Liliana E Ma1,2, Michael Markl1,2, Kelvin Chow1,3, Alireza Vali1, Can Wu4, Susanne Schnell1. 1. Department of Radiology, Northwestern University, Chicago, Illinois. 2. Department of Biomedical Engineering, Northwestern University, Evanston, Illinois. 3. Cardiovascular MR R&D, Siemens Medical Solutions USA, Chicago, Illinois. 4. Philips Healthcare, Andover, Massachusetts.
Abstract
PURPOSE: To evaluate the utility of an efficient triple velocity-encoding (VENC) 4D flow MRI implementation to improve velocity unwrapping of 4D flow MRI data with the same scan time as an interleaved dual-VENC acquisition. METHODS: A balanced 7-point acquisition was used to derive 3 sets of 4D flow images corresponding to 3 different VENCs. These 3 datasets were then used to unwrap the aliased lowest VENC into a minimally aliased, triple-VENC dataset. Triple-VENC MRI was evaluated and compared with dual-VENC MRI over 3 different VENC ranges (50-150, 60-150, and 60-180 cm/s) in vitro in a steadily rotating phantom as well as in a pulsatile flow phantom. In vivo, triple-VENC data of the thoracic aorta were also evaluated in 3 healthy volunteers (2 males, 26-44 years old) with VENC = 50/75/150 cm/s. Two triple-VENC (triconditional and biconditional) and 1 dual-VENC unwrapping algorithms were quantitatively assessed through comparison to a reference, unaliased, single-VENC scan. RESULTS: Triple-VENC 4D flow constant rotation phantom results showed high correlation with the analytical solution (intraclass correlation coefficient = 0.984-0.995, P < .001) and up to a 61% reduction in velocity noise compared with the corresponding single-VENC scans (VENC = 150, 180 cm/s). Pulsatile flow phantom experiments demonstrated good agreement between triple-VENC and single-VENC acquisitions (peak flow < 0.8% difference; peak velocity < 11.7% difference). Triconditional triple-VENC unwrapping consistently outperformed dual-VENC unwrapping, correctly unwrapping more than 83% and 46%-66% more voxels in vitro and in vivo, respectively. CONCLUSION: Triple-VENC 4D flow MRI adds no additional scan time to dual-VENC MRI and has the potential for improved unwrapping to extend the velocity dynamic range beyond dual-VENC methods.
PURPOSE: To evaluate the utility of an efficient triple velocity-encoding (VENC) 4D flow MRI implementation to improve velocity unwrapping of 4D flow MRI data with the same scan time as an interleaved dual-VENC acquisition. METHODS: A balanced 7-point acquisition was used to derive 3 sets of 4D flow images corresponding to 3 different VENCs. These 3 datasets were then used to unwrap the aliased lowest VENC into a minimally aliased, triple-VENC dataset. Triple-VENC MRI was evaluated and compared with dual-VENC MRI over 3 different VENC ranges (50-150, 60-150, and 60-180 cm/s) in vitro in a steadily rotating phantom as well as in a pulsatile flow phantom. In vivo, triple-VENC data of the thoracic aorta were also evaluated in 3 healthy volunteers (2 males, 26-44 years old) with VENC = 50/75/150 cm/s. Two triple-VENC (triconditional and biconditional) and 1 dual-VENC unwrapping algorithms were quantitatively assessed through comparison to a reference, unaliased, single-VENC scan. RESULTS: Triple-VENC 4D flow constant rotation phantom results showed high correlation with the analytical solution (intraclass correlation coefficient = 0.984-0.995, P < .001) and up to a 61% reduction in velocity noise compared with the corresponding single-VENC scans (VENC = 150, 180 cm/s). Pulsatile flow phantom experiments demonstrated good agreement between triple-VENC and single-VENC acquisitions (peak flow < 0.8% difference; peak velocity < 11.7% difference). Triconditional triple-VENC unwrapping consistently outperformed dual-VENC unwrapping, correctly unwrapping more than 83% and 46%-66% more voxels in vitro and in vivo, respectively. CONCLUSION: Triple-VENC 4D flow MRI adds no additional scan time to dual-VENC MRI and has the potential for improved unwrapping to extend the velocity dynamic range beyond dual-VENC methods.
Authors: Liliana E Ma; Michael Markl; Kelvin Chow; Hyungkyu Huh; Christoph Forman; Alireza Vali; Andreas Greiser; James Carr; Susanne Schnell; Alex J Barker; Ning Jin Journal: Magn Reson Med Date: 2019-02-25 Impact factor: 4.668
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