ABSTRACT
INTRODUCTION: Obtaining accurate coronary artery calcium (CAC) score measurements from CCTA datasets with virtual non-iodine (VNI) algorithms would reduce acquisition time and radiation dose. We aimed to assess the agreement of VNI-derived and conventional true non-contrast (TNC)-based CAC scores and to identify the predictors of accuracy. METHODS: CCTA datasets were acquired with either 120 or 140 âkVp. CAC scores and volumes were calculated from TNC and VNI images in 197 consecutive patients undergoing CCTA. CAC density score, mean volume/lesion, aortic Hounsfield units and standard deviations were then measured. Finally, percentage deviation (VNI - TNC/TNC∗100) of CTA-derived CAC scores from non-enhanced scans was calculated for each patient. Predictors (including anthropometric and acquisition parameters, as well as CAC characteristics) of the degree of discrepancy were evaluated using linear regression analysis. RESULTS: While the agreement between TNC and VNI was substantial (mean bias, 6.6; limits of agreement, 178.5/145.3), a non-negligible proportion of patients (36/197, 18.3%) were falsely reclassified as CAC score â= â0 on VNI. The use of higher tube voltage significantly decreased the percentage deviation relative to TNC-based values (ß â= â-0.21 [95%CI: 0.38 to -0.03], p â= â0.020) and a higher CAC density score also proved to be an independent predictor of a smaller difference (ß â= â-0.22 [95%CI: 0.37 to -0.07], p â= â0.006). CONCLUSION: The performance of VNI-based calcium scoring may be improved by increased tube voltage protocols, while the accuracy may be compromised for calcified lesions of lower density. The implementation of VNI in clinical routine, however, needs to be preceded by a solution for detecting smaller lesions as well.
Subject(s)
Calcium , Coronary Artery Disease , Humans , Predictive Value of Tests , Coronary Angiography/methods , Tomography, X-Ray Computed/methods , Algorithms , Coronary Artery Disease/diagnostic imaging , Coronary Vessels/diagnostic imaging , Computed Tomography Angiography/methodsABSTRACT
BACKGROUND/OBJECTIVES: Various adipose tissue compartments play an important role in the development of cardiometabolic diseases. The quantity of different fat compartments is influenced by genetic and environmental factors. The aim of our study was to evaluate the magnitude of genetic and environmental effects on epicardial, subcutaneous and visceral adipose tissue (EAT, SAT and VAT) quantities in a cohort of adult twin pairs. SUBJECTS/METHODS: In this cross-sectional study we investigated adult twins (57 monozygotic (MZ) and 33 dizygotic (DZ) same-gender twin pairs; 180 twin subjects). We measured EAT volume using electrocardiogram-gated native computed tomography (CT) scan of the heart, and abdominal SAT and VAT areas were quantified between the third and fourth lumbar vertebra on native CT images. We calculated genetic and environmental impact on the size of various adipose tissue compartments by analyzing co-twin correlations in MZ and DZ pairs separately, and furthermore by using genetic structural equation models. RESULTS: In co-twin analysis, MZ twins had stronger correlations than DZ twins for EAT (rMZ=0.81, rDZ=0.32), similar to SAT and VAT quantities (rMZ=0.80, rDZ=0.68 and rMZ=0.79, rDZ=0.48, respectively). In multi-trait model fitting analysis, the overall contribution of genetic factors to EAT, SAT and VAT volumes were 80%, 78% and 70%, whereas environmental factors were 20%, 22% and 30%, respectively. Common pathway model analyses indicated that none of the EAT, SAT and VAT phenotypes was independent of the other two. CONCLUSIONS: Genetic factors have substantial influence, while environmental factors have only a modest impact on EAT volume, abdominal SAT and VAT quantities. There is a considerable amount of common genetic background influencing the quantities of all three adipose tissue compartments.
