Predictors of 0.55T Respiratory Navigated Lung MRI Degradation

Motivation: The image quality generated using respiratory triggered sequences on low-field scanners is sometimes degraded, and it is currently not well known what causes this. This degradation can lead to image misinterpretation. Goal(s): Our goal was to determine possible predictors of image quality degradation in low-field lung MRI. Approach: Six radiologists graded anatomic 0.55T MRI images, and then analysis of patient clinical history, demographics, and respiratory navigation was conducted to determine any patterns. Results: We found that clinical conditions including fibrotic interstitial lung disease and pulmonary artery pathologies, as well as descriptors such as increased body mass index can predict image quality degradation. Impact: Our observation of degradative predictors serves as the foundation for research into altering of 0.55T MRI parameters to limit the degree of degradation, so that at-risk patients can still be scanned on these low-field machines with optimal image quality.