title: Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images.
abstract: Intermuscular adipose tissue (IMAT), a novel fat depot linked with metabolic abnormalities, has been measured by whole body MRI. The cross-sectional slice location with the strongest relation to total body IMAT volume has not been established. The aim was to determine the predictive value of each slice location and which slice locations provide the best estimates of whole body IMAT. MRI quantified total adipose tissue of which IMAT, defined as adipose tissue visible within the boundary of the muscle fascia, is a subcomponent. Single-slice IMAT areas were calculated for the calf, thigh, buttock, waist, shoulders, upper arm, and forearm locations in a sample of healthy adult women, African-American [n = 39; body mass index (BMI) 28.5 +/- 5.4 kg/m2; 41.8 +/- 14.8 yr], Asian (n = 21; BMI 21.6 +/- 3.2 kg/m2; 40.9 +/- 16.3 yr), and Caucasian (n = 43; BMI 25.6 +/- 5.3 kg/m2; 43.2 +/- 15.3 yr), and Caucasian men (n = 39; BMI 27.1 +/- 3.8 kg/m2; 45.2 +/- 14.6 yr) and used to estimate total IMAT groups using multiple-regression equations. Midthigh was the best, or near best, single predictor in all groups with adjusted R2 ranging from 0.49 to 0.84. Adding a second and third slice further increased R2 and reduced the error of the estimate. Menopausal status and degree of obesity did not affect the location of the best single slice. The contributions of other slice locations varied by sex and race, but additional slices improved predictions. For group studies, it may be more cost-effective to estimate IMAT based on one or more slices than to acquire and segment for each subject the numerous images necessary to quantify whole body IMAT.
authors.affiliation: Department of Medicine, Obesity Research Center, St. Luke's-Roosevelt Hospital, New York, New York 10025, USA.
authors.forename: Xiang Yan
authors.initials: XY
authors.lastname: Ruan
authors.forename: Dympna
authors.initials: D
authors.lastname: Gallagher
authors.forename: Tamara
authors.initials: T
authors.lastname: Harris
authors.forename: Jeanine
authors.initials: J
authors.lastname: Albu
authors.forename: Steven
authors.initials: S
authors.lastname: Heymsfield
authors.forename: Patrick
authors.initials: P
authors.lastname: Kuznia
authors.forename: Stanley
authors.initials: S
authors.lastname: Heshka
mesh_terms: D000273:Adipose Tissue / Q000033:anatomy & histology*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019412:Anatomy, Cross-Sectional / Q000191:economics / Q000379:methods*; D001823:Body Composition; D015992:Body Mass Index; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000191:economics / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009132:Muscles / Q000033:anatomy & histology; D011237:Predictive Value of Tests; D051598:Whole Body Imaging / Q000191:economics / Q000379:methods