PURPOSE: To determine the limits of agreement of hepatic fat fraction and R2* relaxation rate quantified with accelerated magnetic resonance (MR) imaging reconstructed with combined compressed sensing and parallel imaging compared with conventional fully sampled acquisitions. MATERIALS AND METHODS: Eleven subjects with type 2 diabetes and a healthy control subject were recruited with the approval of the Newcastle and North Tyneside 2 ethics committee and written consent. Undersampled data at ratios of 2.6×, 2.9×, 3.8×, and 4.8× were prospectively acquired in addition to fully sampled data by using five gradient echoes per repetition time at 3.0 T. Fat fraction maps were calculated by using combined compressed sensing and parallel imaging (CS-PI) reconstruction and Bland-Altman analysis performed to assess bias and 95% limits of agreement. Inter- and intrarater analysis was performed for quantitative fat fraction and R2* relaxation rate, and image quality was assessed with a four-point scale by two independent observers. RESULTS: The fat fractions from the accelerated acquisitions had 95% limits of agreement of 1.2%, 1.2%, 1.1%, and 1.5%, respectively, with no bias. When compared with the intra- and interrater 95% limits of agreement (0.7% and 0.8%), acceleration of up to 3.8× did not greatly degrade the fat fraction measurements. No or minimal artifact was detected at 2.6× and 2.9× accelerations, moderate artifact was detected at 3.8× acceleration, and substantial artifact was detected at 4.8× acceleration. CONCLUSION: Prospective undersampling and CS-PI reconstruction of liver fat fractions can be used to accelerate liver fat fraction measurements. The fat fractions and image quality produced were acceptable up to a factor of 3.8×, thereby shortening the required breath-hold duration from 17.7 seconds to 4.7 seconds.
PURPOSE: To determine the limits of agreement of hepatic fat fraction and R2* relaxation rate quantified with accelerated magnetic resonance (MR) imaging reconstructed with combined compressed sensing and parallel imaging compared with conventional fully sampled acquisitions. MATERIALS AND METHODS: Eleven subjects with type 2 diabetes and a healthy control subject were recruited with the approval of the Newcastle and North Tyneside 2 ethics committee and written consent. Undersampled data at ratios of 2.6×, 2.9×, 3.8×, and 4.8× were prospectively acquired in addition to fully sampled data by using five gradient echoes per repetition time at 3.0 T. Fat fraction maps were calculated by using combined compressed sensing and parallel imaging (CS-PI) reconstruction and Bland-Altman analysis performed to assess bias and 95% limits of agreement. Inter- and intrarater analysis was performed for quantitative fat fraction and R2* relaxation rate, and image quality was assessed with a four-point scale by two independent observers. RESULTS: The fat fractions from the accelerated acquisitions had 95% limits of agreement of 1.2%, 1.2%, 1.1%, and 1.5%, respectively, with no bias. When compared with the intra- and interrater 95% limits of agreement (0.7% and 0.8%), acceleration of up to 3.8× did not greatly degrade the fat fraction measurements. No or minimal artifact was detected at 2.6× and 2.9× accelerations, moderate artifact was detected at 3.8× acceleration, and substantial artifact was detected at 4.8× acceleration. CONCLUSION: Prospective undersampling and CS-PI reconstruction of liver fat fractions can be used to accelerate liver fat fraction measurements. The fat fractions and image quality produced were acceptable up to a factor of 3.8×, thereby shortening the required breath-hold duration from 17.7 seconds to 4.7 seconds.
Authors: Felix Lugauer; Dominik Nickel; Jens Wetzl; Berthold Kiefer; Joachim Hornegger; Andreas Maier Journal: MAGMA Date: 2016-11-07 Impact factor: 2.310
Authors: Li Feng; Thomas Benkert; Kai Tobias Block; Daniel K Sodickson; Ricardo Otazo; Hersh Chandarana Journal: J Magn Reson Imaging Date: 2016-12-16 Impact factor: 4.813
Authors: Mikell Yuhasz; Michael J Hoch; Mari Hagiwara; Mary T Bruno; James S Babb; Esther Raithel; Christoph Forman; Abbas Anwar; J Thomas Roland; Timothy M Shepherd Journal: Invest Radiol Date: 2018-12 Impact factor: 6.016