Immune Profile Differences between IgG4-Related Diseases and Primary Sjögren’s Syndrome by Qin Y, Shang L, Wang Y, Feng M, Liang Z, Wang N, Gao C, Luo J

“…IgG subclasses (IgGSc) were detected using a Siemens BN P, and lymphocyte subsets were analyzed using flow cytometry. …”
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Evaluation of Metabolic Characteristics of Brain Tumours Utilising 31-Phosphorus MR Spectroscopy in 3T MRI: A Cross-sectional Study by Nivetha Kannan, Babu Peter Sathyanathan

“…The study included 32 patients diagnosed with brain tumours based on conventional MR imaging, followed by histopathology, and 10 normal healthy volunteers who underwent 31-Phosphorus MR spectroscopy using a customised birdcage 31-P dual-tuned head coil on a Siemens 3-Tesla MRI scanner (Rapid Biomedical, Wurzburg, Germany). …”
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Comparison of CT-like MRI sequences for preoperative planning of cochlear implantation using super-high-resolution CT as a reference by Ulysse Puel, Achille Beysang, Gabriella Hossu, Michael Eliezer, Bouchra Assabah, Khalid Ambarki, Pedro Augusto Gondim Teixeira, Alain Blum, Cécile Parietti-Winkler, Romain Gillet

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Nomogram based on the neutrophil-to-lymphocyte ratio and MR diffusion quantitative parameters for predicting Ki67 expression in hepatocellular carcinoma from a prospective study by Yu-chen Wei, Liang yun, Yan-ling Liang, Robert Grimm, Chongze Yang, Yuan-fang Tao, Sheng-chen Jiang, Jin-yuan Liao

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Preoperative prediction of IDH genotypes and prognosis in adult-type diffuse gliomas: intratumor heterogeneity habitat analysis using dynamic contrast-enhanced MRI and diffusion-we... by Xingrui Wang, Zhenhui Xie, Xiaoqing Wang, Yang Song, Shiteng Suo, Yan Ren, Wentao Hu, Yi Zhu, Mengqiu Cao, Yan Zhou

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Voxelwise characterization of noise for a clinical photon-counting CT scanner with a model-based iterative reconstruction algorithm by Luigi Masturzo, Patrizio Barca, Luca De Masi, Daniela Marfisi, Antonio Traino, Filippo Cademartiri, Marco Giannelli

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Effect of drinking water salinity on lactating cows’ water and feed intake, milk yield, and rumen physiology by A. Iritz, D. Espinoza, M.G. Taye, F. Salhab, Y. Portnik, U. Moallem, Y.A. Ben Meir

“…Therefore, we evaluated the effect of drinking water salinity in an electrical conductivity (EC) range of 400 to 1 000 micro Siemens (µS) / cm (TDS of 200 to 500 ppm) on lactating cows’ performance by artificially creating water EC > 400 µS/cm by adding NaCl. …”
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High Detection Rates for Prostate-specific Membrane Antigen–avid Prostate Cancer Recurrence at Low Prostate-specific Antigen levels on Extended Axial Field-of-view Positron Emissio... by Sarah Thomas, Jason Callahan, Paul Conway, Daniel Moon, Hugh Morgan, Johanna Ingbritsen, Melissa Munro, Robert E. Ware, Phil Dundee, Rodney J. Hicks

“…PET/CT devices with an extended axial field-of-view, such as the Siemens Biograph Vision Quadra (Quadra) scanner, have substantially higher sensitivity than conventional field-of-view scanners. …”
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Association of iron deposition in MS lesion with remyelination capacity using susceptibility source separation MRI by Hyeong-Geol Shin, Woojun Kim, Jung Hwan Lee, Hyun-soo Lee, Yoonho Nam, Jiwoong Kim, Xu Li, Peter C.M. van Zijl, Peter A. Calabresi, Jongho Lee, Jinhee Jang

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Evaluation of gamma rays shielding properties of bismuth tungstate with different morphologies by Qiang Yan, Yong Li, Guowei Wang, Zhengxin Wu, Haitao Zhang, Chuyuan Mao, Zhiqiang Long, Guoqing Liu

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Attitudes of radiologists and interns toward the adoption of GPT-like technologies: a National Survey Study in China by Tianyi Xia, Shijun Zhang, Ben Zhao, Ying Lei, Zebin Xiao, Bingwei Chen, Junhao Zha, Yaoyao Yu, Zhijun Wu, Chunqiang Lu, Tianyu Tang, Yang Song, Yuancheng Wang, Shenghong Ju

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TRACE Model: Predicting Treatment Response to Transarterial Chemoembolization in Unresectable Hepatocellular Carcinoma by Wang W, Zhang Q, Cui Y, Zhang S, Li B, Xia T, Song Y, Zhou S, Ye F, Xiao W, Cao K, Chi Y, Qu J, Zhou G, Chen Z, Zhang T, Chen X, Ju S, Wang YC

“…Weilang Wang,1,* Qi Zhang,2,* Ying Cui,1,* Shuhang Zhang,1 Binrong Li,1 Tianyi Xia,1 Yang Song,3 Shuwei Zhou,1 Feng Ye,4 Wenbo Xiao,5 Kun Cao,6 Yuan Chi,7 Jinrong Qu,8 Guofeng Zhou,9,10 Zhao Chen,11 Teng Zhang,12 Xunjun Chen,13 Shenghong Ju,1 Yuan-Cheng Wang1 1Department of Radiology, Zhongda Hospital, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China; 2Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, People’s Republic of China; 3MR Scientific Marketing, Siemens Healthineers Ltd, Shanghai, People’s Republic of China; 4Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 5Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People’s Republic of China; 6Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, People’s Republic of China; 7Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People’s Republic of China; 8Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, People’s Republic of China; 9Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 10Shanghai Institute of Medical Imaging, Shanghai, People’s Republic of China; 11Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 12Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, People’s Republic of China; 13Department of Radiology, The People’s Hospital of Xuyi County, Huaian, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yuan-Cheng Wang, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, 87 Ding Jia Qiao Road, Nanjing, Jiangsu, 210009, People’s Republic of China, Tel +086 25 83272121, Fax +086 25 83311083, Email yuancheng_wang@seu.edu.cnPurpose: To develop and validate a predictive model for predicting six-month outcome by integrating pretreatment MRI features and one-month treatment response after TACE.Methods: A total of 108 patients with 160 hCCs from a single-arm, multicenter clinical trial (NCT03113955) were analyzed and served as the training cohort. …”
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The impact of preliminary patient hydration on physiological [18F]PSMA-1007 uptake in the urinary bladder on PET/CT by T. L. Antonevskaya, A. I. Khalimon, O. V. Mukhortova, M. M. Khodzhibekova, A. I. Nikiforuk, D. D. Zubkov, G. F. Khamadeeva, D. Yu. Khodakova, T. N. Lazutina, I. V. Pylova, A. V. Leontyev, I. P. Aslanidi

“…Scans were performed using three different PET/CT-systems: GE Discovery IQ Gen 2 (USA), Siemens Biograph 64 mCT and Biograph 64 TruePoint (Germany). …”
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