AI-Based Radiological Imaging for HCC: Current Status and Future of Ultrasound.

作者: Shuichiro Shiina , Tadashi Yamaguchi , Hitoshi Maruyama , Hiroaki Nagamatsu

DOI: 10.3390/DIAGNOSTICS11020292

关键词:

摘要: … -related diagnosis of HCC using radiological … ultrasound (B-mode, contrast-enhanced ultrasound, and elastography)), and discussed the current role, limitation and future of ultrasound. …

参考文章(90)
Giacomo Nebbia, Qian Zhang, Dooman Arefan, Xinxiang Zhao, Shandong Wu, Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics Journal of Digital Imaging. ,vol. 33, pp. 1376- 1386 ,(2020) , 10.1007/S10278-020-00353-X
Hong-Bo Zhu, , Ze-Yu Zheng, Heng Zhao, Jing Zhang, Hong Zhu, Yue-Hua Li, Zhong-Yi Dong, Lu-Shan Xiao, Jun-Jie Kuang, Xiao-Li Zhang, Li Liu, , , , , , , , , , , , Radiomics-based nomogram using CT imaging for noninvasive preoperative prediction of early recurrence in patients with hepatocellular carcinoma. Diagnostic and Interventional Radiology. ,vol. 26, pp. 411- 419 ,(2020) , 10.5152/DIR.2020.19623
Dongsheng Gu, Yongsheng Xie, Jingwei Wei, Wencui Li, Zhaoxiang Ye, Zhongyuan Zhu, Jie Tian, Xubin Li, MRI-Based Radiomics Signature: A Potential Biomarker for Identifying Glypican 3-Positive Hepatocellular Carcinoma. Journal of Magnetic Resonance Imaging. ,vol. 52, pp. 1679- 1687 ,(2020) , 10.1002/JMRI.27199
Qiu-Ping Liu, Xun Xu, Fei-Peng Zhu, Yu-Dong Zhang, Xi-Sheng Liu, Prediction of prognostic risk factors in hepatocellular carcinoma with transarterial chemoembolization using multi-modal multi-task deep learning. EClinicalMedicine. ,vol. 23, pp. 100379- ,(2020) , 10.1016/J.ECLINM.2020.100379
Khaled Bousabarah, Brian Letzen, Jonathan Tefera, Lynn Savic, Isabel Schobert, Todd Schlachter, Lawrence H Staib, Martin Kocher, Julius Chapiro, MingDe Lin, None, Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning. Abdominal Radiology. ,vol. 46, pp. 216- 225 ,(2021) , 10.1007/S00261-020-02604-5
Zhen Zhang, Jie Chen, Hanyu Jiang, Yi Wei, Xin Zhang, Likun Cao, Ting Duan, Zheng Ye, Shan Yao, Xuelin Pan, Bin Song, Gadoxetic acid-enhanced MRI radiomics signature: prediction of clinical outcome in hepatocellular carcinoma after surgical resection Annals of Translational Medicine. ,vol. 8, pp. 870- 870 ,(2020) , 10.21037/ATM-20-3041
Xiuming Zhang, Shijian Ruan, Wenbo Xiao, Jiayuan Shao, Wuwei Tian, Weihai Liu, Zhao Zhang, Dalong Wan, Jiacheng Huang, Qiang Huang, Yunjun Yang, Hanjin Yang, Yong Ding, Wenjie Liang, Xueli Bai, Tingbo Liang, Contrast-enhanced CT radiomics for preoperative evaluation of microvascular invasion in hepatocellular carcinoma: A two-center study. Clinical and translational medicine. ,vol. 10, ,(2020) , 10.1002/CTM2.111
Xiang-Pan Meng, Yuan-Cheng Wang, Shenghong Ju, Chun-Qiang Lu, Bin-Yan Zhong, Cai-Fang Ni, Qi Zhang, Qian Yu, Jian Xu, JianSong Ji, Xiu-Ming Zhang, Tian-Yu Tang, Guanyu Yang, Ziteng Zhao, Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization. Frontiers in Oncology. ,vol. 10, pp. 1196- 1196 ,(2020) , 10.3389/FONC.2020.01196
Jiahui Zhang, Xiaoli Wang, Lixia Zhang, Linpeng Yao, Xing Xue, Siying Zhang, Xin Li, Yuanjun Chen, Peipei Pang, Dongdong Sun, Juan Xu, Yanjun Shi, Feng Chen, Radiomics predict postoperative survival of patients with primary liver cancer with different pathological types. Annals of Translational Medicine. ,vol. 8, pp. 820- 820 ,(2020) , 10.21037/ATM-19-4668
ByungIhn Choi, Masatoshi Kudo, JaeYoung Lee, Yasunori Minami, WonJae Lee, Yi-Hong Chou, WooKyoung Jeong, >Mi-Suk Park, Nobuki Kudo, MinWoo Lee, Ken Kamata, Hiroko Iijima, SoYeon Kim, Kazushi Numata, Katsutoshi Sugimoto, Hitoshi Maruyama, Yasukiyo Sumino, Chikara Ogawa, Masayuki Kitano, Ijin Joo, Junichi Arita, Ja-Der Liang, Hsi-Ming Lin, Christian Nolsoe, OddHelge Gilja, The AFSUMB Consensus Statements and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound using Sonazoid. Journal of Medical Ultrasound. ,vol. 28, pp. 59- 82 ,(2021) , 10.4103/JMU.JMU_124_19