Comparison of gross body fat‐water magnetic resonance imaging at 3 Tesla to dual‐energy X‐ray absorptiometry in obese women

Abstract

Improved understanding of how depot-specific adipose tissue mass predisposes to obesity-related comorbidities could yield new insights into the pathogenesis and treatment of obesity as well as metabolic benefits of weight loss. We hypothesized that three-dimensional contiguous “fat-water” MR imaging (FWMRI) covering the majority of a whole-body field of view (FOV) acquired at 3 Tesla (3T) and coupled with automated segmentation and quantification of amount, type and distribution of adipose and lean soft tissue would show great promise in body composition methodology. Precision of adipose and lean soft tissue measurements in body and trunk regions were assessed for 3T FWMRI and compared to DEXA. Anthropometric, FWMRI and DEXA measurements were obtained in twelve women with BMI 30–39.9 kg/m2. Test-retest results found coefficients of variation for FWMRI that were all under 3%: gross body adipose tissue (GBAT) 0.80%, total trunk adipose tissue (TTAT) 2.08%, visceral adipose tissue (VAT) 2.62%, subcutaneous adipose tissue (SAT) 2.11%, gross body lean soft tissue (GBLST) 0.60%, and total trunk lean soft tissue (TTLST) 2.43%. Concordance correlation coefficients between FWMRI and DEXA were 0.978, 0.802, 0.629, and 0.400 for GBAT, TTAT, GBLST and TTLST, respectively. While Bland Altman plots demonstrated agreement between FWMRI and DEXA for GBAT and TTAT, a negative bias existed for GBLST and TTLST measurements. Differences may be explained by the FWMRI FOV length and potential for DEXA to overestimate lean soft tissue. While more development is necessary, the described 3T FWMRI method combined with fully-automated segmentation is fast (<30 minutes total scan and post-processing time), noninvasive, repeatable and cost effective.

Body mass index in dementia

“…17,18 Since BMI doesn't distinguish between fat tissue and lean muscle mass, it could be a poor marker of the kind of weight excess that causes cardiovascular risk. Direct measures of body fat are preferable, with computed tomography and magnetic resonance imaging volume measurements being the current gold standards, closely followed by dual-energy X-ray absorptiometry, 26 but these methods are costly and impractical. Other biometric indexes have sought to characterize body composition and fat distribution better than BMI.…”

DXA-measured visceral adipose tissue predicts impaired glucose tolerance and metabolic syndrome in obese Caucasian and African-American women

“…We previously demonstrated that DEXA whole body scans are as reliable as whole body continuous MRI for measurement of total fat, total lean, trunk fat and trunk lean masses (39). The present study extends our prior findings by showing that estimating VAT directly from DEXA whole body scans is a more robust indicator of cardiometabolic risk in women with Class I and II obesity of European American and African American descent than other more commonly acquired anthropometric (weight, BMI, waist circumference, waist-hip ratio, waist-height ratio) and DEXA-derived surrogate measures of intra-abdominal adipose tissue (percent body fat, percent trunk fat, percent android fat, android/gynoid ratio).…”

“…Before each acquisition, the scanner was phantom calibrated according to manufacturer instructions. Duplicate scans after repositioning 12 subjects showed coefficients of variation <2% for fat and lean total and trunk masses (39). Scans were imported into an updated version of the software (version 13.6) and reanalyzed using algorithms that provided automatic segmentation of VAT from total abdominal fat within the android region.…”

“…However, such estimation has not distinguished VAT from SAT and the most reliable estimates have come from non-obese persons (35, 37, 38). Nevertheless, we previously showed strong correlations between DEXA and water-suppressed T1 weighted MRI measures of total and regional body composition, with coefficients of variation less than 2% for DEXA-derived adiposity measures (39). More recently, algorithms in updated versions of the software used on DEXA scanners have been developed to segment fat within the android region into VAT and SAT (40).…”

Consuming a balanced high fat diet for 16 weeks improves body composition, inflammation and vascular function parameters in obese premenopausal women

“…Coefficients of variation from repeated measures of 12 randomly selected subjects were 0.58% for fat mass, 0.42% for lean mass, 1.35% for trunk fat and 1.02% for trunk lean [28]. …”