Eur J Nucl Med Mol Imaging DOI 10.1007/s00259-013-2611-8

REVIEW ARTICLE

Molecular imaging of brown adipose tissue in health and disease Matthias Bauwens & Roel Wierts & Bart van Royen & Jan Bucerius & Walter Backes & Felix Mottaghy & Boudewijn Brans

Received: 31 July 2013 / Accepted: 7 October 2013 # Springer-Verlag Berlin Heidelberg 2014

Abstract Purpose Brown adipose tissue (BAT) has transformed from an interfering tissue in oncological 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) to an independent imaging research field. This review takes the perspective from the imaging methodology on which human BAT research has come to rely on heavily. Methods This review analyses relevant PubMed-indexed publications that discuss molecular imaging methods of BAT. In addition, reported links between BAT and human diseases such as obesity are discussed, and the possibilities for imaging in these fields are highlighted. Radiopharmaceuticals aiming at several different biological mechanisms of BAT are discussed and evaluated. Results Prospective, dedicated studies allow visualization of BAT function in a high percentage of human subjects. BAT dysfunction has been implicated in obesity, linked with diabetes and associated with cachexia and atherosclerosis. Presently, 18F-FDG PET/CT is the most useful tool for evaluating M. Bauwens : R. Wierts : J. Bucerius : F. Mottaghy : B. Brans (*) Department of Medical Imaging, Division of Nuclear Medicine, MUMC, Maastricht, Netherlands e-mail: [email protected] M. Bauwens Research School NUTRIM, Maastricht University, Maastricht, Netherlands B. van Royen : W. Backes Department of Medical Imaging, Division of Radiology, MUMC, Maastricht, Netherlands J. Bucerius : F. Mottaghy Division of Nuclear Medicine, Uniklinikum Aachen, Aachen, Germany J. Bucerius Research School CARIM, Maastricht University, Maastricht, Netherlands

therapies aiming at BAT activity. In addition to 18F-FDG, other radiopharmaceuticals such as 99mTc-sestamibi, 123Imetaiodobenzylguanidine (MIBG), 18F-fluorodopa and 18F14(R,S)-[18F]fluoro-6-thia-heptadecanoic acid (FTHA) may have a potential for visualizing other aspects of BAT activity. MRI methods are under continuous development and provide the prospect of functional imaging without ionizing radiation. Conclusion Molecular imaging of BAT can be used to quantitatively assess different aspects of BAT metabolic activity. Keywords Brown adipose tissue . Molecular imaging . PET/ CT . Radiopharmaceuticals . Obesity . Cachexia

Prevalence of brown adipose tissue Brown adipose tissue (BAT) has been an elusive tissue which has only gradually given up its secrets. In the 1990s, as 18Ffluorodeoxyglucose (FDG) positron emission tomography (PET) scans began proliferating in hospitals to be used for whole-body staging in oncology, cervical hot spots were occasionally seen on PET scans but interpreted as interfering with tumour diagnostics, probably being of muscular origin and suppressible with propranolol and diazepam [1, 2]. In 2002 with the advent of hybrid PET/CT, Hany et al. launched their hypothesis that the uptake was due to BAT, as Hounsfield units in these areas indicated negative values, compatible with fat and not muscle [3]. In parallel observations by another group, Cohade et al. [4, 5] introduced the term “USA-fat” (uptake in the supraclavicular area) which they could relate to the ambient outdoor temperature. Nedergaard et al. in an authoritative review in 2007 hence suggested the use of 18F-FDG as a possible research tool [6]. In 2009, several landmark studies appeared in one issue of the New England Journal of Medicine [7–9] which together with other studies [10, 11] definitely established the high incidence of active BAT in adult men using 18F-FDG PET/CT, as well as its

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quantification, its relation to age and body mass index (BMI), and proved with histological biopsies that FDG-avid BAT areas correlated with signature genes of BAT. Prior to 2009, 18F-FDG uptake by BAT was investigated by retrospectively analysing several hundreds or thousands of available PET/CT images routinely performed (Table 1). While this methodology allowed large numbers of scans to be processed and provided strong statistics, the true prevalence of BAT activity could not be assessed from these studies because of the different temperature circumstances under which these PET scans were made. In addition, PET scans were performed in different age groups and in disease states such as cancer and inflammation which are known to affect fat metabolism. This paradox was eloquently demonstrated by Lee et al. in 2010, by comparing multiple 18F-FDG PET/CT scans of a large number of patients [19]. They calculated that in their cohort of patients the chance of detecting BAT in a patient by means of a single scan was about 8.5 %. However, among those patients with BAT who were scanned again after the first (positive) scan, the frequency of at least one other positive scan rose with increasing occasions of study: from 8 % for one additional scan to 65 % in patients with more than four additional scans. This was later confirmed by dedicated prospective PET studies using standardized mild cold exposure that to date have indicated a prevalence of 33–100 % [8, 9, 11, 26, 27], depending on the intensity of the cooling protocol used (air-cooled environment, cold wetsuit). However, these studies were mostly done in healthy, young individuals. Therefore, these data particularly have to be confirmed in older and diseased age groups before the full potential of BAT function changes can be assessed. Table 2 lists the physiological factors that have been identified to influence the detection of BAT. A strong (negative) association has been found with increasing age. Indeed,

Table 1 Retrospective population-based studies trying to determine the prevalence of human BAT using 18F-FDG PET

Authors

retrospective as well as prospective studies have shown this. This may be related to a shifting balance between decreased stimulatory sex hormones and inhibitory effects of glucocorticosteroids [37]. Yoneshiro et al. [30] have shown that age-related decline in BAT activity is associated with accumulation of total, visceral and subcutaneous fat. In paediatric subjects, BAT incidence is higher in newborns (up to 2 years) and pubertal subjects [38, 39]. While retrospective studies cannot yield information on the prevalence of BAT, they do show that outdoor temperature (average per year or current temperature or season) has a negative correlation with BAT detection, in Nordic as well as southern, subtropical climatic zones [31]. Prospective acclimation studies show that not only acute but also chronic ambient temperature changes affect BAT mass, function and 18F-FDG uptake [40, 41]. Only one study in mice has addressed the connection with diurnal rhythm and found that glucose uptake in BAT peaked at approximately 9 h into the light phase [42]. In humans this would correspond to the late afternoon but has not been studied so far. The use of concomitant medication (in particular beta-blockers) as well as hormones (in particular insulin) and cytokine levels are also known to affect BAT [7, 21, 22] and these provide interesting targets for therapeutic manipulation of BAT function.

Function and distribution of BAT Heat production throughout the body Today, we distinguish three types of fat cell phenotypes, namely white, beige or brite and brown adipocytes, which have a distinct ontogeny (for a review, see [43]). The tentative primary

Publication year

Number of subjects

Incidence of BAT detection

Cohade et al. [5]

2003

905

7%

Yeung et al. [12] Truong et al. [13] Kim et al. [14] Williams and Kolodny [15] Cypess et al. [7] Cheng et al. [16] Stefan et al. [17] Au-Yong et al. [18] Lee et al. [19] Pace et al. [20] Ouellet et al. [21] Jacene et al. [22] Yilmaz et al. [23] Huang et al. [24] Skillen et al. [25]

2003 2004 2008 2008 2009 2009 2009 2009 2010 2011 2011 2011 2011 2011 2012

863 845 1,159 1,972 1,972 1,080 3,604 3,614 2,934 848 4,842 908 1,832 1,740 300

4% 2% 3% 5% 5% 4% 5% 5% 8.5 % 8.6 % 6.8 % 6.2 % 2% 1.7 % 9.3 %

Eur J Nucl Med Mol Imaging Table 2 Impact factors on BAT activity in humans Factor (study)

Correlation (statistical power)

Synopsis

BMI [7, 19–21, 28, 29]

Negative, exponential (r=−0.8, p 5 % weight (%) loss) (%)

Overall Favourable non-Hodgkin’s lymphoma NSCLC Genito-urinary Colorectal Breast

60–80 30–40

2–8 34

50 60–70

ND ND

47 56 55–60 10–35

4 6 4 7

20 46 43 80–90

11–13 9–18 15–20 70–80

Pancreas Head and neck Phaeochromocytoma Sarcoma Hibernoma

83–87 10–15 7–23 31–40 Rare

4 ND >30 9 ND

5–25 57 36–74 56–90 >90

5–15 36 ND ND ND

ND no data available, NSCLC non-small cell lung cancer

14(R,S)-[18F]fluoro-6-thia-heptadecanoic acid (FTHA) [123]. 18 F-FTHA uptake in the heart and mitochondrial retention was shown to be insulin sensitive [124]. This fatty acid is metabolized via beta-oxidation, but is irreversibly bound to mitochondrial proteins once the sulphur group is free. This allows quantification of tissue uptake by linearization methods, such as Patlak analysis. In addition to these radiopharmaceuticals, Henkin et al. developed fatty acid coupled to luciferin [125]. While this compound is not applicable in humans due to the short penetration depth of light originating from luciferin, it can be used for preclinical research as it allows non-invasive dynamic imaging of free fatty acid uptake. So far, only one dedicated study to visualize BAT fatty acid uptake has been performed [35]. The study, using six healthy test subjects, showed that 18F-FTHA uptake by BAT under cold-stressed conditions was 2.3 μmol/min, while it was low in ambient temperatures. Although this uptake is rather low [especially when compared to FDG (10.8 μmol/min)], it is not unreasonable because: 1. Free fatty acids represent only a minor part of the fatty acids in the blood, as most lipids are in the form of triglycerides, very low-density lipoprotein (VLDL), lowdensity lipoprotein (LDL) or high-density lipoprotein (HDL) particles. BAT tissue may therefore be more adapted to a high uptake of triglycerides and not free fatty acids such as FTHA. 2. The intracellular pool of lipids in BAT cells is substantial and is the preferential source of energy for BAT [35, 51, 126].

As such, the uptake of new free fatty acids need not be a fast process, resulting in low uptake of 18F-FTHA. These remarks are true for all radiolabelled free fatty acids, rendering them a suboptimal choice for imaging overall BAT activity and capable solely of imaging free fatty acid uptake. In the future, radiolabelled triglycerides may be developed as a further attempt to monitor BAT lipid uptake. The preferential use of intracellular lipids is a feature that cannot be monitored by imaging with radiopharmaceuticals. However, CT is capable of estimating lipid content in BAT tissue over time, allowing one to calculate lipid disappearance/ burning [50, 126]. Considering the widespread use of PET/ CT, a combined approach by measuring both the uptake of the radiopharmaceutical by PET and simultaneously measuring the change in CT signal indicating lipid burning, is entirely within reason for future research. Oxidative metabolism 11

C-Acetate is a radiopharmaceutical targeted at visualizing fatty acid synthase activity and is currently being investigated as a tracer for imaging prostate cancer [127–130]. More importantly, dynamic PET imaging of 11C-acetate allows one to estimate tissue oxidative metabolism. Ouellet et al. showed that 11C-acetate uptake increased approximately twofold when healthy test subjects were exposed to cold [35], a figure that corresponds well to that reported with 15O-labelled O2 [73, 131]. Both 11C and 15O are cyclotron-produced isotopes with a very short half-life however (20 and 2 min, respectively), making their use restricted to research institutes with an in-house cyclotron.

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Mitochondrial activity BAT is distinctive compared to WAT due to its large number of mitochondria, and its mitochondrial density is rivalled only by that of the heart muscle. As a consequence, it is possible to image BAT using tracers targeting mitochondria such as 99mTcsestamibi or 99mTc-tetrofosmin (Fig. 3) [132–134]. In general, these tracers rely on the high mitochondrial membrane voltage as a target. Similar to FDG, the discovery of 99mTc-sestamibi uptake in BAT was accidental as it provided an explanation for the previously undetermined focal uptake spots in the supraclavicular region. So far, no dedicated studies have been performed however, and only one large (n=205) retrospective study [132] was performed which demonstrated a 6.3 % chance of BAT detection. Notably, this number is similar to the detection reported for FDG in retrospective studies. Animal studies with 99mTc-sestamibi have shown that, when compared to FDG, sestamibi has a higher uptake in BAT under basal conditions [135, 136]. However, when the animal is exposed to cold, sestamibi uptake only increases by a factor of about 1.4, while the uptake of FDG increased up to 26-fold. In addition, the sestamibi increase can partly be explained by an increase in BAT blood flow. These results are coherent with the idea that sestamibi targets mitochondrial density, which is unaltered in short-term experiments such as acute cold exposure. As such, MIBI is only suitable to visualize long-term changes in mitochondrial density in BAT. Madar et al. developed a 18F-labelled mitochondrial targeting agent, 18F-fluorobenzyl-triphenylphosphine (FFBnTP), that so far has only entered preclinical trials [137–139]. Similar to sestamibi, this compound showed a relatively high uptake in BAT under basal conditions. Interestingly, 18F-FBnTP uptake in BAT decreased by about 80 % when the animal was exposed to cold. According to the authors, this is due to a decrease in mitochondrial membrane voltage when UCP1 is activated. If confirmed in further (human) studies, this may represent a method to directly and non-invasively monitor UCP1 activity. Adrenergic receptors BAT is predominantly activated by adrenergic receptor signalling from specific nerves, starting in the hypothalamus and ending in BAT. The number of adrenergic receptors on BAT is therefore a good indication of the susceptibility of BAT to be activated, especially when considering that WAT shows only minor amounts of these receptors. 123 I-Metaiodobenzylguanidine (MIBG) and 1 8 Ffluorodopamine (F-DA), originally developed as tracers for neuroendocrine tumours, are now also being used to visualize BAT (Fig. 4) [27, 140–142]. Hadi et al. retrospectively showed this for both 123I-MIBG and 18F-F-DA in around 40 % of phaeochromocytoma patients [140]. Admiraal et al.

showed in a prospective study a detection of BAT in seven of ten healthy test subjects after cold treatment using MIBG (compared to eight of ten when using FDG) [27]. No dynamic studies have been undertaken so far, so changes in receptor density over time remain to be determined. CT, MRI and MRS The radiation dose associated with (18F-FDG) PET/CT studies limits the application of the technique in prospective longitudinal human studies, especially in young healthy subjects. Reducing the administered activity of radiopharmaceutical, in some studies down to 50 MBq 18F-FDG [143], only partially solves this problem. Stand-alone CT results in further reduced radiation doses, but only allows visualization of changes in fat content in BAT over longer periods of time and not instant visualization of BAT metabolic activity [126]. Taken together with the difficulty of accurately delineating (active) BAT from WAT or muscle based only on Hounsfield units, stand-alone CT is inferior compared to PET/CT. MRI, as well as magnetic resonance spectroscopy (MRS), do present radiation-free imaging methods and thus allow multiple scans of the same subject/patient more easily when compared to PET/CT, facilitating longitudinal studies. The earliest application of MRI to BAT was the morphological imaging in rodents [144–146]. BAT was found to have a distinct contrast compared to WAT which corresponded well to histological sectioning. The main origin of contrast between WAT and BAT is the tissue water and fat content. Quantifying the BAT water-fat fraction has been performed using chemical shift imaging, in which water and fat images are obtained by selective excitation of water and fat protons, respectively [147, 148]. More recently, quantification of fat content has been performed using multi-echo MRI sequences [149], where water-fat separation is performed based on the MRI signal change caused by the phase differences between water and fat protons. Alternatively, the water-fat content has been quantified using MRS [150], showing a good correspondence to chemical shift imaging [151]. Water-fat quantification using MRI has convincingly shown that BAT fat fractions in the different studies range from 40 to 80 %, whereas WAT generally has a fat fraction of>80 %. However, it was recently observed that fat fraction in the supraclavicular depots did not correlate strongly with BAT activity as quantified on 18F-FDG PET/CT (r=0.63) [152]. Imaging of BAT perfusion is another potential imaging strategy. BAT is highly vascularized and shows an increase in perfusion upon activation [153]. Furthermore, dynamic T2*-weighted imaging has been used to map perfusion changes upon cold-induced and pharmacological activation of BAT [152, 154, 155]. Recently, PET/MRI devices have also allowed simultaneous or sequential PET and MRI imaging. Considering the ability of PET to visualize metabolic processes in BAT with a high

Eur J Nucl Med Mol Imaging Fig. 3 99mTc-Sestamibi uptake in BAT. Early coronal slices of CT (a), single photon emission computed tomography (SPECT) (b), fused SPECT/CT (c) and maximum intensity projection (MIP) (d) of a 60-year-old woman with primary hyperparathyroidism. BAT is seen in the supraclavicular, axillary and paraspinal areas. Reprinted by permission of the Society of Nuclear Medicine and Molecular Imaging (SNMMI) from [132]

sensitivity, and the ability of MRI to visualize perfusion and intracellular properties (lipid content, water content or even mitochondrial activity [156]), the combination holds great promise for future non-invasive metabolic research of BAT.

identified on the PET/CT images when the following criteria are met [7, 21, 140]: – –

Elevated FDG maximum standardized uptake value (SUVmax) above a certain threshold CT tissue density according to adipose tissue

Quantitative measurement of BAT metabolic activity

In recent years, PET/CT has become the gold standard for the non-invasive visualization of metabolically active BAT. One major challenge in the systematic comparison between PET/ CT studies from various investigators is the lack of a standard methodology for the interpretation and quantification of metabolic BAT activity [157]. In general, BAT is

However, there is currently no standardization in reported SUVmax threshold value (range 1.0–2.5) or in CT density (lower and upper HU ranges −250 to −100 and −50 to −10, respectively) (Table 4). Interestingly, it was recently shown that metabolically active BAT (HU=−62.4±5.3) exhibits significantly higher CT HU than WAT (HU=−86.7±7.0) mainly due to its greater intracellular water content and higher degree of vascularization [39, 157]. In a study of 23 oncological patients who had a high FDG uptake in BAT depots (SUVmax

Fig. 4 MIP images of a patient with phaeochromocytoma. 18F-FDG PET (a) shows typical BAT uptake in the supraclavicular region extending into axillary and paravertebral regions. 18F-F-DA PET (b) and 123I-MIBG

SPECT (c) show BAT uptake in supraclavicular regions. Uptake in paraspinal regions is best seen on 18F-FDG images. Reprinted by permission of SNMMI from [140]

BAT identification and region delineation

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>3) in one PET/CT exam and a low BAT FDG uptake in another exam, significantly higher CT HU in BAT was observed in the high SUV exam than in the low SUV exam (−71.6±18.0 vs −104.4±16.8, p1.5

Semi-quantitative visual score of 1–5 in each depot

Cypess, 2009 [7]

1 .Wide ROI over cervical-supraclavicular-superior mediastinal depots 2. CT HU −250 to −50 3. SUVmax >2.0 (>2 SD of SUVmax in WAT typical depots) 1. Localization characteristic for BAT: bilaterally in neck, supra- and infraclavicular regions, paravertebral (lobster sign) 2. CT HU −250 to −50 and fat-like appearance 3. SUVmax isocontour threshold>2.0 1. Supraclavicular region 2. Circular ROI with a minimum ø of 5 mm and SUVmax >3 1. Neck region 2. SUVmax >2.0

Mass and activity of BAT in g × SUVmean in g/ml (on the basis of CT density of fat 0.9 g/ml)

Pfannenberg, 2010 [29]

Baba, 2010 [50] Yoneshiro, 2011 [30] Ouellet, 2011 [21]

Lee, 2011 [89]

Orava, 2011 [92]

Perkins, 2013 [31]

Vosselman, 2012 [143]

SUVmean and volume of single and multiple 3D isocontour ROIs

SUVmax BAT positive or negative

1. Localization cervical, supraclavicular, paravertebral, perirenal SUVmean, SUVmax BAT activity=SUVmean × 2. SUVmax ≥1.0 volume 3. CT HU −100 to −10 1. Region between sternocleidomastoideus muscle anteriorly, supraclavicular BAT positive or negative joint caudally, and scalenus posterior muscle posteriorly and laterally 2. Tissue>4 mm in diameter (CT) 3. SUVmax >2.0 1. Dynamic PET study Regional glucose uptake rate (μmol/100 g/min) 2. Adjacent (2–3) transaxial ROIs in supraclavicular BAT 3. Regional TAC against radioactivity measured in plasma samples (Patlak-Gjedde model) 1. ROIs: neck/supraclavicular, axillary, mediastinal, paravertebral, perirenal 2. CT HU −250 to −50 1a. Threshold ROIs in area between skull base-kidneys 1b. Discrete ROIs in supraclavicular BAT 2. Threshold CT HU −180 to −10 3. Threshold SUVmax >1.5 (approximately 6 times higher than in WAT)

SUVmax values of regions

1a. SUVtotal =SUVmean × the volume of the region (cm3) 1b. SUVmean, SUVmax

ROI region of interest, ø diameter, TAC time-activity curve, HU Hounsfield units

Using a three-compartment model that accounts for both 15OO2 bound to haemoglobin in vascular spaces and 15O-H2O in tissue and blood spaces, local OEF can be estimated from the (dynamic) PET image and the arterial input function after inhalation of trace quantities of 15O-O2. The OEF model assumes that local blood flow and blood volume (BV, ml/ 100 g) are previously determined. Information about local BV can be obtained from (dynamic) PET data together with the arterial input function after inhalation of trace quantities of 15 O- (or 11C)-labelled CO gas [165, 167, 168]. Local blood flow is measured with 15O-H2O as described previously. Using this technique, Muzik et al. demonstrated that despite increased FDG tracer uptake, human BAT activation contributes little (< 2 %) to total energy expenditure ( < 25 kcal/day) [73, 131]. MRO2 was found to increase significantly during mild cold exposure in BAT-positive subjects (from 0.95±0.74 ml/100 g per

min to 1.62±0.82 ml/100 g per min), resulting from an increased blood flow. However, OEF was demonstrated to be similar during baseline and cold exposure conditions [131], although the cooling protocol of only 20 min may have been suboptimal. The important advantage of these techniques, although very limitedly available and costly, is that owing to the ultrashort half-life of these tracers, the dynamic process of activating and deactivating BAT can be precisely studied and multiple interventions done within one study.

Conclusion BAT plays a role in regulating body weight and active BAT is demonstrably low or absent in obesity, while it is possibly overly active in cancer cachexia. The list of diseases that are correlated

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with BAT activity together with the available interventions to affect BAT lead us to expect an increase in investigations where BAT activity is altered in an attempt to control the disease or at least manage some of its physiological symptoms [69]. Non-invasive imaging, using PET, SPECT, CT or MRI or a combination of these, has the potential to play a major role in assessing drug effects as, in addition to simply measuring weight gain/loss or muscle wasting, imaging has the capacity to visualize BAT activity in the short term as well as in (functionally) different compartments, while it can estimate the quantity of “burned” calories by BAT. This quantity can be a useful parameter in quickly determining the efficacy of drugs that aim to target BAT. BAT substrate metabolism may be further elucidated by multi-tracer studies, and specific tracers targeting active mitochondria and/or UCP1 could be valuable. Acknowledgements The authors wish to convey their thanks to Ivo Pooters, Marielle Visser and Emiel Beijer for their technical support. We are also grateful to Anouk van der Lans, Maarten Vosselman and Guy Vijgen for providing exemplary PET/CT images. Conflicts of interest This work was financially supported by a grant from the Weijerhorst foundation to the Department of Nuclear Medicine in Maastricht.

References 1. Barrington SF, Maisey MN. Skeletal muscle uptake of fluorine-18FDG: effect of oral diazepam. J Nucl Med. 1996;37:1127–9. 2. Hong TS, Shammas A, Charron M, Zukotynski KA, Drubach LA, Lim R. Brown adipose tissue 18F-FDG uptake in pediatric PET/CT imaging. Pediatr Radiol. 2011;41:759–68. doi:10. 1007/s00247-010-1925-y. 3. Hany TF, Gharehpapagh E, Kamel EM, Buck A, Himms-Hagen J, von Schulthess GK. Brown adipose tissue: a factor to consider in symmetrical tracer uptake in the neck and upper chest region. Eur J Nucl Med Mol Imaging. 2002;29:1393–8. doi:10.1007/s00259002-0902-6. 4. Cohade C, Mourtzikos KA, Wahl RL. "USA-Fat": prevalence is related to ambient outdoor temperature-evaluation with 18F-FDG PET/CT. J Nucl Med. 2003;44:1267–70. 5. Cohade C, Osman M, Pannu HK, Wahl RL. Uptake in supraclavicular area fat (“USA-Fat”): description on 18F-FDG PET/CT. J Nucl Med. 2003;44:170–6. 6. Nedergaard J, Bengtsson T, Cannon B. Unexpected evidence for active brown adipose tissue in adult humans. Am J Physiol Endocrinol Metab. 2007;293:E444–52. doi:10.1152/ajpendo. 00691.2006. 7. Cypess AM, Lehman S, Williams G, Tal I, Rodman D, Goldfine AB, et al. Identification and importance of brown adipose tissue in adult humans. N Engl J Med. 2009;360:1509–17. doi:10.1056/ NEJMoa0810780. 8. van Marken Lichtenbelt WD, Vanhommerig JW, Smulders NM, Drossaerts JM, Kemerink GJ, Bouvy ND, et al. Cold-activated brown adipose tissue in healthy men. N Engl J Med. 2009;360: 1500–8. doi:10.1056/NEJMoa0808718. 9. Virtanen KA, Lidell ME, Orava J, Heglind M, Westergren R, Niemi T, et al. Functional brown adipose tissue in healthy adults. N Engl J Med. 2009;360:1518–25. doi:10.1056/NEJMoa0808949.

10. Zingaretti MC, Crosta F, Vitali A, Guerrieri M, Frontini A, Cannon B, et al. The presence of UCP1 demonstrates that metabolically active adipose tissue in the neck of adult humans truly represents brown adipose tissue. FASEB J. 2009;23:3113–20. doi: 10.1096/fj.09-133546. 11. Saito M, Okamatsu-Ogura Y, Matsushita M, Watanabe K, Yoneshiro T, Nio-Kobayashi J, et al. High incidence of metabolically active brown adipose tissue in healthy adult humans: effects of cold exposure and adiposity. Diabetes. 2009;58:1526–31. doi:10. 2337/db09-0530. 12. Yeung HW, Grewal RK, Gonen M, Schöder H, Larson SM. Patterns of (18)F-FDG uptake in adipose tissue and muscle: a potential source of false-positives for PET. J Nucl Med. 2003;44:1789–96. 13. Truong MT, Erasmus JJ, Munden RF, Marom EM, Sabloff BS, Gladish GW, et al. Focal FDG uptake in mediastinal brown fat mimicking malignancy: a potential pitfall resolved on PET/CT. AJR Am J Roentgenol. 2004;183:1127–32. doi:10.2214/ajr.183.4. 1831127. 14. Kim S, Krynyckyi BR, Machac J, Kim CK. Temporal relation between temperature change and FDG uptake in brown adipose tissue. Eur J Nucl Med Mol Imaging. 2008;35:984–9. doi:10.1007/ s00259-007-0670-4. 15. Williams G, Kolodny GM. Method for decreasing uptake of 18FFDG by hypermetabolic brown adipose tissue on PET. AJR Am J Roentgenol. 2008;190:1406–9. doi:10.2214/AJR.07.3205. 16. Cheng WY, Zhu ZH, Ouyang M. Patterns and characteristics of brown adipose tissue uptake of 18F-FDG positron emission tomograph/computed tomography imaging. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2009;31:370–3. 17. Stefan N, Pfannenberg C, Häring HU. The importance of brown adipose tissue. N Engl J Med. 2009;361:416–7. author reply 8–21. 18. Au-Yong IT, Thorn N, Ganatra R, Perkins AC, Symonds ME. Brown adipose tissue and seasonal variation in humans. Diabetes. 2009;58:2583–7. doi:10.2337/db09-0833. 19. Lee P, Greenfield JR, Ho KK, Fulham MJ. A critical appraisal of the prevalence and metabolic significance of brown adipose tissue in adult humans. Am J Physiol Endocrinol Metab. 2010;299:E601–6. doi:10.1152/ajpendo.00298.2010. 20. Pace L, Nicolai E, D’Amico D, Ibello F, Della Morte AM, Salvatore B, et al. Determinants of physiologic 18F-FDG uptake in brown adipose tissue in sequential PET/CT examinations. Mol Imaging Biol. 2011;13:1029–35. doi:10.1007/s11307-010-0431-9. 21. Ouellet V, Routhier-Labadie A, Bellemare W, Lakhal-Chaieb L, Turcotte E, Carpentier AC, et al. Outdoor temperature, age, sex, body mass index, and diabetic status determine the prevalence, mass, and glucose-uptake activity of 18F-FDGdetected BAT in humans. J Clin Endocrinol Metab. 2011;96: 192–9. doi:10.1210/jc.2010-0989. 22. Jacene HA, Cohade CC, Zhang Z, Wahl RL. The relationship between patients’ serum glucose levels and metabolically active brown adipose tissue detected by PET/CT. Mol Imaging Biol. 2011;13:1278–83. doi:10.1007/s11307-010-0379-9. 23. Yilmaz Y, Ones T, Purnak T, Ozguven S, Kurt R, Atug O, et al. Association between the presence of brown adipose tissue and nonalcoholic fatty liver disease in adult humans. Aliment Pharmacol Ther. 2011;34:318–23. doi:10.1111/j.1365-2036.2011.04723.x. 24. Huang YC, Chen TB, Hsu CC, Li SH, Wang PW, Lee BF, et al. The relationship between brown adipose tissue activity and neoplastic status: an (18)F-FDG PET/CT study in the tropics. Lipids Health Dis. 2011;10:238. doi:10.1186/1476-511X-10-238. 25. Skillen A, Currie GM, Wheat JM. Thermal control of brown adipose tissue in 18F-FDG PET. J Nucl Med Technol. 2012;40:99– 103. doi:10.2967/jnmt.111.098780. 26. Vrieze A, Schopman JE, Admiraal WM, Soeters MR, Nieuwdorp M, Verberne HJ, et al. Fasting and postprandial activity of brown

Eur J Nucl Med Mol Imaging

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

adipose tissue in healthy men. J Nucl Med. 2012;53:1407–10. doi: 10.2967/jnumed.111.100701. Admiraal WM, Holleman F, Bahler L, Soeters MR, Hoekstra JB, Verberne HJ. Combining 123I-metaiodobenzylguanidine SPECT/ CT and 18F-FDG PET/CT for the assessment of brown adipose tissue activity in humans during cold exposure. J Nucl Med. 2013;54:208–12. doi:10.2967/jnumed.112.111849. Vijgen GH, Bouvy ND, Teule GJ, Brans B, Hoeks J, Schrauwen P, et al. Increase in brown adipose tissue activity after weight loss in morbidly obese subjects. J Clin Endocrinol Metab. 2012;97: E1229–33. doi:10.1210/jc.2012-1289. Pfannenberg C, Werner MK, Ripkens S, Stef I, Deckert A, Schmadl M, et al. Impact of age on the relationships of brown adipose tissue with sex and adiposity in humans. Diabetes. 2010;59:1789–93. doi: 10.2337/db10-0004. Yoneshiro T, Aita S, Matsushita M, Kameya T, Nakada K, Kawai Y, et al. Brown adipose tissue, whole-body energy expenditure, and thermogenesis in healthy adult men. Obesity (Silver Spring). 2011;19:13–6. doi:10.1038/oby.2010.105. Perkins AC, Mshelia DS, Symonds ME, Sathekge M. Prevalence and pattern of brown adipose tissue distribution of 18F-FDG in patients undergoing PET-CT in a subtropical climatic zone. Nucl M e d C om m un . 2 01 3 ; 3 4 : 1 6 8–7 4 . do i :1 0 . 1 0 97 / M N M . 0b013e32835bbbf0. Cronin CG, Prakash P, Daniels GH, Boland GW, Kalra MK, Halpern EF, et al. Brown fat at PET/CT: correlation with patient characteristics. Radiology. 2012;263:836–42. doi:10.1148/radiol. 12100683. Zukotynski KA, Fahey FH, Laffin S, Davis R, Treves ST, Grant FD, et al. Seasonal variation in the effect of constant ambient temperature of 24 degrees C in reducing FDG uptake by brown adipose tissue in children. Eur J Nucl Med Mol Imaging. 2010;37:1854–60. doi:10.1007/s00259-010-1485-2. Zukotynski KA, Fahey FH, Laffin S, Davis R, Treves ST, Grant FD, et al. Constant ambient temperature of 24 degrees C significantly reduces FDG uptake by brown adipose tissue in children scanned during the winter. Eur J Nucl Med Mol Imaging. 2009;36:602–6. doi:10.1007/s00259-008-0983-y. Ouellet V, Labbé SM, Blondin DP, Phoenix S, Guérin B, Haman F, et al. Brown adipose tissue oxidative metabolism contributes to energy expenditure during acute cold exposure in humans. J Clin Invest. 2012;122:545–52. doi:10.1172/JCI60433. Vogel WV, Valdés Olmos RA, Tijs TJ, Gillies MF, van Elswijk G, Vogt J. Intervention to lower anxiety of 18F-FDG PET/CT patients by use of audiovisual imagery during the uptake phase before imaging. J Nucl Med Technol. 2012;40:92–8. doi:10.2967/jnmt. 111.097964. Nedergaard J, Bengtsson T, Cannon B. Three years with adult human brown adipose tissue. Ann N Y Acad Sci. 2010;1212:E20– 36. doi:10.1111/j.1749-6632.2010.05905.x. Gilsanz V, Hu HH, Kajimura S. Relevance of brown adipose tissue in infancy and adolescence. Pediatr Res. 2012;73:3–9. doi:10.1038/ pr.2012.141. Gilsanz V, Smith ML, Goodarzian F, Kim M, Wren TA, Hu HH. Changes in brown adipose tissue in boys and girls during childhood and puberty. J Pediatr. 2011;160:604–9.e1. doi:10.1016/j.jpeds. 2011.09.035. Yoneshiro T, Aita S, Matsushita M, Kayahara T, Kameya T, Kawai Y, et al. Recruited brown adipose tissue as an antiobesity agent in humans. J Clin Invest. 2013;123:3404–8. doi: 10.1172/JCI67803. van der Lans AA, Hoeks J, Brans B, Vijgen GH, Visser MG, Vosselman MJ, et al. Cold acclimation recruits human brown fat and increases nonshivering thermogenesis. J Clin Invest. 2013;123: 3395–403. doi: 10.1172/JCI68993. van der Veen DR, Shao J, Chapman S, Leevy WM, Duffield GE. A diurnal rhythm in glucose uptake in brown adipose tissue revealed

43.

44. 45.

46.

47.

48.

49.

50.

51.

52. 53.

54.

55.

56.

57.

58.

59.

60.

61.

by in vivo PET-FDG imaging. Obesity (Silver Spring). 2012;20: 1527–9. doi:10.1038/oby.2012.78. Lee P, Swarbrick MM, Ho KK. Brown adipose tissue in adult humans: a metabolic renaissance. Endocr Rev. 2013;34:413–38. doi: 10.1210/er.2012-1081. Jezek P, Garlid KD. Mammalian mitochondrial uncoupling proteins. Int J Biochem Cell Biol. 1998;30:1163–8. Rousset S, Alves-Guerra MC, Mozo J, Miroux B, Cassard-Doulcier AM, Bouillaud F, et al. The biology of mitochondrial uncoupling proteins. Diabetes. 2004;53 Suppl 1:S130–5. Sluse FE. Uncoupling proteins: molecular, functional, regulatory, physiological and pathological aspects. Adv Exp Med Biol. 2012;942:137–56. doi:10.1007/978-94-007-2869-1_6. Jastroch M, Withers K, Klingenspor M. Uncoupling protein 2 and 3 in marsupials: identification, phylogeny, and gene expression in response to cold and fasting in Antechinus flavipes. Physiol Genomics. 2004;17: 130–9. doi:10.1152/physiolgenomics.00165.2003. Jastroch M, Withers KW, Taudien S, Frappell PB, Helwig M, Fromme T, et al. Marsupial uncoupling protein 1 sheds light on the evolution of mammalian nonshivering thermogenesis. P h y s i o l G e n o m i c s . 2 0 0 8 ; 3 2 : 1 6 1 – 9 . d o i : 1 0 . 11 5 2 / physiolgenomics.00183.2007. Cypess AM, Chen YC, Sze C, Wang K, English J, Chan O, et al. Cold but not sympathomimetics activates human brown adipose tissue in vivo. Proc Natl Acad Sci U S A. 2012;109:10001–5. doi: 10.1073/pnas.1207911109. Baba S, Jacene HA, Engles JM, Honda H, Wahl RL. CT Hounsfield units of brown adipose tissue increase with activation: preclinical and clinical studies. J Nucl Med. 2010;51:246–50. doi:10.2967/ jnumed.109.068775. Bartelt A, Bruns OT, Reimer R, Hohenberg H, Ittrich H, Peldschus K, et al. Brown adipose tissue activity controls triglyceride clearance. Nat Med. 2011;17:200–5. doi:10.1038/nm.2297. Heaton JM. The distribution of brown adipose tissue in the human. J Anat. 1972;112:35–9. Lidell ME, Betz MJ, Dahlqvist Leinhard O, Heglind M, Elander L, Slawik M, et al. Evidence for two types of brown adipose tissue in humans. Nat Med. 2013;19:631–4. doi:10.1038/nm.3017. Wu J, Cohen P, Spiegelman BM. Adaptive thermogenesis in adipocytes: is beige the new brown? Genes Dev. 2013;27:234–50. doi:10. 1101/gad.211649.112. Jespersen NZ, Larsen TJ, Peijs L, Daugaard S, Homøe P, Loft A, et al. A classical brown adipose tissue mRNA signature partly overlaps with brite in the supraclavicular region of adult humans. Cell Metab. 2013;17:798–805. doi:10.1016/j.cmet.2013.04.011. van der Lans AA, Hoeks J, Brans B, Vijgen G, Visser M, Vosselman MJ, et al. Cold acclimation recruits BAT and increases nonshivering thermogenesis in humans. J Clin Invest. 2013. Accepted for publication. Vosselman MJ, van Marken Lichtenbelt WD, Schrauwen P. Energy dissipation in brown adipose tissue: from mice to men. Mol Cell Endocrinol. 2013;379:43–50. doi: 10.1016/j.mce.2013.04.017. Bartelt A, Heeren J. The holy grail of metabolic disease: brown adipose tissue. Curr Opin Lipidol. 2012;23:190–5. doi:10.1097/ MOL.0b013e328352dcef. Guerra C, Navarro P, Valverde AM, Arribas M, Brüning J, Kozak LP, et al. Brown adipose tissue-specific insulin receptor knockout shows diabetic phenotype without insulin resistance. J Clin Invest. 2001;108:1205–13. doi:10.1172/JCI13103. Boström P, Wu J, Jedrychowski MP, Korde A, Ye L, Lo JC, et al. A PGC1-alpha-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature. 2012;481:463–8. doi:10.1038/nature10777. Moreno-Navarrete JM, Ortega F, Serrano M, Guerra E, Pardo G, Tinahones F, et al. Irisin is expressed and produced by human muscle and adipose tissue in association with obesity and

Eur J Nucl Med Mol Imaging

62.

63.

64.

65.

66.

67.

68.

69.

70.

71. 72. 73.

74. 75.

76. 77.

78.

79.

80.

insulin resistance. J Clin Endocrinol Metab. 2013;98:E769– 78. doi:10.1210/jc.2012-2749. Sakamoto T, Takahashi N, Sawaragi Y, Naknukool S, Yu R, Goto T, et al. Inflammation induced by RAW macrophages suppresses UCP1 mRNA induction via ERK activation in 10T1/2 adipocytes. Am J Physiol Cell Physiol. 2013;304:C729–38. doi:10.1152/ ajpcell.00312.2012. Parinandi NL, Magalang UJ. Avatars of adipose tissue: the saga of transformation of white fat, the villain into brown fat, the protector. Focus on “inflammation induced by RAW macrophages suppresses the UCP1 mRNA induction via ERK activation in 10T1/2 adipocytes”. Am J Physiol Cell Physiol. 2013;304:C715–6. Pasanisi F, Pace L, Fonti R, Marra M, Sgambati D, De Caprio C, et al. Evidence of brown fat activity in constitutional leanness. J Clin Endocrinol Metab. 2013;98:1214–8. doi:10.1210/jc.2012-2981. Kosmiski LA, Sage-El A, Kealey EH, Bessesen DH. Brown fat activity is not apparent in subjects with HIV lipodystrophy and increased resting energy expenditure. Obesity (Silver Spring). 2011;19:2096–8. doi:10.1038/oby.2011.231. Torriani M, Zanni MV, Fitch K, Stavrou E, Bredella MA, Lim R, et al. Increased FDG uptake in association with reduced extremity fat in HIV patients. Antivir Ther. 2013;18:243–8. doi:10.3851/IMP2420. Kiefer FW, Cohen P, Plutzky J. Fifty shades of brown: perivascular fat, thermogenesis, and atherosclerosis. Circulation. 2012;126: 1012–5. doi:10.1161/CIRCULATIONAHA.112.123521. Fatemi A, Item C, Stöckler-Ipsiroglu S, Ipsiroglu O, Sperl W, Patsch W, et al. Sudden infant death: no evidence for linkage to common polymorphisms in the uncoupling protein-1 and the beta3adrenergic receptor genes. Eur J Pediatr. 2002;161:337–9. doi:10. 1007/s00431-002-0940-x. Vijgen G, van Marken LW, Lichtenbelt W. Brown adipose tissue: clinical impact of a re-discovered thermogenic organ. Front Biosci (Elite Ed). 2013;5:823–33. Ichimiya H, Arakawa S, Sato T, Shimada T, Chiba M, Soma Y, et al. Involvement of brown adipose tissue in subcutaneous fat necrosis of the newborn. Dermatology. 2011;223:207–10. doi:10.1159/000331810. Svacina S. Treatment of obese diabetics. Adv Exp Med Biol. 2012;771:459–64. Schwartz S, Fabricatore AN, Diamond A. Weight reduction in diabetes. Adv Exp Med Biol. 2012;771:438–58. Muzik O, Mangner TJ, Leonard WR, Kumar A, Janisse J, Granneman JG. 15O PET measurement of blood flow and oxygen consumption in cold-activated human brown fat. J Nucl Med. 2013;54:523–31. doi:10.2967/jnumed.112.111336. Stock MJ. Thermogenesis and brown fat: relevance to human obesity. Infusionstherapie. 1989;16:282–4. Cannon B, Nedergaard J. Brown adipose tissue: function and physiological significance. Physiol Rev. 2004;84:277–359. doi:10.1152/ physrev.00015.2003. Rothwell NJ, Stock MJ. A role for brown adipose tissue in dietinduced thermogenesis. Nature. 1979;281:31–5. Rothwell NJ, Stock MJ. Luxuskonsumption, diet-induced thermogenesis and brown fat: the case in favour. Clin Sci (Lond). 1983;64: 19–23. Kim JY, Lee SS. The effects of uncoupling protein 1 and beta3adrenergic receptor gene polymorphisms on weight loss and lipid profiles in obese women. Int J Vitam Nutr Res. 2010;80:87–96. doi: 10.1024/0300-9831/a000009. Kurokawa N. Association of BMI with the beta3 adrenergic receptor gene mutation: a meta-analysis. Nihon Eiseigaku Zasshi. 2011;66:42–6. Feldmann HM, Golozoubova V, Cannon B, Nedergaard J. UCP1 ablation induces obesity and abolishes diet-induced thermogenesis in mice exempt from thermal stress by living at thermoneutrality. Cell Metab. 2009;9:203–9. doi:10.1016/j.cmet.2008.12.014.

81. Lowell BB, S-Susulic V, Hamann A, Lawitts JA, Himms-Hagen J, Boyer BB, et al. Development of obesity in transgenic mice after genetic ablation of brown adipose tissue. Nature. 1993;366:740–2. doi:10.1038/366740a0. 82. Bachman ES, Dhillon H, Zhang CY, Cinti S, Bianco AC, Kobilka BK, et al. betaAR signaling required for diet-induced thermogenesis and obesity resistance. Science. 2002;297:843–5. doi:10.1126/ science.1073160. 83. Vitali A, Murano I, Zingaretti MC, Frontini A, Ricquier D, Cinti S. The adipose organ of obesity-prone C57BL/6J mice is composed of mixed white and brown adipocytes. J Lipid Res. 2012;53:619–29. doi:10.1194/jlr.M018846. 84. Kopecky J, Clarke G, Enerbäck S, Spiegelman B, Kozak LP. Expression of the mitochondrial uncoupling protein gene from the aP2 gene promoter prevents genetic obesity. J Clin Invest. 1995;96: 2914–23. doi:10.1172/JCI118363. 85. Ghorbani M, Claus TH, Himms-Hagen J. Hypertrophy of brown adipocytes in brown and white adipose tissues and reversal of dietinduced obesity in rats treated with a beta3-adrenoceptor agonist. Biochem Pharmacol. 1997;54:121–31. 86. Ghorbani M, Himms-Hagen J. Appearance of brown adipocytes in white adipose tissue during CL 316,243-induced reversal of obesity and diabetes in Zucker fa/fa rats. Int J Obes Relat Metab Disord. 1997;21:465–75. 87. Gunawardana SC, Piston DW. Reversal of type 1 diabetes in mice by brown adipose tissue transplant. Diabetes. 2012;61:674–82. doi: 10.2337/db11-0510. 88. Stanford KI, Middelbeek RJ, Townsend KL, An D, Nygaard EB, Hitchcox KM, et al. Brown adipose tissue regulates glucose homeostasis and insulin sensitivity. J Clin Invest. 2012;123:215–23. doi: 10.1172/JCI62308. 89. Lee P, Zhao JT, Swarbrick MM, Gracie G, Bova R, Greenfield JR, et al. High prevalence of brown adipose tissue in adult humans. J Clin Endocrinol Metab. 2011;96:2450–5. doi:10. 1210/jc.2011-0487. 90. Orava J, Nuutila P, Noponen T, Parkkola R, Viljanen T, Enerbäck S, et al. Blunted metabolic responses to cold and insulin stimulation in brown adipose tissue of obese humans. Obesity (Silver Spring). 2013. doi:10.1002/oby.20456. 91. Ma SW, Foster DO. Uptake of glucose and release of fatty acids and glycerol by rat brown adipose tissue in vivo. Can J Physiol Pharmacol. 1986;64:609–14. 92. Orava J, Nuutila P, Lidell ME, Oikonen V, Noponen T, Viljanen T, et al. Different metabolic responses of human brown adipose tissue to activation by cold and insulin. Cell Metab. 2011;14:272–9. doi: 10.1016/j.cmet.2011.06.012. 93. Lean ME, Murgatroyd PR, Rothnie I, Reid IW, Harvey R. Metabolic and thyroidal responses to mild cold are abnormal in obese diabetic women. Clin Endocrinol (Oxf). 1988;28: 665–73. 94. Fearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL, et al. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12:489–95. doi:10. 1016/S1470-2045(10)70218-7. 95. Martin L, Birdsell L, Macdonald N, Reiman T, Clandinin MT, McCargar LJ, et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013;31:1539–47. doi:10.1200/ JCO.2012.45.2722. 96. Shellock FG, Riedinger MS, Fishbein MC. Brown adipose tissue in cancer patients: possible cause of cancer-induced cachexia. J Cancer Res Clin Oncol. 1986;111:82–5. 97. Bancroft LW, Kransdorf MJ, Peterson JJ, O’Connor MI. Benign fatty tumors: classification, clinical course, imaging appearance, and treatment. Skeletal Radiol. 2006;35:719–33. doi:10.1007/s00256006-0189-y.

Eur J Nucl Med Mol Imaging 98. Craig WD, Fanburg-Smith JC, Henry LR, Guerrero R, Barton JH. Fat-containing lesions of the retroperitoneum: radiologic-pathologic correlation. Radiographics. 2009;29:261–90. doi:10.1148/rg. 291085203. 99. Essadel A, Bensaid Alaoui S, Mssrouri R, Mohammadine E, Benamr S, Taghy A, et al. Hibernoma: a rare case of massive weight loss. Ann Chir. 2002;127:215–7. 100. Datema FR, Ferrier MB, Baatenburg de Jong RJ. Impact of severe malnutrition on short-term mortality and overall survival in head and neck cancer. Oral Oncol. 2011;47:910–4. doi:10.1016/j. oraloncology.2011.06.510. 101. Muliawati Y, Haroen H, Rotty LW. Cancer anorexia - cachexia syndrome. Acta Med Indones. 2012;44:154–62. 102. Baracos VE, Reiman T, Mourtzakis M, Gioulbasanis I, Antoun S. Body composition in patients with non-small cell lung cancer: a contemporary view of cancer cachexia with the use of computed tomography image analysis. Am J Clin Nutr. 2010;91:1133S–7S. doi:10.3945/ajcn.2010.28608C. 103. Coleman MP, Rachet B, Woods LM, Mitry E, Riga M, Cooper N, et al. Trends and socioeconomic inequalities in cancer survival in England and Wales up to 2001. Br J Cancer. 2004;90:1367–73. doi: 10.1038/sj.bjc.6601696. 104. Bachmann J, Ketterer K, Marsch C, Fechtner K, KrakowskiRoosen H, Büchler MW, et al. Pancreatic cancer related cachexia: influence on metabolism and correlation to weight loss and pulmonary function. BMC Cancer. 2009;9:255. doi: 10.1186/1471-2407-9-255. 105. Caan BJ, Kwan ML, Shu XO, Pierce JP, Patterson RE, Nechuta SJ, et al. Weight change and survival after breast cancer in the after breast cancer pooling project. Cancer Epidemiol Biomarkers Prev. 2012;21:1260–71. doi:10.1158/1055-9965.EPI-12-0306. 106. George J, Cannon T, Lai V, Richey L, Zanation A, Hayes DN, et al. Cancer cachexia syndrome in head and neck cancer patients: part II. Pathophysiology. Head Neck. 2007;29:497–507. doi:10.1002/hed. 20630. 107. Petrák O, Haluzíková D, Kaválková P, Štrauch B, Rosa J, Holaj R, et al. Changes in energy metabolism in pheochromocytoma. J Clin Endocrinol Metab. 2013;98:1651–8. doi:10.1210/jc.2012-3625. 108. Nguyen-Martin MA, Hammer GD. Pheochromocytoma: an update on risk groups, diagnosis, and management. Hosp Physician. 2006;42:17–24. 109. Salpeter SR, Malter DS, Luo EJ, Lin AY, Stuart B. Systematic review of cancer presentations with a median survival of six months or less. J Palliat Med. 2011;15:175–85. doi:10.1089/jpm.2011.0192. 110. Gilsanz V, Hu HH, Smith ML, Goodarzian F, Carcich SL, Warburton NM, et al. The depiction of brown adipose tissue is related to disease status in pediatric patients with lymphoma. AJR Am J Roentgenol. 2012;198:909–13. doi:10.2214/AJR.11.7488. 111. Vijgen GH, Bouvy ND, Smidt M, Kooreman L, Schaart G, van Marken Lichtenbelt W. Hibernoma with metabolic impact? BMJ Case Rep. 2012;2012. doi: 10.1136/bcr-2012-006325. 112. Eisenhofer G. Screening for pheochromocytomas and paragangliomas. Curr Hypertens Rep. 2012;14:130–7. doi:10. 1007/s11906-012-0246-y. 113. Lean ME, James WP, Jennings G, Trayhurn P. Brown adipose tissue in patients with phaeochromocytoma. Int J Obes. 1986;10:219–27. 114. Chalfant JS, Smith ML, Hu HH, Dorey FJ, Goodarzian F, Fu CH, et al. Inverse association between brown adipose tissue activation and white adipose tissue accumulation in successfully treated pediatric malignancy. Am J Clin Nutr. 2012;95:1144–9. doi:10.3945/ ajcn.111.030650. 115. Beijer E, Schoenmakers J, Vijgen G, Kessels F, Dingemans A, Schrauwen P, et al. A role of active brown adipose tissue in cancer cachexia? Oncol Rev. 2012;6:88–94. 116. Kortelainen ML. Association between cardiac pathology and fat tissue distribution in an autopsy series of men without premortem

evidence of cardiovascular disease. Int J Obes Relat Metab Disord. 1996;20:245–52. 117. Chang L, Milton H, Eitzman DT, Chen YE. Paradoxical roles of perivascular adipose tissue in atherosclerosis and hypertension. Circ J. 2012;77:11–8. 118. Tewson TJ, Welch MJ, Raichle ME. [18F]-labeled 3-deoxy-3fluoro-D-glucose: synthesis and preliminary biodistribution data. J Nucl Med. 1978;19:1339–45. 119. Krause BJ, Schwarzenböck S, Souvatzoglou M. FDG PET and PET/CT. Recent Results Cancer Res. 2013;187:351–69. doi:10. 1007/978-3-642-10853-2_12. 120. Antar MA. Radiopharmaceuticals for studying cardiac metabolism. Int J Rad Appl Instrum B. 1990;17:103–28. 121. Kaiser KP, Geuting B, Grossmann K, Vester E, Lösse B, Antar MA, et al. Tracer kinetics of 15-(ortho-123/131I-phenyl)-pentadecanoic acid (oPPA) and 15-(para-123/131I-phenyl)-pentadecanoic acid (pPPA) in animals and man. J Nucl Med. 1990;31:1608–16. 122. Tamaki N, Yoshinaga K. Novel iodinated tracers, MIBG and BMIPP, for nuclear cardiology. J Nucl Cardiol. 2011;18:135–43. doi:10.1007/s12350-010-9305-4. 123. DeGrado TR, Coenen HH, Stocklin G. 14(R,S)-[18F]fluoro-6-thiaheptadecanoic acid (FTHA): evaluation in mouse of a new probe of myocardial utilization of long chain fatty acids. J Nucl Med. 1991;32:1888–96. 124. Ci X, Frisch F, Lavoie F, Germain P, Lecomte R, van Lier JE, et al. The effect of insulin on the intracellular distribution of 14(R,S)[18F]fluoro-6-thia-heptadecanoic acid in rats. Mol Imaging Biol. 2006;8:237–44. doi:10.1007/s11307-006-0042-7. 125. Henkin AH, Cohen AS, Dubikovskaya EA, Park HM, Nikitin GF, Auzias MG, et al. Real-time noninvasive imaging of fatty acid uptake in vivo. ACS Chem Biol. 2012;7:1884–91. doi:10.1021/ cb300194b. 126. Lubura M, Hesse D, Neumann N, Scherneck S, Wiedmer P, Schürmann A. Non-invasive quantification of white and brown adipose tissues and liver fat content by computed tomography in mice. PLoS One. 2012;7:e37026. doi:10.1371/journal.pone.0037026. 127. Emonds KM, Swinnen JV, Mortelmans L, Mottaghy FM. Molecular imaging of prostate cancer. Methods. 2009;48:193–9. doi:10.1016/ j.ymeth.2009.03.021. 128. Sun KT, Yeatman LA, Buxton DB, Chen K, Johnson JA, Huang SC, et al. Simultaneous measurement of myocardial oxygen consumption and blood flow using [1-carbon-11]acetate. J Nucl Med. 1998;39:272–80. 129. Czernin J, Porenta G, Brunken R, Krivokapich J, Chen K, Bennett R, et al. Regional blood flow, oxidative metabolism, and glucose utilization in patients with recent myocardial infarction. Circulation. 1993;88:884–95. 130. Czernin J, Benz MR, Allen-Auerbach MS. PET imaging of prostate cancer using C-acetate. PET Clin. 2009;4:163–72. doi:10.1016/j. cpet.2009.05.001. 131. Muzik O, Mangner TJ, Granneman JG. Assessment of oxidative metabolism in brown fat using PET imaging. Front Endocrinol (Lausanne). 2012;3:15. doi:10.3389/fendo.2012.00015. 132. Goetze S, Lavely WC, Ziessman HA, Wahl RL. Visualization of brown adipose tissue with 99mTc-methoxyisobutylisonitrile on SPECT/CT. J Nucl Med. 2008;49:752–6. doi:10.2967/jnumed. 107.048074. 133. Wong KK, Brown RK, Avram AM. Potential false positive Tc-99m sestamibi parathyroid study due to uptake in brown adipose tissue. Clin Nucl Med. 2008;33:346–8. doi:10.1097/RLU. 0b013e31816a795a. 134. Fukuchi K, Ono Y, Nakahata Y, Okada Y, Hayashida K, Ishida Y. Visualization of interscapular brown adipose tissue using (99m)Tctetrofosmin in pediatric patients. J Nucl Med. 2003;44:1582–5. 135. Baba S, Engles JM, Huso DL, Ishimori T, Wahl RL. Comparison of uptake of multiple clinical radiotracers into brown adipose tissue

Eur J Nucl Med Mol Imaging under cold-stimulated and nonstimulated conditions. J Nucl Med. 2007;48:1715–23. doi:10.2967/jnumed.107.041715. 136. Kyparos D, Arsos G, Georga S, Petridou A, Kyparos A, Papageorgiou E, et al. Assessment of brown adipose tissue activity in rats by 99mTc-sestamibi uptake. Physiol Res. 2006;55:653–9. 137. Madar I, Isoda T, Finley P, Angle J, Wahl R. 18F-fluorobenzyl triphenyl phosphonium: a noninvasive sensor of brown adipose tissue thermogenesis. J Nucl Med. 2011;52:808–14. doi:10.2967/ jnumed.110.084657. 138. Madar I, Ravert H, Dipaula A, Du Y, Dannals RF, Becker L. Assessment of severity of coronary artery stenosis in a canine model using the PET agent 18F-fluorobenzyl triphenyl phosphonium: comparison with 99mTc-tetrofosmin. J Nucl Med. 2007;48:1021– 30. doi:10.2967/jnumed.106.038778. 139. Madar I, Ravert H, Nelkin B, Abro M, Pomper M, Dannals R, et al. Characterization of membrane potential-dependent uptake of the novel PET tracer 18F-fluorobenzyl triphenylphosphonium cation. Eur J Nucl Med Mol Imaging. 2007;34:2057–65. doi:10.1007/ s00259-007-0500-8. 140. Hadi M, Chen CC, Whatley M, Pacak K, Carrasquillo JA. Brown fat imaging with (18)F-6-fluorodopamine PET/CT, (18)F-FDG PET/CT, and (123)I-MIBG SPECT: a study of patients being evaluated for pheochromocytoma. J Nucl Med. 2007;48:1077–83. doi: 10.2967/jnumed.106.035915. 141. Okuyama C, Sakane N, Yoshida T, Shima K, Kurosawa H, Kumamoto K, et al. (123)I- or (125)I-metaiodobenzylguanidine visualization of brown adipose tissue. J Nucl Med. 2002;43:1234–40. 142. Okuyama C, Ushijima Y, Kubota T, Yoshida T, Nakai T, Kobayashi K, et al. 123I-Metaiodobenzylguanidine uptake in the nape of the neck of children: likely visualization of brown adipose tissue. J Nucl Med. 2003;44:1421–5. 143. Vosselman MJ, van der Lans AA, Brans B, Wierts R, van Baak MA, Schrauwen P, et al. Systemic beta-adrenergic stimulation of thermogenesis is not accompanied by brown adipose tissue activity in humans. Diabetes. 2012;61:3106–13. doi:10.2337/db12-0288. 144. Osculati F, Leclercq F, Sbarbati A, Zancanaro C, Cinti S, Antonakis K. Morphological identification of brown adipose tissue by magnetic resonance imaging in the rat. Eur J Radiol. 1989;9:112–4. 145. Osculati F, Sbarbati A, Leclercq F, Zancanaro C, Accordini C, Antonakis K, et al. The correlation between magnetic resonance imaging and ultrastructural patterns of brown adipose tissue. J Submicrosc Cytol Pathol. 1991;23:167–74. 146. Sbarbati A, Baldassarri AM, Zancanaro C, Boicelli A, Osculati F. In vivo morphometry and functional morphology of brown adipose tissue by magnetic resonance imaging. Anat Rec. 1991;231:293–7. doi:10.1002/ar.1092310302. 147. Lunati E, Marzola P, Nicolato E, Fedrigo M, Villa M, Sbarbati A. In vivo quantitative lipidic map of brown adipose tissue by chemical shift imaging at 4.7 Tesla. J Lipid Res. 1999;40:1395–400. 148. Sbarbati A, Guerrini U, Marzola P, Asperio R, Osculati F. Chemical shift imaging at 4.7 tesla of brown adipose tissue. J Lipid Res. 1997;38:343–7. 149. Hu HH, Smith Jr DL, Nayak KS, Goran MI, Nagy TR. Identification of brown adipose tissue in mice with fat-water IDEAL-MRI. J Magn Reson Imaging. 2010;31:1195–202. doi:10.1002/jmri.22162. 150. Cavallini I, Marino MA, Tonello C, Marzola P, Nicolato E, Fabene PF, et al. The hydrolipidic ratio in age-related maturation of adipose tissues. Biomed Pharmacother. 2006;60:139–43. doi:10.1016/j. biopha.2006.01.007. 151. Peng XG, Ju S, Fang F, Wang Y, Fang K, Cui X, et al. Comparison of brown and white adipose tissue fat fractions in ob, seipin, and Fsp27 gene knockout mice by chemical shift-selective imaging and

152.

153.

154.

155.

156.

157.

158.

159.

160.

161.

162.

163.

164.

165.

166.

167.

168.

(1)H-MR spectroscopy. Am J Physiol Endocrinol Metab. 2013;304: E160–7. doi:10.1152/ajpendo.00401.2012. van Rooijen BD, van der Lans AA, Brans B, Wildberger JE, Mottaghy FM, Schrauwen P, et al. Imaging cold-activated brown adipose tissue using dynamic T2*-weighted magnetic resonance imaging and 2deoxy-2-[18F]fluoro-D-glucose positron emission tomography. Invest Radiol. 2013;48:708–14. doi:10.1097/RLI.0b013e31829363b8. Foster DO, Frydman ML. Tissue distribution of cold-induced thermogenesis in conscious warm- or cold-acclimated rats reevaluated from changes in tissue blood flow: the dominant role of brown adipose tissue in the replacement of shivering by nonshivering thermogenesis. Can J Physiol Pharmacol. 1979;57:257–70. Chen YI, Cypess AM, Sass CA, Brownell AL, Jokivarsi KT, Kahn CR, et al. Anatomical and functional assessment of brown adipose tissue by magnetic resonance imaging. Obesity (Silver Spring). 2012;20:1519–26. doi:10.1038/oby.2012.22. Khanna A, Branca RT. Detecting brown adipose tissue activity with BOLD MRI in mice. Magn Reson Med. 2012;68:1285–90. doi:10. 1002/mrm.24118. Kemp GJ, Brindle KM. What do magnetic resonance-based measurements of Pi → ATP flux tell us about skeletal muscle metabolism? Diabetes. 2012;61:1927–34. doi:10.2337/db11-1725. Hu HH, Gilsanz V. Developments in the imaging of brown adipose tissue and its associations with muscle, puberty, and health in children. Front Endocrinol (Lausanne). 2011;2:33. doi:10.3389/fendo.2011.00033. Huang YC, Hsu CC, Huang P, Yin TK, Chiu NT, Wang PW, et al. The changes in brain metabolism in people with activated brown adipose tissue: a PET study. Neuroimage. 2011;54:142–7. doi:10. 1016/j.neuroimage.2010.07.058. Ruth M, Wellman T, Mercier G, Szabo T, Apovian C. An automated algorithm to identify and quantify brown adipose tissue in human (18)F-FDG-PET/CT scans. Obesity (Silver Spring). 2013;21:1554– 60. doi:10.1002/oby.20315. Gilsanz V, Chung SA, Jackson H, Dorey FJ, Hu HH. Functional brown adipose tissue is related to muscle volume in children and adolescents. J Pediatr. 2010;158:722–6. doi:10.1016/j.jpeds.2010.11.020. Patlak CS, Blasberg RG. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. J Cereb Blood Flow Metab. 1985;5:584–90. doi:10.1038/jcbfm. 1985.87. Sundaram SK, Freedman NM, Carrasquillo JA, Carson JM, Whatley M, Libutti SK, et al. Simplified kinetic analysis of tumor 18F-FDG uptake: a dynamic approach. J Nucl Med. 2004;45:1328–33. Fox PT, Raichle ME, Mintun MA, Dence C. Nonoxidative glucose consumption during focal physiologic neural activity. Science. 1988;241:462–4. Kety SS, Schmidt CF. The nitrous oxide method for the quantitative determination of cerebral blood flow in man: theory, procedure and normal values. J Clin Invest. 1948;27:476–83. doi:10.1172/JCI101994. Mintun MA, Raichle ME, Martin WR, Herscovitch P. Brain oxygen utilization measured with O-15 radiotracers and positron emission tomography. J Nucl Med. 1984;25:177–87. Hattori N, Bergsneider M, Wu HM, Glenn TC, Vespa PM, Hovda DA, et al. Accuracy of a method using short inhalation of (15)OO(2) for measuring cerebral oxygen extraction fraction with PET in healthy humans. J Nucl Med. 2004;45:765–70. Grubb Jr RL, Raichle ME, Higgins CS, Eichling JO. Measurement of regional cerebral blood volume by emission tomography. Ann Neurol. 1978;4:322–8. doi:10.1002/ana.410040407. Raichle ME, Welch MJ, Grubb Jr RL, Higgins CS, Ter-Pogossian MM, Larson KB. Measurement of regional substrate utilization rates by emission tomography. Science. 1978;199:986–7.