Background
Adipose tissues (AT) are highly metabolically active complex endocrine organs and are classified into white (WAT) and brown AT (BAT) with proinflammatory and anti-inflammatory characteristics. The current study investigated the accuracy of computed tomography (CT) to quantitatively detect BAT and WAT based on Hounsfield unit (HU) threshold compared to standardized uptake values (SUVs) of corresponding AT with the use of positron emission tomography (PET).
Methods
One hundred twenty-four patients who underwent whole-body 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT were studied. The SUVs and HUs of regions of BAT and WAT were measured and compared in these scans. The receiver operator characteristic (ROC) analysis was used to detect the HU threshold values for the detection of BAT and WAT.
Results
The CT HU of BAT, with high 18 F-FDG uptake, was significantly higher compared to WAT (−67.1 ± 8.2 [−10 to −87] versus −93.5 ± 10.1 [−88 to −190], P = .0006). Generalized linear-regression models revealed that mean CT HU of BAT was 26.4 HU higher than that of WAT ( P = .001). A strong agreement between CT HU and PET SUV in measuring metabolically active AT ( r 2 = 0.81, P = .0001) was observed. The ROC curve showed that the optimal cutoff value of CT HU to detect BAT was HU ≥−87 with sensitivity of 83.3% and specificity of 100%, and the negative CT HU below −87 is highly specific for WAT.
Conclusion
In our study, CT can accurately and quantitatively detect BAT and WAT based on CT HU threshold, which is −10 to −87 for BAT and −88 to −190 for WAT.
Increased regional fat distribution plays an important part in the development of an unfavorable metabolic and cardiovascular risk profile . Adipose tissues (AT) are inclusive of two distinct types: white (WAT) and brown AT (BAT). AT is a highly metabolically active complex endocrine organ that generates various molecules with profound local and systemic effects . The most predominant portion of AT is by far WAT, which functions to store energy in the form of triglyceride-containing intracellular droplets as well as to secrete a host of hormones and cytokines (adipokines) that regulate overall energy balance by affecting the function of other tissues including the brain, muscle, and liver . The main function of BAT is to burn fat to generate heat . Despite their similar qualitative properties, WAT and BAT are now recognized as having distinct proinflammatory and anti-inflammatory functions, respectively .
Multiple studies reveal that fluorodeoxyglucose (FDG) positron emission tomography (PET) can accurately measure BAT and WAT . Furthermore, the feasibility of computed tomography (CT) to assess BAT based on Hounsfield units (HU) has been documented . This study investigated the accuracy of CT to a quantitatively detect BAT and WAT based on HU threshold compared to standardized uptake values (SUVs) of corresponding AT with PET.
Methods
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PET/CT Scan
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BAT and WAT Image Analysis
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Statistical Analysis
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Results
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Table 1
Positron Emission Tomography Standardized Uptake Value (SUV) and Computed Tomography (CT) Hounsfield Unit (HU) Values for Brown Adipose Tissue (BAT) versus White Adipose Tissue (WAT)
Variable BAT WAT_P_ Value 18 F-Fluorodeoxyglucose uptake (SUV max ) 6.6 ± 2.8 0.9 ± 0.5 .0001 CT HU −67.1 ± 8.2 (−10 to −87) −98.5 ± 10.1 (−88 to −190) .0006
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Table 2
Relation of Computed Tomography Hounsfield Unit (HU) Values to Brown Adipose Tissue with High Standardized Uptake Value (SUV)
Model White Adipose Tissue (Low SUV) Brown Adipose Tissue (High SUV) HU 0 (Reference) 26.4 (95% confidence interval 14.5–38.3), P = .001
Generalized linear regression models adjusted for age, gender, body mass index, and conventional risk factors.
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Table 3
Area Under the Receiver Operating Characteristic Curve (AUC) to Detect Brown Adipose Tissue with High Standardized Uptake Value (SUV) Based on Computed Tomography Hounsfield Unit Values
Variable AUC (±SE) 95% Confidence Interval_P_ Value Criterion Specificity Sensitivity Brown Adipose Tissue (High SUV) 0.97 (0.03) 0.69-1.0 .0001 −87 100% 83.3%
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Discussion
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Clinical Implications
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Limitations
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Conclusions
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Acknowledgments
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