The purpose of the study was to evaluate signal-fat-fraction (SFF) analysis based on a 2-point-Dixon water–fat separation method in whole-body simultaneous PET/MR imaging for identifying brown adipose tissue (BAT) and discriminating it from white adipose tissue (WAT) using cross-validation via PET. Methods: This retrospective, internal review board–approved study evaluated 66 PET/MR imaging examinations of 33 pediatric patients (mean age, 14.7 y; range, 7.4–21.4 y). Eleven elderly patients were evaluated as controls (mean age, 79.9 y; range, 76.3–88.6 y). Pediatric patients were divided into 2 groups: with and without metabolically active supraclavicular BAT. The standard of reference for the presence of BAT was at least 1 PET examination showing ¹⁸F-FDG uptake. PET/MR imaging included a 2-point Dixon water–fat separation method. Signal intensities in regions of interest on fat and water images and mean standardized uptake values (SUV_mean) were determined bilaterally in supraclavicular and gluteal fat depots. SFF was calculated from the ratio of fat signal over summed water and fat signal. Statistical analysis was conducted using the Student t test and correlation analysis. Results: SFF was significantly lower (P < 0.0001) in supraclavicular BAT than gluteal WAT in all pediatric subjects. Supraclavicular SFF was significantly higher in the control than in the pediatric group (P < 0.0001). In PET-positive patients with multiple examinations, SFF stayed stable whereas SUV_mean fluctuated (median intraindividual change, 5% vs. 91%). No significant correlation between SUV_mean and SFF could be observed for BAT. Conclusion: The results demonstrate that MR imaging–SFF analysis is a reproducible imaging modality for the detection of human BAT and discrimination from WAT. SFF values of BAT are independent from its metabolic activity, making SFF a more reliable parameter for BAT than the commonly used PET signal. However, with the intent to investigate both the composition of BAT and its activation status, hybrid PET/MR imaging might provide supplemental information.

The purpose of this study was to examine the relationship of the proton density fat fraction (PDFF), measured by magnetic resonance imaging (MRI), of supraclavicular and gluteal adipose tissue with subcutaneous and visceral adipose tissue (SAT and VAT) volumes, liver fat fraction and anthropometric obesity markers. The supraclavicular fossa was selected as a typical location where brown adipocytes may be present in humans and the gluteal region was selected as a typical location enclosing primarily white adipocytes. In this cross-sectional study, 61 adults (44 women, median age 29.3 years, range 21-68 years) underwent an MRI examination of the neck and the abdomen/pelvis (3T, Ingenia, Philips Healthcare). PDFF maps of the supraclavicular and gluteal adipose tissue and the liver were generated. Volumes of SAT and VAT were calculated and supraclavicular and subcutaneous fat were segmented using custom-built post-processing algorithms. Body mass index (BMI), waist circumference and waist-to-height ratio were recorded. Statistical analysis was conducted using the Student's t-test and Pearson correlation analysis. Mean supraclavicular PDFF was 75.3±4.7% (range 65.4-83.8%) and mean gluteal PDFF was 89.7±2.9% (range 82.2-94%), resulting in a significant difference (P<0.0001). Supraclavicular PDFF was positively correlated with VAT (r=0.76, P<0.0001), SAT (r=0.73, P<0.0001), liver PDFF (r=0.42, P=0.0008) and all measured anthropometric obesity markers. Gluteal subcutaneous PDFF also correlated with VAT (r=0.59, P<0.0001), SAT (r=0.63, P<0.0001), liver PDFF (r=0.3, P=0.02) and anthropometric obesity markers. The positive correlations between adipose tissue PDFF and imaging, as well as anthropometric obesity markers suggest that adipose tissue PDFF may be useful as a biomarker for improving the characterization of the obese phenotype, for risk stratification and for selection of appropriate treatment strategies.

Background: Adipose tissue (AT) can be classified into white and brown/beige subtypes. Chemical shift encoding‐based water–fat MRI‐techniques allowing simultaneous mapping of proton density fat fraction (PDFF) and T₂* result in a lower PDFF and a shorter T₂* in brown compared with white AT. However, AT T₂* values vary widely in the literature and are primarily based on 6‐echo data. Increasing the number of echoes in a multiecho gradient‐echo acquisition is expected to increase the precision of AT T₂* mapping.Purpose: 1) To mitigate issues of current T₂*‐measurement techniques through experimental design, and 2) to investigate gluteal and supraclavicular AT T₂* and PDFF and their relationship using a 20‐echo gradient‐echo acquisition.Study Type: Prospective.Subjects: Twenty‐one healthy subjects.Field Strength/Sequence Assessment: First, a ground truth signal evolution was simulated from a single‐T₂* water–fat model. Second, a time‐interleaved 20‐echo gradient‐echo sequence with monopolar gradients of neck and abdomen/pelvis at 3 T was performed in vivo to determine supraclavicular and gluteal PDFF and T₂*. Complex‐based water–fat separation was performed for the first 6 echoes and the full 20 echoes. AT depots were segmented.Statistical Tests: Mann‐Whitney test, Wilcoxon signed‐rank test and simple linear regression analysis.Results: Both PDFF and T₂* differed significantly between supraclavicular and gluteal AT with 6 and 20 echoes (PDFF: P < 0.0001 each, T₂*: P = 0.03 / P < 0.0001 for 6/20 echoes). 6‐echo T₂* demonstrated higher standard deviations and broader ranges than 20‐echo T₂*. Regression analyses revealed a strong relationship between PDFF and T₂* values per AT compartment (R² = 0.63 supraclavicular, R² = 0.86 gluteal, P < 0.0001 each).Data Conclusion: The present findings suggest that an increase in the number of sampled echoes beyond 6 does not affect AT PDFF quantification, whereas AT T₂* is considerably affected. Thus, a 20‐echo gradient‐echo acquisition enables a multiparametric analysis of both AT PDFF and T₂* and may therefore improve MR‐based differentiation between white and brown fat.Level of Evidence: 2Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2019;50:424–434.

Ageing, sarcopenia, and malnutrition are associated with quantitative and qualitative changes of body composition. There are several imaging modalities, including magnetic resonance imaging (MRI), for the assessment of trunk muscle tissue composition. In this study, we investigated the gender- and age-related changes in trunk muscle composition using chemical shift encoding-based water–fat MRI. A total of 79 healthy volunteers (26 men: 38.9 ± 10.4 years; 53 women: 39.5 ± 15.0 years) underwent 3T axial MRI using a six-echo multi-echo 3D spoiled gradient echo sequence, allowing for the calculation of the proton density fat fraction (PDFF) in the trunk muscles. PDFF of the abdominal, psoas, and erector spinae muscles were determined. We detected significant positive correlations for abdominal muscle PDFF with age (r = 0.638, p = 0.0001) in men, and for abdominal muscle PDFF (r = 0.709, p = 0.0001) and erector spinae muscle PDFF (r = 0.674, p = 0.0001) with age in women. After adjustment for body mass index (BMI), only the correlation of age and abdominal muscle PDFF in women remained significant (r = 0.631, p = 0.0001). The findings of this study suggest that an increasing fat deposition in muscle is driven primarily by age, rather than BMI, in women. These results further support that PDFF can be considered a valid imaging biomarker of trunk muscle composition.