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For: Mainenti PP, Stanzione A, Guarino S, Romeo V, Ugga L, Romano F, Storto G, Maurea S, Brunetti A. Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging. World J Gastroenterol 2019; 25(35): 5233-5256 [PMID: 31558870 DOI: 10.3748/wjg.v25.i35.5233] [Cited by in CrossRef: 17] [Cited by in F6Publishing: 16] [Article Influence: 5.7] [Reference Citation Analysis]
Number Citing Articles
1 Mirshahvalad SA, Hinzpeter R, Kohan A, Anconina R, Kulanthaivelu R, Ortega C, Metser U, Veit-Haibach P. Diagnostic performance of [18F]-FDG PET/MR in evaluating colorectal cancer: a systematic review and meta-analysis. Eur J Nucl Med Mol Imaging 2022. [PMID: 35705874 DOI: 10.1007/s00259-022-05871-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Wang J, Chen J, Zhou R, Gao Y, Li J. Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients. BMC Cancer 2022;22:420. [PMID: 35439946 DOI: 10.1186/s12885-022-09518-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
3 Al Ghamdi SS, Leeds I, Fang S, Ngamruengphong S. Minimally Invasive Endoscopic and Surgical Management of Rectal Neoplasia. Cancers (Basel) 2022;14:948. [PMID: 35205695 DOI: 10.3390/cancers14040948] [Reference Citation Analysis]
4 Mainenti PP, Stanzione A, Cuocolo R, Grosso RD, Danzi R, Romeo V, Raffone A, Sardo ADS, Giordano E, Travaglino A, Insabato L, Scaglione M, Maurea S, Brunetti A. MRI radiomics: a machine learning approach for the risk stratification of endometrial cancer patients. European Journal of Radiology 2022. [DOI: 10.1016/j.ejrad.2022.110226] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
5 Maclean D, Tsakok M, Gleeson F, Breen DJ, Goldin R, Primrose J, Harris A, Franklin J. Comprehensive Imaging Characterization of Colorectal Liver Metastases. Front Oncol 2021;11:730854. [PMID: 34950575 DOI: 10.3389/fonc.2021.730854] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
6 García-figueiras R, Baleato-gonzález S, Canedo-antelo M, Alcalá L, Marhuenda A. Imaging Advances on CT and MRI in Colorectal Cancer. Curr Colorectal Cancer Rep 2021;17:113-30. [DOI: 10.1007/s11888-021-00468-5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 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] [Cited by in CrossRef: 8] [Cited by in F6Publishing: 7] [Article Influence: 8.0] [Reference Citation Analysis]
8 Stanzione A, Cuocolo R, Verde F, Galatola R, Romeo V, Mainenti PP, Aprea G, Guadagno E, Del Basso De Caro M, Maurea S. Handcrafted MRI radiomics and machine learning: Classification of indeterminate solid adrenal lesions. Magn Reson Imaging 2021;79:52-8. [PMID: 33727148 DOI: 10.1016/j.mri.2021.03.009] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 10.0] [Reference Citation Analysis]
9 Jansen-Winkeln B, Barberio M, Chalopin C, Schierle K, Diana M, Köhler H, Gockel I, Maktabi M. Feedforward Artificial Neural Network-Based Colorectal Cancer Detection Using Hyperspectral Imaging: A Step towards Automatic Optical Biopsy. Cancers (Basel) 2021;13:967. [PMID: 33669082 DOI: 10.3390/cancers13050967] [Cited by in Crossref: 24] [Cited by in F6Publishing: 24] [Article Influence: 24.0] [Reference Citation Analysis]
10 Behrenbruch C, Prabhakaran S, Udayasiri D D, Michael M, Hollande F, Hayes I, Heriot AG, Knowles B, Thomson BN. Association between imaging response and survival following neoadjuvant chemotherapy in patients with resectable colorectal liver metastases: A cohort study. J Surg Oncol 2021;123:1263-73. [PMID: 33524184 DOI: 10.1002/jso.26400] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
11 Fusco R, Granata V, Petrillo A. Introduction to Special Issue of Radiology and Imaging of Cancer. Cancers (Basel) 2020;12:E2665. [PMID: 32961946 DOI: 10.3390/cancers12092665] [Cited by in Crossref: 12] [Cited by in F6Publishing: 12] [Article Influence: 6.0] [Reference Citation Analysis]
12 Stock C. How Dysregulated Ion Channels and Transporters Take a Hand in Esophageal, Liver, and Colorectal Cancer. Rev Physiol Biochem Pharmacol 2020. [PMID: 32875386 DOI: 10.1007/112_2020_41] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
13 Deleu AL, Sathekge MJ, Maes A, De Spiegeleer B, Sathekge M, Van de Wiele C. Characterization of FDG PET Images Using Texture Analysis in Tumors of the Gastro-Intestinal Tract: A Review. Biomedicines 2020;8:E304. [PMID: 32846986 DOI: 10.3390/biomedicines8090304] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
14 Sandach P, Kasper-Virchow S, Rischpler C, Herrmann K. Molecular Imaging and Therapy of Colorectal and Anal Cancer. Semin Nucl Med 2020;50:465-70. [PMID: 32768009 DOI: 10.1053/j.semnuclmed.2020.04.003] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]