Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/11426
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dc.contributor.authorBaker, S Ten
dc.contributor.authorStrauss, B Jen
dc.contributor.authorPrendergast, L Aen
dc.contributor.authorPanagiotopoulos, Siannaen
dc.contributor.authorThomas, G Een
dc.contributor.authorVu, Ten
dc.contributor.authorProietto, Josephen
dc.contributor.authorJerums, Georgeen
dc.date.accessioned2015-05-16T01:01:59Z-
dc.date.available2015-05-16T01:01:59Z-
dc.date.issued2012-01-25en
dc.identifier.citationEuropean Journal of Clinical Nutrition 2012; 66(5): 628-32en
dc.identifier.govdoc22274551en
dc.identifier.otherPUBMEDen
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/11426en
dc.description.abstractSingle-slice abdominal computed tomography or magnetic resonance imaging (MRI) performed to measure visceral adipose tissue in individuals with obesity and diabetes mellitus can also image skeletal muscle. The aim of this study was to validate a method developed in cancer patients using a single abdominal cross-sectional image to estimate fat-free mass (FFM) and appendicular lean tissue mass index (LTMI), a total body skeletal muscle mass surrogate, in an obese cohort of subjects with and without type 2 diabetes.In total, 49 obese subjects (22 with diabetes) recruited into a weight loss study underwent dual-energy X-ray absorptiometry (DXA) and abdominal MRI at baseline. DXA-derived FFM and LTMI were compared with skeletal muscle area at the level of the third lumbar vertebra (L3) on MRI.L3 skeletal muscle area correlated with FFM (R (adj) (2)=0.825; P<0.001) and LTMI (R (adj) (2)=0.6; P<0.001). A simple formula, previously shown to predict LTMI in cancer patients, produced a good estimation of LTMI from L3 skeletal muscle area (95% confidence interval -3.70, 2.56%) in our obese cohort. Equations incorporating age, sex, height, weight and diabetic status improved the relationship between L3 skeletal muscle area and estimated FFM (r=0.976, P<0.001) and LTMI (r=0.879, P<0.001).A single-axial slice at the L3 level can be used to estimate FFM and LTMI in obese diabetic and non-diabetic subjects, allowing precise analysis of body composition using a single imaging modality in clinical research and practice.en
dc.language.isoenen
dc.subject.otherAbdomenen
dc.subject.otherAbsorptiometry, Photon.methodsen
dc.subject.otherBody Compositionen
dc.subject.otherBody Fluid Compartments.radiographyen
dc.subject.otherCohort Studiesen
dc.subject.otherDiabetes Mellitus, Type 2.complicationsen
dc.subject.otherFemaleen
dc.subject.otherHumansen
dc.subject.otherIntra-Abdominal Faten
dc.subject.otherLumbar Vertebraeen
dc.subject.otherMagnetic Resonance Imaging.methodsen
dc.subject.otherMaleen
dc.subject.otherMathematical Conceptsen
dc.subject.otherMiddle Ageden
dc.subject.otherMuscle, Skeletal.pathology.radiographyen
dc.subject.otherObesity.complications.pathologyen
dc.subject.otherPilot Projectsen
dc.titleEstimating dual-energy X-ray absorptiometry-derived total body skeletal muscle mass using single-slice abdominal magnetic resonance imaging in obese subjects with and without diabetes: a pilot study.en
dc.typeJournal Articleen
dc.identifier.journaltitleEuropean journal of clinical nutritionen
dc.identifier.affiliationEndocrine Centre, Austin Health, Heidelberg Repatriation Hospital Campus, Heidelberg West, Victoria, Australiaen
dc.identifier.doi10.1038/ejcn.2012.3en
dc.description.pages628-32en
dc.relation.urlhttps://pubmed.ncbi.nlm.nih.gov/22274551en
dc.identifier.orcid0000-0002-0845-0001-
dc.type.austinJournal Articleen
local.name.researcherJerums, George
item.openairetypeJournal Article-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.deptOffice for Research-
crisitem.author.deptMedicine (University of Melbourne)-
crisitem.author.deptEndocrinology-
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