For: | Li M, Zhu YZ, Zhang YC, Yue YF, Yu HP, Song B. Radiomics of rectal cancer for predicting distant metastasis and overall survival. World J Gastroenterol 2020; 26(33): 5008-5021 [PMID: 32952346 DOI: 10.3748/wjg.v26.i33.5008] |
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URL: | https://www.wjgnet.com/1007-9327/full/v26/i33/5008.htm |
Number | Citing Articles |
1 |
Mou Li, Ling Yang, Yufeng Yue, Jingxu Xu, Chencui Huang, Bin Song. Use of Radiomics to Improve Diagnostic Performance of PI-RADS v2.1 in Prostate Cancer. Frontiers in Oncology 2021; 10 doi: 10.3389/fonc.2020.631831
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2 |
Jacobo Porto-Álvarez, Gary T. Barnes, Alex Villanueva, Roberto García-Figueiras, Sandra Baleato-González, Emilio Huelga Zapico, Miguel Souto-Bayarri. Digital Medical X-ray Imaging, CAD in Lung Cancer and Radiomics in Colorectal Cancer: Past, Present and Future. Applied Sciences 2023; 13(4): 2218 doi: 10.3390/app13042218
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3 |
Silin Chen, Yuan Tang, Ning Li, Jun Jiang, Liming Jiang, Bo Chen, Hui Fang, Shunan Qi, Jing Hao, Ningning Lu, Shulian Wang, Yongwen Song, Yueping Liu, Yexiong Li, Jing Jin. Development and Validation of an MRI-Based Nomogram Model for Predicting Disease-Free Survival in Locally Advanced Rectal Cancer Treated With Neoadjuvant Radiotherapy. Frontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.784156
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4 |
Yan Kong, Muchen Xu, Xianding Wei, Danqi Qian, Yuan Yin, Zhaohui Huang, Wenchao Gu, Leyuan Zhou. CT imaging-based radiomics signatures improve prognosis prediction in postoperative colorectal cancer. Journal of X-Ray Science and Technology: Clinical Applications of Diagnosis and Therapeutics 2023; 31(6): 1281 doi: 10.3233/XST-230090
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5 |
Qing Zhao, Hongxia Zhong, Xu Guan, Lijuan Wan, Xinming Zhao, Shuangmei Zou, Hongmei Zhang. Role of microenvironment characteristics and MRI radiomics in the risk stratification of distant metastases in rectal cancer: a diagnostic study. International Journal of Surgery 2025; 111(1): 200 doi: 10.1097/JS9.0000000000001916
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6 |
Hongyan Huang, Lujun Han, Jianbo Guo, Yanyu Zhang, Shiwei Lin, Shengli Chen, Xiaoshan Lin, Caixue Cheng, Zheng Guo, Yingwei Qiu. Pretreatment MRI–Based Radiomics for Prediction of Rectal Cancer Outcome: A Discovery and Validation Study. Academic Radiology 2024; 31(5): 1878 doi: 10.1016/j.acra.2023.10.055
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7 |
Xiaofang Guo, Yaoyao He, Zilong Yuan, Tingting Nie, Yulin Liu, Haibo Xu. Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer. Journal of Magnetic Resonance Imaging 2025; 61(1): 452 doi: 10.1002/jmri.29396
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8 |
Jun Liu, Ke Liu, Fang Cao, Pingsheng Hu, Feng Bi, Siye Liu, Lian Jian, Jumei Zhou, Shaolin Nie, Qiang Lu, Xiaoping Yu, Lu Wen. MRI-based radiomic nomogram for predicting disease-free survival in patients with locally advanced rectal cancer. Abdominal Radiology 2024; doi: 10.1007/s00261-024-04710-0
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9 |
Zhou Chuanji, Wang Zheng, Lai Shaolv, Meng Linghou, Lu Yixin, Lu Xinhui, Lin Ling, Tang Yunjing, Zhang Shilai, Mo Shaozhou, Zhang Boyang. Comparative study of radiomics, tumor morphology, and clinicopathological factors in predicting overall survival of patients with rectal cancer before surgery. Translational Oncology 2022; 18: 101352 doi: 10.1016/j.tranon.2022.101352
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10 |
Yu-quan Wu, Rui-zhi Gao, Peng Lin, Rong Wen, Hai-yuan Li, Mei-yan Mou, Feng-huan Chen, Fen Huang, Wei-jie Zhou, Hong Yang, Yun He, Ji Wu. An endorectal ultrasound-based radiomics signature for preoperative prediction of lymphovascular invasion of rectal cancer. BMC Medical Imaging 2022; 22(1) doi: 10.1186/s12880-022-00813-6
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11 |
Yongping Hong, Xingxing Chen, Wei Sun, Guofeng Li. MRI-based radiomics features for prediction of pathological deterioration upgrading in rectal tumor. Academic Radiology 2024; doi: 10.1016/j.acra.2024.08.057
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12 |
Yong-Chao Sun, Zi-Dan Zhao, Na Yao, Yu-Wen Jiao, Jia-Wen Zhang, Yue Fu, Wei-Hai Shi. Risk prediction of second primary malignancies in patients after rectal cancer: analysis based on SEER Program. BMC Gastroenterology 2023; 23(1) doi: 10.1186/s12876-023-02974-2
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13 |
Rui Chen, Yan Fu, Xiaoping Yi, Qian Pei, Hongyan Zai, Bihong T. Chen, Xingrong Du. Application of Radiomics in Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer: Strategies and Challenges. Journal of Oncology 2022; 2022: 1 doi: 10.1155/2022/1590620
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14 |
Xiuzhen Yao, Xiandi Zhu, Shuitang Deng, Sizheng Zhu, Guoqun Mao, Jinwen Hu, Wenjie Xu, Sikai Wu, Weiqun Ao. MRI-based radiomics for preoperative prediction of recurrence and metastasis in rectal cancer. Abdominal Radiology 2024; 49(4): 1306 doi: 10.1007/s00261-024-04205-y
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15 |
Jie Dai, Ke-xin Wang, Ling-yu Wu, Xiao-han Bai, Hong-yuan Shi, Qing Xu, Jing Yu. Added value of DCER-features to clinicopathologic model for predicting metachronous metastases in rectal cancer patients. Abdominal Radiology 2024; 49(5): 1341 doi: 10.1007/s00261-023-04153-z
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16 |
Yun Qin, Li-Hua Zhu, Wei Zhao, Jun-Jie Wang, Hao Wang. Review of Radiomics- and Dosiomics-based Predicting Models for Rectal Cancer. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.913683
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17 |
Siyuan Qin, Ke Liu, Yongye Chen, Yan Zhou, Weili Zhao, Ruixin Yan, Peijin Xin, Yupeng Zhu, Hao Wang, Ning Lang. Prediction of pathological response and lymph node metastasis after neoadjuvant therapy in rectal cancer through tumor and mesorectal MRI radiomic features. Scientific Reports 2024; 14(1) doi: 10.1038/s41598-024-72916-9
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18 |
Giuditta Chiloiro, Luca Boldrini, Francesco Preziosi, Davide Cusumano, Poonam Yadav, Angela Romano, Lorenzo Placidi, Jacopo Lenkowicz, Nicola Dinapoli, Michael F. Bassetti, Maria Antonietta Gambacorta, Vincenzo Valentini. A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.831712
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19 |
Iram Shahzadi, Alex Zwanenburg, Annika Lattermann, Annett Linge, Christian Baldus, Jan C. Peeken, Stephanie E. Combs, Markus Diefenhardt, Claus Rödel, Simon Kirste, Anca-Ligia Grosu, Michael Baumann, Mechthild Krause, Esther G. C. Troost, Steffen Löck. Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models. Scientific Reports 2022; 12(1) doi: 10.1038/s41598-022-13967-8
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20 |
Joao Miranda, Natally Horvat, Jose A. B. Araujo-Filho, Kamila S. Albuquerque, Charlotte Charbel, Bruno M. C. Trindade, Daniel L. Cardoso, Lucas de Padua Gomes de Farias, Jayasree Chakraborty, Cesar Higa Nomura. The Role of Radiomics in Rectal Cancer. Journal of Gastrointestinal Cancer 2023; 54(4): 1158 doi: 10.1007/s12029-022-00909-w
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21 |
Yuan-Peng Zhang, Xin-Yun Zhang, Yu-Ting Cheng, Bing Li, Xin-Zhi Teng, Jiang Zhang, Saikit Lam, Ta Zhou, Zong-Rui Ma, Jia-Bao Sheng, Victor C. W. Tam, Shara W. Y. Lee, Hong Ge, Jing Cai. Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling. Military Medical Research 2023; 10(1) doi: 10.1186/s40779-023-00458-8
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22 |
Jie Cheng, Yao-Jia Lao, Qian Wang, Kai Huang, Juan-Li Mou, Jia-Hui Feng, Fan Hu, Meng-Lu Lin, Jun Lin. Predicting Distant Metastasis in Young-Onset Colorectal Cancer After Surgery: A Retrospective Study. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.804038
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23 |
Yuzhou Huang, Shurui Zhou, Yanji Luo, Jinmao Zou, Yaqing Li, Shaojie Chen, Ming Gao, Kaihong Huang, Guoda Lian. Development and validation of a radiomics model of magnetic resonance for predicting liver metastasis in resectable pancreatic ductal adenocarcinoma patients. Radiation Oncology 2023; 18(1) doi: 10.1186/s13014-023-02273-w
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