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For: Ippolito D, Drago SG, Franzesi CT, Fior D, Sironi S. Rectal cancer staging: Multidetector-row computed tomography diagnostic accuracy in assessment of mesorectal fascia invasion. World J Gastroenterol 2016; 22(20): 4891-4900 [PMID: 27239115 DOI: 10.3748/wjg.v22.i20.4891] [Cited by in CrossRef: 9] [Cited by in F6Publishing: 6] [Article Influence: 1.8] [Reference Citation Analysis]
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4 Mahadevan LS, Zhong J, Venkatesulu B, Kaur H, Bhide S, Minsky B, Chu W, Intven M, van der Heide UA, van Triest B, Krishnan S, Hall WA. Imaging predictors of treatment outcomes in rectal cancer: An overview. Critical Reviews in Oncology/Hematology 2018;129:153-62. [DOI: 10.1016/j.critrevonc.2018.06.009] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
5 Ippolito D, Drago SG, Talei Franzesi CR, Casiraghi A, Sironi S. Diagnostic value of fourth-generation iterative reconstruction algorithm with low-dose CT protocol in assessment of mesorectal fascia invasion in rectal cancer: comparison with magnetic resonance. Abdom Radiol 2017;42:2251-60. [DOI: 10.1007/s00261-017-1138-z] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 0.8] [Reference Citation Analysis]
6 Liu S, Yu X, Yang S, Hu P, Hu Y, Chen X, Li Y, Zhang Z, Li C, Lu Q. Machine Learning-Based Radiomics Nomogram for Detecting Extramural Venous Invasion in Rectal Cancer. Front Oncol 2021;11:610338. [PMID: 33842316 DOI: 10.3389/fonc.2021.610338] [Reference Citation Analysis]