Background/objectives To investigate the relationship between the cross-sectional visceral adipose tissue (VAT) areas at different anatomic sites and the total VAT volume in a healthy Chinese population using quantitative computed tomography (QCT), and to identify the optimal anatomic site for a single slice to estimate the total VAT volume. Subjects/methods A total of 389 healthy Chinese subjects aged 19–63 years underwent lumbar spine QCT scans. The cross-sectional area of total adipose tissue and VAT were measured using the tissue composition module of the software (QCT Pro, Mindways) at each intervertebral disc level from T12/L1 to L5/S1, as well as at the umbilical level. The total VAT volume was defined as the fat areas multiplied by the height of vertebral body for all six slices. Statistical analysis was performed to determine the correlation between single-slice VAT areas and the total VAT volume. Moreover, the optimal anatomic site for a single slice to estimate the total VAT volume was identified by multiple regression analysis. Results The cross-sectional area of VAT and subcutaneous adipose tissue (SAT) measured at each anatomic site was all highly correlated with the total VAT volume and the total SAT volume (r = 0.89–0.98). Additionally, the VAT area measured at the L2/L3 level showed the strongest correlation with the total VAT volume (r = 0.98, P < 0.001). Covariates including age, gender, BMI, waist, and hypertension make a slight effect on the prediction of the total VAT volume. Conclusion It is feasible to perform measurements of VAT area on a single slice at L2/L3 level for estimating the total VAT volume.

Purpose: To investigate the feasibility of characterizing arterial plaque composition in terms of water, lipid and protein or calcium using dual energy computed tomography. Characterization of plaque composition can potentially help distinguish vulnerable from stable plaques. Methods: Simulations studies were performed by the CT simulator based on ASTRA tomography toolbox. The beam energy for dual energy images was selected to be 80 kVp and 135 kVp. The radiation dose and energy spectrum for the CT simulator were carefully calibrated with respect to a 320‐slice CT scanner. A digital chest phantom was constructed using Matlab for calibration and plaque measurement. Pure water, lipid, protein or calcium was used for calibration and a mixture of different volume percentages of these materials were used for validation purposes. Non‐calcified plaque was simulated using water, lipid and protein with volumetric percentage range of 35%∼65%, 5%∼60% and 5%∼40%, respectively. Calcified plaque was simulated using water, lipid and calcium with volumetric percentage range of 50%∼80%, 8%∼45% and 3%∼13%, respectively. We employed iterative sinogram processing (ISP) to reduce the beam hardening effect in the simulation to improve the decomposition results. Results: The simulated known composition and dual energy decomposition results were in good agreement. Water, lipid and protein (calcium) mixtures were decomposed into water, lipid and protein (calcium) contents. The RMS errors of volumetric percentage for the water, lipid and protein (non‐calcified plaque) decomposition, as compared to known values, were estimated to be approximately 5.74%, 2.54%, and 0.95% respectively. The RMS errors of volumetric percentage for the water, lipid and Calcium (calcified plaque) decomposition, as compared to known values, were estimated to be approximately 7.4%, 8.64%, and 0.08% respectively. Conclusion: The results of this study suggest that the dual energy decomposition can potentially be used to quantify the water, lipid, and protein or calcium composition of a plaque with relatively good accuracy. Grant funding from Toshiba Medical Systems and Philips Medical Systems