Erika J Ulbrich1, Daniel Nanz1, Olof Dahlqvist Leinhard2, Magda Marcon1, Michael A Fischer3. 1. Institute of Diagnostic and Interventional Radiology, University Hospital and University of Zurich, Zurich, Switzerland. 2. Department of Medical and Health Sciences, Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; and Advanced MR Analytics AB, Linköping, Sweden. 3. Department of Radiology, University Hospital Balgrist, University of Zurich, Zurich, Switzerland.
Abstract
PURPOSE: To determine age- and gender-dependent whole-body adipose tissue and muscle volumes in healthy Swiss volunteers in Dixon MRI in comparison with anthropometric and bioelectrical impedance (BIA) measurements. METHODS: Fat-water-separated whole-body 3 Tesla MRI of 80 healthy volunteers (ages 20 to 62 years) with a body mass index (BMI) of 17.5 to 26.2 kg/m2 (10 men, 10 women per decade). Age and gender-dependent volumes of total adipose tissue (TAT), visceral adipose tissue (VAT), total abdominal subcutaneous adipose tissue (ASAT) and total abdominal adipose tissue (TAAT), and the total lean muscle tissue (TLMT) normalized for body height were determined by semi-automatic segmentation, and correlated with anthropometric and BIA measurements as well as lifestyle parameters. RESULTS: The TAT, ASAT, VAT, and TLMT indexes (TATi, ASATi, VATi, and TLMTi, respectively) (L/m2 ± standard deviation) for women/men were 6.4 ± 1.8/5.3 ± 1.7, 1.6 ± 0.7/1.2 ± 0.5, 0.4 ± 0.2/0.8 ± 0.5, and 5.6 ± 0.6/7.1 ± 0.7, respectively. The TATi correlated strongly with ASATi (r > 0.93), VATi, BMI and BIA (r > 0.70), and TAATi (r > 0.96), and weak with TLMTi for both genders (r > -0.34). The VAT was the only parameter showing an age dependency (r > 0.32). The BMI and BIA showed strong correlation with all MR-derived adipose tissue volumes. The TAT mass was estimated significantly lower from BIA than from MRI (both genders P < .001; mean bias -5 kg). CONCLUSIONS: The reported gender-specific MRI-based adipose tissue and muscle volumes might serve as normative values. The estimation of adipose tissue volumes was significantly lower from anthropometric and BIA measurements than from MRI. Magn Reson Med 79:449-458, 2018.
PURPOSE: To determine age- and gender-dependent whole-body adipose tissue and muscle volumes in healthy Swiss volunteers in Dixon MRI in comparison with anthropometric and bioelectrical impedance (BIA) measurements. METHODS: Fat-water-separated whole-body 3 Tesla MRI of 80 healthy volunteers (ages 20 to 62 years) with a body mass index (BMI) of 17.5 to 26.2 kg/m2 (10 men, 10 women per decade). Age and gender-dependent volumes of total adipose tissue (TAT), visceral adipose tissue (VAT), total abdominal subcutaneous adipose tissue (ASAT) and total abdominal adipose tissue (TAAT), and the total lean muscle tissue (TLMT) normalized for body height were determined by semi-automatic segmentation, and correlated with anthropometric and BIA measurements as well as lifestyle parameters. RESULTS: The TAT, ASAT, VAT, and TLMT indexes (TATi, ASATi, VATi, and TLMTi, respectively) (L/m2 ± standard deviation) for women/men were 6.4 ± 1.8/5.3 ± 1.7, 1.6 ± 0.7/1.2 ± 0.5, 0.4 ± 0.2/0.8 ± 0.5, and 5.6 ± 0.6/7.1 ± 0.7, respectively. The TATi correlated strongly with ASATi (r > 0.93), VATi, BMI and BIA (r > 0.70), and TAATi (r > 0.96), and weak with TLMTi for both genders (r > -0.34). The VAT was the only parameter showing an age dependency (r > 0.32). The BMI and BIA showed strong correlation with all MR-derived adipose tissue volumes. The TAT mass was estimated significantly lower from BIA than from MRI (both genders P < .001; mean bias -5 kg). CONCLUSIONS: The reported gender-specific MRI-based adipose tissue and muscle volumes might serve as normative values. The estimation of adipose tissue volumes was significantly lower from anthropometric and BIA measurements than from MRI. Magn Reson Med 79:449-458, 2018.
Authors: Nicolas Linder; Kilian Solty; Anna Hartmann; Tobias Eggebrecht; Matthias Blüher; Roland Stange; Harald Busse Journal: BMC Med Imaging Date: 2019-10-22 Impact factor: 1.930
Authors: Jürgen Machann; Norbert Stefan; Robert Wagner; Andreas Fritsche; Jimmy D Bell; Brandon Whitcher; Hans-Ulrich Häring; Andreas L Birkenfeld; Konstantin Nikolaou; Fritz Schick; E Louise Thomas Journal: Nutrients Date: 2020-07-11 Impact factor: 5.717
Authors: Wolfgang M Thaiss; Sergios Gatidis; Tina Sartorius; Jürgen Machann; Andreas Peter; Thomas K Eigentler; Konstantin Nikolaou; Bernd J Pichler; Manfred Kneilling Journal: Cancer Immunol Immunother Date: 2020-11-01 Impact factor: 6.968
Authors: Antoine Verger; Carina Stegmayr; Norbert Galldiks; Axel Van Der Gucht; Philipp Lohmann; Gabriele Stoffels; Nadim J Shah; Gereon R Fink; Simon B Eickhoff; Eric Guedj; Karl-Josef Langen Journal: Neuroimage Clin Date: 2017-11-08 Impact factor: 4.881
Authors: Magnus Borga; Janne West; Jimmy D Bell; Nicholas C Harvey; Thobias Romu; Steven B Heymsfield; Olof Dahlqvist Leinhard Journal: J Investig Med Date: 2018-03-25 Impact factor: 2.895