Huiwen Luo1,2,3, Ante Zhu1,4, Curtis N Wiens1, Jitka Starekova1, Ann Shimakawa5, Scott B Reeder1,4,6,7,8, Kevin M Johnson1,6, Diego Hernando1,2,4,6,9. 1. Radiology, University of Wisconsin-Madison, Madison, WI, USA. 2. Biomedical Engineering, Vanderbilt University, Nashville, TN, USA. 3. Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA. 4. Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA. 5. Global MR Applications and Workflow, GE Healthcare, Madison, WI, USA. 6. Medical Physics, University of Wisconsin-Madison, Madison, WI, USA. 7. Medicine, University of Wisconsin-Madison, Madison, WI, USA. 8. Emergency Medicine, University of Wisconsin-Madison, Madison, WI, USA. 9. Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA.
Abstract
PURPOSE: 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 R 2 ∗ . METHODS: A free-breathing multi-repetition 2D CSE acquisition with motion-corrected averaging using nonlocal means (NLM) was proposed. PDFF and R 2 ∗ 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 R 2 ∗ measurements in regions of interest. RESULTS: In simulations, 2D NLM resulted in lower standard deviations (STDs) of PDFF (2.7%) and R 2 ∗ (8.2 s - 1 ) compared to direct averaging (PDFF: 3.1%, R 2 ∗ : 13.6 s - 1 ) and 2D 1ave (PDFF: 8.7%, R 2 ∗ : 33.2 s - 1 ). 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 R 2 ∗ of 2D NLM were comparable to those of 2D direct averaging (p>0.05). 2D NLM reduced bias, particularly in R 2 ∗ (-5.73 to -0.36 s - 1 ) that arises in direct averaging (-3.96 to 11.22 s - 1 ) in the presence of motion. CONCLUSIONS: 2D CSE-NLM enables accurate mapping of PDFF and R 2 ∗ in the liver during free-breathing.
PURPOSE: 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 R 2 ∗ . METHODS: A free-breathing multi-repetition 2D CSE acquisition with motion-corrected averaging using nonlocal means (NLM) was proposed. PDFF and R 2 ∗ 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 R 2 ∗ measurements in regions of interest. RESULTS: In simulations, 2D NLM resulted in lower standard deviations (STDs) of PDFF (2.7%) and R 2 ∗ (8.2 s - 1 ) compared to direct averaging (PDFF: 3.1%, R 2 ∗ : 13.6 s - 1 ) and 2D 1ave (PDFF: 8.7%, R 2 ∗ : 33.2 s - 1 ). 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 R 2 ∗ of 2D NLM were comparable to those of 2D direct averaging (p>0.05). 2D NLM reduced bias, particularly in R 2 ∗ (-5.73 to -0.36 s - 1 ) that arises in direct averaging (-3.96 to 11.22 s - 1 ) in the presence of motion. CONCLUSIONS:2D CSE-NLM enables accurate mapping of PDFF and R 2 ∗ in the liver during free-breathing.
Authors: Inaki Rabanillo; Santiago Aja-Fernandez; Carlos Alberola-Lopez; Diego Hernando Journal: IEEE Trans Med Imaging Date: 2017-10-09 Impact factor: 10.048
Authors: Fan Lam; S Derin Babacan; Justin P Haldar; Michael W Weiner; Norbert Schuff; Zhi-Pei Liang Journal: Magn Reson Med Date: 2014-03 Impact factor: 4.668