.
• Reconstructed cardiac CINE images exhibit quality comparable to breath-held acquisitions.
• Demonstrated efficacy in both simulated and in vivo data for dynamic cardiac MRI.

Conclusions:

• The novel framework enables high-quality, accelerated cardiac CINE MRI with robust motion correction.
• This approach overcomes limitations of previous methods by handling nonrigid motion.
• Facilitates free-breathing cardiac MRI acquisition without compromising image quality.