Assessing Tissue Hydration Dynamics Based on Water/Fat Separated MRI.

BACKGROUND: Optimal fluid status is an important issue in hemodialysis. Clinical evaluation of volume status and different diagnostic tools are used to determine hydration status in these patients. However, there is still no accurate method for this assessment. PURPOSE: To propose and evaluate relative lean water signal (LWSrel ) as a water-fat MRI-based tissue hydration measurement. STUDY TYPE: Prospective. POPULATION: A total of 16 healthy subjects (56 ± 6 years, 0 male) and 11 dialysis patients (60.3 ± 12.3 years, 9 male; dialysis time per week 15 ± 3.5 hours, dialysis duration 31.4 ± 27.9 months). FIELD STRENGTH/SEQUENCE: A 3 T; 3D spoiled gradient echo. ASSESSMENT: LWSrel , a measurement of the water concentration of tissue, was estimated from fat-referenced MR images. Segmentations of total adipose tissue as well as thigh and calf muscles were used to measure LWSrel and tissue volumes. LWSrel was compared between healthy subjects and dialysis patients, the latter before and after dialysis. Bioimpedance-based body composition monitor over hydration (BCM OH) was also measured. STATISTICAL TESTS: T-tests were used to compare differences between the healthy subjects and dialysis patients, as well as changes between before and after dialysis. Pearson correlation was calculated between MRI and non-MRI biomarkers. A P value <0.05 was considered statistically significant. RESULTS: The LWSrel in adipose tissue was significantly higher in the dialysis cohort compared with the healthy cohort (246.8% ± 60.0% vs. 100.0% ± 10.8%) and decreased significantly after dialysis (246.8 ± 60.0% vs. 233.8 ± 63.4%). Thigh and calf muscle volumes also significantly decreased by 3.78% ± 1.73% and 2.02% ± 2.50% after dialysis. There was a significant correlation between changes in adipose tissue LWSrel and ultrafiltration volume (r = 87), as well as with BCM OH (r = 0.66). DATA CONCLUSION: MRI-based LWSrel and tissue volume measurements are sensitive to tissue hydration changes occurring during dialysis. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

Body Composition Profiling in the UK Biobank Imaging Study.

OBJECTIVE: This study aimed to investigate the value of imaging-based multivariable body composition profiling by describing its association with coronary heart disease (CHD), type 2 diabetes (T2D), and metabolic health on individual and population levels. METHODS: The first 6,021 participants scanned by UK Biobank were included. Body composition profiles (BCPs) were calculated, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VAT), thigh muscle volume, liver fat, and muscle fat infiltration (MFI), determined using magnetic resonance imaging. Associations between BCP and metabolic status were investigated using matching procedures and multivariable statistical modeling. RESULTS: Matched control analysis showed that higher VAT and MFI were associated with CHD and T2D (P < 0.001). Higher liver fat was associated with T2D (P < 0.001) and lower liver fat with CHD (P < 0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (P < 0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity. CONCLUSIONS: Body composition profiling enabled an intuitive visualization of body composition and showed the complexity of associations between fat distribution and metabolic status, stressing the importance of a multivariable approach. Different diseases were linked to different BCPs, which could not be described by a single fat compartment alone.

Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method.

Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m2) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R2) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.