Dataset Information

Differences in [18F]FDG uptake in BAT of UCP1 -/- and UCP1?+/+?during adrenergic stimulation of non-shivering thermogenesis.

ABSTRACT: BACKGROUND:Brown adipose tissue (BAT) is a fat tissue found in most mammals that helps regulate energy balance and core body temperature through a sympathetic process known as non-shivering thermogenesis. BAT activity is commonly detected and quantified in [18F]FDG positron emission tomography/computed tomography (PET/CT) scans, and radiotracer uptake in BAT during adrenergic stimulation is often used as a surrogate measure for identifying thermogenic activity in the tissue. BAT thermogenesis is believed to be contingent upon the expression of the protein UCP1, but conflicting results have been reported in the literature concerning [18F]FDG uptake within BAT of mice with and without UCP1. Differences in animal handling techniques such as feeding status, type of anesthetic, type of BAT stimulation, and estrogen levels were identified as possible confounding variables for [18F]FDG uptake. In this study, we aimed to assess differences in BAT [18F]FDG uptake between wild-type and UCP1-knockout mice using a protocol that minimizes possible variations in BAT stimulation caused by different stress responses to mouse handling. RESULTS:[18F]FDG PET/CT scans were run on mice that were anesthetized with pentobarbital after stimulation of non-shivering thermogenesis by norepinephrine. While in wild-type mice [18F]FDG uptake in BAT increased significantly with norepinephrine stimulation of BAT, there was no consistent change in [18F]FDG uptake in BAT of mice lacking UCP1. CONCLUSIONS:[18F]FDG uptake within adrenergically stimulated BAT of wild-type and UCP1-knockout mice can significantly vary such that an [18F]FDG uptake threshold cannot be used to differentiate wild-type from UCP1-knockout mice. However, while an increase in BAT [18F]FDG uptake during adrenergic stimulation is consistently observed in wild-type mice, in UCP1-knockout mice [18F]FDG uptake in BAT seems to be independent of ?3-adrenergic stimulation of non-shivering thermogenesis.

SUBMITTER: McHugh CT

PROVIDER: S-EPMC7648812 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Differences in [<sup>18</sup>F]FDG uptake in BAT of UCP1 -/- and UCP1 +/+ during adrenergic stimulation of non-shivering thermogenesis.

McHugh Christian T CT Garside John J Barkes Jared J Frank Jonathan J Dragicevich Constance C Yuan Hong H Branca Rosa T RT

EJNMMI research 20201107 1

<h4>Background</h4>Brown adipose tissue (BAT) is a fat tissue found in most mammals that helps regulate energy balance and core body temperature through a sympathetic process known as non-shivering thermogenesis. BAT activity is commonly detected and quantified in [<sup>18</sup>F]FDG positron emission tomography/computed tomography (PET/CT) scans, and radiotracer uptake in BAT during adrenergic stimulation is often used as a surrogate measure for identifying thermogenic activity in the tissue. B ...[more]

PMID: 33159596

Similar Datasets

Project description:PurposeTo quantify the post-radiotherapy 2-[(18)F]-fluoro-2-deoxyglucose (FDG) pulmonary uptake dose-response in lung cancer patients and determine its relationship with radiation pneumonitis symptoms.Methods and materialsThe data from 24 patients treated for lung cancer with thoracic radiotherapy who received restaging PET/CT imaging between 4 and 12 weeks after radiotherapy completion were evaluated. Their radiation dose distribution was registered with the post-treatment restaging PET/CT. Using histogram analysis, the voxel average FDG-PET uptake vs. radiation dose was obtained for each case and linear regression was performed. The resulting slope, the pulmonary metabolic radiation response (PMRR), was used to characterize the dose-response. The Common Toxicity Criteria version 3 was used to score clinical pulmonary toxicity symptoms. Receiver operating characteristic (ROC) curves were used to determine the level of FDG uptake vs. dose, MLD, V(5), V(10), V(20), and V(30) that can best predict symptomatic and asymptomatic patients.ResultsThe median time between radiotherapy completion and FDG-PET imaging was 59 days (range, 26-70 days). The median of the mean SUV from lung that received 0-5 Gy was 1.00 (range, 0.37-1.48), 5-10 Gy was 1.01 (range, 0.37-1.77), 10-20 Gy was 1.04 (0.42-1.53), and >20 Gy was 1.29 (range, 0.41-8.01). Using the dose range of 0 Gy to the maximum dose minus 10 Gy, hierarchical linear regression model of the radiation dose and normalized FDG uptake per case found an adequate fit with the linear model. Pneumonitis scores were: Grade 0 for 13, Grade 1 for 5, Grade 2 for 6, and Grade 3, 4 or 5 for none. Using a PMRR threshold of 0.017 yields an associated true positive rate of 0.67 and false positive rate of 0.15 with average error of 30%. A V(5) threshold of 57.6 gives an associated true positive rate of 0.67 and false positive rate of 0.05 with a 20% average error.ConclusionThe metabolic radiation pneumonitis dose-response was evaluated from post-treatment FDG-PET/CT imaging. Statistical modeling found a linear relationship. The FDG uptake dose-response and V(5) correlated with symptomatic radiation pneumonitis.

Project description:BackgroundAssessment of dual time point (DTP) positron emission tomography was carried out with the aim of a quantitative determination of Km, the metabolic uptake rate of [18F]fluorodeoxyglucose as a measure of glucose consumption.MethodsStarting from the Patlak equation, it is shown that Km?mt/ca0+V?r/?a, where mt is the secant slope of the tissue response function between the dual time point measurements centered at t?=?t0. ca0=ca(t0) denotes arterial tracer concentration, V?r is an estimate of the Patlak intercept, and ?a is the time constant of the ca(t) decrease. We compared the theoretical predictions with the observed relation between Ks=mt/ca0 and Km in a group of nine patients with liver metastases of colorectal cancer for which dynamic scans were available, and Km was derived from conventional Patlak analysis. Twenty-two lesion regions of interest (ROIs) were evaluated. ca(t) was determined from a three-dimensional ROI in the aorta. Furthermore, the correlation between Km and late standard uptake value (SUV) as well as retention index was investigated. Additionally, feasibility of the approach was demonstrated in a whole-body investigation.ResultsPatlak analysis yielded a mean Vr of V?r=0.53±0.08 ml/ml. The patient averaged ?a was 99?±?23 min. Linear regression between Patlak-derived Km and DTP-derived Ks according to Ks?=?b?·?Km?+?a yielded b?=?0.98?±?0.05 and a?=?-0.0054?±?0.0013 ml/min/ml (r?=?0.98) in full accordance with the theoretical predictions b?=?1 and a?-V?r/?a. Ks exhibits better correlation with Km than late SUV and retention index, respectively. Ks(c)=Ks+V?r/?a is proposed as a quantitative estimator of Km which is independent of patient weight, scan time, and scanner calibration.ConclusionQuantification of Km from dual time point measurements compatible with clinical routine is feasible. The proposed approach eliminates the issues of static SUV and conventional DTP imaging regarding influence of chosen scanning times and inter-study variability of the input function. Ks and Ks(c) exhibit improved stability and better correlation with the true Km. These properties might prove especially relevant in the context of radiation treatment planning and therapy response control.

Project description:We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).

Dataset Information

Differences in [18F]FDG uptake in BAT of UCP1 -/- and UCP1?+/+?during adrenergic stimulation of non-shivering thermogenesis.

Publications

Differences in [<sup>18</sup>F]FDG uptake in BAT of UCP1 -/- and UCP1 +/+ during adrenergic stimulation of non-shivering thermogenesis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure