Metabolic markers, regional adiposity, and adipose cell size: relationship to insulin resistance in African-American as compared with Caucasian women.

BACKGROUND/OBJECTIVES: African-American women have the greatest prevalence of obesity in the United States, and higher rates of type 2 diabetes than Caucasian women, yet paradoxically lower plasma triglycerides (TG), visceral fat and intrahepatic fat, and higher high-density lipoprotein (HDL)-cholesterol. Visceral fat has not been evaluated against insulin resistance in African-American women, and TG/HDL-cholesterol has been criticized as a poor biomarker for insulin resistance in mixed-sex African-American populations. Adipocyte hypertrophy, reflecting adipocyte dysfunction, predicts insulin resistance in Caucasians, but has not been studied in African-Americans. Our goal was to assess whether traditional correlates of insulin resistance, measures of adiposity and adipocyte characteristics similarly predict peripheral insulin resistance in African-American and Caucasian women. SUBJECTS/METHODS: Thirty-four healthy African-American (n = 17) and Caucasian (n = 17) women, matched for age (mean = 53.0 yrs) and body mass index (BMI) (mean = 30 kg/m2), underwent a steady-state plasma glucose test to measure insulin sensitivity; computed tomography (fat distribution); and a periumbilical scalpel biopsy (adipocyte characterization). By-race analyzes utilized analysis of covariance; linear regressions evaluated relationships between metabolic/adipose variables. All analyses adjusted for BMI and menopausal status. RESULTS: Insulin sensitivity did not differ between groups (p = 0.65). Neither BMI, nor %body fat or thigh fat predicted insulin resistance in African-American women. Fasting TG (p = 0.046), HDL-cholesterol (p = 0.0006) and TG/HDL-cholesterol ratio (p = 0.009) strongly predicted insulin resistance in African-American women. Despite being lower in African-American women, hepatic fat and visceral adipose tissue (VAT) correlated with insulin resistance in both groups, as did fasting glucose, VAT/SAT (subcutaneous adipose tissue) ratio, and %SAT (inverse). CONCLUSIONS: Total adiposity measures and adipocyte hypertrophy did not predict insulin resistance in African-American women, but did in Caucasian women. Plasma TG and HDL-cholesterol were significant predictors of insulin resistance in African-American women. Our findings demonstrate the need to identify race and sex-specific biomarkers for metabolic risk profiling.

SENSE phase-constrained magnitude reconstruction with iterative phase refinement.

Conventional sensitivity encoding (SENSE) reconstruction is based on equations in the complex domain. However, for many MRI applications only the magnitude is relevant. If there exists an estimate of the underlying phase information, a magnitude-only phase-constrained reconstruction can help to improve the conditioning of the SENSE reconstruction problem. Consequently, this reduces g-factor-related noise enhancement. In previous attempts at phase-constrained SENSE reconstruction, image quality was hampered by strong aliasing artifacts resulting from inadequate phase estimates and high sensitivity to phase errors. If a full-resolution phase image is used, a significant reduction in aliasing errors and better noise properties compared to SENSE can be obtained. An iterative scheme that improves the phase estimate to better approximate the phase is presented. The mathematical framework of the new approach is provided together with comparisons of conventional SENSE, phase-constrained SENSE, and the new phase-refinement method. Both theory and experimental verification demonstrate significantly better noise performance at high reduction factors, i.e., close to the theoretical limit. For applications that need only magnitude data, an iterative phase-constrained SENSE reconstruction can provide substantial SNR improvement over SENSE reconstruction and less artifacts than phase-constrained SENSE.