{"paper_id":"48cb8776-e7e5-4d52-8211-8d98e79876e1","body_text":"Effect of β3-Adrenergic Receptor Agonists on [18F]FDG Uptake in Brown Adipose Tissues in the PET images of Elderly Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of β3-Adrenergic Receptor Agonists on [18F]FDG Uptake in Brown Adipose Tissues in the PET images of Elderly Patients John Kenneth V. Gacula, Kenichiro Ogane, Kaori Fuse, Miyako Morooka Chikanishi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6603701/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Aug, 2025 Read the published version in EJNMMI Research → Version 1 posted 5 You are reading this latest preprint version Abstract Background Brown adipose tissues (BAT) are highly vascularized and mitochondria-rich tissues that are related to thermogenesis. Physiologic [18F]fluorodeoxyglucose ([18F]FDG) uptake in BAT may be caused by several factors, including certain drugs that utilizes β-adrenergic receptors. Recently, increased [18F]FDG BAT uptake among elderly patients (aged 60 years old and above) receiving β3-adrenergic receptor agonists have been reported. With the increasing use of β3-adrenergic receptor agonists for overactive bladder, little is known about the medication and increased [18F]FDG BAT uptake. This study investigates the association of β3-adrenergic receptor agonists treatment with increased [18F]FDG uptake in BAT among elderly patients through a retrospective review of their [18F]FDG positron emission tomography (PET) scans that exhibit increased [18F]FDG BAT uptake. Assessment of [18F]FDG BAT uptake was performed via visual inspection and SUVmax measurement in eight selected regions of interest, namely: cervical, periclavicular, axillary, mediastinal, paravertebral, para-abdominal aortic, perirenal, and perisplenic regions. Drug history and clinical records of the patients were reviewed to determine history of β3-adrenergic receptor agonists use relative to their [18F]FDG PET study. Results Forty-four elderly patients with one [18F]FDG PET scan each were analyzed. Among the eight regions of interest, the increased [18F]FDG BAT uptake in the perirenal region of elderly patients receiving β3-adrenergic receptor agonists, compared to those not receiving, was statistically significant in both visual (p = < 0.001) and SUVmax (p = 0.027) analysis. All patients receiving β3-adrenergic receptor agonists exhibited increased [18F]FDG BAT uptake in the paravertebral region. Conclusion Elderly patients aged 60 years old and above receiving β3-adrenergic receptor agonist treatment may exhibit increased [18F]FDG BAT uptake, most especially in the perirenal area. [18F]FDG PET brown adipose tissue overactive bladder vibegron mirabegron elderly Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Brown fat adipose tissues (BAT) or brown fat are highly vascularized, mitochondria-rich tissues found throughout the body, mainly in the supraclavicular, intrascapular, mediastinal, axillary, paravertebral, supra- and peri-renal regions [1]. Their expression of heat-producing protein uncoupling protein 1 (UCP 1) that breaks down fat to produce heat makes them vital in thermogenesis [2]. They are regulated by norepinephrine signaling through the presence of β3-receptors [1]. They also demonstrate increased glucose utilization when activated, leading to physiologically increased [ 18 F ]fluorodeoxyglucose ([ 18 F]FDG) uptake on [ 18 F]FDG positron emission tomography (PET) imaging [3,4]. The long-standing notion that BAT tissues are only abundant in newborns and children and decreases through aging has been questioned by the presence of increased [ 18 F]FDG uptake on the [ 18 F]FDG PET images of adults [4–9]. The presence of increased physiologic uptake of [ 18 F]FDG in BAT among [ 18 F]FDG PET scans is not uncommon in nuclear medicine. Several factors have been studied and are associated with it, namely: cold ambient temperature, age (younger than older people), sex (prevalent in females), lower weight and body mass index, and lower plasma glucose levels, among others [4,5,9–14]. Even substances that have direct and indirect effects on β-adrenergic receptor like caffeine, nicotine, and ephedrine are linked to BAT activation, leading to hypermetabolism and, consequently, increased [ 18 F]FDG uptake [15,16]. Recent studies have reported increased [ 18 F]FDG uptake in BAT is observed among elderly patients receiving β3-adrenergic receptor (β3-AR) agonists treatment [17,18]. β3-AR agonists are used for treating overactive bladder (OAB) due to the presence of β3-AR in the detrusor muscle and urothelium, leading to detrusor relaxation and reducing bladder tone. Mirabegron is the first approved drug under the said class, with a 50 mg starting dose prescribed in Japan [19]. With the widespread utilization of β3-AR agonists among elderly patients with OAB, little is known about the possibility of β3-AR agonists-induced [ 18 F]FDG uptake in BAT. Nuclear medicine physicians and radiologists should be aware of this and be cautious in interpreting [ 18 F]FDG PET scans. Hence, this study aims to identify the association of β3-AR agonists treatment with increased [ 18 F]FDG uptake in BAT among elderly patients (aged 60 years and above). Furthermore, we aim to identify the prevalence and characterize its occurrence through eight anatomical regions of interest in elderly patients receiving β3-AR agonists treatment, and the possible confounding factors that may affect increased [ 18 F]FDG BAT uptake in elderly patients with and without β3-AR agonists treatment. MATERIALS AND METHODS Hybrid images using [ 18 F]FDG PET, including computed tomography (CT) and magnetic resonance imaging (MRI), done in the National Cancer Center Hospital (NCC) in Japan from January 2011 to April 2025 were retrospectively reviewed. Inclusion criteria include elderly patients aged 60 years and above with [ 18 F]FDG PET scans showing increased [ 18 F]FDG uptake in BAT. This is to reduce the likelihood of false-negative findings [6]. Drug history and clinical records of the patients were then reviewed to determine if they were receiving β3-AR agonists, either vibegron (Beova®) or mirabegron (Betanis®), relative to the schedule of their [ 18 F]FDG PET examination. Exclusion criteria include patients aged less than 60 years of age, with scans without identifiable increased physiologic [ 18 F]FDG BAT uptake, with incomplete or missing drug history, those diagnosed with conditions related to excessive catecholamine release that may induce increased BAT [ 18 F]FDG uptake (e.g. pheochromocytoma) [20,21]. For patients with multiple [ 18 F]FDG PET scans, only the examination wherein increased [ 18 F]FDG uptake in BAT was first observed was retained for analysis. Confounding factors that may contribute to increased [ 18 F]FDG uptake in BAT were collected from the patient’s records and documented for analysis, namely patient’s sex, age, body mass index (BMI), blood glucose level, certain parameters of complete blood count (white blood cells [WBC], hemoglobin, and platelet), and renal function (creatinine and eGFR). Ambient temperature prior to the scan was also collected. For outpatient scans, the recorded outside ambient temperatures one hour before [ 18 F]FDG injection were based from the database of Japan Meteorological Agency [22]. As for inpatient scans, the ambient temperature was set at 24.0°C, which is the temperature of air-conditioned inpatient rooms in the hospital. Waiver of informed consent was provided by institution review board (research proposal number 2018-049). PET Scanning Protocol In accordance with the guidelines of European Association of Nuclear Medicine, the hospital follows standard patient preparations for [ 18 F]FDG PET imaging. Patients are advised to fast for at least four hours prior to the scan to ensure that the patient’s blood glucose is within normal or acceptable limits (set at below 200 mg/dL) to proceed with the examination [23]. Blood glucose levels were measured using a glucometer and recorded prior to injection of radiotracer.[23] The activity of the radiotracer was computed based on the patient’s weight and height (3 to 4 MBq/kg) and administered intravenously, followed by an average 60 minutes rest prior to acquisition of images. Image acquisition begins at the pelvic region towards the head. Both whole-body CT and the adaptive PET/CT images were reconstructed using time-of-fight ordered-subsets expectation maximization (TOF-OSEM). The voxel size for whole-body PET was 3.125 × 3.125 × 2.780 mm 3 (matrix size, 192 × 192). The whole-body PET/CT image acquisition was initiated at a 2-minute acquisition time per bed position. For attenuation correction of the PET data from the PET/CT scanner, the reconstruction software provided by the manufacturer uses attenuation maps generated based on the 3D CT images obtained for every bed position. The procedure for CT-based attenuation correction was implemented in the post-processing software of the scanner and operated automatically. As for [ 18 F]FDG PET/MRI examination, whole body MRI was performed after 60 minutes, followed by the local MRI after 20 minutes (total of 80 minutes). Image acquisition of local PET is done at 3-minute per bed, while whole body is done at 2-minute per bed. During the [ 18 F]FDG PET examination, the room temperature was set at 24℃ to avoid cold stimulation. Further measures to ensure temperature control and thermal insulation were instituted, like provision of blankets when requested by the patient. PET Analysis through Visual Assessment and SUVmax Measurements The [ 18 F]FDG PET images were assessed by the radiologist and nuclear medicine specialist authors. Increased [ 18 F]FDG uptake in BAT were evaluated in the eight anatomic regions of interest (ROI), namely: cervical, periclavicular, axillary, mediastinal, paraabdominal aortic, paravertebral, perirenal, and perisplenic areas [6,24]. The [ 18 F]FDG uptake in these regions were then compared with the maximum standard uptake value (SUVmax) in the subcutaneous fat at the lumbar region. To avoid false-positives due to [ 18 F]FDG uptake by malignant tumors, correlation with attenuated-corrected CT images were done to ensure that the area is within the fat concentration range (CT value of -100 to 0 Hounsfield unit [HU]). A patient is classified to have increased [ 18 F]FDG uptake when it is detected in any of the aforementioned regions. The detection involves two ways of determination: via visual and SUVmax measurement. Assessment of increased [ 18 F]FDG uptake in BAT through SUVmax determination was limited only in the PET/CT scans (n = 38). Statistical Analysis All the statistical analyses were performed using IBM SPSS Version 30 (IBM Corp., Armonk, NY, USA). Each of the eight ROIs were analyzed using Fisher's exact probability test after confirming that more than 20% of all cells had an expected frequency of less than five in the cross-tabulation table, considering a positive or negative history of treatment with β3-AR agonists and [ 18 F]FDG uptake in BAT as the non-corresponding nominal variables. Statistical significance is set at p value ≤ 0.05. The measured SUVmax values of [ 18 F]FDG uptake in each of the eight ROIs were used as a continuous variable. Shapiro-Wilk test was done to check for normality. When normality could not be determined, the median value was calculated followed by Mann-Whitney test to compare the two groups (receiving and not receiving β3-AR agonist treatment). RESULTS Patient Characteristics The selection and enrollment of the FDG PET scans of patients for analysis is summarized using a flow diagram in Fig. 1 . Initially, 55 [ 18 F]FDG PET scans that exhibited increased [ 18 F]FDG BAT uptake were identified. Six multiple scans were removed, with the first scan of the patient that exhibited increased [ 18 F]FDG BAT uptake was retained. Further scrutiny lead to exclusion of five scans as the identified [ 18 F]FDG uptake is not in the BAT of the regions of interest. The characteristics of the patients included in the analysis are summarized in Table 1 . A total of 44 elderly patients (aged ≥ 60 years old) with one scan each were included in the analysis, 13 (29.5%) of which are taking β3-AR agonists while 31 (70.5%) are not. Table 1 Characteristics of patients included in the analysis (n = 44) Age (in years) range 60–93 (73.2) Sex Female 35 (79.5%) Male 9 (20.5%) Height (cm) 156 (± 8.0) Weight (kg) 52.7 (± 9.7) BMI (kg/m 2 ) 21.7 (± 4.0) Diagnosis or Malignancy Lung carcinoma 15 (34.1%) Lymphoma 7 (15.9%) Breast carcinoma 3 (6.8%) Pancreatic carcinoma 2 (4.5%) Soft tissue tumor 2 (4.5%) Leukemia 1 (2.3%) Tongue carcinoma 1 (2.3%) Rectal carcinoma 1 (2.3%) Esophageal carcinoma 1 (2.3%) Merkel cell carcinoma 1 (2.3%) Cervical cancer 1 (2.3%) Renal cancer 1 (2.3%) Colon carcinoma 1 (2.3%) Ovarian carcinoma 1 (2.3%) Pleomorphic spindle cell sarcoma 1 (2.3%) Bladder carcinoma 1 (2.3%) Glioma 1 (2.3%) Pleomorphic adenoma 1 (2.3%) Anterior mediastinal mass 1 (2.3%) Pancreatic bile duct dilation 1 (2.3%) Confounding Factors Table 2 summarizes the mean, standard deviation, and p values for the confounding factors between the two elderly groups: age, BMI, ambient temperature, CBC (WBC, hemoglobin, and platelet) and renal function (creatinine and eGFR) parameters. Among the confounding factors analyzed, only the mean age was statistically significant ( p = 0.008) between two groups (78.2 for elderly receiving β3-AR agonists; 71.7 for those not receiving β3-AR agonists). Table 2 Mean, standard deviation, and p values among the confounding factors between the two groups (patients with & without β3-AR agonists) Patients with β3-AR agonists (n = 13) Patients without β3-AR agonists (n = 31) p Age (years) 78.2 (± 9.2) 71.1 (± 6.9) 0.008 Weight (kg) 54.4 (± 12.9) 52.1 (± 8.2) 0.475 BMI (kg/m 2 ) 22.7 (± 5.2) 21.3 (± 3.3) 0.312 Ambient temperature (ᵒC) 18.3 (± 7.4) 14.9 (± 8.6) 0.215 Blood glucose (mg/dL) 104.5 (± 16.4) 110.1 (± 19.4) 0.365 White Blood Cell (10 3 /µL) 6.2 (± 2.5) 6.0 (± 1.6) 0.866 Hemoglobin (g/dL) 12.8 (± 2.0) 12.2 (± 1.5) 0.283 Platelet (10 4 /mL) 22.8 (± 22.8) 23.7 (± 6.5) 0.690 Creatinine (mg/dL) 0.79 (± 0.19) 0.75 (± 0.19) 0.543 eGFR (mL/min/1.37m 2 ) 61.4 (± 13.2) 64.4 (± 15.4) 0.543 Assessment by Visual Analysis Table 3 summarizes the findings for the visual assessment of increased [ 18 F]FDG uptake among the eight regions of BAT. All of the elderly patients receiving β3-AR agonists revealed increased [ 18 F]FDG BAT uptake in the paravertebral region (n = 13; 100%). Compared to elderly patients not receiving β3-AR agonists, no significant association ( p = 0.302) was identified. Among the eight ROIs, only the cervical ( p = 0.045), para-abdominal aortic ( p = 0.012), and perirenal ( p = < 0.001) showed statistical difference. Table 3 Visual assessment of the presence or absence [ 18 F]FDG uptake in BAT between elderly patients ( ≥ 60 years old) with and without β3-AR agonists among the eight regions of interest (n = 44) Region of interest Patients with β3-AR agonists (n = 13) Patients without β3-AR agonists (n = 31) p Cervical 10 12 0.045 Periclavicular 3 5 0.676 Axillary 1 0 0.295 Mediastinal 6 7 0.155 Para-abdominal aortic 6 3 0.012 Paravertebral 13 27 0.302 Perirenal 8 1 < 0.001 Perisplenic 1 0 0.295 Assessment by SUVmax Determination Table 4 summarizes the mean SUVmax values for each region among the two elderly patient groups. Based on the SUVmax values measured in the eight ROIs, the paravertebral region recorded the highest mean SUVmax for both groups: 10.92 (± 5.65) for elderly patients receiving β3-AR agonists, and 8.69 (± 6.24) for those not receiving the treatment. Similar to the visual analysis, no significant association ( p = 0.310) was identified. Among the eight ROIs, only the axillary ( p = 0.048) and perirenal ( p = 0.027) regions showed significant differences. Table 4 Mean SUVmax values (and standard deviation) between the elderly patients ( ≥ 60 years old) with and without β3-AR agonists across the eight regions of interest (n = 38) Region of interest Mean SUVmax in patients with β3-AR agonists (n = 11) Mean SUVmax in patients without β3-AR agonists (n = 27) p Cervical 8.21 (± 8.04) 3.44 (± 4.24) 0.076 Periclavicular 2.12 (± 2.70) 1.94 (± 3.09) 0.612 Axillary 1.30 (± 1.46) 0.72 (± 0.25) 0.048 Mediastinal 6.03 (± 5.45) 3.26 (± 3.12) 0.095 Para-abdominal aortic 4.83 (± 4.23) 1.86 (± 1.20) 0.076 Paravertebral 10.92 (± 5.65) 8.69 (± 6.24) 0.310 Perirenal 6.02 (± 5.93) 1.59 (± 1.87) 0.027 Perisplenic 1.76 (± 1.82) 1.12 (± 0.41) 0.201 Overall Assessment With the p values determined in the eight regions from the two means of assessment, it has been identified that only the perirenal region was statistically significant for both. Table 5 shows the characteristics and presence or absence of [ 18 F]FDG uptake among the eight regions of interest in the 10 patients identified to have been taking β3-AR agonists during [ 18 F]FDG PET examination. All patients have results of visual assessment, while only eight (PET/CT only) have measured SUVmax values. Figures 2 and 3 are representative images for the increased [ 18 F]FDG BAT uptake in the PET scans reviewed and analyzed. Table 5 Characteristics and assessment among patients receiving β3-AR agonists (n = 13) # Sex Age BMI (kg/m 2 ) Ambient temp (ᵒC) Primary/Diagnosis Type of β3-AR agonists FDG uptake in BAT (Visual/SUVmax) Cervical Periclavicular Axillary Mediastinal Para-abdominal Aortic Paravertebral Perirenal Perisplenic 1 F 87 17.5 25.0 Breast Vibegron 50 mg ⬤ 3.16 0.55 0.93 1.78 1.52 ⬤ 7.15 1.85 1.05 2 F 63 15.1 18.1 Lung Mirabegron 50 mg ⬤ 18.1 ⬤ 9.75 ⬤ 5.59 ⬤ 12.49 ⬤ 7.3 ⬤ 12.27 ⬤ 4.00 1.29 3 M 83 23.9 9.5 Lymphoma Mirabegron 25 mg ⬤ 4.08 0.84 0.48 ⬤ 13.57 1.72 ⬤ 6.51 ⬤ 17.43 1.22 4 M 81 28.9 27.9 Soft tissue tumor (MFS) Vibegron 50 mg ⬤ 8.86 1.01 0.47 ⬤ 5.96 ⬤ 7.48 ⬤ 12.62 ⬤ 14.14 1.55 5 F 78 23.3 20.7 MCC Vibegron 50 mg 0.78 0.57 1.14 1.79 1.23 ⬤ 10.33 ⬤ 5.11 0.51 6 F 83 28.6 11.7 Lung Vibegron 50 mg 1.01 1.27 1.56 ⬤ 10.82 ⬤ 13.36 ⬤ 25.07 ⬤ 7.77 1.96 7 F 60 20.3 29.5 Lung Vibegron 50 mg ⬤ 19.77 0.93 0.65 1.85 1.78 ⬤ 10.53 0.70 1.16 8 M 83 15.4 3.0 Lung Vibegron 50 mg 0.70 1.07 0.62 1.38 1.50 ⬤ 3.89 0.92 0.97 9 F 73 31.0 8.9 Breast Vibegron 50mg ⬤ 22.17 ⬤ 3.59 1.01 1.14 1.42 ⬤ 11.27 0.62 0.82 10 M 93 25.2 20.0 Bladder Vibegron 50mg ⬤ 6.71 1.09 0.97 1.82 ⬤ 5.79 ⬤ 14.11 2.06 1.75 11 F 79 17.7 18.0 Pancreatic bile duct dilation Vibegron 50mg ⬤ 4.94 ⬤ 2.70 0.87 ⬤ 13.70 ⬤ 9.98 ⬤ 6.41 ⬤ 11.6 ⬤ 7.11 12 F 72 22.2 20.0 Glioma Vibegron 50mg ⬤ - - - ⬤ - ⬤ - ⬤ - ⬤ - - 13 F 81 25.6 6.1 Pancreatic Vibegron 50mg ⬤ - - - - - ⬤ - ⬤ - - Patients # 1–11 are PET/CT, # 12–13 are PET/MRI; MFS = myxofibrosarcoma; MCC: Merkel cell carcinoma; ⬤ - positive for increased FDG uptake via visual assessment DISCUSSION This study aims to identify the association of β3-AR agonists treatment and increased [ 18 F]FDG uptake in BAT among elderly patients (aged 60 years and above). In the retrospective review of 44 scans exhibiting increased [ 18 F]FDG BAT uptake through visual analysis and SUVmax determination, we have identified the significant statistical difference in certain anatomical regions between the two groups of elderly patients: with and without β3-AR agonist treatment. Visual analysis led to significant difference in the cervical, paraabdominal aortic, and perirenal regions between the two groups of elderly patients. Analysis of mean SUVmax values identified the axillary and perirenal regions to have statistical difference between the two elderly groups. To further strengthen the association, the two means of analysis were compared, with only the perirenal area that is consistently significant between the two groups. There is a high chance that the increased physiologic [ 18 F]FDG uptake in the perirenal BAT in an elderly patient receiving β3-AR agonist treatment is likely due to drug-induced hypermetabolism. This is consistent with reported cases involving elderly patients receiving β3-AR agonist for OAB and exhibiting increased [ 18 F]FDG BAT uptake in their PET scans [18,25]. However, literature remains limited about this effect of β3-AR agonist. Our study proves that there is a possible association between β3-AR agonist and increased [ 18 F]FDG BAT uptake. Readers of [ 18 F]FDG PET scans with such finding should exclude adrenal uptake, both benign (adenoma) or malignant (metastases), and other disease entities (e.g. pheochromocytoma) [26]. More so, correlation with attenuation-corrected CT images to differentiate BAT versus adrenal uptake should be done. Further studies, prospective and/or randomized control trial, focused in the perirenal BAT and effect of β3-AR agonist in its metabolism may provide more perspective and stronger association. Cypess et al (2015) have identified the presence of increased [ 18 F]FDG BAT uptake, via SUVmean measurements, in the cervical-supraclavicular-axillary, paravertebral, paraaortic, perihepatic, perirenal, and perisplenic regions in healthy and younger patients receiving is β3-AR agonist [27]. Amidst the difference in the characteristics of the sample, this coincides with our findings that patients receiving β3-AR agonist exhibit increased [ 18 F]FDG BAT uptake in the paravertebral region, albeit statistically insignificant. However, our study also identified low average SUVmax values in the axillary and perisplenic areas. One possible cause is the difference in the dose of β3-AR agonist administered, with them intentionally providing 200 mg versus to the standard 50 mg that is indicated for OAB [27]. The higher dose could have induced hypermetabolism of BAT in the eight studied regions, hence enhancing the increased [ 18 F]FDG BAT uptake. However, administering the 200 mg of β3-AR agonist could cause adverse effects that are detrimental to elderly patients [24]. On the other hand, the low uptake in the perihepatic and perisplenic areas are negligible and do not pose a problem for [ 18 F]FDG PET readers. Several other regions have been identified to have significant difference between the two groups of elderly, but only in one of the two means of analysis: cervical and paraabdominal aortic regions for visual assessment; and axillary region for SUVmax determination. The effect of β3-AR agonist cannot be entirely ruled-out, but other factors should be considered for the increased [ 18 F]FDG uptake by BAT. Several studies have identified how colder temperature, younger age, lower BMI, and blood glucose levels could affect [ 18 F]FDG uptake by BAT [4,5,9–14]. Increased [ 18 F]FDG BAT uptake is expected with lower temperature on the day of the scan, which we measured using the recorded ambient temperature. In our study, the mean ambient temperature is lower for elderly patients not receiving β3-AR agonist, but is insignificant ( p = 0.215) compared to the group receiving β3-AR agonist. Lower BMI is also recorded for elderly patients not receiving β3-AR agonist, but similarly insignificant ( p = 0.312). Cancer-cachexia has also been hypothesized to affect BAT activity [5]. Considering that [ 18 F]FDG PET is a vital imaging in oncology, all of the patients included in the analysis are diagnosed with malignancy and are expected to have at least one scan. The mean weight is lower in patients not receiving β3-AR agonist and, similar to the aforementioned factors, is insignificant ( p = 0.475) when compared with the other groups. Several studies have also reported increased [ 18 F]FDG BAT uptake lower blood glucose levels, similar to the patients receiving β3-AR agonist, but is also insignificant ( p = 0.365) [13,14]. We also included other parameters that have not yet been studied or linked with increased [ 18 F]FDG BAT uptake, like WBC, hemoglobin, platelet counts, creatinine, and eGFR. Similarly, no significant difference was identified among these factors. Nevertheless, we cannot disregard their possible effect. BAT is known to decrease markedly with age, with younger population easily stimulated by cold temperature [28]. Given that the patients in this study are limited only to those 60 years and above, there seems to be a wide age range (60 to 93 years old) and statistical difference between the two groups ( p = 0.008). This is quite expected with Japan’s recorded life expectancy at birth of 84.5, higher than the 77.4 in the Western Pacific Region and 71.4 in the world [29]. Even with the notion that BAT volume is inversely proportional to age, this is consistent with the findings of other studies that BAT remains present in adults [4–9]. Other factors that may contribute to the increased [ 18 F]FDG BAT uptake between the two groups are not covered in this study, like presence of absence of diabetes and status of cancer, among others [14,28]. The authors do recognize the limitations in this study. Only a total of 44 elderly patients with increased [ 18 F]FDG BAT uptake were included in the analysis. The low number of samples is likely due to quality control and standard measures implemented to minimize [ 18 F]FDG BAT uptake in PET scans. Much lower is the number of elderly patients that were receiving β3-AR agonist treatment (n = 13). The group also exhibits heterogeneity with the difference in the type of β3-AR agonist, either vibegron or mirabegron, and dose they are taking per day. Even with complete drug history, the adherence with the dose and regimen of β3-AR agonist could not be determined and should have been scrutinized. Furthermore, the retrospective review of [ 18 F]FDG PET images is based on the presence of BAT uptake. Though this is justified, it may not include all patients taking β3-AR agonists that underwent [ 18 F]FDG PET scan. To further analyze the association of β3-AR agonists and increased [ 18 F]FDG uptake in BAT, the authors recommend doing prospective studies with larger number of patients taking β3-AR agonists as sample. Furthermore, patients without malignancy receiving the said drug should also be included. A subgroup analysis could also be done between vibegron or mirabegron and their effect in [ 18 F]FDG BAT uptake. CONCLUSION Elderly patients (aged 60 years old and above) receiving β3-AR agonist treatment may exhibit increased [ 18 F]FDG BAT uptake, most especially in the perirenal area. In other regions where increased [ 18 F]FDG BAT uptake is observed, age could have an effect. A review of β3-AR agonist treatment regimens should be done prior to interpreting [ 18 F]FDG PET scans. Abbreviations [ 18 F]FDG [ 18 F]fluorodeoxyglucose BAT brown adipose tissue BMI body max index CBC complete blood count CT computed tomography HU Hounsfield unit MIP maximum intensity projection MRI magnetic resonance imaging OAB overactive bladder PET positron emission tomography ROI regions of interest SUVmax standardized uptake values maximum TOF OSEM-time-of-fight ordered-subsets expectation maximization UCP1 uncoupling protein 1 WBC whole blood cell β3 AR-β3-adrenergic receptor Declarations Ethics Approval: The study protocol was approved by the Ethics Committee of National Cancer Center Hospital (Research proposal number 2018-049). Consent for publication: Not applicable Availability of data and material: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests: The authors declare that they have no competing interests. Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contributions: JKVG: conceptualization, investigation, data curation, formal analysis, writing (original draft, review, and editing) KO: conceptualization, methodology, investigation KF: investigation MM: investigation KI: conceptualization, methodology, investigation, supervision, writing (editing) Acknowledgements: Not applicable References Cannon B, Nedergaard J. Brown Adipose Tissue: Function and Physiological Significance. Physiol Rev 2004;84:277–359. https://doi.org/10.1152/physrev.00015.2003. Sharma BK, Patil M, Satyanarayana A. Negative Regulators of Brown Adipose Tissue (BAT)-Mediated Thermogenesis. J Cell Physiol 2014;229:1901–7. https://doi.org/10.1002/jcp.24664. Inokuma K, Okamatsu-Ogura Y, Omachi A, Matsushita Y, Kimura K, Yamashita H, et al. 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Hao R, Yuan L, Zhang N, Li C, Yang J. Brown adipose tissue: distribution and influencing factors on FDG PET/CT scan. Journal of Pediatric Endocrinology and Metabolism 2012;25. https://doi.org/10.1515/jpem-2012-0029. 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. https://doi.org/10.1007/s11307-010-0431-9. Steinberg JD, Vogel W, Vegt E. Factors influencing brown fat activation in FDG PET/CT: a retrospective analysis of 15,000 + cases. Br J Radiol 2017;90. https://doi.org/10.1259/bjr.20170093. 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-FDG-Detected BAT in Humans. J Clin Endocrinol Metab 2011;96:192–9. https://doi.org/10.1210/jc.2010-0989. Wu C, Cheng W, Xing H, Dang Y, Li F, Zhu Z. Brown Adipose Tissue Can Be Activated or Inhibited within an Hour before 18 F-FDG Injection: A Preliminary Study with MicroPET. Biomed Res Int 2011;2011. https://doi.org/10.1155/2011/159834. Baba S, Tatsumi M, Ishimori T, Lilien DL, Engles JM, Wahl RL. Effect of Nicotine and Ephedrine on the Accumulation of 18F-FDG in Brown Adipose Tissue. Journal of Nuclear Medicine 2007;48:981–6. https://doi.org/10.2967/jnumed.106.039065. Brahmbhatt P, Ataei F, Parent EE, Sharma A. Atypically Intense Pharmacologically Induced Brown Fat Activation on FDG PET/CT. Clin Nucl Med 2023;48:233–6. https://doi.org/10.1097/RLU.0000000000004520. Okuyama C, Kikuchi R, Ikeuchi T. FDG Uptake in Brown Adipose Tissue Activated by a β3-Adrenergic Receptor Agonist Prescribed for Overactive Bladder. Clin Nucl Med 2020;45:628–31. https://doi.org/10.1097/RLU.0000000000003078. Warren K, Burden H, Abrams P. Mirabegron in overactive bladder patients: efficacy review and update on drug safety. Ther Adv Drug Saf 2016;7:204–16. https://doi.org/10.1177/2042098616659412. Yamaga LYI, Thom AF, Wagner J, Baroni RH, Hidal JT, Funari MG. The effect of catecholamines on the glucose uptake in brown adipose tissue demonstrated by 18F-FDG PET/CT in a patient with adrenal pheochromocytoma. Eur J Nucl Med Mol Imaging 2008;35:446–7. https://doi.org/10.1007/s00259-007-0538-7. Kuji I, Imabayashi E, Minagawa A, Matsuda H, Miyauchi T. Brown adipose tissue demonstrating intense FDG uptake in a patient with mediastinal pheochromocytoma. Ann Nucl Med 2008;22:231–5. https://doi.org/10.1007/s12149-007-0096-x. Japan Meteorological Agency 2025. https://www.jma.go.jp/jma/indexe.html (accessed March 17, 2025). Boellaard R, Delgado-Bolton R, Oyen WJG, Giammarile F, Tatsch K, Eschner W, et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging 2015;42:328–54. https://doi.org/10.1007/s00259-014-2961-x. Vosselman MJ, van der Lans AAJJ, Brans B, Wierts R, van Baak MA, Schrauwen P, et al. Systemic β-Adrenergic Stimulation of Thermogenesis Is Not Accompanied by Brown Adipose Tissue Activity in Humans. Diabetes 2012;61:3106–13. https://doi.org/10.2337/db12-0288. Yamamoto Y, Kojima D, Kurihara H. Pitfalls in FDG-PET/CT: Unique brown fat activation due to a β3-adrenergic receptor agonist in a patient with treated uterine cervical cancer. Journal of Clinical Images and Medical Case Reports 2024;5. https://doi.org/10.52768/2766-7820/2805. Park J, Byun BH, Jung CW, Moon H, Chang KJ, Lim I, et al. Perirenal 18F-FDG Uptake in a Patient with a Pheochromocytoma. Nucl Med Mol Imaging 2014;48:233–6. https://doi.org/10.1007/s13139-014-0276-2. Cypess AM, Weiner LS, Roberts-Toler C, Elía EF, Kessler SH, Kahn PA, et al. Activation of Human Brown Adipose Tissue by a β3-Adrenergic Receptor Agonist. Cell Metab 2015;21:33–8. https://doi.org/10.1016/j.cmet.2014.12.009. Yoneshiro T, Ogawa T, Okamoto N, Matsushita M, Aita S, Kameya T, et al. Impact of UCP1 and β3AR gene polymorphisms on age-related changes in brown adipose tissue and adiposity in humans. Int J Obes 2013;37:993–8. https://doi.org/10.1038/ijo.2012.161. World Health Organization. Health at a glance: Japan. 2024. Cite Share Download PDF Status: Published Journal Publication published 04 Aug, 2025 Read the published version in EJNMMI Research → Version 1 posted Editorial decision: Major Revision 24 May, 2025 Reviewers agreed at journal 09 May, 2025 Reviewers invited by journal 09 May, 2025 Editor assigned by journal 08 May, 2025 First submitted to journal 07 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6603701\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":454415318,\"identity\":\"b355845e-4541-49fa-b681-18ad03cc72dc\",\"order_by\":0,\"name\":\"John Kenneth V. Gacula\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0001-5414-741X\",\"institution\":\"Philippine General Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"John\",\"middleName\":\"Kenneth V.\",\"lastName\":\"Gacula\",\"suffix\":\"\"},{\"id\":454415319,\"identity\":\"b9691acd-6817-48eb-a214-0ec9eac85a58\",\"order_by\":1,\"name\":\"Kenichiro Ogane\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Cancer Center Hospital: Kokuritsu Gan Kenkyu Center Chuo Byoin\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kenichiro\",\"middleName\":\"\",\"lastName\":\"Ogane\",\"suffix\":\"\"},{\"id\":454415320,\"identity\":\"c859578f-843d-4d80-b77c-be22207f28e3\",\"order_by\":2,\"name\":\"Kaori Fuse\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Cancer Center Hospital: Kokuritsu Gan Kenkyu Center Chuo Byoin\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kaori\",\"middleName\":\"\",\"lastName\":\"Fuse\",\"suffix\":\"\"},{\"id\":454415321,\"identity\":\"51c217ca-5ba1-48f5-b409-5a8b8940c360\",\"order_by\":3,\"name\":\"Miyako Morooka Chikanishi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Cancer Center Hospital: Kokuritsu Gan Kenkyu Center Chuo Byoin\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Miyako\",\"middleName\":\"Morooka\",\"lastName\":\"Chikanishi\",\"suffix\":\"\"},{\"id\":454415322,\"identity\":\"88812410-cee8-4697-a6fc-fda9f1bbafef\",\"order_by\":4,\"name\":\"Kimiteru Ito\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACCWYGhgMMDDYwPhuRWg4wpJGiBUQcYDhMgsMk27kTD3+oOJ/H336A+cUHBr48glqkmXk3HDhw5naxxJkENssZDGzFBLXIgbQcbLuduEGCgc2Yh4EtsYFILedI0CIN0XIApIX5MVFaJJuBWs6cSU6ccSaxjXGGARF+kTh/dvOHigq7xP72w4c/fKg4RjjEkABjmwSDwbEEUrQwMH9gYKghTcsoGAWjYBSMCAAAagI9f1Z3MKoAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0003-0905-6767\",\"institution\":\"National Cancer Center Hospital: Kokuritsu Gan Kenkyu Center Chuo Byoin\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Kimiteru\",\"middleName\":\"\",\"lastName\":\"Ito\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-05-06 13:47:16\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6603701/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6603701/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s13550-025-01286-8\",\"type\":\"published\",\"date\":\"2025-08-04T15:57:00+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":82795193,\"identity\":\"e27edce6-56a5-4b51-8ce4-c7713d0f9301\",\"added_by\":\"auto\",\"created_at\":\"2025-05-15 10:33:46\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":44469,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFlow diagram for the selection of elderly patients with [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans showing increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6603701/v1/1ae94630b6fd0cb07fb6970e.png\"},{\"id\":82795202,\"identity\":\"59751588-487f-43f4-b14f-fac04d17ff8c\",\"added_by\":\"auto\",\"created_at\":\"2025-05-15 10:33:46\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":604190,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e[\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the PET images 63-year-old female diagnosed with lung carcinoma and taking β3-AR agonist (mirabegron) at the time of examination (Case #2). (a) Maximum intensity projection image showing [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in the cervical, periclavicular, axillary, mediastinal, para-abdominal aortic, paravertebral, and perirenal regions. (b) Axial PET/CT fusion and (c) CT images showing [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the axillary region (yellow arrows). The uptake in the paraclavicular area (light blue arrows) correlates with hypermetabolic lymphadenopathy on CT, emphasizing the importance of reviewing the CT images to ensure differentiation with BAT. (d) Axial PET/CT fusion and (e) CT images exhibiting [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the para-abdominal aorta region (pink arrows). (f) Axial PET/CT fusion and (g) CT images revealing [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the perirenal region (orange arrows).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6603701/v1/603f83dcf155983aaf380bf2.png\"},{\"id\":82797119,\"identity\":\"aaaea993-e796-4bd7-a74f-f73e17de2ba9\",\"added_by\":\"auto\",\"created_at\":\"2025-05-15 10:41:46\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":878516,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e[\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the PET images 81-year-old male diagnosed with myxofibrosarcoma and taking β3-AR agonist (vibegron) at the time of examination (Case #4). (a) Maximum intensity projection image showing [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in the cervical, mediastinal, para-abdominal aortic, paravertebral, and perirenal regions. (b) Axial PET/CT fusion and (c) CT images showing [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the mediastinal region (red arrows). (d) Axial PET/CT fusion and (e) CT images exhibiting [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the paravertebral region. (f) Axial PET/CT fusion and (g) CT images revealing [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the bilateral perirenal regions (light blue arrows).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6603701/v1/5fe1ac44df528e246fd9e283.png\"},{\"id\":88814067,\"identity\":\"9a364403-30f0-4787-8d1b-d0613b70e7b1\",\"added_by\":\"auto\",\"created_at\":\"2025-08-11 16:05:31\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2743454,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6603701/v1/d590bd58-56e1-4028-8baa-e43643cf1ede.pdf\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Effect of β3-Adrenergic Receptor Agonists on [18F]FDG Uptake in Brown Adipose Tissues in the PET images of Elderly Patients\",\"fulltext\":[{\"header\":\"INTRODUCTION\",\"content\":\"\\u003cp\\u003eBrown fat adipose tissues (BAT) or brown fat are highly vascularized, mitochondria-rich tissues found throughout the body, mainly in the supraclavicular, intrascapular, mediastinal, axillary, paravertebral, supra- and peri-renal regions [1]. Their expression of heat-producing protein uncoupling protein 1 (UCP 1) that breaks down fat to produce heat makes them vital in thermogenesis [2]. They are regulated by norepinephrine signaling through the presence of β3-receptors [1]. They also demonstrate increased glucose utilization when activated, leading to physiologically increased [\\u003csup\\u003e18\\u003c/sup\\u003eF ]fluorodeoxyglucose ([\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG) uptake on [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG positron emission tomography (PET) imaging [3,4]. The long-standing notion that BAT tissues are only abundant in newborns and children and decreases through aging has been questioned by the presence of increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake on the [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET images of adults [4\\u0026ndash;9].\\u003c/p\\u003e \\u003cp\\u003eThe presence of increased physiologic uptake of [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG in BAT among [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans is not uncommon in nuclear medicine. Several factors have been studied and are associated with it, namely: cold ambient temperature, age (younger than older people), sex (prevalent in females), lower weight and body mass index, and lower plasma glucose levels, among others [4,5,9\\u0026ndash;14]. Even substances that have direct and indirect effects on β-adrenergic receptor like caffeine, nicotine, and ephedrine are linked to BAT activation, leading to hypermetabolism and, consequently, increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake [15,16]. Recent studies have reported increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT is observed among elderly patients receiving β3-adrenergic receptor (β3-AR) agonists treatment [17,18]. β3-AR agonists are used for treating overactive bladder (OAB) due to the presence of β3-AR in the detrusor muscle and urothelium, leading to detrusor relaxation and reducing bladder tone. Mirabegron is the first approved drug under the said class, with a 50 mg starting dose prescribed in Japan [19].\\u003c/p\\u003e \\u003cp\\u003eWith the widespread utilization of β3-AR agonists among elderly patients with OAB, little is known about the possibility of β3-AR agonists-induced [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT. Nuclear medicine physicians and radiologists should be aware of this and be cautious in interpreting [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans. Hence, this study aims to identify the association of β3-AR agonists treatment with increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT among elderly patients (aged 60 years and above). Furthermore, we aim to identify the prevalence and characterize its occurrence through eight anatomical regions of interest in elderly patients receiving β3-AR agonists treatment, and the possible confounding factors that may affect increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in elderly patients with and without β3-AR agonists treatment.\\u003c/p\\u003e\"},{\"header\":\"MATERIALS AND METHODS\",\"content\":\"\\u003cp\\u003eHybrid images using [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET, including computed tomography (CT) and magnetic resonance imaging (MRI), done in the National Cancer Center Hospital (NCC) in Japan from January 2011 to April 2025 were retrospectively reviewed. Inclusion criteria include elderly patients aged 60 years and above with [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans showing increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT. This is to reduce the likelihood of false-negative findings [6]. Drug history and clinical records of the patients were then reviewed to determine if they were receiving β3-AR agonists, either vibegron (Beova\\u0026reg;) or mirabegron (Betanis\\u0026reg;), relative to the schedule of their [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET examination. Exclusion criteria include patients aged less than 60 years of age, with scans without identifiable increased physiologic [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake, with incomplete or missing drug history, those diagnosed with conditions related to excessive catecholamine release that may induce increased BAT [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake (e.g. pheochromocytoma) [20,21]. For patients with multiple [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans, only the examination wherein increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT was first observed was retained for analysis.\\u003c/p\\u003e \\u003cp\\u003eConfounding factors that may contribute to increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT were collected from the patient\\u0026rsquo;s records and documented for analysis, namely patient\\u0026rsquo;s sex, age, body mass index (BMI), blood glucose level, certain parameters of complete blood count (white blood cells [WBC], hemoglobin, and platelet), and renal function (creatinine and eGFR). Ambient temperature prior to the scan was also collected. For outpatient scans, the recorded outside ambient temperatures one hour before [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG injection were based from the database of Japan Meteorological Agency [22]. As for inpatient scans, the ambient temperature was set at 24.0\\u0026deg;C, which is the temperature of air-conditioned inpatient rooms in the hospital. Waiver of informed consent was provided by institution review board (research proposal number 2018-049).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePET Scanning Protocol\\u003c/h2\\u003e \\u003cp\\u003eIn accordance with the guidelines of European Association of Nuclear Medicine, the hospital follows standard patient preparations for [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET imaging. Patients are advised to fast for at least four hours prior to the scan to ensure that the patient\\u0026rsquo;s blood glucose is within normal or acceptable limits (set at below 200 mg/dL) to proceed with the examination [23]. Blood glucose levels were measured using a glucometer and recorded prior to injection of radiotracer.[23] The activity of the radiotracer was computed based on the patient\\u0026rsquo;s weight and height (3 to 4 MBq/kg) and administered intravenously, followed by an average 60 minutes rest prior to acquisition of images.\\u003c/p\\u003e \\u003cp\\u003eImage acquisition begins at the pelvic region towards the head. Both whole-body CT and the adaptive PET/CT images were reconstructed using time-of-fight ordered-subsets expectation maximization (TOF-OSEM). The voxel size for whole-body PET was 3.125 \\u0026times; 3.125 \\u0026times; 2.780 mm\\u003csup\\u003e3\\u003c/sup\\u003e (matrix size, 192 \\u0026times; 192). The whole-body PET/CT image acquisition was initiated at a 2-minute acquisition time per bed position. For attenuation correction of the PET data from the PET/CT scanner, the reconstruction software provided by the manufacturer uses attenuation maps generated based on the 3D CT images obtained for every bed position. The procedure for CT-based attenuation correction was implemented in the post-processing software of the scanner and operated automatically. As for [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET/MRI examination, whole body MRI was performed after 60 minutes, followed by the local MRI after 20 minutes (total of 80 minutes). Image acquisition of local PET is done at 3-minute per bed, while whole body is done at 2-minute per bed.\\u003c/p\\u003e \\u003cp\\u003eDuring the [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET examination, the room temperature was set at 24℃ to avoid cold stimulation. Further measures to ensure temperature control and thermal insulation were instituted, like provision of blankets when requested by the patient.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003ePET Analysis through Visual Assessment and SUVmax Measurements\\u003c/h3\\u003e\\n\\u003cp\\u003eThe [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET images were assessed by the radiologist and nuclear medicine specialist authors. Increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT were evaluated in the eight anatomic regions of interest (ROI), namely: cervical, periclavicular, axillary, mediastinal, paraabdominal aortic, paravertebral, perirenal, and perisplenic areas [6,24]. The [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in these regions were then compared with the maximum standard uptake value (SUVmax) in the subcutaneous fat at the lumbar region. To avoid false-positives due to [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake by malignant tumors, correlation with attenuated-corrected CT images were done to ensure that the area is within the fat concentration range (CT value of -100 to 0 Hounsfield unit [HU]). A patient is classified to have increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake when it is detected in any of the aforementioned regions. The detection involves two ways of determination: via visual and SUVmax measurement. Assessment of increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT through SUVmax determination was limited only in the PET/CT scans (n\\u0026thinsp;=\\u0026thinsp;38).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical Analysis\\u003c/h2\\u003e \\u003cp\\u003eAll the statistical analyses were performed using IBM SPSS Version 30 (IBM Corp., Armonk, NY, USA). Each of the eight ROIs were analyzed using Fisher's exact probability test after confirming that more than 20% of all cells had an expected frequency of less than five in the cross-tabulation table, considering a positive or negative history of treatment with β3-AR agonists and [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT as the non-corresponding nominal variables. Statistical significance is set at \\u003cem\\u003ep\\u003c/em\\u003e value\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026le;\\u003c/span\\u003e\\u0026thinsp;0.05.\\u003c/p\\u003e \\u003cp\\u003eThe measured SUVmax values of [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in each of the eight ROIs were used as a continuous variable. Shapiro-Wilk test was done to check for normality. When normality could not be determined, the median value was calculated followed by Mann-Whitney test to compare the two groups (receiving and not receiving β3-AR agonist treatment).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"RESULTS\",\"content\":\"\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePatient Characteristics\\u003c/h2\\u003e \\u003cp\\u003eThe selection and enrollment of the FDG PET scans of patients for analysis is summarized using a flow diagram in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Initially, 55 [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans that exhibited increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake were identified. Six multiple scans were removed, with the first scan of the patient that exhibited increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake was retained. Further scrutiny lead to exclusion of five scans as the identified [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake is not in the BAT of the regions of interest.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe characteristics of the patients included in the analysis are summarized in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. A total of 44 elderly patients (aged\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026ge;\\u003c/span\\u003e\\u0026thinsp;60 years old) with one scan each were included in the analysis, 13 (29.5%) of which are taking β3-AR agonists while 31 (70.5%) are not.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eCharacteristics of patients included in the analysis (n\\u0026thinsp;=\\u0026thinsp;44)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"2\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (in years) range\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e60\\u0026ndash;93 (73.2)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSex\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e35 (79.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9 (20.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHeight (cm)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e156 (\\u0026plusmn;\\u0026thinsp;8.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWeight (kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e52.7 (\\u0026plusmn;\\u0026thinsp;9.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBMI (kg/m\\u003csup\\u003e2\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e21.7 (\\u0026plusmn;\\u0026thinsp;4.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDiagnosis or Malignancy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLung carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15 (34.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLymphoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7 (15.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBreast carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3 (6.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePancreatic carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (4.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSoft tissue tumor\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (4.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLeukemia\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTongue carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRectal carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEsophageal carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMerkel cell carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCervical cancer\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRenal cancer\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eColon carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOvarian carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePleomorphic spindle cell sarcoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBladder carcinoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGlioma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePleomorphic adenoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAnterior mediastinal mass\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePancreatic bile duct dilation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (2.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eConfounding Factors\\u003c/h2\\u003e \\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e summarizes the mean, standard deviation, and \\u003cem\\u003ep\\u003c/em\\u003e values for the confounding factors between the two elderly groups: age, BMI, ambient temperature, CBC (WBC, hemoglobin, and platelet) and renal function (creatinine and eGFR) parameters. Among the confounding factors analyzed, only the mean age was statistically significant (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.008) between two groups (78.2 for elderly receiving β3-AR agonists; 71.7 for those not receiving β3-AR agonists).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eMean, standard deviation, and p values among the confounding factors between the two groups (patients with \\u0026amp; without β3-AR agonists)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePatients with β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;13)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePatients without β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;31)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (years)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e78.2 (\\u0026plusmn;\\u0026thinsp;9.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e71.1 (\\u0026plusmn;\\u0026thinsp;6.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.008\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWeight (kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e54.4 (\\u0026plusmn;\\u0026thinsp;12.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52.1 (\\u0026plusmn;\\u0026thinsp;8.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.475\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBMI (kg/m\\u003csup\\u003e2\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22.7 (\\u0026plusmn;\\u0026thinsp;5.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e21.3 (\\u0026plusmn;\\u0026thinsp;3.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.312\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAmbient temperature (ᵒC)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18.3 (\\u0026plusmn;\\u0026thinsp;7.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.9 (\\u0026plusmn;\\u0026thinsp;8.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.215\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBlood glucose (mg/dL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e104.5 (\\u0026plusmn;\\u0026thinsp;16.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e110.1 (\\u0026plusmn;\\u0026thinsp;19.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.365\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWhite Blood Cell (10\\u003csup\\u003e3\\u003c/sup\\u003e/\\u0026micro;L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.2 (\\u0026plusmn;\\u0026thinsp;2.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6.0 (\\u0026plusmn;\\u0026thinsp;1.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.866\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHemoglobin (g/dL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e12.8 (\\u0026plusmn;\\u0026thinsp;2.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12.2 (\\u0026plusmn;\\u0026thinsp;1.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.283\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePlatelet (10\\u003csup\\u003e4\\u003c/sup\\u003e/mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22.8 (\\u0026plusmn;\\u0026thinsp;22.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e23.7 (\\u0026plusmn;\\u0026thinsp;6.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.690\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCreatinine (mg/dL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.79 (\\u0026plusmn;\\u0026thinsp;0.19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.75 (\\u0026plusmn;\\u0026thinsp;0.19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.543\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eeGFR (mL/min/1.37m\\u003csup\\u003e2\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e61.4 (\\u0026plusmn;\\u0026thinsp;13.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e64.4 (\\u0026plusmn;\\u0026thinsp;15.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.543\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eAssessment by Visual Analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e summarizes the findings for the visual assessment of increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake among the eight regions of BAT. All of the elderly patients receiving β3-AR agonists revealed increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the paravertebral region (n\\u0026thinsp;=\\u0026thinsp;13; 100%). Compared to elderly patients not receiving β3-AR agonists, no significant association (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.302) was identified. Among the eight ROIs, only the cervical (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.045), para-abdominal aortic (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.012), and perirenal (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) showed statistical difference.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eVisual assessment of the presence or absence [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT between elderly patients (\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026ge;\\u003c/span\\u003e\\u0026thinsp;60 years old) with and without β3-AR agonists among the eight regions of interest (n\\u0026thinsp;=\\u0026thinsp;44)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRegion of interest\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePatients with β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;13)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePatients without β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;31)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCervical\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.045\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePericlavicular\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.676\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAxillary\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.295\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMediastinal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.155\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePara-abdominal aortic\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.012\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eParavertebral\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.302\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePerirenal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePerisplenic\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.295\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eAssessment by SUVmax Determination\\u003c/h3\\u003e\\n\\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e summarizes the mean SUVmax values for each region among the two elderly patient groups. Based on the SUVmax values measured in the eight ROIs, the paravertebral region recorded the highest mean SUVmax for both groups: 10.92 (\\u0026plusmn;\\u0026thinsp;5.65) for elderly patients receiving β3-AR agonists, and 8.69 (\\u0026plusmn;\\u0026thinsp;6.24) for those not receiving the treatment. Similar to the visual analysis, no significant association (\\u003cem\\u003ep\\u0026thinsp;=\\u003c/em\\u003e\\u0026thinsp;0.310) was identified. Among the eight ROIs, only the axillary (\\u003cem\\u003ep\\u0026thinsp;=\\u003c/em\\u003e\\u0026thinsp;0.048) and perirenal (\\u003cem\\u003ep\\u0026thinsp;=\\u003c/em\\u003e\\u0026thinsp;0.027) regions showed significant differences.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eMean SUVmax values (and standard deviation) between the elderly patients (\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026ge;\\u003c/span\\u003e\\u0026thinsp;60 years old) with and without β3-AR agonists across the eight regions of interest (n\\u0026thinsp;=\\u0026thinsp;38)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRegion of interest\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMean SUVmax in patients with β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;11)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMean SUVmax in patients without β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;27)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCervical\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8.21 (\\u0026plusmn;\\u0026thinsp;8.04)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.44 (\\u0026plusmn;\\u0026thinsp;4.24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.076\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePericlavicular\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.12 (\\u0026plusmn;\\u0026thinsp;2.70)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.94 (\\u0026plusmn;\\u0026thinsp;3.09)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.612\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAxillary\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.30 (\\u0026plusmn;\\u0026thinsp;1.46)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.72 (\\u0026plusmn;\\u0026thinsp;0.25)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.048\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMediastinal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.03 (\\u0026plusmn;\\u0026thinsp;5.45)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.26 (\\u0026plusmn;\\u0026thinsp;3.12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.095\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePara-abdominal aortic\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.83 (\\u0026plusmn;\\u0026thinsp;4.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.86 (\\u0026plusmn;\\u0026thinsp;1.20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.076\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eParavertebral\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10.92 (\\u0026plusmn;\\u0026thinsp;5.65)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8.69 (\\u0026plusmn;\\u0026thinsp;6.24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.310\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePerirenal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.02 (\\u0026plusmn;\\u0026thinsp;5.93)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.59 (\\u0026plusmn;\\u0026thinsp;1.87)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.027\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePerisplenic\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.76 (\\u0026plusmn;\\u0026thinsp;1.82)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.12 (\\u0026plusmn;\\u0026thinsp;0.41)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.201\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eOverall Assessment\\u003c/h2\\u003e \\u003cp\\u003eWith the \\u003cem\\u003ep\\u003c/em\\u003e values determined in the eight regions from the two means of assessment, it has been identified that only the perirenal region was statistically significant for both. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e shows the characteristics and presence or absence of [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake among the eight regions of interest in the 10 patients identified to have been taking β3-AR agonists during [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET examination. All patients have results of visual assessment, while only eight (PET/CT only) have measured SUVmax values. Figures\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e are representative images for the increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the PET scans reviewed and analyzed.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eCharacteristics and assessment among patients receiving β3-AR agonists (n\\u0026thinsp;=\\u0026thinsp;13)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"23\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c14\\\" colnum=\\\"14\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c15\\\" colnum=\\\"15\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c16\\\" colnum=\\\"16\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c17\\\" colnum=\\\"17\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c18\\\" colnum=\\\"18\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c19\\\" colnum=\\\"19\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c20\\\" colnum=\\\"20\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c21\\\" colnum=\\\"21\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c22\\\" colnum=\\\"22\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c23\\\" colnum=\\\"23\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e#\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eSex\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eAge\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eBMI (kg/m\\u003csup\\u003e2\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eAmbient temp (ᵒC)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003ePrimary/Diagnosis\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eType of β3-AR agonists\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"16\\\" nameend=\\\"c23\\\" namest=\\\"c8\\\"\\u003e \\u003cp\\u003eFDG uptake in BAT (Visual/SUVmax)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c9\\\" namest=\\\"c8\\\"\\u003e \\u003cp\\u003eCervical\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c11\\\" namest=\\\"c10\\\"\\u003e \\u003cp\\u003ePericlavicular\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c13\\\" namest=\\\"c12\\\"\\u003e \\u003cp\\u003eAxillary\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c15\\\" namest=\\\"c14\\\"\\u003e \\u003cp\\u003eMediastinal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c17\\\" namest=\\\"c16\\\"\\u003e \\u003cp\\u003ePara-abdominal Aortic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c19\\\" namest=\\\"c18\\\"\\u003e \\u003cp\\u003eParavertebral\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c21\\\" namest=\\\"c20\\\"\\u003e \\u003cp\\u003ePerirenal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c23\\\" namest=\\\"c22\\\"\\u003e \\u003cp\\u003ePerisplenic\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e87\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e25.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eBreast\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e3.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.93\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e1.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e1.52\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e7.15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e1.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.05\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e18.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLung\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eMirabegron\\u003c/p\\u003e \\u003cp\\u003e50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e18.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e9.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e5.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e12.49\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e7.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e12.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e4.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e23.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e9.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLymphoma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eMirabegron\\u003c/p\\u003e \\u003cp\\u003e25 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e4.08\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.84\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e13.57\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e1.72\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e6.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e17.43\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e81\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e28.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e27.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eSoft tissue tumor (MFS)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e8.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.47\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e5.96\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e7.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e12.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e14.14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e78\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e23.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e20.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eMCC\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.57\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1.14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e1.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e1.23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e10.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e5.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e0.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e28.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e11.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLung\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e1.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e10.82\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e13.36\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e25.07\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e7.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.96\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e60\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e20.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e29.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLung\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron\\u003c/p\\u003e \\u003cp\\u003e50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e19.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.93\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e1.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e1.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e10.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e0.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLung\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron\\u003c/p\\u003e \\u003cp\\u003e50 mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e1.07\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e1.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e1.50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e3.89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e0.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e31.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e8.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eBreast\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e22.17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e3.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e1.14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e1.42\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e11.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e0.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e0.82\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e93\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e25.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e20.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eBladder\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e6.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e1.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e1.82\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e5.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e14.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e2.06\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e1.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e18.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003ePancreatic bile duct dilation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e4.94\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e2.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.87\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e13.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e9.98\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e6.41\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e11.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e7.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e72\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e20.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eGlioma\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e81\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e25.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e6.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003ePancreatic\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eVibegron 50mg\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c15\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c16\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c17\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c18\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c19\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c20\\\"\\u003e \\u003cp\\u003e⬤\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c21\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c22\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c23\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"23\\\" nameend=\\\"c23\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003ePatients # 1\\u0026ndash;11 are PET/CT, # 12\\u0026ndash;13 are PET/MRI; MFS\\u0026thinsp;=\\u0026thinsp;myxofibrosarcoma; MCC: Merkel cell carcinoma; ⬤ - positive for increased FDG uptake via visual assessment\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"DISCUSSION\",\"content\":\"\\u003cp\\u003eThis study aims to identify the association of β3-AR agonists treatment and increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT among elderly patients (aged 60 years and above). In the retrospective review of 44 scans exhibiting increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake through visual analysis and SUVmax determination, we have identified the significant statistical difference in certain anatomical regions between the two groups of elderly patients: with and without β3-AR agonist treatment. Visual analysis led to significant difference in the cervical, paraabdominal aortic, and perirenal regions between the two groups of elderly patients. Analysis of mean SUVmax values identified the axillary and perirenal regions to have statistical difference between the two elderly groups. To further strengthen the association, the two means of analysis were compared, with only the perirenal area that is consistently significant between the two groups. There is a high chance that the increased physiologic [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in the perirenal BAT in an elderly patient receiving β3-AR agonist treatment is likely due to drug-induced hypermetabolism. This is consistent with reported cases involving elderly patients receiving β3-AR agonist for OAB and exhibiting increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in their PET scans [18,25]. However, literature remains limited about this effect of β3-AR agonist. Our study proves that there is a possible association between β3-AR agonist and increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake. Readers of [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans with such finding should exclude adrenal uptake, both benign (adenoma) or malignant (metastases), and other disease entities (e.g. pheochromocytoma) [26]. More so, correlation with attenuation-corrected CT images to differentiate BAT versus adrenal uptake should be done. Further studies, prospective and/or randomized control trial, focused in the perirenal BAT and effect of β3-AR agonist in its metabolism may provide more perspective and stronger association.\\u003c/p\\u003e \\u003cp\\u003eCypess et al (2015) have identified the presence of increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake, via SUVmean measurements, in the cervical-supraclavicular-axillary, paravertebral, paraaortic, perihepatic, perirenal, and perisplenic regions in healthy and younger patients receiving is β3-AR agonist [27]. Amidst the difference in the characteristics of the sample, this coincides with our findings that patients receiving β3-AR agonist exhibit increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in the paravertebral region, albeit statistically insignificant. However, our study also identified low average SUVmax values in the axillary and perisplenic areas. One possible cause is the difference in the dose of β3-AR agonist administered, with them intentionally providing 200 mg versus to the standard 50 mg that is indicated for OAB [27]. The higher dose could have induced hypermetabolism of BAT in the eight studied regions, hence enhancing the increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake. However, administering the 200 mg of β3-AR agonist could cause adverse effects that are detrimental to elderly patients [24]. On the other hand, the low uptake in the perihepatic and perisplenic areas are negligible and do not pose a problem for [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET readers. Several other regions have been identified to have significant difference between the two groups of elderly, but only in one of the two means of analysis: cervical and paraabdominal aortic regions for visual assessment; and axillary region for SUVmax determination. The effect of β3-AR agonist cannot be entirely ruled-out, but other factors should be considered for the increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake by BAT.\\u003c/p\\u003e \\u003cp\\u003eSeveral studies have identified how colder temperature, younger age, lower BMI, and blood glucose levels could affect [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake by BAT [4,5,9\\u0026ndash;14]. Increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake is expected with lower temperature on the day of the scan, which we measured using the recorded ambient temperature. In our study, the mean ambient temperature is lower for elderly patients not receiving β3-AR agonist, but is insignificant (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.215) compared to the group receiving β3-AR agonist. Lower BMI is also recorded for elderly patients not receiving β3-AR agonist, but similarly insignificant (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.312). Cancer-cachexia has also been hypothesized to affect BAT activity [5]. Considering that [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET is a vital imaging in oncology, all of the patients included in the analysis are diagnosed with malignancy and are expected to have at least one scan. The mean weight is lower in patients not receiving β3-AR agonist and, similar to the aforementioned factors, is insignificant (\\u003cem\\u003ep\\u0026thinsp;=\\u003c/em\\u003e\\u0026thinsp;0.475) when compared with the other groups. Several studies have also reported increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake lower blood glucose levels, similar to the patients receiving β3-AR agonist, but is also insignificant (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.365) [13,14]. We also included other parameters that have not yet been studied or linked with increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake, like WBC, hemoglobin, platelet counts, creatinine, and eGFR. Similarly, no significant difference was identified among these factors. Nevertheless, we cannot disregard their possible effect. BAT is known to decrease markedly with age, with younger population easily stimulated by cold temperature [28]. Given that the patients in this study are limited only to those 60 years and above, there seems to be a wide age range (60 to 93 years old) and statistical difference between the two groups (\\u003cem\\u003ep\\u0026thinsp;=\\u003c/em\\u003e\\u0026thinsp;0.008). This is quite expected with Japan\\u0026rsquo;s recorded life expectancy at birth of 84.5, higher than the 77.4 in the Western Pacific Region and 71.4 in the world [29]. Even with the notion that BAT volume is inversely proportional to age, this is consistent with the findings of other studies that BAT remains present in adults [4\\u0026ndash;9]. Other factors that may contribute to the increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake between the two groups are not covered in this study, like presence of absence of diabetes and status of cancer, among others [14,28].\\u003c/p\\u003e \\u003cp\\u003eThe authors do recognize the limitations in this study. Only a total of 44 elderly patients with increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake were included in the analysis. The low number of samples is likely due to quality control and standard measures implemented to minimize [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake in PET scans. Much lower is the number of elderly patients that were receiving β3-AR agonist treatment (n\\u0026thinsp;=\\u0026thinsp;13). The group also exhibits heterogeneity with the difference in the type of β3-AR agonist, either vibegron or mirabegron, and dose they are taking per day. Even with complete drug history, the adherence with the dose and regimen of β3-AR agonist could not be determined and should have been scrutinized. Furthermore, the retrospective review of [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET images is based on the presence of BAT uptake. Though this is justified, it may not include all patients taking β3-AR agonists that underwent [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scan. To further analyze the association of β3-AR agonists and increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG uptake in BAT, the authors recommend doing prospective studies with larger number of patients taking β3-AR agonists as sample. Furthermore, patients without malignancy receiving the said drug should also be included. A subgroup analysis could also be done between vibegron or mirabegron and their effect in [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake.\\u003c/p\\u003e\"},{\"header\":\"CONCLUSION\",\"content\":\"\\u003cp\\u003eElderly patients (aged 60 years old and above) receiving β3-AR agonist treatment may exhibit increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake, most especially in the perirenal area. In other regions where increased [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG BAT uptake is observed, age could have an effect. A review of β3-AR agonist treatment regimens should be done prior to interpreting [\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG PET scans.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e[\\u003csup\\u003e18\\u003c/sup\\u003eF]FDG\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e[\\u003csup\\u003e18\\u003c/sup\\u003eF]fluorodeoxyglucose\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBAT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ebrown adipose tissue\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBMI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ebody max index\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCBC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ecomplete blood count\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ecomputed tomography\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHU\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHounsfield unit\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eMIP\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003emaximum intensity projection\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eMRI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003emagnetic resonance imaging\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eOAB\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eoveractive bladder\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003ePET\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003epositron emission tomography\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eROI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eregions of interest\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eSUVmax\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003estandardized uptake values maximum\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eTOF\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eOSEM-time-of-fight ordered-subsets expectation maximization\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eUCP1\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003euncoupling protein 1\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eWBC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ewhole blood cell\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eβ3\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAR-β3-adrenergic receptor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eEthics Approval: The study protocol was approved by the Ethics Committee of National Cancer Center Hospital (Research proposal number 2018-049).\\u003c/p\\u003e\\n\\u003cp\\u003eConsent for publication: Not applicable\\u003c/p\\u003e\\n\\u003cp\\u003eAvailability of data and material: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting Interests: The authors declare that they have no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003eFunding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003eAuthor Contributions:\\u003c/p\\u003e\\n\\u003cp\\u003eJKVG: conceptualization, investigation, data curation, formal analysis, writing (original draft, review, and editing)\\u003c/p\\u003e\\n\\u003cp\\u003eKO: conceptualization, methodology, investigation\\u003c/p\\u003e\\n\\u003cp\\u003eKF: investigation\\u003c/p\\u003e\\n\\u003cp\\u003eMM: investigation\\u003c/p\\u003e\\n\\u003cp\\u003eKI: conceptualization, methodology, investigation, supervision, writing (editing)\\u003c/p\\u003e\\n\\u003cp\\u003eAcknowledgements: Not applicable\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eCannon B, Nedergaard J. 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Patterns of brown fat uptake of 18F-fluorodeoxyglucose in positron emission tomography/computed tomography scan. Indian Journal of Nuclear Medicine 2015;30:320. https://doi.org/10.4103/0972-3919.164147.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee P, Greenfield JR, Ho KKY, Fulham MJ. A critical appraisal of the prevalence and metabolic significance of brown adipose tissue in adult humans. American Journal of Physiology-Endocrinology and Metabolism 2010;299:E601\\u0026ndash;6. https://doi.org/10.1152/ajpendo.00298.2010.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCypess AM, Lehman S, Williams G, Tal I, Rodman D, Goldfine AB, et al. Identification and Importance of Brown Adipose Tissue in Adult Humans. New England Journal of Medicine 2009;360:1509\\u0026ndash;17. https://doi.org/10.1056/NEJMoa0810780.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVirtanen KA, Lidell ME, Orava J, Heglind M, Westergren R, Niemi T, et al. Functional Brown Adipose Tissue in Healthy Adults. New England Journal of Medicine 2009;360:1518\\u0026ndash;25. https://doi.org/10.1056/NEJMoa0808949.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNedergaard J, Bengtsson T, Cannon B. Unexpected evidence for active brown adipose tissue in adult humans. American Journal of Physiology-Endocrinology and Metabolism 2007;293:E444\\u0026ndash;52. https://doi.org/10.1152/ajpendo.00691.2006.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShao X, Shao X, Wang X, Wang Y. Characterization of brown adipose tissue 18 F-FDG uptake in PET/CT imaging and its influencing factors in the Chinese population. 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Determinants of Physiologic 18F-FDG Uptake in Brown Adipose Tissue in Sequential PET/CT Examinations. Mol Imaging Biol 2011;13:1029\\u0026ndash;35. https://doi.org/10.1007/s11307-010-0431-9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSteinberg JD, Vogel W, Vegt E. Factors influencing brown fat activation in FDG PET/CT: a retrospective analysis of 15,000\\u0026thinsp;+\\u0026thinsp;cases. Br J Radiol 2017;90. https://doi.org/10.1259/bjr.20170093.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOuellet 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-FDG-Detected BAT in Humans. 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Nucl Med Mol Imaging 2014;48:233\\u0026ndash;6. https://doi.org/10.1007/s13139-014-0276-2.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCypess AM, Weiner LS, Roberts-Toler C, El\\u0026iacute;a EF, Kessler SH, Kahn PA, et al. Activation of Human Brown Adipose Tissue by a β3-Adrenergic Receptor Agonist. Cell Metab 2015;21:33\\u0026ndash;8. https://doi.org/10.1016/j.cmet.2014.12.009.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYoneshiro T, Ogawa T, Okamoto N, Matsushita M, Aita S, Kameya T, et al. Impact of UCP1 and β3AR gene polymorphisms on age-related changes in brown adipose tissue and adiposity in humans. Int J Obes 2013;37:993\\u0026ndash;8. https://doi.org/10.1038/ijo.2012.161.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWorld Health Organization. Health at a glance: Japan. 2024.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":true,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"ejnmmi-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ejre\",\"sideBox\":\"Learn more about [EJNMMI Research](http://ejnmmires.springeropen.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/ejre/default.aspx\",\"title\":\"EJNMMI Research\",\"twitterHandle\":\"@officialEANM\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"[18F]FDG PET, brown adipose tissue, overactive bladder, vibegron, mirabegron, elderly\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6603701/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6603701/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eBrown adipose tissues (BAT) are highly vascularized and mitochondria-rich tissues that are related to thermogenesis. Physiologic [18F]fluorodeoxyglucose ([18F]FDG) uptake in BAT may be caused by several factors, including certain drugs that utilizes β-adrenergic receptors. Recently, increased [18F]FDG BAT uptake among elderly patients (aged 60 years old and above) receiving β3-adrenergic receptor agonists have been reported. With the increasing use of β3-adrenergic receptor agonists for overactive bladder, little is known about the medication and increased [18F]FDG BAT uptake. This study investigates the association of β3-adrenergic receptor agonists treatment with increased [18F]FDG uptake in BAT among elderly patients through a retrospective review of their [18F]FDG positron emission tomography (PET) scans that exhibit increased [18F]FDG BAT uptake. Assessment of [18F]FDG BAT uptake was performed via visual inspection and SUVmax measurement in eight selected regions of interest, namely: cervical, periclavicular, axillary, mediastinal, paravertebral, para-abdominal aortic, perirenal, and perisplenic regions. Drug history and clinical records of the patients were reviewed to determine history of β3-adrenergic receptor agonists use relative to their [18F]FDG PET study.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eForty-four elderly patients with one [18F]FDG PET scan each were analyzed. Among the eight regions of interest, the increased [18F]FDG BAT uptake in the perirenal region of elderly patients receiving β3-adrenergic receptor agonists, compared to those not receiving, was statistically significant in both visual (p\\u0026thinsp;=\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) and SUVmax (p\\u0026thinsp;=\\u0026thinsp;0.027) analysis. All patients receiving β3-adrenergic receptor agonists exhibited increased [18F]FDG BAT uptake in the paravertebral region.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e \\u003cp\\u003eElderly patients aged 60 years old and above receiving β3-adrenergic receptor agonist treatment may exhibit increased [18F]FDG BAT uptake, most especially in the perirenal area.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Effect of β3-Adrenergic Receptor Agonists on [18F]FDG Uptake in Brown Adipose Tissues in the PET images of Elderly Patients\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-05-15 10:33:41\",\"doi\":\"10.21203/rs.3.rs-6603701/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Major Revision\",\"date\":\"2025-05-24T11:43:42+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"\",\"date\":\"2025-05-09T23:17:44+00:00\",\"index\":0,\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-05-09T15:23:24+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-05-09T03:35:42+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"EJNMMI Research\",\"date\":\"2025-05-08T00:33:27+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"ejnmmi-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ejre\",\"sideBox\":\"Learn more about [EJNMMI Research](http://ejnmmires.springeropen.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/ejre/default.aspx\",\"title\":\"EJNMMI Research\",\"twitterHandle\":\"@officialEANM\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"74056c62-7978-4b98-be61-4251ec267a0c\",\"owner\":[],\"postedDate\":\"May 15th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-08-11T15:59:08+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6603701\",\"link\":\"https://doi.org/10.1186/s13550-025-01286-8\",\"journal\":{\"identity\":\"ejnmmi-research\",\"isVorOnly\":false,\"title\":\"EJNMMI Research\"},\"publishedOn\":\"2025-08-04 15:57:00\",\"publishedOnDateReadable\":\"August 4th, 2025\"},\"versionCreatedAt\":\"2025-05-15 10:33:41\",\"video\":\"\",\"vorDoi\":\"10.1186/s13550-025-01286-8\",\"vorDoiUrl\":\"https://doi.org/10.1186/s13550-025-01286-8\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6603701\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6603701\",\"identity\":\"rs-6603701\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}