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Cited by in F6Publishing
For: Xu Y, Xu Q, Ma Y, Duan J, Zhang H, Liu T, Li L, Sun H, Shi K, Xie S, Wang W. Characterizing MRI features of rectal cancers with different KRAS status.BMC Cancer. 2019;19:1111. [PMID: 31727020 DOI: 10.1186/s12885-019-6341-6] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 3.3] [Reference Citation Analysis]
Number Citing Articles
1 Tripathi P, Hai Y, Li Z, Shen Y, Hu X, Hu D. Morphometric assessment of the mesorectal fat in Chinese Han population: A clinical MRI study. Sci Prog 2021;104:368504211016214. [PMID: 33960865 DOI: 10.1177/00368504211016214] [Reference Citation Analysis]
2 Zhang S, Yu M, Chen D, Li P, Tang B, Li J. Role of MRI‑based radiomics in locally advanced rectal cancer (Review). Oncol Rep 2022;47:34. [PMID: 34935061 DOI: 10.3892/or.2021.8245] [Reference Citation Analysis]
3 Badic B, Tixier F, Cheze Le Rest C, Hatt M, Visvikis D. Radiogenomics in Colorectal Cancer. Cancers (Basel) 2021;13:973. [PMID: 33652647 DOI: 10.3390/cancers13050973] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
4 Crimì F, Capelli G, Spolverato G, Bao QR, Florio A, Milite Rossi S, Cecchin D, Albertoni L, Campi C, Pucciarelli S, Stramare R. MRI T2-weighted sequences-based texture analysis (TA) as a predictor of response to neoadjuvant chemo-radiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). Radiol med 2020;125:1216-24. [DOI: 10.1007/s11547-020-01215-w] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
5 Ciardiello F, Ciardiello D, Martini G, Napolitano S, Tabernero J, Cervantes A. Clinical management of metastatic colorectal cancer in the era of precision medicine. CA Cancer J Clin 2022. [PMID: 35472088 DOI: 10.3322/caac.21728] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Lu ZH, Xia KJ, Jiang H, Jiang JL, Wu M. Textural differences based on apparent diffusion coefficient maps for discriminating pT3 subclasses of rectal adenocarcinoma. World J Clin Cases 2021; 9(24): 6987-6998 [PMID: 34540954 DOI: 10.12998/wjcc.v9.i24.6987] [Reference Citation Analysis]
7 Bonde A, Smith DA, Kikano E, Yoest JM, Tirumani SH, Ramaiya NH. Overview of serum and tissue markers in colorectal cancer: a primer for radiologists. Abdom Radiol (NY) 2021;46:5521-35. [PMID: 34415413 DOI: 10.1007/s00261-021-03243-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Song K, Zhao Z, Wang J, Qiang Y, Zhao J, Zia MB. Segmentation-based multi-scale attention model for KRAS mutation prediction in rectal cancer. Int J Mach Learn & Cyber . [DOI: 10.1007/s13042-021-01447-w] [Reference Citation Analysis]
9 Fernandes MC, Horvat N. Editorial for "A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Prediction of KRAS Mutation in Rectal Cancer". J Magn Reson Imaging 2022. [PMID: 35575434 DOI: 10.1002/jmri.28233] [Reference Citation Analysis]
10 Capelli G, Campi C, Bao QR, Morra F, Lacognata C, Zucchetta P, Cecchin D, Pucciarelli S, Spolverato G, Crimì F. 18F-FDG-PET/MRI texture analysis in rectal cancer after neoadjuvant chemoradiotherapy. Nucl Med Commun 2022. [PMID: 35471653 DOI: 10.1097/MNM.0000000000001570] [Reference Citation Analysis]
11 Qi Y, Zhao T, Han M. The application of radiomics in predicting gene mutations in cancer. Eur Radiol. [DOI: 10.1007/s00330-021-08520-6] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
12 Hu J, Xia X, Wang P, Peng Y, Liu J, Xie X, Liao Y, Wan Q, Li X. Predicting Kirsten Rat Sarcoma Virus Gene Mutation Status in Patients With Colorectal Cancer by Radiomics Models Based on Multiphasic CT. Front Oncol 2022;12:848798. [DOI: 10.3389/fonc.2022.848798] [Reference Citation Analysis]
13 Stanzione A, Verde F, Romeo V, Boccadifuoco F, Mainenti PP, Maurea S. Radiomics and machine learning applications in rectal cancer: Current update and future perspectives. World J Gastroenterol 2021; 27(32): 5306-5321 [PMID: 34539134 DOI: 10.3748/wjg.v27.i32.5306] [Reference Citation Analysis]
14 Coppola F, Giannini V, Gabelloni M, Panic J, Defeudis A, Lo Monaco S, Cattabriga A, Cocozza MA, Pastore LV, Polici M, Caruso D, Laghi A, Regge D, Neri E, Golfieri R, Faggioni L. Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice. Diagnostics (Basel) 2021;11:756. [PMID: 33922483 DOI: 10.3390/diagnostics11050756] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
15 Zhang Z, Shen L, Wang Y, Wang J, Zhang H, Xia F, Wan J, Zhang Z. MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients. Front Oncol 2021;11:614052. [PMID: 34026605 DOI: 10.3389/fonc.2021.614052] [Reference Citation Analysis]