Leveraging Compressed Sensing for Improvement of FIDDLE Image Quality Rather Than for Acquisition Speed

Motivation: Imperfect breath holding and cardiac arrhythmia create chest wall and cardiac ghosting in conventional segmented dark-blood LGE images (FIDDLE) often rendering them non-clinical. Goal(s): We aimed to apply compressed sensing ‘CS’ as the solution to this problem, to acquire FIDDLE images without ghosting, even in challenging patients. Approach: CS can acquire multiple high-spatial and excellent-temporal resolution single shots that intrinsically never display ghosting artifacts. Sparsity is created along the shot dimension, enabling CS to reconstruct the generally not-so-sparse FIDDLE images. Single shot averaging further improves SNR. Results: The CS FIDDLE images show high SNR and no ghosting. They should simplify clinical imaging. Impact: The CS FIDDLE method should improve clinical CMR image quality and alleviate the need for repeated acquisitions due to poor breath holding. It also enables using CS for the acquisition of single still-frame images with intrinsically higher SNR.