Abstract
BackgroundVisceral adiposity is a risk factor for many chronic diseases. Existing methods to quantify visceral adipose tissue volume using computed tomographic (CT) images often use a single slice, are manual, and are time consuming, making them impractical for large population studies. We developed and validated a method to accurately, rapidly, and robustly measure visceral adipose tissue volume using CT images.MethodsIn-house software, Medical Executable for the Efficient and Robust Quantification of Adipose Tissue (MEERQAT), was developed to calculate visceral adipose tissue volume using a series of CT images within a manually identified region of interest. To distinguish visceral and subcutaneous adipose tissue, ellipses are drawn through the rectus abdominis and transverse abdominis using manual and automatic processes. Visceral and subcutaneous adipose tissue volumes are calculated by counting the numbers of voxels corresponding to adipose tissue in the region of interest. MEERQAT’s ellipse interpolation method was validated by comparing visceral adipose volume from 10 patients’ CT scans with corresponding results from manually delineated scans. Accuracy of visceral adipose quantification was tested using a phantom consisting of animal fat and tissues. Robustness of the method was tested by determining intra-observer and inter-observer coefficients of variation (CV).ResultsThe mean difference in visceral adipose tissue volume between manual and elliptical delineation methods was -0.54 ± 4.81%. In the phantom, our measurement differed from the known adipose volume by ≤ 7.5% for all scanning parameters. Mean inter-observer CV for visceral adipose tissue volume was 0.085, and mean intra-observer CV for visceral adipose tissue volume was 0.059.ConclusionsWe have developed and validated a robust method of accurately and quickly determining visceral adipose tissue volume in any defined region of interest using CT imaging.
Highlights
Excess visceral adipose tissue increases the risk of diabetes, cardiovascular disease, and several types of cancer [1,2,3,4]
In-house software, Medical Executable for the Efficient and Robust Quantification of Adipose Tissue (MEERQAT), was developed to calculate visceral adipose tissue volume using a series of computed tomographic (CT) images within a manually identified region of interest
We have developed and validated a robust method of accurately and quickly determining visceral adipose tissue volume in any defined region of interest using CT imaging
Summary
Excess visceral adipose tissue increases the risk of diabetes, cardiovascular disease, and several types of cancer [1,2,3,4]. A method to reliably and rapidly measure visceral adipose tissue volume may provide important prognostic information and be of use within both clinical and research settings. Regarding CT, most methods examine a single axial CT slice at the umbilical level to estimate VAT and SAT volumes using two-dimensional measurements [7, 8]. Researchers have shown that planimetric estimates yield significantly different SAT volume to VAT volume ratios than volumetric measurements [10, 11]. As a result, existing approaches to quantifying VAT with CT do not use volumetric methods when large numbers of patients are analyzed. Existing methods to quantify visceral adipose tissue volume using computed tomographic (CT) images often use a single slice, are manual, and are time consuming, making them impractical for large population studies. We developed and validated a method to accurately, rapidly, and robustly measure visceral adipose tissue volume using CT images
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