Metabolic syndrome screening using visceral adipose tissue (VAT) from opportunistic MRI locations in a multi-ethnic population

Evaluation of visceral adipose tissue thresholds for elevated metabolic syndrome risk across diverse populations: A systematic review

Beyond obesity, excess levels of visceral adipose tissue (VAT) significantly contribute to the risk of developing metabolic syndrome (MetS), although thresholds for increased risk vary based on population, regions of interest, and units of measure employed. We sought to determine whether a common threshold exists that is indicative of heightened MetS risk across all populations, accounting for sex, age, BMI, and race/ethnicity. A systematic literature review was conducted in September 2023, presenting threshold values for elevated MetS risk. Standardization equations harmonized the results from DXA, CT, and MRI systems to facilitate a comparison of threshold variations across studies. A total of 52 papers were identified. No single threshold could accurately indicate elevated risk for both males and females across varying BMI, race/ethnicity, and age groups. Thresholds fluctuated from 70 to 165.9 cm2, with reported values consistently lower in females. Generally, premenopausal females and younger adults manifested elevated risks at lower VAT compared to their older counterparts. Notably, Asian populations exhibited elevated risks at lower VAT areas (70-136 cm2) compared to Caucasian populations (85.6-165.9 cm2). All considered studies reported associations of VAT without accommodating covariates. No single VAT area threshold for elevated MetS risk was discernible post-harmonization by technology, units of measure, and region of interest. This review summarizes available evidence for MetS risk assessment in clinical practice. Further exploration of demographic-specific interactions between VAT area and other risk factors is imperative to comprehensively delineate overarching MetS risk.

Predictors of visceral and subcutaneous adipose tissue and muscle density: The ShapeUp! Kids study

BACKGROUND AND AIMS

Body fat distribution, i.e., visceral (VAT), subcutaneous adipose tissue (SAT) and intramuscular fat, is important for disease prevention, but sex and ethnic differences are not well understood. Our aim was to identify anthropometric, demographic, and lifestyle predictors for these outcomes.

METHODS AND RESULTS

The cross-sectional ShapeUp!Kids study was conducted among five ethnic groups aged 5-18 years. All participants completed questionnaires, anthropometric measurements, and abdominal MRI scans. VAT and SAT areas at four lumbar levels and muscle density were assessed manually. General linear models were applied to estimate coefficients of determination (R2) and to compare the fit of VAT and SAT prediction models. After exclusions, the study population had 133 male and 170 female participants. Girls had higher BMI-z scores, waist circumference (WC), and SAT than boys but lower VAT/SAT and muscle density. SAT, VAT, and VAT/SAT but not muscle density differed significantly by ethnicity. R2 values were higher for SAT than VAT across groups and improved slightly after adding WC. For SAT, R2 increased from 0.85 to 0.88 (girls) and 0.62 to 0.71 (boys) when WC was added while VAT models improved from 0.62 to 0.65 (girls) and 0.57 to 0.62 (boys). VAT values were significantly lower among Blacks than Whites with little difference for the other groups.

CONCLUSION

This analysis in a multiethnic population identified BMI-z scores and WC as the major predictors of MRI-derived SAT and VAT and highlights the important ethnic differences that need to be considered in diverse populations.

Visceral adipose tissue reference data computed for GE HealthCare DXA from the National Health and Nutrition Examination Survey data set

OBJECTIVE

The National Health and Nutrition Examination Survey (NHANES) characterizes body composition representative of the US population using dual-energy x-ray absorptiometry (DXA) scans. These population-level trends of abdominal subcutaneous and visceral adipose tissue (SAT and VAT) are useful for identifying measures associated with increased disease risk. Recently, VAT and SAT data collected by Hologic DXA in NHANES were published online; however, there are known differences in the absolute calibration of DXA systems by make. The purpose of this study was to create reference tables suitable for calculating z scores and percentile values for GE HealthCare (GEHC) DXA systems.

METHODS

DXA scans were acquired on participants aged 8 to 59 years using Hologic systems. DXA measures were converted to GEHC and described using the least median squares curve fitting method in pediatrics (aged <20 years) and adults (aged 20-59 years).

RESULTS

A total of 11,972 adults and 7298 pediatrics were included for this analysis. Adult and pediatric curves were generated by sex and by ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian, Other) and were derived as a function of age.

CONCLUSIONS

These results show the ability to generate VAT and SAT reference data for GEHC systems using Hologic DXA data representative of the US youth and adult population.

Harnessing artificial intelligence in radiology to augment population health

This review article serves to highlight radiological services as a major cost driver for the healthcare sector, and the potential improvements in productivity and cost savings that can be generated by incorporating artificial intelligence (AI) into the radiology workflow, referencing Singapore healthcare as an example. More specifically, we will discuss the opportunities for AI in lowering healthcare costs and supporting transformational shifts in our care model in the following domains: predictive analytics for optimising throughput and appropriate referrals, computer vision for image enhancement (to increase scanner efficiency and decrease radiation exposure) and pattern recognition (to aid human interpretation and worklist prioritisation), natural language processing and large language models for optimising reports and text data-mining. In the context of preventive health, we will discuss how AI can support population level screening for major disease burdens through opportunistic screening and democratise expertise to increase access to radiological services in primary and community care.

Association of Endocrine Disrupting Chemicals With the Metabolic Syndrome Among Women in the Multiethnic Cohort Study

Metabolic syndrome (MetS) is associated with a high risk of cardiovascular disease, a leading cause of death among women. MetS is a diagnosis of at least 3 of the following: high blood pressure, high fasting glucose, high triglycerides, high waist circumference, and low high-density lipoprotein cholesterol. Epidemiological studies suggest that endocrine disrupting chemical (EDC) exposure is positively associated with individual components of MetS, but evidence of an association between EDCs and MetS remains inconsistent. In a cross-sectional analysis within the Multiethnic Cohort Study, we evaluated the association between 4 classes of urinary EDCs (bisphenol A [BPA], triclosan, parabens, and phthalates) and MetS among 1728 women. Multivariable logistic regression was used to estimate odds ratios and 95% CI for the association between tertiles of each EDC and MetS adjusting for age, body mass index (BMI), racial and ethnic group, and breast cancer status. Stratified analyses by race and ethnicity and BMI were conducted. MetS was identified in 519 (30.0%) women. We did not detect statistically significant associations of MetS with BPA, triclosan, or phthalate metabolite excretion. MetS was inversely associated with total parabens (Ptrend = .002). Although there were suggestive inverse associations between EDCs and MetS among Latino and African American women, and women with BMI < 30 kg/m2, there was no statistically significant heterogeneity in associations by race and ethnicity or BMI. These findings suggest an inverse association between parabens and MetS in larger multiethnic studies. Prospective analyses to investigate suggested differences in associations by race, ethnicity, and BMI are warranted.

Optimal cutoff values for visceral fat volume to predict metabolic syndrome in a Korean population

Previous studies have reported the association between visceral fat and metabolic syndrome (MS); however, just few studies have been conducted to evaluate the relationship between actual visceral fat volume (VFV) and MS. This study aimed to obtain 3 dimensional VFV and subcutaneous fat volume (SFV) using abdominal computed tomography (CT) and determine MS-predictive cutoff values.A total of 250 individuals, aged 27 to 80 years, who underwent health screening with abdominal CT between November 2019 and May 2020 were included. The subcutaneous (SFA) and visceral (VFA) fat areas were quantified using axial images obtained at the level of the lowest to the highest part of the umbilicus. The SFV and VFV were quantified from the highest level of the liver dome to the pelvic floor on axial CT images. The Aquarius iNtuition software program (TeraRecon, Foster City, CA) was used to calculate the SFA, VFA, SFV, and VFV. Subcutaneous fat mass and visceral fat mass (VFM) were measured using an adipose tissue density of 0.9 g/mL. We used the modified criteria of MS proposed by the Third National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults and waist circumference of ≥90 cm in men and ≥85 cm in women to define MS. Multivariate analysis of covariance was used to compare the fat areas, volumes, and mass according to the presence of MS and sex. Additionally, a receiver operating characteristic curve analysis was performed to determine the cutoff values for VFV, SFV, VFM, subcutaneous fat mass, VFA, and SFA associated with MS.Of the assessed variables, VFV and VFM had the highest area under the receiver operating characteristic curve value for predicting MS in both men and women: 0.811 (95% confidence interval, 0.743-0.868) for men and 0.826 (95% confidence interval, 0.727-0.900) for women. The MS-predictive cutoff values were 4852 cm3 and 4366.8 g for men and 3101 cm3 and 2790.9 g for women, respectively. Further, large, population-based studies are needed to validate these cutoff values.