Population‐based cohort imaging: skeletal muscle mass by magnetic resonance imaging in correlation to bioelectrical‐impedance analysis
Background Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may...
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| Published in | Journal of cachexia, sarcopenia and muscle Vol. 13; no. 2; pp. 976 - 986 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Germany
John Wiley & Sons, Inc
01.04.2022
John Wiley and Sons Inc Wiley |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2190-5991 2190-6009 2190-6009 |
| DOI | 10.1002/jcsm.12913 |
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| Abstract | Background
Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA.
Methods
Subjects from a population‐based cohort underwent BIA (50 kHz, 0.8 mA) and whole‐body MRI including chemical‐shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat‐free cross‐sectional area by a standardized manual segmentation‐algorithm and normalized to subjects' body height2 (abdominal muscle mass indices: AMMIMRI).
Results
Among 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m2). MRI‐based and BIA‐based measures of muscle mass were strongly correlated, particularly in non‐obese subjects [r < 0.74 in non‐obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMITotal(MRI) was significantly higher in obese as compared with non‐obese subjects (3246.7 ± 606.1 mm2/m2 vs. 2839.0 ± 535.8 mm2/m2, P < 0.001, respectively), whereas the ratio AMMIFat‐free/AMMITotal (by MRI) was significantly higher in non‐obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMIFat‐free(MRI) (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMITotal(MRI) and significantly and inversely with the ratio AMMIFat‐free(MRI)/AMMITotal(MRI) (P < 0.001).
Conclusions
MRI‐based assessment of muscle mass is feasible in population‐based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI‐based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight. |
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| AbstractList | Abstract Background Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA. Methods Subjects from a population‐based cohort underwent BIA (50 kHz, 0.8 mA) and whole‐body MRI including chemical‐shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat‐free cross‐sectional area by a standardized manual segmentation‐algorithm and normalized to subjects' body height2 (abdominal muscle mass indices: AMMIMRI). Results Among 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m2). MRI‐based and BIA‐based measures of muscle mass were strongly correlated, particularly in non‐obese subjects [r < 0.74 in non‐obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMITotal(MRI) was significantly higher in obese as compared with non‐obese subjects (3246.7 ± 606.1 mm2/m2 vs. 2839.0 ± 535.8 mm2/m2, P < 0.001, respectively), whereas the ratio AMMIFat‐free/AMMITotal (by MRI) was significantly higher in non‐obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMIFat‐free(MRI) (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMITotal(MRI) and significantly and inversely with the ratio AMMIFat‐free(MRI)/AMMITotal(MRI) (P < 0.001). Conclusions MRI‐based assessment of muscle mass is feasible in population‐based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI‐based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight. Background Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA. Methods Subjects from a population‐based cohort underwent BIA (50 kHz, 0.8 mA) and whole‐body MRI including chemical‐shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat‐free cross‐sectional area by a standardized manual segmentation‐algorithm and normalized to subjects' body height2 (abdominal muscle mass indices: AMMIMRI). Results Among 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m2). MRI‐based and BIA‐based measures of muscle mass were strongly correlated, particularly in non‐obese subjects [r < 0.74 in non‐obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMITotal(MRI) was significantly higher in obese as compared with non‐obese subjects (3246.7 ± 606.1 mm2/m2 vs. 2839.0 ± 535.8 mm2/m2, P < 0.001, respectively), whereas the ratio AMMIFat‐free/AMMITotal (by MRI) was significantly higher in non‐obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMIFat‐free(MRI) (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMITotal(MRI) and significantly and inversely with the ratio AMMIFat‐free(MRI)/AMMITotal(MRI) (P < 0.001). Conclusions MRI‐based assessment of muscle mass is feasible in population‐based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI‐based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight. Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical-impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA.BACKGROUNDSkeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical-impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA.Subjects from a population-based cohort underwent BIA (50 kHz, 0.8 mA) and whole-body MRI including chemical-shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat-free cross-sectional area by a standardized manual segmentation-algorithm and normalized to subjects' body height2 (abdominal muscle mass indices: AMMIMRI ).METHODSSubjects from a population-based cohort underwent BIA (50 kHz, 0.8 mA) and whole-body MRI including chemical-shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat-free cross-sectional area by a standardized manual segmentation-algorithm and normalized to subjects' body height2 (abdominal muscle mass indices: AMMIMRI ).Among 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m2 ). MRI-based and BIA-based measures of muscle mass were strongly correlated, particularly in non-obese subjects [r < 0.74 in non-obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMITotal(MRI) was significantly higher in obese as compared with non-obese subjects (3246.7 ± 606.1 mm2 /m2 vs. 2839.0 ± 535.8 mm2 /m2 , P < 0.001, respectively), whereas the ratio AMMIFat-free /AMMITotal (by MRI) was significantly higher in non-obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMIFat-free(MRI) (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMITotal(MRI) and significantly and inversely with the ratio AMMIFat-free(MRI) /AMMITotal(MRI) (P < 0.001).RESULTSAmong 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m2 ). MRI-based and BIA-based measures of muscle mass were strongly correlated, particularly in non-obese subjects [r < 0.74 in non-obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMITotal(MRI) was significantly higher in obese as compared with non-obese subjects (3246.7 ± 606.1 mm2 /m2 vs. 2839.0 ± 535.8 mm2 /m2 , P < 0.001, respectively), whereas the ratio AMMIFat-free /AMMITotal (by MRI) was significantly higher in non-obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMIFat-free(MRI) (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMITotal(MRI) and significantly and inversely with the ratio AMMIFat-free(MRI) /AMMITotal(MRI) (P < 0.001).MRI-based assessment of muscle mass is feasible in population-based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI-based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight.CONCLUSIONSMRI-based assessment of muscle mass is feasible in population-based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI-based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight. BackgroundSkeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA.MethodsSubjects from a population‐based cohort underwent BIA (50 kHz, 0.8 mA) and whole‐body MRI including chemical‐shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat‐free cross‐sectional area by a standardized manual segmentation‐algorithm and normalized to subjects' body height2 (abdominal muscle mass indices: AMMIMRI).ResultsAmong 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m2). MRI‐based and BIA‐based measures of muscle mass were strongly correlated, particularly in non‐obese subjects [r < 0.74 in non‐obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMITotal(MRI) was significantly higher in obese as compared with non‐obese subjects (3246.7 ± 606.1 mm2/m2 vs. 2839.0 ± 535.8 mm2/m2, P < 0.001, respectively), whereas the ratio AMMIFat‐free/AMMITotal (by MRI) was significantly higher in non‐obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMIFat‐free(MRI) (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMITotal(MRI) and significantly and inversely with the ratio AMMIFat‐free(MRI)/AMMITotal(MRI) (P < 0.001).ConclusionsMRI‐based assessment of muscle mass is feasible in population‐based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI‐based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight. Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical-impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA. Subjects from a population-based cohort underwent BIA (50 kHz, 0.8 mA) and whole-body MRI including chemical-shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat-free cross-sectional area by a standardized manual segmentation-algorithm and normalized to subjects' body height (abdominal muscle mass indices: AMMI ). Among 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m ). MRI-based and BIA-based measures of muscle mass were strongly correlated, particularly in non-obese subjects [r < 0.74 in non-obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMI was significantly higher in obese as compared with non-obese subjects (3246.7 ± 606.1 mm /m vs. 2839.0 ± 535.8 mm /m , P < 0.001, respectively), whereas the ratio AMMI /AMMI (by MRI) was significantly higher in non-obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMI (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMI and significantly and inversely with the ratio AMMI /AMMI (P < 0.001). MRI-based assessment of muscle mass is feasible in population-based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI-based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight. |
| Author | Fischer, Marc Rospleszcz, Susanne Storz, Corinna Fabian, Jana Nikolaou, Konstantin Peters, Annette Roemer, Frank Kraus, Mareen S. Kiefer, Lena S. Rathmann, Wolfgang Lorbeer, Roberto Meisinger, Christa Schlett, Christopher L. Bamberg, Fabian Heier, Margit Machann, Jürgen |
| AuthorAffiliation | 2 Department of Epidemiology Ludwig‐Maximilians‐University München Munich Germany 8 German Center for Diabetes Research (DZD) Neuherberg Germany 11 Institute for Biometrics and Epidemiology German Diabetes Center Duesseldorf Germany 14 KORA Study Centre University Hospital Augsburg Augsburg Germany 16 Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine University of Freiburg Freiburg Germany 15 Department of Neuroradiology, University Medical Center Freiburg, Faculty of Medicine University of Freiburg Freiburg Germany 7 Institute for Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich University of Tuebingen Tuebingen Germany 10 Department of Radiology Boston University School of Medicine Boston MA USA 3 Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany 13 Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München German Research C |
| AuthorAffiliation_xml | – name: 6 Section of Experimental Radiology, Department of Diagnostic and Interventional Radiology University of Tuebingen Tuebingen Germany – name: 15 Department of Neuroradiology, University Medical Center Freiburg, Faculty of Medicine University of Freiburg Freiburg Germany – name: 12 Chair of Epidemiology Ludwig‐Maximilians‐University München, UNIKA‐T Augsburg Augsburg Germany – name: 9 Department of Radiology University of Erlangen–Nuremberg Erlangen Germany – name: 14 KORA Study Centre University Hospital Augsburg Augsburg Germany – name: 8 German Center for Diabetes Research (DZD) Neuherberg Germany – name: 11 Institute for Biometrics and Epidemiology German Diabetes Center Duesseldorf Germany – name: 3 Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany – name: 5 German Centre for Cardiovascular Research (DZHK e.V.) Munich Germany – name: 4 Department of Radiology Ludwig‐Maximilians‐University Hospital Munich Germany – name: 13 Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany – name: 1 Department of Diagnostic and Interventional Radiology University of Tuebingen Tuebingen Germany – name: 10 Department of Radiology Boston University School of Medicine Boston MA USA – name: 2 Department of Epidemiology Ludwig‐Maximilians‐University München Munich Germany – name: 7 Institute for Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich University of Tuebingen Tuebingen Germany – name: 16 Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine University of Freiburg Freiburg Germany |
| Author_xml | – sequence: 1 givenname: Lena S. orcidid: 0000-0002-3999-559X surname: Kiefer fullname: Kiefer, Lena S. email: lena.kiefer@med.uni-tuebingen.de organization: University of Tuebingen – sequence: 2 givenname: Jana surname: Fabian fullname: Fabian, Jana organization: University of Tuebingen – sequence: 3 givenname: Susanne surname: Rospleszcz fullname: Rospleszcz, Susanne organization: German Research Center for Environmental Health – sequence: 4 givenname: Roberto surname: Lorbeer fullname: Lorbeer, Roberto organization: German Centre for Cardiovascular Research (DZHK e.V.) – sequence: 5 givenname: Jürgen surname: Machann fullname: Machann, Jürgen organization: German Center for Diabetes Research (DZD) – sequence: 6 givenname: Mareen S. surname: Kraus fullname: Kraus, Mareen S. organization: University of Tuebingen – sequence: 7 givenname: Marc surname: Fischer fullname: Fischer, Marc organization: University of Tuebingen – sequence: 8 givenname: Frank surname: Roemer fullname: Roemer, Frank organization: Boston University School of Medicine – sequence: 9 givenname: Wolfgang surname: Rathmann fullname: Rathmann, Wolfgang organization: German Diabetes Center – sequence: 10 givenname: Christa surname: Meisinger fullname: Meisinger, Christa organization: German Research Center for Environmental Health – sequence: 11 givenname: Margit surname: Heier fullname: Heier, Margit organization: University Hospital Augsburg – sequence: 12 givenname: Konstantin surname: Nikolaou fullname: Nikolaou, Konstantin organization: University of Tuebingen – sequence: 13 givenname: Annette surname: Peters fullname: Peters, Annette organization: German Center for Diabetes Research (DZD) – sequence: 14 givenname: Corinna surname: Storz fullname: Storz, Corinna organization: University of Freiburg – sequence: 15 givenname: Christopher L. surname: Schlett fullname: Schlett, Christopher L. organization: University of Freiburg – sequence: 16 givenname: Fabian surname: Bamberg fullname: Bamberg, Fabian organization: University of Freiburg |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35080141$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1007/s00198-009-1059-y 10.1038/sj.ejcn.1602880 10.1002/jmri.22036 10.1055/s-0042-104510 10.1111/codi.12805 10.1093/jn/137.12.2775 10.1093/gerona/glu034 10.1016/j.ejrad.2018.06.023 10.1016/S1470-2045(10)70218-7 10.1093/ageing/afq034 10.1002/jcsm.12268 10.1002/jmri.21754 10.1007/s40520-014-0281-4 10.2337/db16-0630 10.1093/oxfordjournals.aje.a009520 10.1038/srep38395 10.1038/sj.ijo.0802968 10.1007/s00223-013-9757-z 10.1152/jappl.2000.89.2.465 10.1002/jso.24025 10.1249/MSS.0b013e3181641bed |
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| Copyright | 2022 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders. 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Keywords | Magnetic resonance imaging Skeletal muscle mass Quantitative imaging biomarker Fat-free skeletal muscle mass Skeletal muscle segmentation |
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| PublicationTitle | Journal of cachexia, sarcopenia and muscle |
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| References_xml | – volume: 112 start-page: 503 year: 2015 end-page: 509 article-title: The impact of sarcopenia on survival and complications in surgical oncology: a review of the current literature publication-title: J Surg Oncol – volume: 27 start-page: 249 year: 2015 end-page: 254 article-title: Sarcopenia: a predictor of mortality and the need for early diagnosis and intervention publication-title: Aging Clin Exp Res – volume: 37 start-page: 742 year: 2016 end-page: 748 article-title: Age‐ and level‐dependence of fatty infiltration in lumbar paravertebral muscles of healthy volunteers publication-title: Spine (Phila. Pa. 1976) – volume: 105 start-page: 261 year: 2018 end-page: 268 article-title: Assessment of the degree of abdominal myosteatosis by magnetic resonance imaging in subjects with diabetes, prediabetes and healthy controls from the general population publication-title: Eur J Radiol – volume: 21 start-page: 543 year: 2010 end-page: 559 article-title: Sarcopenia: etiology, clinical consequences, intervention, and assessment publication-title: Osteoporos Int – year: 2000 – volume: 12 start-page: 489 year: 2011 end-page: 495 article-title: Definition and classification of cancer cachexia: an international consensus publication-title: Lancet Oncol – volume: 93 start-page: 201 year: 2013 end-page: 210 article-title: Tools in the assessment of sarcopenia publication-title: Calcif Tissue Int – volume: 69 start-page: 1154 year: 2014 end-page: 1161 article-title: Association of sarcopenia with short‐ and long‐term mortality in older adults admitted to acute care wards: results from the CRIME study publication-title: J Gerontol A Biol Sci Med Sci – volume: 40 start-page: 918 year: 2008 end-page: 925 article-title: Effect of maturation on the relationship between muscle size and force production publication-title: Med Sci Sports Exerc – volume: 29 start-page: 594 year: 2005 end-page: 602 article-title: Percent body fat measured by BIA and DEXA in obese, African‐American adolescent girls publication-title: Int J Obes – volume: 29 start-page: 1340 year: 2009 end-page: 1345 article-title: Intermuscular adipose tissue (IMAT): association with other adipose tissue compartments and insulin sensitivity publication-title: J Magn Reson Imaging – volume: 39 start-page: 412 year: 2010 end-page: 423 article-title: Sarcopenia: European consensus on definition and diagnosis publication-title: Age Ageing – volume: 66 start-page: 158 year: 2017 end-page: 169 article-title: Subclinical disease burden as assessed by whole‐body MRI in subjects with prediabetes, subjects with diabetes, and normal control subjects from the general population: the KORA‐MRI study publication-title: Diabetes – volume: 91 start-page: 1 year: 2018 end-page: 9 article-title: Inter‐ and intraobserver variability of an anatomical landmark‐based, manual segmentation method by MRI for the assessment of skeletal muscle fat content and area in subjects from the general population publication-title: Br J Radiol – volume: 91 start-page: 1 year: 2018 end-page: 10 article-title: The role of visceral and subcutaneous adipose tissue measurements and their ratio by magnetic resonance imaging in subjects with prediabetes, diabetes and healthy controls from a general population without cardiovascular disease publication-title: Br J Radiol – volume: 89 start-page: 465 year: 2000 end-page: 471 article-title: Estimation of skeletal muscle mass by bioelectrical impedance analysis publication-title: J Appl Physiol – volume: 17 start-page: 20 year: 2014 end-page: 26 article-title: Simple psoas cross‐sectional area measurement is a quick and easy method to assess sarcopenia and predicts major surgical complications publication-title: Colorectal Dis – volume: 147 start-page: 755 year: 1998 end-page: 763 article-title: Epidemiology of sarcopenia among the elderly in New Mexico publication-title: Am J Epidemiol – volume: 137 start-page: 2775 year: 2007 end-page: 2780 article-title: Dual‐energy X‐ray absorptiometry is a valid tool for assessing skeletal muscle mass in older women publication-title: J Nutr – volume: 31 start-page: 430 year: 2010 end-page: 439 article-title: Topography mapping of whole body adipose tissue using a fully automated and standardized procedure publication-title: J Magn Reson Imaging – volume: 9 start-page: 269 year: 2018 end-page: 278 article-title: Pitfalls in the measurement of muscle mass: a need for a reference standard publication-title: J Cachexia Sarcopenia Muscle – volume: 6 start-page: 1 year: 2016 end-page: 8 article-title: Skeletal muscle mass adjusted by height correlated better with muscular functions than that adjusted by body weight in defining sarcopenia publication-title: Nat Sci Reports – volume: 62 start-page: 1372 year: 2008 end-page: 1378 article-title: Can dual energy X‐ray absorptiometry provide a valid assessment of changes in thigh muscle mass with strength training in older adults? publication-title: Eur J Clin Nutr – volume: 188 start-page: 652 year: 2016 end-page: 661 article-title: Population‐based imaging and radiomics: rationale and perspective of the german national cohort MRI study publication-title: Fortschr Röntgenstr – ident: e_1_2_6_5_1 doi: 10.1007/s00198-009-1059-y – volume: 91 start-page: 1 year: 2018 ident: e_1_2_6_19_1 article-title: The role of visceral and subcutaneous adipose tissue measurements and their ratio by magnetic resonance imaging in subjects with prediabetes, diabetes and healthy controls from a general population without cardiovascular disease publication-title: Br J Radiol – ident: e_1_2_6_22_1 doi: 10.1038/sj.ejcn.1602880 – ident: e_1_2_6_18_1 doi: 10.1002/jmri.22036 – ident: e_1_2_6_25_1 doi: 10.1055/s-0042-104510 – volume: 91 start-page: 1 year: 2018 ident: e_1_2_6_12_1 article-title: Inter‐ and intraobserver variability of an anatomical landmark‐based, manual segmentation method by MRI for the assessment of skeletal muscle fat content and area in subjects from the general population publication-title: Br J Radiol – ident: e_1_2_6_13_1 doi: 10.1111/codi.12805 – ident: e_1_2_6_23_1 doi: 10.1093/jn/137.12.2775 – ident: e_1_2_6_6_1 doi: 10.1093/gerona/glu034 – ident: e_1_2_6_17_1 doi: 10.1016/j.ejrad.2018.06.023 – ident: e_1_2_6_26_1 doi: 10.1016/S1470-2045(10)70218-7 – ident: e_1_2_6_4_1 doi: 10.1093/ageing/afq034 – ident: e_1_2_6_7_1 doi: 10.1002/jcsm.12268 – ident: e_1_2_6_15_1 doi: 10.1002/jmri.21754 – ident: e_1_2_6_3_1 doi: 10.1007/s40520-014-0281-4 – ident: e_1_2_6_9_1 doi: 10.2337/db16-0630 – ident: e_1_2_6_20_1 doi: 10.1093/oxfordjournals.aje.a009520 – ident: e_1_2_6_16_1 doi: 10.1038/srep38395 – ident: e_1_2_6_24_1 doi: 10.1038/sj.ijo.0802968 – ident: e_1_2_6_8_1 doi: 10.1007/s00223-013-9757-z – ident: e_1_2_6_10_1 – ident: e_1_2_6_11_1 doi: 10.1152/jappl.2000.89.2.465 – ident: e_1_2_6_2_1 doi: 10.1002/jso.24025 – volume: 37 start-page: 742 year: 2016 ident: e_1_2_6_14_1 article-title: Age‐ and level‐dependence of fatty infiltration in lumbar paravertebral muscles of healthy volunteers publication-title: Spine (Phila. 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| Snippet | Background
Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance... Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical-impedance analysis... BackgroundSkeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical‐impedance... Abstract Background Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases.... |
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| SubjectTerms | Abdomen Body fat Body Weight Electric Impedance Fat‐free skeletal muscle mass Female Humans Lipids Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Muscle, Skeletal - diagnostic imaging Muscle, Skeletal - physiology Obesity - complications Original Quantitative imaging biomarker Skeletal muscle mass Skeletal muscle segmentation |
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| Title | Population‐based cohort imaging: skeletal muscle mass by magnetic resonance imaging in correlation to bioelectrical‐impedance analysis |
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