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4. Targeting pro-inflammatory T cells as a novel therapeutic approach to potentially resolve atherosclerosis in humans

Author

Fan, Lin, Liu, Junwei, Hu, Wei, Chen, Zexin, Lan, Jie, Zhang, Tongtong, Zhang, Yang, Wu, Xianpeng, Zhong, Zhiwei, Zhang, Danyang, Zhang, Jinlong, Qin, Rui, Chen, Hui, Zong, Yunfeng, Zhang, Jianmin, Chen, Bing, Jiang, Jun, Cheng, Jifang, Zhou, Jingyi, Gao, Zhiwei, Liu, Zhenjie, Chai, Ying, Fan, Junqiang, Wu, Pin, Chen, Yinxuan, Zhu, Yuefeng, Wang, Kai, Yuan, Ying, Huang, Pintong, Zhang, Ying, Feng, Huiqin, Song, Kaichen, Zeng, Xun, Zhu, Wei, Hu, Xinyang, Yin, Weiwei, Chen, Wei, and Wang, Jian’an

Published
2024
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5. Author Correction: Targeting pro-inflammatory T cells as a novel therapeutic approach to potentially resolve atherosclerosis in humans

Author

Fan, Lin, Liu, Junwei, Hu, Wei, Chen, Zexin, Lan, Jie, Zhang, Tongtong, Zhang, Yang, Wu, Xianpeng, Zhong, Zhiwei, Zhang, Danyang, Zhang, Jinlong, Qin, Rui, Chen, Hui, Zong, Yunfeng, Zhang, Jianmin, Chen, Bing, Jiang, Jun, Cheng, Jifang, Zhou, Jingyi, Gao, Zhiwei, Liu, Zhenjie, Chai, Ying, Fan, Junqiang, Wu, Pin, Chen, Yinxuan, Zhu, Yuefeng, Wang, Kai, Yuan, Ying, Huang, Pintong, Zhang, Ying, Feng, Huiqin, Song, Kaichen, Zeng, Xun, Zhu, Wei, Hu, Xinyang, Yin, Weiwei, Chen, Wei, and Wang, Jian’an

Published
2024
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10. Automated Diagnosis and Phenotyping of Tuberculosis Using Serum Metabolic Fingerprints.

Author

Liu, Yajing, Wang, Ruimin, Zhang, Chao, Huang, Lin, Chen, Jifan, Zeng, Yiqing, Chen, Hongjian, Wang, Guowei, Qian, Kun, and Huang, Pintong

Subjects
METABOLOMIC fingerprinting, MACHINE learning, METABOLIC models, COMMUNICABLE diseases, MASS spectrometry
Abstract

Tuberculosis (TB) stands as the second most fatal infectious disease after COVID‐19, the effective treatment of which depends on accurate diagnosis and phenotyping. Metabolomics provides valuable insights into the identification of differential metabolites for disease diagnosis and phenotyping. However, TB diagnosis and phenotyping remain great challenges due to the lack of a satisfactory metabolic approach. Here, a metabolomics‐based diagnostic method for rapid TB detection is reported. Serum metabolic fingerprints are examined via an automated nanoparticle‐enhanced laser desorption/ionization mass spectrometry platform outstanding by its rapid detection speed (measured in seconds), minimal sample consumption (in nanoliters), and cost‐effectiveness (approximately $3). A panel of 14 m z−1 features is identified as biomarkers for TB diagnosis and a panel of 4 m z−1 features for TB phenotyping. Based on the acquired biomarkers, TB metabolic models are constructed through advanced machine learning algorithms. The robust metabolic model yields a 97.8% (95% confidence interval (CI), 0.964‐0.986) area under the curve (AUC) in TB diagnosis and an 85.7% (95% CI, 0.806‐0.891) AUC in phenotyping. In this study, serum metabolic biomarker panels are revealed and develop an accurate metabolic tool with desirable diagnostic performance for TB diagnosis and phenotyping, which may expedite the effective implementation of the end‐TB strategy. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Can 3D Multiparametric Ultrasound Imaging Predict Prostate Biopsy Outcome?

Author

Chen, Peiran, Turco, Simona, Wang, Yao, Jager, Auke, Daures, Gautier, Wijkstra, Hessel, Zwart, Wim, Huang, Pintong, Mischi, Massimo, Chen, Peiran, Turco, Simona, Wang, Yao, Jager, Auke, Daures, Gautier, Wijkstra, Hessel, Zwart, Wim, Huang, Pintong, and Mischi, Massimo

Abstract

Objectives: To assess the value of 3D multiparametric ultrasound imaging, combining hemodynamic and tissue stiffness quantifications by machine learning, for the prediction of prostate biopsy outcomes. Methods: After signing informed consent, 54 biopsy-naïve patients underwent a 3D dynamic contrast-enhanced ultrasound (DCE-US) recording, a multi-plane 2D shear-wave elastography (SWE) scan with manual sweeping from base to apex of the prostate, and received 12-core systematic biopsies (SBx). 3D maps of 18 hemodynamic parameters were extracted from the 3D DCE-US quantification and a 3D SWE elasticity map was reconstructed based on the multi-plane 2D SWE acquisitions. Subsequently, all the 3D maps were segmented and subdivided into 12 regions corresponding to the SBx locations. Per region, the set of 19 computed parameters was further extended by derivation of eight radiomic features per parameter. Based on this feature set, a multiparametric ultrasound approach was implemented using five different classifiers together with a sequential floating forward selection method and hyperparameter tuning. The classification accuracy with respect to the biopsy reference was assessed by a group-k-fold cross-validation procedure, and the performance was evaluated by the Area Under the Receiver Operating Characteristics Curve (AUC). Results: Of the 54 patients, 20 were found with clinically significant prostate cancer (csPCa) based on SBx. The 18 hemodynamic parameters showed mean AUC values varying from 0.63 to 0.75, and SWE elasticity showed an AUC of 0.66. The multiparametric approach using radiomic features derived from hemodynamic parameters only produced an AUC of 0.81, while the combination of hemodynamic and tissue-stiffness quantifications yielded a significantly improved AUC of 0.85 for csPCa detection (p-value < 0.05) using the Gradient Boosting classifier. Conclusions: Our results suggest 3D multiparametric ultrasound imaging combining hemodynamic and tissue-stiff

Published
2024

27. New Technologies in the Assessment of Carotid Stenosis: Beyond the Color-Doppler Ultrasound—High Frame Rate Vector-Flow and 3D Arterial Analysis Ultrasound

Author

David, Emanuele, primary, Martinelli, Ombretta, additional, Pacini, Patrizia, additional, Di Serafino, Marco, additional, Huang, Pintong, additional, Dolcetti, Vincenzo, additional, Del Gaudio, Giovanni, additional, Barr, Richard G., additional, Renda, Maurizio, additional, Lucarelli, Giuseppe T., additional, Di Marzo, Luca, additional, Clevert, Dirk A., additional, Solito, Carmen, additional, Di Bella, Chiara, additional, and Cantisani, Vito, additional

Published
2023
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28. Percutaneous ultrasound-guided radiofrequency ablation for giant desmoid tumors of the intra-abdominal cavity in a patient with Gardner syndrome

Author

Wang, Liping, Xu, Dong, Chen, Liyu, and Huang, Pintong

Subjects
Polyposis, Familial -- Case studies, Radiofrequency ablation -- Case studies -- Usage, Gastrointestinal tumors -- Case studies -- Care and treatment, Health
Abstract

Byline: Liping. Wang, Dong. Xu, Liyu. Chen, Pintong. Huang Gardner syndrome (GS) is a rare variant of familial adenomatous polyposis, leading to numerous intra- and extracolonic lesions. Extracolonic lesions of [...]

Published
2021

33. Multiparametric ultrasound and machine learning for prostate cancer localization

Author

Chen, Peiran, Calis, Metin, Wijkstra, Hessel, Huang, Pintong, Hunyadi, Borbála, Mischi, Massimo, Urology, APH - Quality of Care, CCA - Cancer Treatment and Quality of Life, CCA - Imaging and biomarkers, APH - Personalized Medicine, Center for Care & Cure Technology Eindhoven, Biomedical Diagnostics Lab, Eindhoven MedTech Innovation Center, Signal Processing Systems, EAISI Health, and NeuroPlatform

Subjects
machine learning, SDG 3 - Good Health and Well-being, multilinear singular value decomposition, ultrasound, prostate cancer
Abstract

A cost-effective, widely available, and practical diagnostic imaging tool for prostate cancer (PCa) localization is still lacking. Recently, the contrast-ultrasound dispersion imaging (CUDI) technique has been developed for PCa localization by quantifying dynamic contrast-enhanced ultrasound (DCE-US) acquisitions. Tissue stiffness is an additional PCa biomarker that can be quantified by ultrasound shear-wave elastography (SWE). In this work, a dedicated preprocessing of 3D DCE-US acquisitions was investigated by using multilinear singular value decomposition (MLSVD), aiming at improving the CUDI performance. Moreover, the diagnostic potential of a multiparametric ultrasound imaging approach combining 3D CUDI features with SWE tissue elasticity for clinically significant (cs)PCa localization was evaluated by comparison with the histopathological outcome of systematic biopsies. In this multiparametric approach, the performance of five classifiers was evaluated and compared for biopsy-region csPCa classification. The classification performance was assessed by the area under the Receiver Operating Characteristics curve (AUC) in a k-fold cross validation fashion comprising sequential floating forward selection of the features. The combination of CUDI features with MLSVD preprocessing and SWE elasticity yielded the best AUC=0.87 for csPCa localization. Our results suggest 3D multiparametric ultrasound imaging approach combing a dedicated preprocessing step to be a useful tool for PCa diagnostics.

Published
2022
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37. Auto-Segmentation Ultrasound-Based Radiomics Technology to Stratify Patient With Diabetic Kidney Disease: A Multi-Center Retrospective Study

Author

Chen, Jifan, primary, Jin, Peile, additional, Song, Yue, additional, Feng, Liting, additional, Lu, Jiayue, additional, Chen, Hongjian, additional, Xin, Lei, additional, Qiu, Fuqiang, additional, Cong, Zhang, additional, Shen, Jiaxin, additional, Zhao, Yanan, additional, Xu, Wen, additional, Cai, Chenxi, additional, Zhou, Yan, additional, Yang, Jinfeng, additional, Zhang, Chao, additional, Chen, Qin, additional, Jing, Xiang, additional, and Huang, Pintong, additional

Published
2022
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38. Expert consensus workshop report: Guidelines for thermal ablation of thyroid tumors (2019 edition)

Author

Xu, Dong, Ge, Minghua, Yang, Ankui, Cheng, Ruochuan, Sun, Hui, Wang, Hongcheng, Zhang, Jianquan, Cheng, Zhigang, Wu, Zeyu, Wang, Zhongmin, Zhai, Bo, Che, Yin, Chen, Lin, Chen, Liyu, Cheng, Wen, Dong, Gang, Duan, Peiyan, Fan, Weijun, Fei, Jian, Fu, Rongzhan, Gao, Meizhuo, Huang, Pintong, Jiang, Tianan, Kuang, Jian, Li, Honghao, Li, Ping, Li, Xinying, Li, Zhihui, Lu, Man, Luo, Yukun, Qin, Huadong, Qin, Jianwu, Tan, Zhuo, Tang, Lina, Wang, Zhaohui, Wang, Shurong, Wang, Xiaoping, Wu, Gaosong, Xie, Xiaoyan, Xu, Haimiao, Yin, Detao, Qiu, Xinguang, Jichun, Y., Yu, Jianjun, Zhan, Weiwei, Zhang, Fujun, Zhang, Junqing, Zheng, Rongqin, Zheng, Xiangqian, Zheng, Yuanyi, Zhu, Youhua, Zou, Yinghua, Meng, Zhiqiang, Ye, Xin, Li, Hailiang, Li, Xiao, Lin, Zhengyu, Wang, Lijing, Wang, Liping, Yang, Chen, Wang, Yifan, Zhou, Linyan, Ou, Di, Wang, Jiafeng, Gao, Ming, Xu, Huixiong, Liang, Ping, and Teng, Gaojun

Subjects
Workshops (Educational programs) -- Conferences, meetings and seminars -- Reports, Thyroid diseases -- Conferences, meetings and seminars -- Reports, Ablation (Surgery) -- Conferences, meetings and seminars -- Reports, Tumors -- Conferences, meetings and seminars -- Reports, Health
Abstract

Byline: Dong. Xu, Minghua. Ge, Ankui. Yang, Ruochuan. Cheng, Hui. Sun, Hongcheng. Wang, Jianquan. Zhang, Zhigang. Cheng, Zeyu. Wu, Zhongmin. Wang, Bo. Zhai, Yin. Che, Lin. Chen, Liyu. Chen, Wen. [...]

Published
2020

39. Multiparametric ultrasound and machine learning for prostate cancer localization

Author

Chen, Peiran (author), Calis, Metin (author), Wijkstra, Hessel (author), Huang, Pintong (author), Hunyadi, Borbala (author), Mischi, Massimo (author), Chen, Peiran (author), Calis, Metin (author), Wijkstra, Hessel (author), Huang, Pintong (author), Hunyadi, Borbala (author), and Mischi, Massimo (author)

Abstract

A cost-effective, widely available, and practical diagnostic imaging tool for prostate cancer (PCa) localization is still lacking. Recently, the contrast-ultrasound dispersion imaging (CUDI) technique has been developed for PCa localization by quantifying dynamic contrast-enhanced ultrasound (DCE-US) acquisitions. Tissue stiffness is an additional PCa biomarker that can be quantified by ultrasound shear-wave elastography (SWE). In this work, a dedicated preprocessing of 3D DCE-US acquisitions was investigated by using multilinear singular value decomposition (MLSVD), aiming at improving the CUDI performance. Moreover, the diagnostic potential of a multiparametric ultrasound imaging approach combining 3D CUDI features with SWE tissue elasticity for clinically significant (cs)PCa localization was evaluated by comparison with the histopathological outcome of systematic biopsies. In this multiparametric approach, the performance of five classifiers was evaluated and compared for biopsy-region csPCa classification. The classification performance was assessed by the area under the Receiver Operating Characteristics curve (AUC) in a k-fold cross validation fashion comprising sequential floating forward selection of the features. The combination of CUDI features with MLSVD preprocessing and SWE elasticity yielded the best AUC=0.87 for csPCa localization. Our results suggest 3D multiparametric ultrasound imaging approach combing a dedicated preprocessing step to be a useful tool for PCa diagnostics., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

Published
2022

41. Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study

Author

Liu, Yajing, primary, Chen, Jifan, additional, Zhang, Chao, additional, Li, Qunying, additional, Zhou, Hang, additional, Zeng, Yiqing, additional, Zhang, Ying, additional, Li, Jia, additional, Xv, Wen, additional, Li, Wencun, additional, Zhu, Jianing, additional, Zhao, Yanan, additional, Chen, Qin, additional, Huang, Yi, additional, Li, Hongming, additional, Huang, Ying, additional, Yang, Gaoyi, additional, and Huang, Pintong, additional

Published
2022
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42. Distinct molecular phenotype and the potential prognostic value of immune prognostic index and tumor infiltrating lymphocytes in hepatoid adenocarcinoma of stomach

Author

Kang, Muxing, primary, Ma, Xiaojing, additional, Shi, Jifei, additional, Chen, Guofeng, additional, Jin, Xiaoli, additional, Wang, Jun, additional, Lin, Lele, additional, Wu, Zhiwei, additional, Chen, Kaibo, additional, Xu, Jinghong, additional, Huang, Pintong, additional, and Chen, Jian, additional

Published
2022
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44. Additional file 1 of Enhancement of antitumor immunotherapy using mitochondria-targeted cancer cell membrane-biomimetic MOF-mediated sonodynamic therapy and checkpoint blockade immunotherapy

Author

Luo, Jiali, Wang, Xue, Shi, Zhan, Zeng, Yiqing, He, Liangcan, Cao, Jing, Sun, Yu, Zhang, Tao, and Huang, Pintong

Abstract

Additional file 1: Figure S1. a Cellular uptake of Zr-TCPP(TPP)/R837@M. b In vitro cell viability of 4T1 cells. Figure S2. 4T1, MDA-MB-468, Hepa1-6, and Bxpc-3 after 8 h incubation with Zr-TCPP(TPP)/R837. Figure S3. CRT exposure. Figure S4. a The ex vivo fluorescence image of major organs and tumour and b quantification analysis of the tissue content of Zr-TCPP(TPP)/R837 and Zr-TCPP(TPP)/R837@M; data are expressed as means ± SD (n = 3). Statistical significance was calculated by one-way ANOVA Tukey's multiple comparisons test. P-value: *P

Published
2022
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46. The Role of CEUS in the Evaluation of Thyroid Cancer: From Diagnosis to Local Staging

Author

Sorrenti, Salvatore, primary, Dolcetti, Vincenzo, additional, Fresilli, Daniele, additional, Del Gaudio, Giovanni, additional, Pacini, Patrizia, additional, Huang, Pintong, additional, Camponovo, Chiara, additional, Leoncini, Andrea, additional, D’Andrea, Vito, additional, Pironi, Daniele, additional, Frattaroli, Fabrizio, additional, Trimboli, Pierpaolo, additional, Radzina, Maija, additional, and Cantisani, Vito, additional

Published
2021
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49. Deep learning-based carotid plaque vulnerability classification with multicentre contrast-enhanced ultrasound video: a comparative diagnostic study

Author

Guang, Yang, primary, He, Wen, additional, Ning, Bin, additional, Zhang, Hongxia, additional, Yin, Chen, additional, Zhao, Mingchang, additional, Nie, Fang, additional, Huang, Pintong, additional, Zhang, Rui-Fang, additional, Yong, Qiang, additional, Guo, Yanli, additional, Yuan, Jianjun, additional, Wang, Yicheng, additional, Yuan, Lijun, additional, Ruan, Litao, additional, Yu, Tengfei, additional, Song, Haiman, additional, and Zhang, Yukang, additional

Published
2021
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50. A Nomogram Based on Combining Clinical Features and Contrast Enhanced Ultrasound LI-RADS Improves Prediction of Microvascular Invasion in Hepatocellular Carcinoma

Author

Zhou, Hang, primary, Sun, Jiawei, additional, Jiang, Tao, additional, Wu, Jiaqi, additional, Li, Qunying, additional, Zhang, Chao, additional, Zhang, Ying, additional, Cao, Jing, additional, Sun, Yu, additional, Jiang, Yifan, additional, Liu, Yajing, additional, Zhou, Xianli, additional, and Huang, Pintong, additional

Published
2021
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