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Deep learning networks have recently demonstrated yielded impressive progress for multi-exposure image fusion. However, how to restore realistic texture details while correcting color distortion is still a challenging problem to be solved. To alleviate the aforementioned issues, in this paper, we propose an attention-guided global-local adversarial learning network for fusing extreme exposure images in a coarse-to-fine manner. Firstly, the coarse fusion result is generated under the guidance of attention weight maps, which acquires the essential region of interest from both sides. Secondly, we formulate an edge loss function, along with a spatial feature transform layer, for refining the fusion process. So that it can take full use of the edge information to deal with blurry edges. Moreover, by incorporating global-local learning, our method can balance pixel intensity distribution and correct the color distortion on spatially varying source images from both image/patch perspectives. Such a global-local discriminator ensures all the local patches of the fused images align with realistic normal-exposure ones. Extensive experimental results on two publicly available datasets show that our method drastically outperforms state-of-the-art methods in visual inspection and objective analysis. Furthermore, sufficient ablation experiments prove that our method has significant advantages in generating high-quality fused results with appealing details, clear targets, and faithful color. Source code will be available at https://github.com/JinyuanLiu-CV/AGAL. [ABSTRACT FROM AUTHOR]

A novel method has been established for the construction of C–S bonds using redox-active esters with disulfides in the presence of Ru-photoredox catalyst. This method exhibits remarkable functional group tolerance across a wide scope of substrates. Under mild conditions, a structurally diverse array of aryl alkyl sulfides is successfully and efficiently obtained through decarboxylative cross-coupling. [ABSTRACT FROM AUTHOR]

Aim. To develop predictive equations of lean body mass (LBM) suitable for healthy southern Chinese adults with a large sample. LBM measured by dual-energy X-ray absorptiometry (DXA) are considered as the standard ones. Methods. Retrospective analysis was conducted on the consecutive people who did total body measurement with DXA from July 2005 to October 2015. People with diseases that might affect LBM were excluded and overall 12,194 subjects were included in this study. Information about the 10,683 subjects (2,987 males and 7,696 females) from July 2005 to November 2014 was used to establish equations. These subjects were grouped by sex and then subdivided according to their body mass index (BMI). The female group was divided into another two subgroups: the premenopausal and postmenopausal subgroups. Equations were developed through stepwise multilinear regression analysis of height, weight, age, and BMI. Information about the 1,511 subjects (395 males and 1116 females) from December 2014 to October 2015 was used to verify the established equations. Results. BMI, height, weight, and age were introduced into the equations as independent variables in the male group, while age was proved to have no influence on LBM in the female group. Regrouping according to BMI or menopause did not increase the predictive ability of equations. Good agreement between LBM evaluated by equation (LBM_PE) and LBM measured by DXA (LBM_DXA) was observed in both the male and female groups. Conclusion. Predictive equations of LBM suitable for healthy southern Chinese adults are established with a large sample. BMI was related to LBM content; however, there is no need for further group based on BMI or menopause while developing LBM questions. [ABSTRACT FROM AUTHOR]

Background: Brain metastases (BMs) are common complications in patients with non-small cell lung cancer (NSCLC). The purpose of this study was to investigate whether the metabolic parameters derived from preoperative 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) can predict BM development in patients with surgically resected NSCLC., Methods: We retrospectively reviewed 128 consecutive patients with stage I-IIIA NSCLC who underwent 18 F-FDG PET/CT before curative surgery at The First Affiliated Hospital of Jinan University between November 2012 and October 2021. By drawing a volume of interest (VOI), the maximum standardized uptake values (SUV max ), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor as well as the mean SUV (SUV mean ) of the liver and arterial blood were measured. The tumor-to-liver SUV ratio (TLR) and tumor-to-blood SUV ratio (TBR) were also calculated. Receiver operating characteristic curve analysis was used to determine the best cut-off values for positron emission tomography (PET) parameters to predict BM-free survival, and Cox proportional hazards regression analysis was used to assess the predictive value of clinical variables and PET parameters., Results: The median follow-up duration for survival patients was 23.4 months, and 15 patients (11.7%) experienced BM as the initial relapse site. The cumulative rates of BM over the course of 1, 2, and 5 years were 4.5%, 10.5%, and 17.5%, respectively. The optimal cut-off values for the prediction of BM-free survival were 7.7, 4.9, and 4.5 for SUV max , TLR, and TBR, and 5.5 mL and 16.1 for MTV and TLG, respectively. In the Cox proportional hazards model, the risk of BM was significantly associated with TLR [hazard ratio (HR) =10.712; 95% confidence interval (CI): 2.958-38.801; P<0.001] and MTV (HR =3.150; 95% CI: 0.964-10.293; P=0.020) after adjusting for tumor stage, clinicopathological factors, and other PET parameters., Conclusions: Preoperative TLR and MTV of the primary tumor may be helpful in predicting BM development in patients with surgically resected NSCLC. Tumor metabolic parameters may potentially be used to stratify the risk of BM and determine individualized surveillance strategies., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-385/coif). The authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Background: The precision reflecting repeated measurement error of quantitative parameters of flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) for evaluating the therapeutic effect of solid tumor can help observe whether a real biologic change in glucose metabolism occurred, or if the change was caused by errors before and after the treatment., Methods: A total of 18 VX2 tumor-bearing male New Zealand rabbits confirmed by pathology were used, three of which were used for determining the best scanning time point after injection and 15 for a precision experiment by repeating PET/CT scans for three consecutive days. The PET volume computer-assisted reading (PET VCAR) software (GE Healthcare) was used to analyze the standardized uptake value (SUV) and total lesion glycolysis (TLG) parameters. The lean body mass (LBM) to calculate the SUV corrected for lean body mass (SUL) parameters was measured using dual energy X-ray absorptiometry (DXA). The precision was represented as the coefficient of variation of root mean square (RMS-CV) and standard deviation of root mean square (RMS-SD). The least significant change (LSC) was also calculated when considering precision., Results: The precision of SUV parameters, including SUV max , SUV mean and SUV peak ranged from 18.3% to 18.8%, which was similar to that of the SUL parameters (18.0-18.4%). Using 80% confidence interval (CI), the LSC of SUV max and SUL peak were 33.1% and 33.3%, respectively; using 95% CI, the LSC of SUV max and SUL peak were 50.1% and 51.0%, respectively., Conclusions: This research established the method of precision in a rabbit VX2 tumor model, which can be used for monitoring changes to assess the effects of drug treatment on solid tumors in experimental studies with 18 F-FDG PET/CT imaging., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-1079/coif). All authors report that this work was supported by the National Natural Science Foundation of China (No. 81871383), Medical Scientific Research Foundation of Guangdong Province (No. A2018135), Fundamental Research Funds for the Central Universities (No. 21617311) and Science and Technology Program of Guangzhou (No. 201804010440). The authors have no other conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Background: Osteoporosis in pre-dialysis chronic kidney disease (CKD) patients has been overlooked, and the risk factors of osteoporosis in these patients have not been adequately studied., Objective: To identify risk factors for osteoporosis in pre-dialysis CKD patients and develop predictive models to estimate the likelihood of osteoporosis., Methods: Dual-energy X-ray absorptiometry was used to measure bone mineral density, and clinical examination results were collected from 326 pre-dialysis CKD patients. Binary logistic regression was employed to explore the risk factors associated with osteoporosis and develop predictive models., Results: In this cohort, 53.4% ( n  = 174) were male, 46.6% ( n  = 152) were female, and 21.8% ( n  = 71) were diagnosed with osteoporosis. Among those diagnosed with osteoporosis, 67.6% ( n  = 48) were female and 32.4% ( n  = 23) were male. Older age and low 25-(OH)-Vitamin D levels were identified as risk factors for osteoporosis in males. For females, older age, being underweight, higher bone alkaline phosphatase (NBAP), and advanced CKD (G5) were significant risk factors, while higher iPTH was protective. Older age, being underweight, and higher NBAP were risk factors for osteoporosis in the G1-4 subgroup. In the G5 subgroup, older age and higher NBAP increased the risk, while high 25-(OH)-Vitamin D or iPTH had protective effects. Nomogram models were developed to assess osteoporosis risk in pre-dialysis patients based on gender and renal function stage., Conclusion: Risk factors for osteoporosis vary by gender and renal function stages. The nomogram clinical prediction models we constructed may aid in the rapid screening of patients at high risk of osteoporosis.

Objective: This study aimed to establish and validate the nomograms for predicting overall survival (OS) probabilities in differentiated thyroid cancer (DTC) patients who received and did not receive radioiodine therapy (RAI), respectively., Methods: In this study, 11, 099 patients diagnosed with DTC in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2016 were selected. Whether they have RAI, they are divided into RAI (n=6427) and non-RAI (n=4672) groups. They were randomly assigned to either a training cohort (RAI: n=4498, non-RAI: n=3263) or a validation cohort (RAI: n=1929, non-RAI: n=1399) using R software to divide the patients in a 7-to-3 ratio randomly. Variables were selected using a backward stepwise method in a Cox regression model to determine the independent prognostic factors, which were then utilized to build two nomograms to predict the 5-, 8-, and 10-year OS probabilities in DTC patients with or without RAI. The concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the performance of our models., Results: The multivariate analyses demonstrated that birth of the year, race, histological type, tumor size, grade, TNM stage, lymph node dissections, surgery, and chemotherapy were risk factors for OS. Compared to the AJCC stage, the C-index (RAI: training group: 0.911 vs. 0.810, validation group: 0.873 vs. 0.761; non-RAI: training group: 0.903 vs. 0.846, validation group: 0.892 vs. 0.808). The AUC values for the training cohort (RAI: 0.940, 0.933, and 0.942; non-RAI: 0.891, 0.884, and 0.852 for the 5-, 8-, and 10-year OS, respectively) and validation cohort (RAI: 0.855, 0.825, and 0.900, non-RAI: 0.867, 0.896, and 0.899), and the calibration plots of both two models all exhibited better performance. Additionally, the NRI and IDI further showed that they exhibited good 5-, 8-, and 10-year net benefits., Conclusion: We have established the prediction models of DTC patients with or without RAI respectively through various variables. The nomogram may be more targeted to guide clinical decisions in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ran, Gong, Shang, Wei and Xu.)

Objectives: Brain metastases (BMs) are a major cause leading to the failure of treatment management for non-small-cell lung cancer (NSCLC) patients. The purpose of this study was to evaluate the predictive value of baseline metabolic tumor burden on 18 F-FDG PET/CT measured with metabolic tumor volume (MTV) and total lesion glycolysis (TLG) for brain metastases (BMs) development in patients with locally advanced non-small-cell lung cancer (NSCLC) after treatment., Methods: Forty-seven patients with stage IIB-IIIC NSCLC who underwent baseline 18 F-FDG PET/CT examinations were retrospectively reviewed. The maximum standardized uptake value (SUV max ), MTV, and TLG of the primary tumor (SUV maxT , MTV T , and TLG T ), metastatic lymph nodes (SUV maxN , MTV N , and TLG N ), and whole-body tumors (SUV maxWB , MTV WB , and TLG WB ) were measured. The optimal cut-off values of PET parameters to predict brain metastasis-free survival were obtained using Receiver operating characteristic (ROC) analysis, and the predictive value of clinical variables and PET parameters were evaluated using Cox proportional hazards regression analysis., Results: The median follow-up duration was 25.0 months for surviving patients, and 13 patients (27.7%) developed BM. The optimal cut-off values were 21.1 mL and 150.0 g for MTV T and TLG T , 20.0, 10.9 mL and 55.6 g for SUV maxN , MTV N and TLG N , and 27.9, 27.4 mL and 161.0 g for SUV maxWB , MTV WB and TLG WB , respectively. In the Cox proportional hazards models, the risk of BM was significantly associated with MTV N and MTV WB or TLG N and TLG WB after adjusting for histological cell type, N stage, SUV maxN , and SUV maxWB ., Conclusions: Baseline metabolic tumor burden (MTV and TLG) evaluated from the level of metastatic lymph nodes and whole-body tumors are significant predictive factors for BM development in patients with locally advanced NSCLC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Shang, You, Dong, Li, Cheng, Tang, Guo, Gong, Ling and Xu.)

Objective: The purpose of this study was to examine bone turnover markers, estradiol, parathyroid hormone, and 25 hydroxyvitamin D, in cynomolgus monkeys at different ages to improve our understanding of the changes in bone turnover markers throughout the life cycle of cynomolgus monkeys and to provide a basis for the establishment of a non-human primate model of osteoporosis., Methods: Total Body Bone Mineral Density and Total Body Bone Mineral Content were measured using Dual-Energy X-Ray Absorptiometry in cynomolgus monkeys at different ages. Serum bone turnover marker' levels were measured using enzyme immunoassays at each age group, and the relationship between bone turnover markers and age was assessed by Spearman rank correlation analysis to investigate the relationship between bone turnover markers and age in female cynomolgus monkeys., Results: Total Body Bone Mineral Density in female cynomolgus monkeys peaked at 10 years of age and then formed a plateau that was maintained until old age. Procollagen I Aminoterminal Propeptide, Bone Alkaline Phosphatase, Osteocalcin, and C-Terminal Telopeptide Of Type I Collagen peaked at 1 to 3 years of age and gradually decreased with age, leveling off by 10 years of age. Estradiol, parathyroid hormone, and 25 hydroxyvitamin D, follicle-stimulating hormone, luteinizing hormone, were not significantly different among age groups., Conclusion: This paper provides data on trends in bone turnover markers throughout the life cycle of female cynomolgus monkeys, which are similar to human changes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Li, Cai, Dong, Hou, Li, Guo, Zeng, Cheng, Shang, Ling, Gong and Xu.)

Multiple myeloma (MM) is a neoplastic plasma cell proliferative disorder characterized by various osteolytic bone destruction as a radiological morphological marker. Functional imaging, particularly nuclear medicine imaging, is a promising method to visualize disease processes before the appearance of structural changes by targeting specific biomarkers related to metabolism ability, tumor microenvironment as well as neoplastic receptors. In addition, by targeting particular antigens with therapeutic antibodies, immuno-PET imaging can support the development of personalized theranostics. At present, various imaging agents have been prepared and evaluated in MM at preclinical and clinical levels. A summary overview of molecular functional imaging in MM is provided, and commonly used radiotracers are characterized., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Shang, Ye, Zhao, Xu, Zeng and Wang.)

Background: Dual-energy X-ray absorptiometry (DXA) is a well-accepted tool for monitoring skeletal and body composition changes in biomedical studies. The nonhuman primate model is suitable for studies exploring the pathogenesis of and novel treatments for osteoporosis. Our objectives are to determine the precision of DXA detection in cynomolgus monkeys and to identify the difference in precision in lumbar bone mineral density (BMD) with various segment selections., Methods: Thirty adult female cynomolgus monkeys underwent duplicate total body DXA scans. Total body bone mineral density (BMD TB ) and body composition, including bone mineral content (BMC TB ), lean mass (LM TB ), and fat mass (FM TB ), were analyzed by enCORE software, while lumbar BMD was obtained by manual region-of-interest analysis. The precision was represented as the root-mean-square standard deviation (RMS-SD) and coefficient of variation (RMS-CV%), and least significant changes (LSCs) were reported., Results: The RMS-SD (RMS-CV%) of the repeated DXA analyses for BMD TB , BMC TB , LM TB and FM TB were 0.002 g/cm 2 (0.50%), 0.90 g (0.42%), 0.015 kg (0.49%), and 0.031 kg (2.71%), respectively. The regional BMD precision (RMS-CV%) of the lumbar spine with various combinations ranged from 0.70% to 1.09%, The LSCs with 80% statistical confidence (LSC 80 ) ranged from 1.27% to 1.97%, and LSC 95 ranged from 1.94% to 3.01%., Conclusions: DXA provided excellent reproducibility in the measurements of BMD and body composition in nonhuman primates. We find DXA reliable for total and regional measurement in skeletal research and the evaluation of osteoporosis treatment with monkeys as animal models., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/qims-21-799). YL is the head of Research and Development Department in Guangdong Landau Biotechnology Co. Ltd. The other authors have no conflicts of interest to declare., (2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Objectives: This study was an attempt to investigate the variation trend of body composition with ageing and explore the association between regional body composition and bone mineral density (BMD)., Design: Cross-sectional study., Setting and Participants: A total of 5749 healthy adults aged 20-95 years was recruited from 2004 to 2017., Primary Outcome Measures: Whole-body lean mass (LM), fat mass (FM), android FM, gynoid FM, appendicular lean mass (ALM) and BMD in the lumbar spine, femoral neck and total hip were obtained by dual-energy X-ray absorptiometry (DXA). The android/gynoid fat mass ratio (A/G FMR) based on DXA scan was calculated as an indicator of adipose distribution. Pearson correlation and multiple linear regression analyses were used to determine the associations between body composition, adipose distribution, and BMD of each skeletal site., Results: Whole-body FM, percentage of whole-body FM, Android FM and A/G FMR consistently increased with age in both genders, especially in women, and ALM began to decrease in the fifth decade for both men and women. In multivariable linear regression models with age, body mass index, A/G FMR and ALM as predictor variables, ALM was associated with the most BMD variance of all skeletal sites in men (standard β ranged from 0.207 to 0.405, p<0.001), although not the largest but still a positive predictor of BMD in women (standard β ranged from 0.074 to 0.186, p<0.05). A/G FMR was an inverse predictor of BMD at all skeletal sites for women (standard β ranged from -249 to -0.052, p<0.01) but not in men., Conclusions: In this large cohort of Chinese adults, ALM had a strong positive association with BMD in both genders. A/G FMR as an indicator of central adipose accumulation was inversely associated with BMD in women but not in men., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Vascular endothelial growth factor receptors (VEGFRs) are well recognized as significant biomarkers of tumor angiogenesis. Herein, we have developed a first-of-its-kind peptide-based VEGFR positron emission tomography (PET) tracer. The novel [ 64 Cu]VEGF 125-136 peptide possessed satisfactory radio-characteristics and showed good specificity for the visualization of VEGFR in various mouse models, in which the tumor-specific radioactivity uptake was highly correlated to the VEGFR expression level. Moreover, the tracer showed high tumor uptake (ca. 5.89 %ID/g at 20 min postinjection in B16F10 mice) and excellent pharmacokinetics, achieving the maximum imaging quality within 1 h after injection. These features convey [ 64 Cu]VEGF 125-136 as a promising, clinically translatable PET tracer for the imaging of tumor angiogenesis., Competing Interests: The authors declare no competing financial interest., (Copyright © 2020 American Chemical Society.)