Free-breathing liver fat and quantification using motion-corrected averaging based on a nonlocal means algorithm.

Abstract

To propose a motion-robust chemical shift-encoded (CSE) method with high signal-to-noise (SNR) for accurate quantification of liver proton density fat fraction (PDFF) and . A free-breathing multi-repetition 2D CSE acquisition with motion-corrected averaging using nonlocal means (NLM) was proposed. PDFF and quantified with 2D CSE-NLM were compared to two alternative 2D techniques: direct averaging and single acquisition (2D 1ave) in a digital phantom. Further, 2D NLM was compared in patients to 3D techniques (standard breath-hold, free-breathing and navigated), and the alternative 2D techniques. A reader study and quantitative analysis (Bland-Altman, correlation analysis, paired Student's t-test) were performed to evaluate the image quality and assess PDFF and measurements in regions of interest. In simulations, 2D NLM resulted in lower standard deviations (STDs) of PDFF (2.7%) and (8.2 ) compared to direct averaging (PDFF: 3.1%, : 13.6 ) and 2D 1ave (PDFF: 8.7%, : 33.2 ). In patients, 2D NLM resulted in fewer motion artifacts than 3D free-breathing and 3D navigated, less signal loss than 2D direct averaging, and higher SNR than 2D 1ave. Quantitatively, the STDs of PDFF and of 2D NLM were comparable to those of 2D direct averaging (p>0.05). 2D NLM reduced bias, particularly in (-5.73 to -0.36 ) that arises in direct averaging (-3.96 to 11.22 ) in the presence of motion. 2D CSE-NLM enables accurate mapping of PDFF and in the liver during free-breathing.