Dataset Information

Accurate quantification of brown adipose tissue mass by xenon-enhanced computed tomography.

ABSTRACT: Detection and quantification of brown adipose tissue (BAT) mass remains a major challenge, as current tomographic imaging techniques are either nonspecific or lack the necessary resolution to quantify BAT mass, especially in obese phenotypes, in which this tissue may be present but inactive. Here, we report quantification of BAT mass by xenon-enhanced computed tomography. We show that, during stimulation of BAT thermogenesis, the lipophilic gas xenon preferentially accumulates in BAT, leading to a radiodensity enhancement comparable to that seen in the lungs. This enhancement is mediated by a selective reduction in BAT vascular resistance, which greatly increases vascular perfusion of BAT. This enhancement enables precise identification and quantification of BAT mass not only in lean, but also in obese, mouse phenotypes, in which this tissue is invisible to conventional tomographic imaging techniques. The method is developed and validated in rodents and then applied in macaques to assess its feasibility in larger species.

SUBMITTER: Branca RT

PROVIDER: S-EPMC5776810 | biostudies-other | 2018 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Accurate quantification of brown adipose tissue mass by xenon-enhanced computed tomography.

Branca Rosa T RT McCallister Andrew A Yuan Hong H Aghajanian Amir A Faber James E JE Weimer Nicholas N Buchanan Riley R Floyd Carlos S CS Antonacci Michael M Zhang Le L Burant Alex A

Proceedings of the National Academy of Sciences of the United States of America 20171218 1

Detection and quantification of brown adipose tissue (BAT) mass remains a major challenge, as current tomographic imaging techniques are either nonspecific or lack the necessary resolution to quantify BAT mass, especially in obese phenotypes, in which this tissue may be present but inactive. Here, we report quantification of BAT mass by xenon-enhanced computed tomography. We show that, during stimulation of BAT thermogenesis, the lipophilic gas xenon preferentially accumulates in BAT, leading to ...[more]

PMID: 29255046

Similar Datasets

Project description:ObjectivesObesity and its distribution pattern are important factors for the prediction of the onset of diabetes in humans. Since several mouse models are suitable to study the pathophysiology of type 2 diabetes the aim was to validate a novel computed tomograph model (Aloka-Hitachi LCT-200) for the quantification of visceral, subcutaneous, brown and intrahepatic fat depots in mice.MethodsDifferent lean and obese mouse models (C57BL/6, B6.V-Lep(ob), NZO) were used to determine the most adequate scanning parameters for the detection of the different fat depots. The data were compared with those obtained after preparation and weighing the fat depots. Liver fat content was determined by biochemical analysis.ResultsThe correlations between weights of fat tissues on scale and weights determined by CT were significant for subcutaneous (r(2) = 0.995), visceral (r(2) = 0.990) and total white adipose tissue (r(2) = 0.992). Moreover, scans in the abdominal region, between lumbar vertebrae L4 to L5 correlated with whole-body fat distribution allowing experimenters to reduce scanning time and animal exposure to radiation and anesthesia. Test-retest reliability and measurements conducted by different experimenters showed a high reproducibility in the obtained results. Intrahepatic fat content estimated by CT was linearly related to biochemical analysis (r(2) = 0.915). Furthermore, brown fat mass correlated well with weighted brown fat depots (r(2) = 0.952). In addition, short-term cold-expose (4 °C, 4 hours) led to alterations in brown adipose tissue attributed to a reduction in triglyceride content that can be visualized as an increase in Hounsfield units by CT imaging.ConclusionThe 3D imaging of fat by CT provides reliable results in the quantification of total, visceral, subcutaneous, brown and intrahepatic fat in mice. This non-invasive method allows the conduction of longitudinal studies of obesity in mice and therefore enables experimenters to investigate the onset of complex diseases such as diabetes and obesity.

Project description:BACKGROUND:Positron emission tomography (PET) is increasingly applied for in vivo brown adipose tissue (BAT) research in healthy volunteers. To limit the radiation exposure, the injected 18F-FDG tracer dose should be as low as possible. With simultaneous PET/MR imaging, the radiation exposure due to computed tomography (CT) can be avoided, but more importantly, the PET acquisition time can often be increased to match the more extensive magnetic resonance (MR) imaging protocol. The potential gain in detected coincidence counts, due to the longer acquisition time, can then be applied to decrease the injected tracer dose. The aim of this study was to investigate the minimal 18F-FDG dose for a 10-min time-of-flight (TOF) PET/MR acquisition that would still allow accurate quantification of supraclavicular BAT volume and activity. METHODS:Twenty datasets from 13 volunteers were retrospectively included from a prospective clinical study. PET emission datasets were modified to simulate step-wise reductions of the original 75?MBq injected dose. The resulting PET images were visually and quantitatively assessed and compared to a 4-min reference scan. For the visual assessment, the image quality and artifacts were scored using a 5-point and a 3-point Likert scale. For the quantitative analysis, image noise and artifacts, BAT metabolic activity, BAT metabolic volume (BMV), and total BAT glycolysis (TBG) were investigated. RESULTS:The visual assessment showed still good image quality for the 35%, 30%, and 25% activity reconstructions with no artifacts. Quantitatively, the background noise was similar to the reference for the 35% and 30% activity reconstructions and the artifacts started to increase significantly in the 25% and lower activity reconstructions. There was no significant difference in supraclavicular BAT metabolic activity, BMV, and TBG between the reference and the 35% to 20% activity reconstructions. CONCLUSIONS:This study indicates that when the PET acquisition time is matched to the 10-min MRI protocol, the injected 18F-FDG tracer dose can be reduced to approximately 19?MBq (25%) while maintaining image quality and accurate supraclavicular BAT quantification. This could decrease the effective dose from 1.4?mSv to 0.36?mSv.

Project description:Pericoronary adipose tissue (PCAT) features on Computed Tomography (CT) have been shown to reflect local inflammation and increased cardiovascular risk. Our goal was to determine whether PCAT radiomics extracted from coronary CT angiography (CCTA) images are associated with intravascular optical coherence tomography (IVOCT)-identified vulnerable-plaque characteristics (e.g., microchannels (MC) and thin-cap fibroatheroma (TCFA)). The CCTA and IVOCT images of 30 lesions from 25 patients were registered. The vessels with vulnerable plaques were identified from the registered IVOCT images. The PCAT-radiomics features were extracted from the CCTA images for the lesion region of interest (PCAT-LOI) and the entire vessel (PCAT-Vessel). We extracted 1356 radiomic features, including intensity (first-order), shape, and texture features. The features were reduced using standard approaches (e.g., high feature correlation). Using stratified three-fold cross-validation with 1000 repeats, we determined the ability of PCAT-radiomics features from CCTA to predict IVOCT vulnerable-plaque characteristics. In the identification of TCFA lesions, the PCAT-LOI and PCAT-Vessel radiomics models performed comparably (Area Under the Curve (AUC) ± standard deviation 0.78 ± 0.13, 0.77 ± 0.14). For the identification of MC lesions, the PCAT-Vessel radiomics model (0.89 ± 0.09) was moderately better associated than the PCAT-LOI model (0.83 ± 0.12). In addition, both the PCAT-LOI and the PCAT-Vessel radiomics model identified coronary vessels thought to be highly vulnerable to a similar standard (i.e., both TCFA and MC; 0.88 ± 0.10, 0.91 ± 0.09). The most favorable radiomic features tended to be those describing the texture and size of the PCAT. The application of PCAT radiomics can identify coronary vessels with TCFA or MC, consistent with IVOCT. Furthermore, the use of CCTA radiomics may improve risk stratification by noninvasively detecting vulnerable-plaque characteristics that are only visible with IVOCT.

Dataset Information

Accurate quantification of brown adipose tissue mass by xenon-enhanced computed tomography.

Publications

Accurate quantification of brown adipose tissue mass by xenon-enhanced computed tomography.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets