OBJECTIVE: To develop a magnetic resonance imaging (MRI)-based approach for quantifying absolute fat mass in organs, muscles, and adipose tissues, and to validate its accuracy against reference chemical analysis (CA). METHODS: Chemical-shift imaging can accurately decompose water and fat signals from the acquired MRI data. A proton density fat fraction (PDFF) can be computed from the separated images, and reflects the relative fat content on a voxel-by-voxel basis. The PDFF is mathematically closely related to the fat mass fraction and can be converted to absolute fat mass in grams by multiplying by the voxel volume and the mass density of fat. In this validation study, 97 freshly excised and unique samples from four pigs, comprising of organs, muscles, and adipose and lean tissues were imaged by MRI and then analyzed independently by CA. Linear regression was used to assess correlation, agreement, and measurement differences between MRI and CA. RESULTS: Considering all 97 samples, a strong correlation and agreement was obtained between MRI and CA-derived fat mass (slope = 1.01, intercept = 1.99g, r(2) = 0.98, p < 0.01). The mean difference d between MRI and CA was 2.17±3.40g. MRI did not exhibit any tendency to under or overestimate CA (p > 0.05). When considering samples from each pig separately, the results were (slope = 1.05, intercept = 1.11g, r(2) = 0.98, d = 2.66±4.36g), (slope = 0.99, intercept = 2.33g, r(2) = 0.99, d = 1.88±2.68g), (slope = 1.07, intercept = 1.52g, r(2) = 0.96, d = 2.73±2.50g), and (slope=0.92, intercept=2.84g, r(2) = 0.97, d = 1.18±3.90g), respectively. CONCLUSION: Chemical-shift MRI and PDFF provides an accurate means of determining absolute fat mass in organs, muscles, and adipose and lean tissues.
OBJECTIVE: To develop a magnetic resonance imaging (MRI)-based approach for quantifying absolute fat mass in organs, muscles, and adipose tissues, and to validate its accuracy against reference chemical analysis (CA). METHODS: Chemical-shift imaging can accurately decompose water and fat signals from the acquired MRI data. A proton density fat fraction (PDFF) can be computed from the separated images, and reflects the relative fat content on a voxel-by-voxel basis. The PDFF is mathematically closely related to the fat mass fraction and can be converted to absolute fat mass in grams by multiplying by the voxel volume and the mass density of fat. In this validation study, 97 freshly excised and unique samples from four pigs, comprising of organs, muscles, and adipose and lean tissues were imaged by MRI and then analyzed independently by CA. Linear regression was used to assess correlation, agreement, and measurement differences between MRI and CA. RESULTS: Considering all 97 samples, a strong correlation and agreement was obtained between MRI and CA-derived fat mass (slope = 1.01, intercept = 1.99g, r(2) = 0.98, p < 0.01). The mean difference d between MRI and CA was 2.17±3.40g. MRI did not exhibit any tendency to under or overestimate CA (p > 0.05). When considering samples from each pig separately, the results were (slope = 1.05, intercept = 1.11g, r(2) = 0.98, d = 2.66±4.36g), (slope = 0.99, intercept = 2.33g, r(2) = 0.99, d = 1.88±2.68g), (slope = 1.07, intercept = 1.52g, r(2) = 0.96, d = 2.73±2.50g), and (slope=0.92, intercept=2.84g, r(2) = 0.97, d = 1.18±3.90g), respectively. CONCLUSION: Chemical-shift MRI and PDFF provides an accurate means of determining absolute fat mass in organs, muscles, and adipose and lean tissues.
Authors: Mark Bydder; Takeshi Yokoo; Gavin Hamilton; Michael S Middleton; Alyssa D Chavez; Jeffrey B Schwimmer; Joel E Lavine; Claude B Sirlin Journal: Magn Reson Imaging Date: 2008-02-21 Impact factor: 2.546
Authors: Thorsten A Bley; Oliver Wieben; Christopher J François; Jean H Brittain; Scott B Reeder Journal: J Magn Reson Imaging Date: 2010-01 Impact factor: 4.813
Authors: Geraldine H Kang; Irene Cruite; Masoud Shiehmorteza; Tanya Wolfson; Anthony C Gamst; Gavin Hamilton; Mark Bydder; Michael S Middleton; Claude B Sirlin Journal: J Magn Reson Imaging Date: 2011-07-18 Impact factor: 4.813
Authors: Scott B Reeder; Charles A McKenzie; Angel R Pineda; Huanzhou Yu; Ann Shimakawa; Anja C Brau; Brian A Hargreaves; Garry E Gold; Jean H Brittain Journal: J Magn Reson Imaging Date: 2007-03 Impact factor: 4.813
Authors: Catherine D G Hines; Huanzhou Yu; Ann Shimakawa; Charles A McKenzie; Jean H Brittain; Scott B Reeder Journal: J Magn Reson Imaging Date: 2009-11 Impact factor: 4.813
Authors: Dimitrios C Karampinos; Gerd Melkus; Thomas Baum; Jan S Bauer; Ernst J Rummeny; Roland Krug Journal: Magn Reson Med Date: 2014-03 Impact factor: 4.668
Authors: Lorenzo Nardo; Dimitrios C Karampinos; Drew A Lansdown; Julio Carballido-Gamio; Sonia Lee; Roberto Maroldi; C Benjamin Ma; Thomas M Link; Roland Krug Journal: J Magn Reson Imaging Date: 2013-09-24 Impact factor: 4.813
Authors: James L Hopkins; Paul N Hopkins; Eliot A Brinton; Ted D Adams; Lance E Davidson; M Nazeem Nanjee; Steven C Hunt Journal: Metab Syndr Relat Disord Date: 2017-06-28 Impact factor: 1.894
Authors: Christina S Gee; Jennifer T K Nguyen; Candice J Marquez; Julia Heunis; Andrew Lai; Cory Wyatt; Misung Han; Galateia Kazakia; Andrew J Burghardt; Dimitrios C Karampinos; Julio Carballido-Gamio; Roland Krug Journal: J Magn Reson Imaging Date: 2014-11-25 Impact factor: 4.813
Authors: Tatiana Toro-Ramos; Bret H Goodpaster; Isaiah Janumala; Susan Lin; Gladys W Strain; John C Thornton; Patrick Kang; Anita P Courcoulas; Alfons Pomp; Dympna Gallagher Journal: Obesity (Silver Spring) Date: 2014-11-11 Impact factor: 5.002
Authors: Kate Sutherland; Aimee B Lowth; Nick Antic; A Simon Carney; Peter G Catcheside; Ching Li Chai-Coetzer; Michael Chia; John-Charles Hodge; Andrew Jones; Billingsley Kaambwa; Richard Lewis; Stuart MacKay; R Doug McEvoy; Eng H Ooi; Alison J Pinczel; Nigel McArdle; Guy Rees; Bhajan Singh; Nicholas Stow; Edward M Weaver; Richard J Woodman; Charmaine M Woods; Aeneas Yeo; Peter A Cistulli Journal: Sleep Date: 2021-12-10 Impact factor: 6.313