Adipose Quantification Research Articles

#1326096: Quantification of Adiposity, Liver and Pancreas Fat with Magnetic Resonance Imaging in T2DM: Insights From the One Year Of Digital Twin Intervention Trial

#1326096: Quantification of Adiposity, Liver and Pancreas Fat with Magnetic Resonance Imaging in T2DM: Insights From the One Year Of Digital Twin Intervention Trial

Abstract #1325516: Quantification of Adiposity, Liver and Pancreas Fat With Magnetic Resonance Imaging in T2DM: Insights From the One Year of Digital Twin Intervention Trial

Abstract #1325516: Quantification of Adiposity, Liver and Pancreas Fat With Magnetic Resonance Imaging in T2DM: Insights From the One Year of Digital Twin Intervention Trial

Leptin as an obesity marker in rheumatoid arthritis.

The determination of excess of body fat mass provides a more suitable determinant of obesity in rheumatoid arthritis patients; however, body mass index (BMI) may not be accurate for the quantification of adiposity. To identify a marker of excess adiposity in women with rheumatoid arthritis (RA) using different methods for fat mass evaluation. A cross-sectional study was conducted in adult female patients with RA. Disease activity was assessed by DAS28-ESR, and obesity was determined by waist circumference (WC), BMI and dual-energy X-ray absorptiometry (DXA). The Human Bone Metabolism kit (Merck Millipore, Darmstadt, Alemanha) was used to determine the plasma levels of leptin, TNF-α, IL-6, and IL-1β by quantification of serum proteins by technical microspheres (LUMINEX, TX, USA). Adiponectin was measured by enzyme-linked immunosorbent assay sandwich kit (R&D Systems, Minneapolis, MN, USA). Eighty-nine female patients, median age of 55.4 (± 11.6) years, and median disease duration of 16.4 (± 14.9) years were included. The frequency of obesity was 33.7% according to BMI, 89.9% with WC, and 56.1% with DXA. The median serum leptin concentration was the only marker that correlated with body fat percentage according to the three methods. This correlation was positive and not influenced by DAS28, C-reactive protein, erythrocyte sedimentation rate, or inflammatory cytokines levels (IL-6, TNF-α, IL-1β). Analysis of ROC curves determined the cut-off point of 10.3ng/mL of leptin as an obesity marker, with a sensitivity of 96.43% and a specificity of 23.81%. Serum leptin correlates positively with fat mass and is potentially useful in excess fat mass determination in clinical practice.

CT-based assessment of visceral adiposity and outcomes for esophageal adenocarcinoma.

Various methods of quantifying and correlating obesity to outcomes for patients with esophageal adenocarcinoma (EA) have been evaluated. Published data suggest that quantification of adiposity may be more accurate than body mass index (BMI) as a prognostic factor. We report our analysis of adiposity as a prognostic factor in a series of patients with EA. This single institution retrospective review included patients with EA who underwent esophagectomy from 1994-2008. Patients with BMI <20 were excluded. Using the preoperative CT scan, the visceral (VFA), subcutaneous (SFA), and total abdominal fat (TFA) areas were calculated. Each was contoured on a Siemens Leonardo workstation at the level of the iliac crest (L4/5). The Hounsfield threshold was -30 to -130. Outcomes were analyzed using Kaplan-Meier method and log-rank analysis. Multivariate analysis (MVA) was performed using the Cox proportion hazard regression model. We identified 126 patients for the analysis. There were no statistically significant differences in overall survival or disease-free survival between groups above and below the medians for TFA, SFA, or VFA/SFA ratio. However, an increase in VFA was significantly associated with worsened OS and DFS when we further classified patients into quartiles. Patients with VFA ≥182 cm2 had larger tumor size (P=0.016), fewer involved lymph nodes (P=0.047), longer operating times (P=0.032), and were more likely to be males (P=0.042). Published data have demonstrated an association between treatment outcomes and degree of adiposity; our study found a correlation between VFA and OS and DFS in patients with EA. Median TFA, SFA, and VFA/SFA were not prognostic on MVA. While VFA >182 cm2 was associated with larger tumors, there were also fewer lymph nodes harvested in this group.

Development and validation of a rapid and robust method to determine visceral adipose tissue volume using computed tomography images.

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.

A detection-driven and sparsity-constrained deformable model for fascia lata labeling and thigh inter-muscular adipose quantification

Quantification of the thigh inter-muscular adipose tissue (IMAT) plays a critical role in various medical data analysis tasks, e.g., the analysis of physical performance or the diagnosis of knee osteoarthritis. Several techniques have been proposed to perform automated thigh tissues quantification. However, none of them has provided an effective method to track fascia lata, which is an important anatomic trail to distinguish between subcutaneous adipose tissue (SAT) and IMAT in the thigh. As a result, the estimates of IMAT may not be accurate due to the unclear appearance cues, complicated anatomic, or pathological characteristics of the fascia lata. Thus, prior tissue information, e.g., intensity, orientation and scale, becomes critical to infer the fascia lata location from magnetic resonance (MR) images. In this paper, we propose a novel detection-driven and sparsity-constrained deformable model to obtain accurate fascia lata labeling. The model’s deformation is driven by the detected control points on fascia lata through a discriminative detector in a narrow-band fashion. By using a sparsity-constrained optimization, the deformation is solved from errors and outliers suppression. The proposed approach has been evaluated on a set of 3D MR thigh volumes. In a comparison with the state-of-the-art framework, our approach produces superior performance.

SP2-9 Diagnostic criteria of lipodystrophy in HIV-infected patients

IntroductionThe prevalence of lipodystrophy ranges from 2 to 84% and the range of findings stems from differences between the populations studied and lack of standardised diagnostic criteria. The diagnosis of...

In vivo quantification of subcutaneous and visceral adiposity by micro-computed tomography in a small animal model

Accurate and precise techniques that identify the quantity and distribution of adipose tissue in vivo are critical for investigations of adipose development, obesity, or diabetes. Here, we tested whether in vivo micro-computed tomography (microCT) can be used to provide information on the distribution of total, subcutaneous and visceral fat volume in the mouse. Ninety C57BL/6J mice (weight range: 15.7–46.5 g) were microCT scanned in vivo at 5 months of age and subsequently sacrificed. Whole body fat volume (base of skull to distal tibia) derived from in vivo microCT was significantly ( p < 0.001) correlated with the ex vivo tissue weight of discrete perigonadal ( R 2 = 0.94), and subcutaneous ( R 2 = 0.91) fat pads. Restricting the analysis of tissue composition to the abdominal mid-section between L1 and L5 lumbar vertebrae did not alter the correlations between total adiposity and explanted fat pad weight. Segmentation allowed for the precise discrimination between visceral and subcutaneous fat as well as the quantification of adipose tissue within specific anatomical regions. Both the correlations between visceral fat pad weight and microCT determined visceral fat volume ( R 2 = 0.95, p < 0.001) as well as subcutaneous fat pad weight and microCT determined subcutaneous fat volume ( R 2 = 0.91, p < 0.001) were excellent. Data from these studies establish in vivo microCT as a non-invasive, quantitative tool that can provide an in vivo surrogate measure of total, visceral, and subcutaneous adiposity during longitudinal studies. Compared to current imaging techniques with similar capabilities, such as microMRI or the combination of DEXA with NMR, it may also be more cost-effective and offer higher spatial resolutions.