Quantification of absolute fat mass using an adipose tissue reference signal model

Oxidative gaseous air pollutant exposure interacts with PNPLA3-I148M genotype to influence liver fat fraction and multi-omics profiles in young adults

PNPLA3-I148M genotype is the strongest predictive single-nucleotide polymorphism for liver fat. We examine whether PNPLA3-I148M modifies associations between oxidative gaseous air pollutant exposure (Oxwt) with i) liver fat and ii) multi-omics profiles of miRNAs and metabolites linked to liver fat. Participants were 69 young adults (17-22 years) from the Meta-AIR cohort. Prior-month residential Oxwt exposure (redox-weighted oxidative capacity of nitrogen dioxide and ozone) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Liver fat fraction was assessed by MRI. Serum miRNAs and metabolites were assayed via NanoString nCounter and LC-HRMS, respectively. Multi-omics factor analysis (MOFA) was used to identify latent factors with shared variance across omics layers. Multivariable linear regression models adjusted for age, sex, body mass index, and genotype with liver fat or MOFA factors as an outcome and examined PNPLA3 (rs738409; CC/CG vs. GG) as a multiplicative interaction term. Overall, a standard deviation difference in Oxwt exposure was associated with 8.9% relative increase in liver fat (p = 0.04) and this relationship differed by PNPLA3 genotype (p-value for interaction term: pintx<0.001), whereby relative increases in liver fat for GG and CC/CG participants were 71.8% and 2.4%, respectively. There was no main effect of Oxwt on MOFA Factor 1 expression (p = 0.85), but there was an interaction with PNPLA3 genotype (pintx = 0.01), whereby marginal slopes were 0.211 and -0.017 for GG and CC/CG participants, respectively. MOFA Factor 1 in turn was associated with liver fat (p = 0.006). MOFA Factor 1 miRNAs targeted genes in Fatty Acid Biosynthesis and Metabolism and Lysine Degradation pathways. MOFA Factor 9 was also associated with liver fat and was comprised of branched-chain keto acid and amino acid metabolites. The effects of Oxwt exposure on liver fat is exacerbated in young adults with two PNPLA3 risk alleles, potentially through differential effects on miRNA and/or metabolite profiles.

Dihydroxyacetone phosphate is a novel predictor of hepatic fibrosis in Latino adolescents with obesity

OBJECTIVES

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common pediatric liver disease and can progress to liver fibrosis. Latino adolescents have increased MASLD and fibrosis risk. While fibrosis is diagnosed by biopsy or imaging, more accessible, noninvasive, and economical screening methods are needed. We aimed to use plasma metabolomics/lipidomics to identify potential fibrosis biomarkers in Latino adolescents with obesity.

METHODS

Liver stiffness (LS) was measured in 93 Latino adolescents with obesity using magnetic resonance elastography. Metabolites and lipids were extracted from plasma and identified on Compound Discoverer. Associations between metabolites/lipids and fibrosis (LS > 2.73 kPa) were determined using linear regression models after covariate adjustment. False discovery rate (FDR) adjusted Pearson's correlations were performed. Analytes yielding significant FDR-adjusted correlations were examined further by receiver operator curve analysis.

RESULTS

Mean (±standard deviation) alanine transaminase (ALT) was 45.7(±65.2) IU/L, hepatic fat fraction was 12.7(±9.1)%, and LS was 2.4(±0.3) kPa. We identified 795 metabolites and 413 lipids in plasma, but only one single metabolite, dihydroxyacetone phosphate (DHAP), a marker of triglyceride synthesis, was significantly associated with fibrosis after FDR adjustment (p < 0.05). In terms of predicting fibrosis, ALT had an area under the curve (AUC) of 0.79, and DHAP had an AUC of 0.79. When combined, ALT + DHAP had an AUC of 0.89.

CONCLUSIONS

The combination of ALT + DHAP may have the potential as an accurate, noninvasive test for liver fibrosis. Our data are limited to Latino children with obesity, and a larger cohort should be examined to further validate this novel biomarker.

The effect of fat model variation on muscle fat fraction quantification in a cross-sectional cohort

Spectroscopic imaging, rooted in Dixon's two-echo spin sequence to distinguish water and fat, has evolved significantly in acquisition and processing. Yet precise fat quantification remains a persistent challenge in ongoing research. With adequate phase characterization and correction, the fat composition models will impact measurements of fatty tissue. However, the effect of the used fat model in low-fat regions such as healthy muscle is unknown. In this study, we investigate the effect of assumed fat composition, in terms of chain length and double bond count, on fat fraction quantification in healthy muscle, while addressing phase and relaxometry confounders. For this purpose, we acquired bilateral thigh datasets from 38 healthy volunteers. Fat fractions were estimated using the IDEAL algorithm employing three different fat models fitted with and without the initial phase constrained. After data processing and model fitting, we used a convolutional neural net to automatically segment all thigh muscles and subcutaneous fat to evaluate the fitted parameters. The fat composition was compared with those reported in the literature. Overall, all the observed estimated fat composition values fall within the range of previously reported fatty acid composition based on gas chromatography measurements. All methods and models revealed different estimates of the muscle fat fractions in various evaluated muscle groups. Lateral differences changed from 0.5% to 5.3% in the hamstring muscle groups depending on the chosen method. The lowest observed left-right differences in each muscle group were all for the fat model estimating the number of double bonds with the initial phase unconstrained. With this model, the left-right differences were 0.64% ± 0.31%, 0.50% ± 0.27%, and 0.50% ± 0.40% for the quadriceps, hamstrings, and adductors muscle groups, respectively. Our findings suggest that a fat model estimating double bond numbers while allowing separate phases for each chemical species, given some assumptions, yields the best fat fraction estimate for our dataset.

Volumetric muscle composition analysis in sporadic inclusion body myositis using fat-referenced magnetic resonance imaging: Disease pattern, repeatability, and natural progression

INTRODUCTION/AIMS

Fat-referenced magnetic resonance imaging (MRI) has emerged as a promising volumetric technique for measuring muscular volume and fat in neuromuscular disorders, but the experience in inflammatory myopathies remains limited. Therefore, this work aimed at describing how sporadic inclusion body myositis (sIBM) manifests on standardized volumetric fat-referenced MRI muscle measurements, including within-scanner repeatability, natural progression rate, and relationship to clinical parameters.

METHODS

Ten sIBM patients underwent whole-leg Dixon MRI at baseline (test-retest) and after 12 months. The lean muscle volume (LMV), muscle fat fraction (MFF), and muscle fat infiltration (MFI) of the quadriceps, hamstrings, adductors, medial gastrocnemius, and tibialis anterior were computed. Clinical assessments of IBM Functional Rating Scale (IBMFRS) and knee extension strength were also performed. The baseline test-retest MRI measurements were used to estimate the within-subject standard deviation (sw). 12-month changes were derived for all parameters.

RESULTS

The MRI measurements showed high repeatability in all muscles; sw ranged from 2.7 to 18.0 mL for LMV, 0.7-1.3 percentage points (pp) for MFF, and 0.2-0.7 pp for MFI. Over 12 months, average LMV decreased by 7.4% while MFF and MFI increased by 3.8 pp and 1.8 pp, respectively. Mean IBMFRS decreased by 2.4 and mean knee extension strength decreased by 32.8 N.

DISCUSSION

The MRI measurements showed high repeatability and 12-month changes consistent with muscle atrophy and fat replacement as well as a decrease in both muscle strength and IBMFRS. Our findings suggest that fat-referenced MRI measurements are suitable for assessing disease progression and treatment response in inflammatory myopathies.

Ambient air pollution exposure is associated with liver fat and stiffness in Latino youth with a more pronounced effect in those with PNPLA3 genotype and more advanced liver disease

BACKGROUND

Exposure to ambient air pollutants has emerged as a risk for metabolic-dysfunction associated steatotic liver disease (MASLD).

OBJECTIVES

We sought to examine associations between short-term (prior month) and long-term (prior year) ambient air pollution exposure with hepatic fat fraction (HFF) and liver stiffness in Latino youth with obesity. A secondary aim was to investigate effect modification by patatin-like phospholipase domain-containing protein 3 (PNPLA3) genotype and liver disease severity.

METHODS

Data was analyzed from 113 Latino youth (age 11-19) with obesity in Southern California. Individual exposure to particulate matter with aerodynamic diameter ≤ 2.5μm (PM2.5), ≤ 10μm (PM10), nitrogen dioxide (NO2), 8-hour maximum ozone (8hrMax-O3), 24-hr O3, and redox-weighted oxidative capacity (Oxwt) were estimated using residential address histories and United States Environmental Protection Agency air quality observations. HFF and liver stiffness were measured using magnetic resonance imaging. Linear models were used to determine associations between short-term and long-term exposure to air pollutants with HFF and liver stiffness. Modification by PNPLA3 and liver disease severity was then examined.

RESULTS

Short-term exposure to 8hrMax-O3 was positively associated with HFF. Relationships between air pollution exposure and HFF were not impacted by PNPLA3 genotype or liver disease severity. Long-term exposure to 8hrMax-O3 and Oxwt were positively associated with liver stiffness. Associations between air pollution exposure and liver stiffness depended on PNPLA3 genotype, such that individuals with GG genotypes exhibited stronger, more positive relationships between short-term exposure to PM10, 8hrMax-O3, 24-hr O3, and Oxwt and liver stiffness than individuals with CC/CG genotypes. In addition, relationships between short-term exposure to NO2 and liver stiffness were stronger in those with severe liver disease.

DISCUSSION

Air pollution exposure may be a risk factor for liver disease among Latino youth with obesity, particularly in those with other preexisting risks for liver damage.

Compositional and Functional MRI of Skeletal Muscle: A Review

Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Associations of dietary sugars with liver stiffness in Latino adolescents with obesity differ on PNPLA3 and liver disease severity

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common paediatric liver disease. Latinos have high MASLD risk due to 50% prevalence of GG genotype of PNPLA3. Our primary aim was to evaluate associations between dietary carbohydrates/sugars and liver stiffness in Latino adolescents with obesity. Our secondary aim was to examine effect modification by (a) PNPLA3 genotype or (b) liver disease severity. Data were obtained from 114 Latino adolescents with obesity involved in two prior studies. No associations were seen between dietary carbohydrates/sugars and liver stiffness in the group as a whole. In subjects with GG genotype of PNPLA3, total sugar, fructose, sucrose, and glucose were associated with liver stiffness. Positive relationships between carbohydrate, total sugar, and sucrose and liver stiffness were stronger in those with MASLD and fibrosis compared to those with healthy livers and MASLD without fibrosis.

Exposure to ambient air pollutants, serum miRNA networks, lipid metabolism, and non-alcoholic fatty liver disease in young adults

BACKGROUND AND AIM

Ambient air pollution (AAP) exposure has been associated with altered blood lipids and liver fat in young adults. MicroRNAs regulate gene expression and may mediate these relationships. This work investigated associations between AAP exposure, serum microRNA networks, lipid profiles, and non-alcoholic fatty liver disease (NAFLD) risk in young adults.

METHODS

Participants were 170 young adults (17-22 years) from the Meta-AIR cohort of the Children's Health Study (CHS). Residential AAP exposure (PM2.5, PM10, NO2, 8-hour maximum O3, redox-weighted oxidative capacity [Oxwt]) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Fasting serum lipids were assayed. Liver fat was imaged by MRI and NAFLD was defined by ≥ 5.5% hepatic fat fraction. Serum microRNAs were measured via NanoString and microRNA networks were constructed by weighted gene correlation network analysis. The first principal component of each network represented its expression profile. Multivariable mixed effects regression models adjusted for sociodemographic, behavioral, and clinical covariates; baseline CHS town code was a random effect. Effects estimates are scaled to one standard deviation of exposure. Mediation analysis explored microRNA profiles as potential mediators of exposure-outcome associations. DIANA-mirPATH identified overrepresented gene pathways targeted by miRNA networks.

RESULTS

Prior-month Oxwt was associated with NAFLD (OR=3.45; p = 0.003) and inversely associated with microRNA Network A (β = -0.016; p = 0.026). Prior-year NO2 was associated with non-HDL-cholesterol (β = 7.13; p = 0.01) and inversely associated with miRNA Network A (β = -0.019; p = 0.022). Network A expression was inversely associated with NAFLD (OR=0.35; p = 0.010) and non-HDL-C (β = -6.94 mg/dL; p = 0.035). Network A members miR-199a/b-3p and miR-130a, which both target fatty acid synthase, mediated 21% of the association between prior-month Oxwt exposure with NAFLD (p = 0.048) and 23.3% of the association between prior-year NO2 exposure and non-HDL-cholesterol (p = 0.026), respectively.

CONCLUSIONS

Exposure to AAP may contribute to adverse lipid profiles and NAFLD risk among young adults via altered expression of microRNA profiles.

Body composition profiling at 0.55T: Feasibility and precision

PURPOSE

Body composition MRI captures the distribution of fat and lean tissues throughout the body, and provides valuable biomarkers of obesity, metabolic disease, and muscle disorders, as well as risk assessment. Highly reproducible protocols have been developed for 1.5T and 3T MRI. The purpose of this work was to demonstrate the feasibility and test-retest repeatability of MRI body composition profiling on a 0.55T whole-body system.

METHODS

Healthy adult volunteers were scanned on a whole-body 0.55T MRI system using the integrated body RF coil. Experiments were performed to refine parameter settings such as TEs, resolution, flip angle, bandwidth, acceleration, and oversampling factors. The final protocol was evaluated using a test-retest study with subject removal and replacement in 10 adult volunteers (5 M/5F, age 25-60, body mass index 20-30).

RESULTS

Compared to 1.5T and 3T, the optimal flip angle at 0.55T was higher (15°), due to the shorter T1 times, and the optimal echo spacing was larger, due to smaller chemical shift between water and fat. Overall image quality was comparable to conventional field strengths, with no significant issues with fat/water swapping or inadequate SNR. Repeatability coefficient of visceral fat, subcutaneous fat, total thigh muscle volume, muscle fat infiltration, and liver fat were 11.8 cL (2.2%), 46.9 cL (1.9%), 14.6 cL (0.5%), 0.1 pp (2%), and 0.2 pp (5%), respectively (coefficient of variation in parenthesis).

CONCLUSIONS

We demonstrate that 0.55T body composition MRI is feasible and present optimized scan parameters. The resulting images provide satisfactory quality for automated post-processing and produce repeatable results.

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 (LWS_rel ) 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

LWS_rel , 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 LWS_rel and tissue volumes. LWS_rel 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 LWS_rel 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 LWS_rel and ultrafiltration volume (r = 87), as well as with BCM OH (r = 0.66).

DATA CONCLUSION

MRI-based LWS_rel and tissue volume measurements are sensitive to tissue hydration changes occurring during dialysis.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 3.

Clinical Intervention to Reduce Dietary Sugar Does Not Affect Liver Fat in Latino Youth, Regardless of PNPLA3 Genotype: A Randomized Controlled Trial

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) among Latinos is partially attributed to a prevalent C>G polymorphism in the patatin-like phospholipase 3 (PNPLA3) gene. Cross-sectional analyses in Latino children showed the association between dietary sugar and liver fat was exacerbated by GG genotype. Pediatric feeding studies show extreme sugar restriction improves liver fat, but no prior trial has examined the impact of a clinical intervention or whether effects differ by PNPLA3 genotype.

OBJECTIVES

We aimed to test effects of a clinical intervention to reduce dietary sugar compared with standard dietary advice on change in liver fat, and secondary-endpoint changes in liver fibrosis, liver enzymes, and anthropometrics; and whether effects differ by PNPLA3 genotype (assessed retrospectively) in Latino youth with obesity (BMI ≥ 95th percentile).

METHODS

This parallel-design trial randomly assigned participants (n = 105; mean baseline liver fat: 12.7%; mean age: 14.8 y) to control or sugar reduction (goal of ≤10% of calories from free sugar) for 12 wk. Intervention participants met with a dietitian monthly and received delivery of bottled water. Changes in liver fat, by MRI, were assessed by intervention group via general linear models.

RESULTS

Mean free sugar intake decreased in intervention compared with control [11.5% to 7.3% compared with 13.9% to 10.7% (% energy), respectively; P = 0.02], but there were no significant effects on liver outcomes or anthropometrics (Pall > 0.10), and no PNPLA3 interactions (Pall > 0.10). In exploratory analyses, participants with whole-body fat mass (FM) reduction (mean ± SD: -1.9 ± 2.4 kg), irrespective of randomization, had significant reductions in liver fat compared with participants without FM reduction (median: -2.1%; IQR: -6.5% to -0.8% compared with 0.3%; IQR: -1.0% to 1.1%; P < 0.001).

CONCLUSIONS

In Latino youth with obesity, a dietitian-led sugar reduction intervention did not improve liver outcomes compared with control, regardless of PNPLA3 genotype. Results suggest FM reduction is important for liver fat reduction, confirming clinical recommendations of weight loss and a healthy diet for pediatric NAFLD.This trial was registered at clinicaltrials.gov as NCT02948647.

The effect on precision and T1 bias comparing two flip angles when estimating muscle fat infiltration using fat-referenced chemical shift-encoded imaging

Investigation of the effect on accuracy and precision of different parameter settings is important for quantitative MRI. The purpose of this study was to investigate T1 bias and precision for muscle fat infiltration (MFI) measurements using fat-referenced chemical shift MFI measurements at flip angles of 5° and 10°. The fat-referenced measurements were compared with fat fractions, which is a more commonly used measure of MFI. This retrospective study was performed on data from a clinical intervention study including 40 postmenopausal women. Test and retest images were acquired with a 3-T scanner using four-point 3D spoiled gradient multiecho acquisition. Postprocessing included T2* correction and fat-referenced calibration, where the fat signal was calibrated using adipose tissue as reference. The mean MFI was calculated in six different muscle regions using both the fat-referenced fat signal and the fat fraction, defined as the fat signal divided by the sum of the fat and water signals. Both methods used the same fat and water images as input. The variance of the difference between mean MFI from test and retest was used as the measure of precision. The signal-to-noise ratio (SNR) characteristics were analyzed by measuring the full width at half maximum (FWHM) of the fat signal distribution. There was no difference in the mean MFI at different flip angles for the fat-referenced technique (p = 0.66), while the measured fat fractions were 3.3 percentage points larger for 10° compared with 5° (p < 0.001). No significant difference in the precision was found in any of the muscles analyzed. However, the FWHM of the fat signal distribution was significantly (p = 0.01) lower at 10°. This strenghtens the hypothesis that fat-referenced MFI is insensitive to flip angle-induced T1 bias in CSE-MRI, enabling usage of a higher and more SNR-effective flip angle. The lower FWHM in fat-referenced MFI at 10° indicates that high flip angle acquisition is advantageous even although no significant differences in precision were observed comparing 5° and 10°.

Pericardial adipose tissue, cardiac structures, and cardiovascular risk factors in school-age children

Aims 

We examined the associations of pericardial adipose tissue with cardiac structures and cardiovascular risk factors in children.

Methods and results 

We performed a cross-sectional analysis in a population-based cohort study among 2892 children aged 10 years (2404 normal weight and 488 overweight/obese). Pericardial adipose tissue mass was estimated by magnetic resonance imaging (MRI) and indexed on height³. Left ventricular mass (LVM) and left ventricular mass-to-volume ratio (LMVR) were estimated by cardiac MRI. Cardiovascular risk factors included android adipose tissue percentage obtained by Dual-energy X-ray absorptiometry, blood pressure and glucose, insulin, cholesterol, and triglycerides concentrations. Adverse outcomes were defined as values above the 75 percentile. Median pericardial adipose tissue index was 3.6 (95% range 1.6–7.1) among normal weight and 4.7 (95% range 2.0–8.9) among overweight children. A one standard deviation (1 SD) higher pericardial adipose tissue index was associated with higher LMVR [0.06 standard deviation scores, 95% confidence interval (CI) 0.02–0.09], increased odds of high android adipose tissue [odd ratio (OR) 2.08, 95% CI 1.89–2.29], high insulin concentrations (OR 1.17, 95% CI 1.06–1.30), an atherogenic lipid profile (OR 1.22, 95% CI 1.11–1.33), and clustering of cardiovascular risk factors (OR 1.56, 95% CI 1.36–1.79). Pericardial adipose tissue index was not associated with LVM, blood pressure, and glucose concentrations. The associations showed largely the same directions but tended to be weaker among normal weight than among overweight children.

Conclusion 

Pericardial adipose tissue is associated with cardiac adaptations and cardiovascular risk factors already in childhood in both normal weight and overweight children.

MRI adipose tissue and muscle composition analysis-a review of automation techniques

MRI is becoming more frequently used in studies involving measurements of adipose tissue and volume and composition of skeletal muscles. The large amount of data generated by MRI calls for automated analysis methods. This review article presents a summary of automated and semi-automated techniques published between 2013 and 2017. Technical aspects and clinical applications for MRI-based adipose tissue and muscle composition analysis are discussed based on recently published studies. The conclusion is that very few clinical studies have used highly automated analysis methods, despite the rapidly increasing use of MRI for body composition analysis. Possible reasons for this are that the availability of highly automated methods has been limited for non-imaging experts, and also that there is a limited number of studies investigating the reproducibility of automated methods for MRI-based body composition analysis.

Advanced body composition assessment: from body mass index to body composition profiling

This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat, in combination with rapid scanning protocols and efficient image analysis tools, makes quantitative MRI a powerful tool for advanced body composition assessment.

Magnetic resonance rotator cuff fat fraction and its relationship with tendon tear severity and subject characteristics

BACKGROUND

Compared with the Goutallier classification, chemical shift-based magnetic resonance (MR) fat quantification has superior reliability and accuracy in evaluation of muscle fatty infiltration. We used this method to assess the relationship between rotator cuff (RC) muscle fat fractions, tendon disease severity, and subject characteristics.

METHODS

In total, 182 subjects with shoulder symptoms underwent shoulder MR imaging including additional sequences for fat quantitation. Then, fat fraction maps were manually segmented, and custom software was used to compute the fat fraction. Goutallier scores were also obtained. The relationship between fat fraction and tendon tear severity and subject characteristics was assessed with descriptive statistics, analysis of variance, Student t test of different subgroups, and simple and multiple linear regression analysis.

RESULTS

Statistically higher supraspinatus fat fractions were observed in subgroups with tendon tears >3 cm, retraction >1 cm, age >50 years, body mass index (BMI) >30, higher Goutallier score, female gender, and longer symptom duration. A significant linear relationship was seen between RC fat fraction and tendon disease severity, age, and BMI but not symptom duration. Multiple regression models with fat fraction and tendon disease, age, BMI, and gender were significant for all 4 muscles (P < .001). The slope of fatty infiltration increase with age was reduced after adjustment for tendon disease, BMI, and gender.

CONCLUSION

RC fat fraction assessed by chemical shift MR demonstrated a significant linear relationship with tendon tear severity, age, BMI, and gender but not with symptom duration.

Characterization of brown adipose tissue by water-fat separated magnetic resonance imaging

BACKGROUND

To evaluate the possibility of quantifying brown adipose tissue (BAT) volume and fat concentration with a high resolution, long echo time, dual-echo Dixon imaging protocol.

METHODS

A 0.42 mm isotropic resolution water-fat separated MRI protocol was implemented by using the second opposite-phase echo and third in-phase echo. Fat images were calibrated with regard to the intensity of nearby white adipose tissue (WAT) to form relative fat content (RFC) images. To evaluate the ability to measure BAT volume and RFC contrast dynamics, rats were divided into two groups that were kept at 4° or 22°C for 5 days. The rats were then scanned in a 70 cm bore 3.0 Tesla MRI scanner and a human dual energy CT. Interscapular, paraaortal, and perirenal BAT (i/pa/pr-BAT) depots as well as WAT and muscle were segmented in the MRI and CT images. Biopsies were collected from the identified BAT depots.

RESULTS

The biopsies confirmed that the three depots identified with the RFC images consisted of BAT. There was a significant linear correlation (P < 0.001) between the measured RFC and the Hounsfield units from DECT. Significantly lower iBAT RFC (P = 0.0064) and significantly larger iBAT and prBAT volumes (P = 0.0017) were observed in the cold stimulated rats.

CONCLUSION

The calibrated Dixon images with RFC scaling can depict BAT and be used to measure differences in volume, and fat concentration, induced by cold stimulation. The high correlation between RFC and HU suggests that the fat concentration is the main RFC image contrast mechanism.

Whole-body MRI-based fat quantification: a comparison to air displacement plethysmography

PURPOSE

To demonstrate the feasibility of an algorithm for MRI whole-body quantification of internal and subcutaneous fat and quantitative comparison of total adipose tissue to air displacement plethysmography (ADP).

MATERIALS AND METHODS

For comparison with ADP, whole-body MR data of 11 volunteers were obtained using a continuously moving table Dixon sequence. Resulting fat images were corrected for B1 related intensity inhomogeneities before fat segmentation.

RESULTS

The performed MR measurements of the whole body provided a direct comparison to ADP measurements. The segmentation of subcutaneous and internal fat in the abdomen worked reliably with an accuracy of 98%. Depending on the underlying model for fat quantification, the resultant MR fat masses represent an upper and a lower limit for the true fat masses. In comparison to ADP, the results were in good agreement with ρ ≥ 0.97, P < 0.0001.

CONCLUSION

Whole-body fat quantities derived noninvasively by using a continuously moving table Dixon acquisition were directly compared with ADP. The accuracy of the method and the high reproducibility of results indicate its potential for clinical applications.

Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle

PURPOSE

To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach.

MATERIALS AND METHODS

Unsupervised standard k-means clustering was used to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages: tissue, muscle, and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared with a manual segmentation.

RESULTS

The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R(2): 0.96) and for cases with up to moderate IMAT area in the calf (R(2): 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation.

CONCLUSION

The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total postprocessing time.

Quantification of low fat contents: a comparison of MR imaging and spectroscopy methods at 1.5 and 3 T

Magnetic resonance spectroscopy (MRS) has long been considered the golden standard for non-invasive measurement of tissue fat content. With improved techniques for fat/water separation, imaging has become an alternative to MRS for fat quantification. Several imaging models have been proposed, but their performance relative to MRS at very low fat contents is yet not fully established. In this work, imaging and spectroscopy were compared at 1.5 T and 3 T in phantoms with 0-3% fat fraction (FF). We propose a multispectral model with individual a priori R(2) relaxation rates for water and fat, and a common unknown R(2)' relaxation. Magnitude and complex image reconstructions were also compared. Best accuracy was obtained with the imaging method at 1.5 T. At 3 T, the FFs were underestimated due to larger fat-water phase shifts. Agreement between measured and true FF was excellent for the imaging method at 1.5 T (imaging: FF(meas)=0.98 FF(true)-0.01%, spectroscopy: FF(meas)=0.77 FF(true)+0.08%), and fair at 3 T (imaging: FF(meas)=0.91 FF(true)-0.19%, spectroscopy: FF(meas)=0.79 FF(true)+0.02%). The imaging method was able to quantify FFs down to approx. 0.5%. We conclude that the suggested imaging model is capable of fat quantification with accuracy and precision similar to or better than spectroscopy and offers an improvement vs. a model with a common R(2)* relaxation only.

T₁-corrected fat quantification using chemical shift-based water/fat separation: application to skeletal muscle

Chemical shift-based water/fat separation, like iterative decomposition of water and fat with echo asymmetry and least-squares estimation, has been proposed for quantifying intermuscular adipose tissue. An important confounding factor in iterative decomposition of water and fat with echo asymmetry and least-squares estimation-based intermuscular adipose tissue quantification is the large difference in T(1) between muscle and fat, which can cause significant overestimation in the fat fraction. This T(1) bias effect is usually reduced by using small flip angles. T(1) -correction can be performed by using at least two different flip angles and fitting for T(1) of water and fat. In this work, a novel approach for the water/fat separation problem in a dual flip angle experiment is introduced and a new approach for the selection of the two flip angles, labeled as the unequal small flip angle approach, is developed, aiming to improve the noise efficiency of the T(1) -correction step relative to existing approaches. It is shown that the use of flip angles, selected such the muscle water signal is assumed to be T(1) -independent for the first flip angle and the fat signal is assumed to be T(1) -independent for the second flip angle, has superior noise performance to the use of equal small flip angles (no T(1) estimation required) and the use of large flip angles (T(1) estimation required).

MR water quantitative priors improves the accuracy of optical breast imaging

Magnetic resonance (MR) guided optical breast imaging is a promising modality to improve the specificity of breast imaging, because it provides high-resolution quantitative maps of total hemoglobin, oxygen saturation, water content, and optical scattering. These properties have been shown to distinguish malignant from benign lesions. However, the optical detection hardware required for deep tissue imaging has poor spectral sensitivity which limits accurate water quantification; this reduces the accuracy of hemoglobin quantification. We present a methodology to improve optical quantification by utilizing the ability of Dixon MR imaging to quantitatively estimate water and fat; this technique effectively reduces optical crosstalk between water and oxyhemoglobin. The techniques described in this paper reduce hemoglobin quantification error by as much as 38%, as shown in a numerical phantom, and an experimental phantom. Error is reduced by as much 20% when imperfect MR water quantification is given. These techniques may also increase contrast between diseased and normal tissue, as shown in breast tissue in vivo. It is also shown that using these techniques may permit fewer wavelengths to be used with similar quantitative accuracy, enabling higher temporal resolution. In addition, it is shown that these techniques can improve the ability of MRI to quantify water in the presence of bias in the Dixon water/fat separation.

Change in the proton T(1) of fat and water in mixture

This work describes observed changes in the proton T(1) relaxation time of both water and lipid when they are in relatively homogeneous mixtures. Results obtained from vegetable oil-water emulsions, pork kidney and lard mixtures, and excised samples of white and brown adipose tissues are presented to demonstrate this change in T(1) as a function of mixture fat fraction. As an initial proof of concept, a simpler acetone-water experiment was performed to take advantage of complete miscibility between acetone and water and both components' single chemical shift peaks. Single-voxel MR spectroscopy was used to measure the T(1) of predominant methylene spins in fat and the T(1) of water spins in each setup. In the vegetable oil-water emulsions, the T(1) of fat varied by as much as 3-fold when water was the dominant mixture component. The T(1) of pure lard increased by 170 msec (+37%) when it was blended with lean kidney tissue in a 16% fatty mixture. The fat T(1) of lipid-rich white adipose tissue was 312 msec. In contrast, the fat T(1) of leaner brown adipose tissue (fat fraction 53%) was 460 msec. A change in the water T(1) from that of pure water was also observed in the experiments.