| For: | Zhu WS, Shi SY, Yang ZH, Song C, Shen J. Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure. World J Gastroenterol 2020; 26(11): 1208-1220 [PMID: 32231424 DOI: 10.3748/wjg.v26.i11.1208] |
|---|---|
| URL: | https://www.wjgnet.com/1007-9327/full/v26/i11/1208.htm |
| Number | Citing Articles |
| 1 |
Zahra Bagherpour, Mojtaba Safari, Pedram Fadavi, Mahsa Haghpanah, Manijeh Beigi. Predicting Radiation-Induced Skin Toxicity in Breast Cancer: A Machine Learning Approach Combining Radiomic and Dosimetric Features. Journal of Medical and Biological Engineering 2025; 45(2) doi: 10.1007/s40846-025-00943-6
|
| 2 |
Kun-Lun He, Ying-Dong Du, Xi-Xiang Lin, You Zhou, Li-Yuan Zhang, Pan Liu, Jun-Feng Wang, Ming-Xiang Zhu, Xiao Wang. Multivariable prognostic models for post-hepatectomy liver failure: An updated systematic review. World Journal of Hepatology 2025; 17(4): 103330 doi: 10.4254/wjh.v17.i4.103330
Abstract(478) |
Core Tip(418) |
Full Article(HTML)(1407)
|
Full Article (PDF)-1436K(133)
|
Full Article with Cover (PDF)-1606K(148)
|
Full Article (XML)-225K(91)
|
Audio-2640K(29)
|
Peer-Review Report-206K(92)
|
Answering Reviewers-224K(84)
|
Supplementary Material-140K(110)
|
Times Cited (3)
|
Total Visits (2664)
|
Open
|
| 3 |
Zhaoqi Shi, Wenli Cai, Xu Feng, Jingwei Cai, Yuelong Liang, Junjie Xu, Junhao Zhen, Xiao Liang. Radiomics Analysis of Gd-EOB-DTPA Enhanced Hepatic MRI for Assessment of Functional Liver Reserve. Academic Radiology 2022; 29(2) doi: 10.1016/j.acra.2021.04.019
|
| 4 |
Fatih Işık, Ahmet Yalçın, Sinan Yılmaz, Muhammed Furkan Barutcigil, Ahmet Tugrul Akkus, Adem Karaman, Gürkan Öztürk, Hakan Dursun, Fatih Alper. Prediction of hepatic functional reserve using a gadoxetic acid–enhanced MRI–derived ‘Severity Index’. BMC Medical Imaging 2025; 26(1) doi: 10.1186/s12880-025-02097-y
|
| 5 |
Calin Muntean, Vasile Gaborean, Razvan Constantin Vonica, Sebastian Aurelian Stefaniga, Alaviana Monique Faur, Catalin Vladut Ionut Feier. Machine Learning Models for Predicting Post-Hepatectomy Liver Failure: A Systematic Review. AI 2026; 7(5) doi: 10.3390/ai7050166
|
| 6 |
Jérémy Dana, Aïna Venkatasamy, Antonio Saviano, Joachim Lupberger, Yujin Hoshida, Valérie Vilgrain, Pierre Nahon, Caroline Reinhold, Benoit Gallix, Thomas F. Baumert. Conventional and artificial intelligence-based imaging for biomarker discovery in chronic liver disease. Hepatology International 2022; 16(3) doi: 10.1007/s12072-022-10303-0
|
| 7 |
Dalia Fahmy, Ahmed Alksas, Ahmed Elnakib, Ali Mahmoud, Heba Kandil, Ashraf Khalil, Mohammed Ghazal, Eric van Bogaert, Sohail Contractor, Ayman El-Baz. The Role of Radiomics and AI Technologies in the Segmentation, Detection, and Management of Hepatocellular Carcinoma. Cancers 2022; 14(24) doi: 10.3390/cancers14246123
|
| 8 |
Fei Xiang, Xiaoyuan Liang, Lili Yang, Xingyu Liu, Sheng Yan. CT radiomics nomogram for the preoperative prediction of severe post-hepatectomy liver failure in patients with huge (≥ 10 cm) hepatocellular carcinoma. World Journal of Surgical Oncology 2021; 19(1) doi: 10.1186/s12957-021-02459-0
|
| 9 |
Maria Elena Laino, Francesco Fiz, Pierandrea Morandini, Guido Costa, Fiore Maffia, Mario Giuffrida, Ilaria Pecorella, Matteo Gionso, Dakota Russell Wheeler, Martina Cambiaghi, Luca Saba, Martina Sollini, Arturo Chiti, Victor Savevsky, Guido Torzilli, Luca Viganò. A virtual biopsy of liver parenchyma to predict the outcome of liver resection. Updates in Surgery 2023; 75(6) doi: 10.1007/s13304-023-01495-7
|
| 10 |
Aysegul Sagir Kahraman. Radiomics in Hepatocellular Carcinoma. Journal of Gastrointestinal Cancer 2020; 51(4) doi: 10.1007/s12029-020-00493-x
|
| 11 |
Sandra Baleato-González, Joan C. Vilanova, Antonio Luna, Rafael Menéndez de Llano, Juan Pablo Laguna-Reyes, Diogo M. Machado-Pereira, Anaberta Bermúdez-Naveira, Iria Osorio-Vázquez, Lidia Alcalá-Mata, Roberto García-Figueiras. Current and Advanced Applications of Gadoxetic Acid–enhanced MRI in Hepatobiliary Disorders. RadioGraphics 2023; 43(4) doi: 10.1148/rg.220087
|
| 12 |
Xue-Qin Gong, Yun-Yun Tao, Yao–Kun Wu, Ning Liu, Xi Yu, Ran Wang, Jing Zheng, Nian Liu, Xiao-Hua Huang, Jing-Dong Li, Gang Yang, Xiao-Qin Wei, Lin Yang, Xiao-Ming Zhang. Progress of MRI Radiomics in Hepatocellular Carcinoma. Frontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.698373
|
| 13 |
Xing Wen, Xu Feng, Yao Kang, Long Xu. Application Progress of Gd-EOB-DTPA-Enhanced MRI T1 Mapping in Hepatic Diffuse Diseases. Current Medical Imaging Reviews 2022; 18(12) doi: 10.2174/1573405617666211130153450
|
| 14 |
Luca Viganò, Angela Ammirabile, Alexander Zwanenburg. Radiomics in liver surgery: defining the path toward clinical application. Updates in Surgery 2023; 75(6) doi: 10.1007/s13304-023-01620-6
|
| 15 |
Simone Famularo, Cesare Maino, Flavio Milana, Francesco Ardito, Gianluca Rompianesi, Cristina Ciulli, Simone Conci, Anna Gallotti, Giuliano La Barba, Maurizio Romano, Michela De Angelis, Stefan Patauner, Camilla Penzo, Agostino Maria De Rose, Jacques Marescaux, Michele Diana, Davide Ippolito, Antonio Frena, Luigi Boccia, Giacomo Zanus, Giorgio Ercolani, Marcello Maestri, Gian Luca Grazi, Andrea Ruzzenente, Fabrizio Romano, Roberto Ivan Troisi, Felice Giuliante, Matteo Donadon, Guido Torzilli. Preoperative prediction of post hepatectomy liver failure after surgery for hepatocellular carcinoma on CT-scan by machine learning and radiomics analyses. European Journal of Surgical Oncology 2025; 51(7) doi: 10.1016/j.ejso.2024.109462
|
| 16 |
Kui Sun, Liting Shi, Jianfeng Qiu, Yuteng Pan, Ximing Wang, Haiyan Wang. Multi-phase contrast-enhanced magnetic resonance image-based radiomics-combined machine learning reveals microscopic ultra-early hepatocellular carcinoma lesions. European Journal of Nuclear Medicine and Molecular Imaging 2022; 49(8) doi: 10.1007/s00259-022-05742-8
|
| 17 |
Qiuzhi Chen, Yu Wang, Lei Ou, Chunmei Guo, Bo Li, Xiaoliang Chen, Yuanyuan Yang. Preoperative ⁶⁸Ga-FAPI-04 PET/CT-derived liver fibrosis quantification independently predicts post-hepatectomy liver failure: a histologically validated study. European Journal of Nuclear Medicine and Molecular Imaging 2026; doi: 10.1007/s00259-026-07946-8
|
| 18 |
Shuaitong Zhang, Wei Mu, Di Dong, Jingwei Wei, Mengjie Fang, Lizhi Shao, Yu Zhou, Bingxi He, Song Zhang, Zhenyu Liu, Jianhua Liu, Jie Tian. The Applications of Artificial Intelligence in Digestive System Neoplasms: A Review. Health Data Science 2023; 3 doi: 10.34133/hds.0005
|
| 19 |
Luca Vigano, Martina Sollini, Francesca Ieva, Francesco Fiz, Guido Torzilli. Chemotherapy-Associated Liver Injuries: Unmet Needs and New Insights for Surgical Oncologists. Annals of Surgical Oncology 2021; 28(8) doi: 10.1245/s10434-021-10069-z
|
| 20 |
Jingwei Wei, Hanyu Jiang, Yu Zhou, Jie Tian, Felipe S. Furtado, Onofrio A. Catalano. Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinoma. Digestive and Liver Disease 2023; 55(7) doi: 10.1016/j.dld.2022.12.015
|
| 21 |
Feng Che, Jing Zhu, Qian Li, Hanyu Jiang, Yi Wei, Bin Song. Emerging Role of MRI‐Based Artificial Intelligence in Individualized Treatment Strategies for Hepatocellular Carcinoma: A Narrative Review. Journal of Magnetic Resonance Imaging 2026; 63(1) doi: 10.1002/jmri.70048
|
| 22 |
Paulo Herman, Cesar Higa Nomura, Fabricio Ferreira Coelho, Jayasree Chakraborty, Charlotte Charbel, Maria Clara Fernandes, Jose de Arimateia Batista Araujo-Filho, Gilton Marques Fonseca, Natally Horvat, Joao Miranda. Current status and future perspectives of radiomics in hepatocellular carcinoma. World Journal of Gastroenterology 2023; 29(1): 43-60 doi: 10.3748/wjg.v29.i1.43
|
| 23 |
Joseph P. Doyle, Pranav H. Patel, Nikoletta Petrou, Joshua Shur, Matthew Orton, Sacheen Kumar, Ricky H. Bhogal. Radiomic applications in upper gastrointestinal cancer surgery. Langenbeck's Archives of Surgery 2023; 408(1) doi: 10.1007/s00423-023-02951-z
|
| 24 |
Lun Lin, Yinghui Jin, Wenxin Hu. Prognostic Survival Prediction of Patients with Liver Cirrhosis based on Radiomics Data and Clinical Features. Proceedings of the 2024 5th International Conference on Computing, Networks and Internet of Things 2024; doi: 10.1145/3670105.3670129
|
| 25 |
Changfeng Li, Qiang Wang, Mengda Zou, Ping Cai, Xuesong Li, Kai Feng, Leida Zhang, Ernesto Sparrelid, Torkel B. Brismar, Kuansheng Ma. A radiomics model based on preoperative gadoxetic acid–enhanced magnetic resonance imaging for predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1164739
|
| 26 |
Qiang Wang, Anrong Wang, Ernesto Sparrelid, Jiaxing Zhang, Ying Zhao, Kuansheng Ma, Torkel B. Brismar. Predictive value of gadoxetic acid–enhanced MRI for posthepatectomy liver failure: a systematic review. European Radiology 2022; 32(3) doi: 10.1007/s00330-021-08297-8
|
| 27 |
Feier Ding, Takashi Ota, Shuo Cai, Hui Ma, Masahiro Yanagawa, Atsushi Nakamoto, Noriyuki Tomiyama, Yidi Chen, Bin Song, Xinya Zhao. Predictive model development and validation of functional liver imaging score for prognosis of patients with hepatocellular carcinoma after surgical resection: a multicenter study. La radiologia medica 2025; 131(2) doi: 10.1007/s11547-025-02110-y
|
| 28 |
Jingwei Wei, Meng Niu, Ouyang Yabo, Yu Zhou, Xiaoke Ma, Xue Yang, Hanyu Jiang, Hui Hui, Hongyi Cao, Binwei Duan, Hongjun Li, Dawei Ding, Jie Tian. Advances in artificial intelligence techniques drive the application of radiomics in the clinical research of hepatocellular carcinoma. iLIVER 2022; 1(1) doi: 10.1016/j.iliver.2022.02.005
|
| 29 |
Christoph F Dietrich, Fan Jiang, Xin-Wu Cui, Peng-Hua Liu, Gong-Quan Chen, Mei Peng, Xue Liu, Wei Liu. Artificial intelligence for hepatitis evaluation. World Journal of Gastroenterology 2021; 27(34): 5715-5726 doi: 10.3748/wjg.v27.i34.5715
|