Improved visualization of free-running cardiac magnetic resonance by respiratory phase using principal component analysis

Abstract

Rationale and objectives

To support cardiac MR acquisitions during breathing without ECG, we developed software to mitigate the effects of respiratory displacement of the heart. The algorithm resolves respiratory motions and cardiac cycles from DICOM files. The new software automatically detects heartbeats from expiration and inspiration to decrease apparent respiratory motion.

Materials and methods

Our software uses principal component analysis to resolve respiratory motions from cardiac cycles. It groups heartbeats from expiration and inspiration to decrease apparent respiratory motion. The respiratory motion correction was evaluated on short-axis views (acquired with compressed sensing) of 11 healthy subjects and 8 cardiac patients. Two expert radiologists, blinded to the processing, assessed the dynamic images in terms of blood-myocardial contrast, endocardial interface definition, and motion artifacts.

Results

The smallest correlation coefficients between end-systolic frames of the original dynamic scans averaged 0.79. After segregation of cardiac cycles by respiratory phase, the mean correlation coefficients between cardiac cycles were 0.94±0.03 at end-expiration and 0.90±0.08 at end-inspiration. The improvements in correlation coefficients were significant in paired t-tests for healthy subjects and heart patients at end-expiration. Clinical assessment preferred cardiac cycles during end-expiration, which maintained or enhanced scores in 90% of healthy subjects and 83% of the heart patients. Performance remained high with arrhythmia and irregular breathing present.

Conclusion

Heartbeats collected from end-expiration mitigate respiratory motion and are accessible by applying the new software to DICOM files from real-time CMR. Inspiratory heartbeats are also accessible for examination of arrhythmias or abnormalities at end-inspiration.