BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Yin JD, Song LR, Lu HC, Zheng X. Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps. World J Gastroenterol 2020; 26(17): 2082-2096 [PMID: 32536776 DOI: 10.3748/wjg.v26.i17.2082]
URL: https://www.wjgnet.com/1948-5204/full/v26/i17/2082.htm
Number Citing Articles
1
Chunli Li, Jiandong Yin. Radiomics Nomogram Based on Radiomics Score from Multiregional Diffusion-Weighted MRI and Clinical Factors for Evaluating HER-2 2+ Status of Breast CancerDiagnostics 2021; 11(8): 1491 doi: 10.3390/diagnostics11081491
2
Valerio Nardone, Alfonso Reginelli, Roberta Grassi, Giovanna Vacca, Giuliana Giacobbe, Antonio Angrisani, Alfredo Clemente, Ginevra Danti, Pierpaolo Correale, Salvatore Francesco Carbone, Luigi Pirtoli, Lorenzo Bianchi, Angelo Vanzulli, Cesare Guida, Roberto Grassi, Salvatore Cappabianca. Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and SurgeryCancers 2022; 14(12): 3004 doi: 10.3390/cancers14123004
3
Huiying Li, Bingyuan Wang, Yang Wang. 2′-Fucosyllactose Suppresses Angiogenesis and Alleviates Toxic Effects of 5-Fu in a HCT116 Colon Tumor-Bearing ModelMolecules 2022; 27(21): 7255 doi: 10.3390/molecules27217255
4
Hui Feng, Gaofeng Shi, Hui Liu, Qian Xu, Ning Zhang, Jie Kuang. Free-breathing radial volumetric interpolated breath-hold examination sequence and dynamic contrast-enhanced MRI combined with diffusion-weighted imaging for assessment of solitary pulmonary nodulesMagnetic Resonance Imaging 2021; 75: 100 doi: 10.1016/j.mri.2020.10.009
5
Xue Lin, Sheng Zhao, Huijie Jiang, Fucang Jia, Guisheng Wang, Baochun He, Hao Jiang, Xiao Ma, Jinping Li, Zhongxing Shi. A radiomics-based nomogram for preoperative T staging prediction of rectal cancerAbdominal Radiology 2021; 46(10): 4525 doi: 10.1007/s00261-021-03137-1
6
Alessandra Borgheresi, Federica De Muzio, Andrea Agostini, Letizia Ottaviani, Alessandra Bruno, Vincenza Granata, Roberta Fusco, Ginevra Danti, Federica Flammia, Roberta Grassi, Francesca Grassi, Federico Bruno, Pierpaolo Palumbo, Antonio Barile, Vittorio Miele, Andrea Giovagnoni. Lymph Nodes Evaluation in Rectal Cancer: Where Do We Stand and Future PerspectiveJournal of Clinical Medicine 2022; 11(9): 2599 doi: 10.3390/jcm11092599
7
Cheng Wang, Ying Ma, Yanyun Liu, Longxi Li, Chang Cui, Huiyuan Qin, Zhongqiang Zhao, Chunxiang Li, Weizhu Ju, Minglong Chen, Dianfu Li, Weihua Zhou. Texture analysis of SPECT myocardial perfusion provides prognostic value for dilated cardiomyopathyJournal of Nuclear Cardiology 2023; 30(2): 504 doi: 10.1007/s12350-022-03006-4
8
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 StudyAcademic Radiology 2023;  doi: 10.1016/j.acra.2023.10.055
9
Bo Deng, Qian Wang, Yuanqing Liu, Yanwei Yang, Xiaolong Gao, Hui Dai. A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancerAbdominal Radiology 2024;  doi: 10.1007/s00261-023-04164-w
10
Jiajun Luo, Hongxue Wu, Yue Jiang, Yu Yang, Jingwen Yuan, Qiang Tong, Deguang Song. The Role of Heart Rate, Body Temperature, and Respiratory Rate in Predicting Anastomotic Leakage following Surgery for Rectal CancerMediators of Inflammation 2021; 2021: 1 doi: 10.1155/2021/8698923
11
Hui Wang, Xiaoyong Chen, Jingfeng Ding, Shuitang Deng, Guoqun Mao, Shuyuan Tian, Xiandi Zhu, Weiqun Ao. Novel multiparametric MRI-based radiomics in preoperative prediction of perirectal fat invasion in rectal cancerAbdominal Radiology 2022; 48(2): 471 doi: 10.1007/s00261-022-03759-z
12
Yan-song Xu, Gang Liu, Chang Zhao, Shao-long Lu, Chen-yan Long, Hua-ge Zhong, Yi Chen, Ling-xu Huang, Zheng Liang. Prognostic Value of Combined Preoperative Carcinoembryonic Antigen and Prognostic Nutritional Index in Patients With Stage II–III Colon CancerFrontiers in Surgery 2021; 8 doi: 10.3389/fsurg.2021.667154
13
Arnaldo Stanzione, Francesco Verde, Valeria Romeo, Francesca Boccadifuoco, Pier Paolo Mainenti, Simone Maurea. Radiomics and machine learning applications in rectal cancer: Current update and future perspectivesWorld Journal of Gastroenterology 2021; 27(32): 5306-5321 doi: 10.3748/wjg.v27.i32.5306
14
Toru Tochigi, Sophia C. Kamran, Anushri Parakh, Yoshifumi Noda, Balaji Ganeshan, Lawrence S. Blaszkowsky, David P. Ryan, Jill N. Allen, David L. Berger, Jennifer Y. Wo, Theodore S. Hong, Avinash Kambadakone. Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysisEuropean Radiology 2022; 32(4): 2426 doi: 10.1007/s00330-021-08303-z
15
Xin Zhu, Dan-Dan Ye, Jian-Hua Wang, Jing Li, Shao-Wei Liu. Diagnostic performance of texture analysis in the differential diagnosis of perianal fistulising Crohn’s disease and glandular anal fistulaWorld Journal of Gastrointestinal Surgery 2023; 15(5): 882-891 doi: 10.4240/wjgs.v15.i5.882
16
Leyao Wang, Bing Feng, Sicong Wang, Jiesi Hu, Meng Liang, Dengfeng Li, Shuang Wang, Xiaohong Ma, Xinming Zhao. Diagnostic value of whole-tumor apparent diffusion coefficient map radiomics analysis in predicting early recurrence of solitary hepatocellular carcinoma ≤ 5 cmAbdominal Radiology 2022; 47(9): 3290 doi: 10.1007/s00261-022-03582-6
17
Jinlian Jin, Haiyan Zhou, Shulin Sun, Zhe Tian, Haibing Ren, Jinwu Feng, Xinping Jiang. Machine learning based gray-level co-occurrence matrix early warning system enables accurate detection of colorectal cancer pelvic bone metastases on MRIFrontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1121594
18
Jia You, Jiandong Yin. Performances of Whole Tumor Texture Analysis Based on MRI: Predicting Preoperative T Stage of Rectal CarcinomasFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.678441
19
Li Zhao, Meng Liang, Yang Yang, Xinming Zhao, Hongmei Zhang. Histogram models based on intravoxel incoherent motion diffusion-weighted imaging to predict nodal staging of rectal cancerEuropean Journal of Radiology 2021; 142: 109869 doi: 10.1016/j.ejrad.2021.109869
20
Giuseppe Di Costanzo, Raffaele Ascione, Andrea Ponsiglione, Anna Giacoma Tucci, Serena Dell’Aversana, Francesca Iasiello, Enrico Cavaglià. Artificial intelligence and radiomics in magnetic resonance imaging of rectal cancer: a reviewExploration of Targeted Anti-tumor Therapy 2023; : 406 doi: 10.37349/etat.2023.00142
21
Min-Yi Wu, Qi-Jia Han, Zhu Ai, Yu-Ying Liang, Hao-Wen Yan, Qi Xie, Zhi-Ming Xiang. Assessment of chemotherapy resistance changes in human colorectal cancer xenografts in rats based on MRI histogram featuresFrontiers in Oncology 2024; 14 doi: 10.3389/fonc.2024.1301649
22
Chunli Li, Jiandong Yin. Radiomics Based on T2-Weighted Imaging and Apparent Diffusion Coefficient Images for Preoperative Evaluation of Lymph Node Metastasis in Rectal Cancer PatientsFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.671354
23
Mohammed S. Alshuhri, Abdulaziz Alduhyyim, Haitham Al-Mubarak, Ahmad A. Alhulail, Othman I. Alomair, Yahia Madkhali, Rakan A. Alghuraybi, Abdullah M. Alotaibi, Abdullalh G. M. Alqahtani. Investigating the Feasibility of Predicting KRAS Status, Tumor Staging, and Extramural Venous Invasion in Colorectal Cancer Using Inter-Platform Magnetic Resonance Imaging Radiomic FeaturesDiagnostics 2023; 13(23): 3541 doi: 10.3390/diagnostics13233541