| For: | Inchingolo R, Maino C, Cannella R, Vernuccio F, Cortese F, Dezio M, Pisani AR, Giandola T, Gatti M, Giannini V, Ippolito D, Faletti R. Radiomics in colorectal cancer patients. World J Gastroenterol 2023; 29(19): 2888-2904 [PMID: 37274803 DOI: 10.3748/wjg.v29.i19.2888] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v29/i19/2888.htm |
| Number | Citing Articles |
| 1 |
Rui Wang, Zhi-Xiang Xing, Xiao Yu, Zhi-Da Long. Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis. World Journal of Gastrointestinal Oncology 2025; 17(1): 96598 doi: 10.4251/wjgo.v17.i1.96598
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Answering Reviewers-71K(107)
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Supplementary Material-383K(109)
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Times Cited (8)
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Total Visits (3243)
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| 2 |
Vincenza Granata, Roberta Fusco, Maria Chiara Brunese, Gerardo Ferrara, Fabiana Tatangelo, Alessandro Ottaiano, Antonio Avallone, Vittorio Miele, Nicola Normanno, Francesco Izzo, Antonella Petrillo. Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment. Diagnostics 2024; 14(2) doi: 10.3390/diagnostics14020152
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| 3 |
Brigitte Scott. Updates in BRAF V600E-Mutated Metastatic Colorectal Cancer. EMJ Oncology 2024; doi: 10.33590/emjoncol/JDXK9403
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| 4 |
Mingzhu Yuan, Qi Long, Xufang Sun. OCTA-based research on changes of retinal microcirculation in digestive tract malignancy. Photodiagnosis and Photodynamic Therapy 2024; 49 doi: 10.1016/j.pdpdt.2024.104270
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| 5 |
Haiming Zhang, Zhenyu Li, Fengtao Zhang, Hengguo Li. CT-based radiomics features for the differential diagnosis of nodular goiter and papillary thyroid carcinoma: an analysis employing propensity score matching. Frontiers in Oncology 2024; 14 doi: 10.3389/fonc.2024.1465941
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| 6 |
Jia Zhang, Wenxiang Huang, Yang Li, Xuan Zhang, Yong Chen, Shaohao Chen, Qiu Ming, Qing Jiang, Yingjie Xv. Interpretable Machine Learning Radiomics Model Predicts 5-year Recurrence-Free Survival in Non-metastatic Clear Cell Renal Cell Carcinoma: A Multicenter and Retrospective Cohort Study. Academic Radiology 2025; 32(7) doi: 10.1016/j.acra.2025.03.042
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| 7 |
Lu-Na Bai, Lu-Xian Zhang. Effectiveness of magnetic resonance imaging and spiral computed tomography in the staging and treatment prognosis of colorectal cancer. World Journal of Gastrointestinal Surgery 2024; 16(7): 2135-2144 doi: 10.4240/wjgs.v16.i7.2135
Abstract(557) |
Core Tip(573) |
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Full Article (PDF)-2891K(134)
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Full Article with Cover (PDF)-3371K(353)
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Full Article (Word)-1040K(5)
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Full Article (XML)-91K(136)
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Audio-651K(17)
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Peer-Review Report-238K(108)
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Answering Reviewers-52K(112)
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Times Cited (1)
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Total Visits (2720)
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Open
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| 8 |
Qiaoling Chen, Qianwen Zhang, Zhihui Li, Shaoting Zhang, Yuwei Xia, Hao Wang, Yong Lu, Anqi Zheng, Chengwei Shao, Fu Shen. MRI-based habitat analysis for pathologic response prediction after neoadjuvant chemoradiotherapy in rectal cancer: a multicenter study. European Radiology 2025; 36(3) doi: 10.1007/s00330-025-11997-0
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| 9 |
Yongna Cheng, Ziming Feng, Xiangming Wang. Construction and Value Analysis of a Prognostic Assessment Model Based on Radiomics and Genetic Data for Colorectal Cancer. British Journal of Hospital Medicine 2025; 86(3) doi: 10.12968/hmed.2024.0620
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| 10 |
Hao Jiang, Wei Guo, Xue Lin, Zhuo Yu, Yudie Qin, Zhongqi Sun, Hongbo Hu, Jinping Li, Linhan Zhang, Qiong Wu, Huijie Jiang. Multiparametric MRI radiomics nomogram predicts synchronous distant metastasis in rectal cancer. Scientific Reports 2026; 16(1) doi: 10.1038/s41598-026-35973-w
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| 11 |
Zhong-Qiu Wang, Ying Tian, Liang Zeng, Marcus J Daniels, Bin Qin, Shuai Ren. Developing and validating a computed tomography radiomics strategy to predict lymph node metastasis in pancreatic cancer. World Journal of Radiology 2025; 17(8): 109373 doi: 10.4329/wjr.v17.i8.109373
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| 12 |
Jeba Karunya Ramireddy, A. Sathya, Balu Krishna Sasidharan, Amal Joseph Varghese, Arvind Sathyamurthy, Neenu Oliver John, Anuradha Chandramohan, Ashish Singh, Anjana Joel, Rohin Mittal, Dipti Masih, Kripa Varghese, Grace Rebekah, Thomas Samuel Ram, Hannah Mary T. Thomas. Can Pretreatment MRI and Planning CT Radiomics Improve Prediction of Complete Pathological Response in Locally Advanced Rectal Cancer Following Neoadjuvant Treatment?. Journal of Gastrointestinal Cancer 2024; 55(3) doi: 10.1007/s12029-024-01073-z
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| 13 |
Zhiyun Xu, Yijiang Lu, Fengyi Zuo, Hanlin Ding, Yipeng Feng, Xiaokang Shen, Xuming Song, Wenjie Xia, Qixing Mao, Bing Chen, Rutao Li, Hui Wang, Lin Xu, Gaochao Dong, Feng Jiang. Integration of habitat radiomics and traditional radiomic features for predicting pathological complete response in esophageal squamous cell carcinoma following neoadjuvant immunotherapy and chemotherapy: a multicenter comparative study. Journal of Translational Medicine 2026; 24(1) doi: 10.1186/s12967-025-07522-y
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| 14 |
Junfeng Yan, Qiushuang Wang, Qiang Li, Jiatong Lu, Qiang Tong. Preoperative magnetic resonance imaging–based radiomics nomogram model for predicting postoperative anastomotic leakage in colorectal cancer. Annals of Coloproctology 2025; 41(6) doi: 10.3393/ac.2025.00689.0098
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| 15 |
Xin Xiong, Xiaodong Ji, Xilong Yang, Wei Wang, Xianfeng Wei. Integrating CT radiomics and transcriptomics: a biologically-informed machine learning model for predicting chemotherapy response in advanced laryngeal cancer. Frontiers in Oncology 2026; 16 doi: 10.3389/fonc.2026.1740896
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| 16 |
Tingting Gong, Ying Gao, He Li, Jianqiu Wang, Zili Li, Qinghai Yuan. Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI. Abdominal Radiology 2025; 50(12) doi: 10.1007/s00261-025-04965-1
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| 17 |
I. Valle, C. Conticello, D. Ravizza, D. Lavacchi, D. Pallaoro, G.L. Grazi, D. Rossini, L. Antonuzzo. Navigating Disappearing Liver Metastases in Colorectal Cancer: A Review of Surgical and Non-Surgical Approaches. Clinical Oncology 2026; 49 doi: 10.1016/j.clon.2025.103981
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| 18 |
Luwen Zhang, Yubing Shen, Wentao Gu, Peng Wu. Multimodal learning in gastrointestinal diseases. Gastroenterology & Endoscopy 2025; 3(4) doi: 10.1016/j.gande.2025.10.001
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| 19 |
Sunya Fu, Dawei Chen, Yuqin Zhang, Xiao Yu, Lu Han, Jiazi Yu, Yupeng Zheng, Liang Zhao, Yidong Xu, Ying Tan, Mian Yang. A CT-based radiomics tumor quality and quantity model to predict early recurrence after radical surgery for colorectal liver metastases. Clinical and Translational Oncology 2024; 27(3) doi: 10.1007/s12094-024-03645-8
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| 20 |
Gui-Wen Lyu, Tong Tong, Gen-Dong Yang, Jing Zhao, Zi-Fan Xu, Na Zheng, Zhi-Fang Zhang. Bibliometric and visual analysis of radiomics for evaluating lymph node status in oncology. Frontiers in Medicine 2024; 11 doi: 10.3389/fmed.2024.1501652
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| 21 |
Malik Laich, Mathias Brugel, Pierre Henri Conze, Marwan Abbas, Mohammed Ben Abdelghanie, Faiza Khemissa, Sylvie Kircher, Karine Le Malicot, Côme Lepage, Thomas Aparicio, Christine Hoeffel, Olivier Bouché, Claire Carlier. Association between induced organ atrophy assessed by artificial intelligence-generated automatic segmentation and efficacy of bevacizumab in combination with chemotherapy in metastatic colorectal cancer. Cancer Imaging 2025; 25(1) doi: 10.1186/s40644-025-00951-4
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| 22 |
Joanna Urbaniec-Stompór, Maciej Michalak, Janusz Godlewski. Correlating Ultrastructural Changes in the Invasion Area of Colorectal Cancer with CT and MRI Imaging. International Journal of Molecular Sciences 2024; 25(18) doi: 10.3390/ijms25189905
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| 23 |
PelvEx Collaborative. The Utility of T2-Weighted MRI Radiomics in the Prediction of Post-Exenteration Disease Recurrence: A Multi-Centre Externally Validated Study via the PelvEx Collaborative. Cancers 2025; 17(18) doi: 10.3390/cancers17183061
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| 24 |
Jian-Ping Wang, Ze-Ning Zhang, Ding-Bo Shu, Ya-Nan Huang, Wei Tang, Hong-Bo Zhao, Zhen-Hua Zhao, Ji-Hong Sun. Machine learning‑based radiomics models for the prediction of metachronous liver metastases in patients with colorectal cancer: A multimodal study. Oncology Letters 2025; 30(2) doi: 10.3892/ol.2025.15140
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| 25 |
Yayan Lu, Xue Gao, Xi Wang, Weiqian Wang, Jincao Xu. Diagnostic accuracy of nasal endoscopy, computed tomography and magnetic resonance imaging for chronic rhinosinusitis and sinonasal polyps: a systematic review and meta-analysis. The Journal of Laryngology & Otology 2026; 140(4) doi: 10.1017/S002221512610437X
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| 26 |
Nicolò Gennaro, Moataz Soliman, Amir A. Borhani, Linda Kelahan, Hatice Savas, Ryan Avery, Kamal Subedi, Tugce A. Trabzonlu, Chase Krumpelman, Vahid Yaghmai, Young Chae, Jochen Lorch, Devalingam Mahalingam, Mary Mulcahy, Al Benson, Ulas Bagci, Yuri S. Velichko. Delta Radiomics and Tumor Size: A New Predictive Radiomics Model for Chemotherapy Response in Liver Metastases from Breast and Colorectal Cancer. Tomography 2025; 11(3) doi: 10.3390/tomography11030020
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| 27 |
Benjamin Keel, Aaron Quyn, David Jayne, Samuel David Relton. State-of-the-art performance of deep learning methods for pre-operative radiologic staging of colorectal cancer lymph node metastasis: a scoping review. BMJ Open 2024; 14(12) doi: 10.1136/bmjopen-2024-086896
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| 28 |
Yanjun Liu, Huanying Yin, Jiaojiao Li, Zimeng Wang, Wenjiang Wang, Shujun Cui. CT-Based radiomics and deep learning for the preoperative prediction of peritoneal metastasis in ovarian cancers. Abdominal Radiology 2025; 51(4) doi: 10.1007/s00261-025-05162-w
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| 29 |
Kaitlyn M. Weyman, Anai N. Kothari. Artificial Intelligence for the Treatment and Management of Colorectal Liver Metastases. Clinics in Colon and Rectal Surgery 2026; 39(03) doi: 10.1055/a-2769-1413
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| 30 |
Andrew Barakat, Steven Cajamarca, Kevin J. Chang. Advancements in Screening Strategies for Early-Onset Colorectal Cancer (EOCRC). Radiologic Clinics of North America 2026; 64(3) doi: 10.1016/j.rcl.2026.01.014
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| 31 |
Sin‐Hua Moi, Ming‐Yii Huang, Shu‐Han Yang, Chien‐Jang Chen, Ying‐Pei Jhong, Tun‐Wei Hsu, Chien‐Chih Ke. Integrating CT‐Based Radiomics Analysis With Serum CEA Level to Predict Neoadjuvant Chemoradiotherapy Response in Colorectal Cancer. The Kaohsiung Journal of Medical Sciences 2026; doi: 10.1002/kjm2.70241
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| 32 |
Ilaria Ambrosini, Roberto Francischello, Salvatore Claudio Fanni, Lorenzo Faggioni, Giacomo Aringhieri, Rachele Fruzza, Karolina Cwiklinska, Francesca Pia Caputo, Gayane Aghakhanyan, Emanuele Neri, Riccardo Lencioni, Dania Cioni. Radiomics analysis of restaging MRI for detection of pathological complete response in locally advanced rectal cancer. European Journal of Radiology Open 2026; 16 doi: 10.1016/j.ejro.2026.100762
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| 33 |
Haolin Nie, Sanskar Thakur, Anup Shetty, Lukai Wang, Md. Iqbal Hossain, Sitai Kou, Ahmed Eltahir, Jared Yee, Aaron Luo, Steve R. Hunt, Matthew G. Mutch, William C. Chapman, Quing Zhu. Photoacoustic-ultrasound endoscopy for assessment of rectal cancer treatment response: A prospective study with T2-weighted MRI radiomics comparison. Photoacoustics 2026; 50 doi: 10.1016/j.pacs.2026.100840
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| 34 |
Petr Tsarkov, Vladimir Balaban, Harutyun Babajanyan, Abe Fingerhut, Inna Tulina, Mingze He. Lateral pelvic lymph node positivity (LPLNP) score: predictive clinic-radiological model of lateral pelvic lymph node involvement in rectal cancer patients. International Journal of Colorectal Disease 2024; 39(1) doi: 10.1007/s00384-024-04717-5
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| 35 |
Long Wu, Huan Wu, Chen Li, Baofang Zhang, Xiaoyun Li, Yunhuan Zhen, Haiyang Li. Radiomics in colorectal cancer. iRADIOLOGY 2023; 1(3) doi: 10.1002/ird3.29
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| 36 |
Roberto Cannella. Combined quantitative and radiomics model can predict outcomes in patients with initially unresectable colorectal liver metastases treated with chemotherapy. Abdominal Radiology 2024; 50(2) doi: 10.1007/s00261-024-04529-9
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| 37 |
Nan Yao, Wenqiang Li, Ning Duan, Fuzhou Han, Guoyong Yu, Jun Qu. Biomarker guided combination strategies and perioperative integration for immune cold microsatellite stable colorectal cancer. Discover Oncology 2026; 17(1) doi: 10.1007/s12672-026-04575-3
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| 38 |
A. Brunetti, G. M. Zaccaria, E. Sibilano, S. Marzi, A. Vidiri, V. Bevilacqua. Development and independent validation of explainable radiomics-based machine learning models for prognosis in colorectal liver metastases. Frontiers in Digital Health 2026; 7 doi: 10.3389/fdgth.2025.1752699
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| 39 |
Simona Marzi, Antonello Vidiri, Anna Ianiro, Chiara Parrino, Sergio Ruggiero, Claudio Trobiani, Leonardo Teodoli, Giulio Vallati, Giovanni Trillò, Maria Ciolina, Francesca Sperati, Andrea Scarinci, Matteo Virdis, Michele Droz Dit Busset, Tommaso Stecca, Marco Massani, Giovanni Morana, Gian Luca Grazi. CT-Based Radiomics Models with External Validation for Prediction of Recurrence and Disease-Specific Mortality After Radical Surgery of Colorectal Liver Metastases. Annals of Surgical Oncology 2025; 32(13) doi: 10.1245/s10434-025-18248-y
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| 40 |
Alessio Danilo Inchingolo, Alessandra Laforgia, Angelo Michele Inchingolo, Giulia Latini, Carmen Pezzolla, Paola Nardelli, Andrea Palermo, Francesco Inchingolo, Giuseppina Malcangi, Gianna Dipalma. Rapid palate expansion's impact on nasal breathing: A systematic review. International Journal of Pediatric Otorhinolaryngology 2025; 190 doi: 10.1016/j.ijporl.2025.112248
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| 41 |
Yu-Yin Wang, Cui-Ping Zhang, Qing-Biao Zhang, Xing-Yan Le, Jun-Bang Feng, Chuan-Ming Li. Future directions of image-guided thermal ablation in colorectal cancer lung oligometastases. World Journal of Gastroenterology 2026; 32(2): 114727 doi: 10.3748/wjg.v32.i2.114727
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| 42 |
Antonio Galluzzo, Ginevra Danti, Linda Calistri, Diletta Cozzi, Daniele Lavacchi, Daniele Rossini, Lorenzo Antonuzzo, Sebastiano Paolucci, Francesca Castiglione, Luca Messerini, Fabio Cianchi, Vittorio Miele. Prediction of Microsatellite Instability in Colorectal Cancer Using Two Internally Validated Radiomic Models. Tomography 2025; 11(11) doi: 10.3390/tomography11110126
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| 43 |
Jingui Wang, Kexin Wang, Junling Zhang, Yingchao Wu, Yong Jiang, Guowei Chen, Zhanbing Liu, Tao Wu, Yuanlian Wan, Xiaoying Wang, Xin Wang. Development of a CT radiomics model for detection of bladder invasion by colorectal carcinoma. Scientific Reports 2025; 15(1) doi: 10.1038/s41598-025-99222-2
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| 44 |
Boqi Zhou, Huaqing Tan, Yuxuan Wang, Bin Huang, Zhijie Wang, Shihui Zhang, Xiaobo Zhu, Zhan Wang, Junlin Zhou, Yuntai Cao. A computed tomography-based radiomics prediction model for BRAF mutation status in colorectal cancer. Abdominal Radiology 2025; 50(11) doi: 10.1007/s00261-025-04983-z
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| 45 |
Demet Doğan, Coşku Öksüz, Özgür Çakır, Oğuzhan Urhan. CT-Based Radiomic Signatures Associated with Serum CEA Status in Colon Cancer. Diagnostics 2026; 16(8) doi: 10.3390/diagnostics16081221
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| 46 |
Ying Wei, Junqin Zhang. Multimodal radiomics for precision management of colorectal cancer. Discover Oncology 2026; 17(1) doi: 10.1007/s12672-026-04751-5
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| 47 |
Hongwei Zhang, Kexin Wang, Shurong Liu, Guowei Chen, Yong Jiang, Yingchao Wu, Xiaocong Pang, Xiaoying Wang, Junling Zhang, Xin Wang. Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features. Cancer Imaging 2025; 25(1) doi: 10.1186/s40644-025-00876-y
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| 48 |
Elena Yatsenko, Denis S Baranovskii, Irina Kondrasheva, Anna Smirnova, Ilya D Klabukov. Predictive model based on magnetic resonance imaging for chemotherapy response in colorectal cancer: Toward a radiologic biopsy approach. World Journal of Gastrointestinal Oncology 2026; 18(1): 115117 doi: 10.4251/wjgo.v18.i1.115117
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| 49 |
Wen-Yu Luan, Hao Lin, Yan-Dong Miao. Recommendations for articles and reviews in colorectal cancer-related research at the year-end of 2023. World Journal of Gastroenterology 2024; 30(30): 3548-3553 doi: 10.3748/wjg.v30.i30.3548
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| 50 |
M.C. de Grandis, I. Baraibar, O. Prior, M. Balaguer-Montero, F. Salvà, J. Ros, M. Rodríguez-Castells, J. Tabernero, S. Lonardi, R. Perez-Lopez, E. Élez. Differentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches. ESMO Open 2025; 10(8) doi: 10.1016/j.esmoop.2025.105520
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| 51 |
Francesco Celotto, Giulia Capelli, Stefania Ferrari, Marco Scarpa, Salvatore Pucciarelli, Gaya Spolverato. Application and use of artificial intelligence in colorectal cancer surgery: where are we?. Artificial Intelligence Surgery 2024; 4(4) doi: 10.20517/ais.2024.26
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| 52 |
Ningxin Chen, Boyang Zang, Yangjia Chen, Yuki Arita. Predicting one-year post-surgical recurrence in colorectal liver metastasis using CT radiomics and machine learning. PLOS One 2025; 20(8) doi: 10.1371/journal.pone.0330828
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| 53 |
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| 54 |
Liqiang Shi, Xipeng Wang, Chengqiang Li, Yaya Bai, Yajie Zhang, Hecheng Li. Radiomics applications in the modern management of esophageal squamous cell carcinoma. Medical Oncology 2025; 42(7) doi: 10.1007/s12032-025-02775-5
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| 55 |
Yuhao Fan, Rong Niu, Jianxiong Gao, Yan Sun, Jinbao Feng, Yaoting Zhu, Mengyue Hu, Yunmei Shi, Yuetao Wang, Xiaonan Shao, Qianyun Wang. New Advances in Imaging-Based Preoperative Prediction of STAS in Lung Adenocarcinoma: From CT and PET/CT to Radiomics and Deep Learning. Academic Radiology 2026; 33(1) doi: 10.1016/j.acra.2025.10.009
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| 56 |
聪 刘. Application of Multimodal Radiomics in Assessing Neoadjuvant Therapeutic Efficacy for Breast Cancer. Journal of Clinical Personalized Medicine 2026; 5(01) doi: 10.12677/jcpm.2026.51047
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| 57 |
Tingting Hong, Heng Zhang, Qiming Zhao, Li Liu, Jun Sun, Shudong Hu, Yong Mao. A Hybrid Machine Learning CT-Based Radiomics Nomogram for Predicting Cancer-Specific Survival in Curatively Resected Colorectal Cancer. Academic Radiology 2025; 32(5) doi: 10.1016/j.acra.2024.12.022
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| 58 |
Fei-Wen Feng, Fei-Yu Jiang, Yuan-Qing Liu, Qi Sun, Rong Hong, Chun-Hong Hu, Su Hu. Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer. European Radiology 2024; 35(1) doi: 10.1007/s00330-024-10918-x
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| 59 |
Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti. Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach. Heliyon 2025; 11(1) doi: 10.1016/j.heliyon.2024.e41404
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| 60 |
Yanhong Jin, Lifang Gong, Siyu Tang. A predictive model for treatment efficacy in RAS wild-type advanced colorectal cancer: development and external validation for EGFR inhibitor plus anti-angiogenic therapy based on a retrospective cohort. Scientific Reports 2026; 16(1) doi: 10.1038/s41598-026-44562-w
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| 61 |
Monica Kassavin, Kevin J. Chang. Computed Tomography Colonography. Radiologic Clinics of North America 2025; 63(3) doi: 10.1016/j.rcl.2024.09.009
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