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For: Canellas R, Mehrkhani F, Patino M, Kambadakone A, Sahani D. Characterization of Portal Vein Thrombosis (Neoplastic Versus Bland) on CT Images Using Software-Based Texture Analysis and Thrombus Density (Hounsfield Units). AJR Am J Roentgenol. 2016;207:W81-W87. [PMID: 27490095 DOI: 10.2214/ajr.15.15928] [Cited by in Crossref: 28] [Cited by in F6Publishing: 11] [Article Influence: 4.7] [Reference Citation Analysis]
Number Citing Articles
1 Wang Z, Chen X, Wang J, Cui W, Ren S, Wang Z. Differentiating hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinoma based on CT texture analysis. Acta Radiol 2020;61:595-604. [PMID: 31522519 DOI: 10.1177/0284185119875023] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
2 Feng P, Wang ZD, Fan W, Liu H, Pan JJ. Diagnostic advances of artificial intelligence and radiomics in gastroenterology. Artif Intell Gastroenterol 2020; 1(2): 37-50 [DOI: 10.35712/aig.v1.i2.37] [Reference Citation Analysis]
3 Minoda AM, Cadete RBF, Teixeira SR, Muglia VF, Elias Junior J, de Melo-Leite AF. The ABCD of portal vein thrombosis: a systematic approach. Radiol Bras 2020;53:424-9. [PMID: 33304012 DOI: 10.1590/0100-3984.2019.0109] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Bae JS, Lee JM, Yoon JH, Jang S, Chung JW, Lee KB, Yi NJ, Lee JH. How to Best Detect Portal Vein Tumor Thrombosis in Patients with Hepatocellular Carcinoma Meeting the Milan Criteria: Gadoxetic Acid-Enhanced MRI versus Contrast-Enhanced CT. Liver Cancer 2020;9:293-307. [PMID: 32647632 DOI: 10.1159/000505191] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
5 Mähringer-Kunz A, Meyer FI, Hahn F, Müller L, Düber C, Pinto Dos Santos D, Galle PR, Weinmann A, Kloeckner R, Schotten S. Hepatic vein tumor thrombosis in patients with hepatocellular carcinoma: Prevalence and clinical significance. United European Gastroenterol J 2021;9:590-7. [PMID: 34077613 DOI: 10.1002/ueg2.12098] [Reference Citation Analysis]
6 Wijnen N, Brouwers L, Jebbink EG, Heyligers JMM, Bemelman M. Comparison of segmentation software packages for in-hospital 3D print workflow. J Med Imaging (Bellingham) 2021;8:034004. [PMID: 34222558 DOI: 10.1117/1.JMI.8.3.034004] [Reference Citation Analysis]
7 Wei J, Jiang H, Gu D, Niu M, Fu F, Han Y, Song B, Tian J. Radiomics in liver diseases: Current progress and future opportunities. Liver Int 2020;40:2050-63. [PMID: 32515148 DOI: 10.1111/liv.14555] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
8 Cannella R, Taibbi A, Porrello G, Dioguardi Burgio M, Cabibbo G, Bartolotta TV. Hepatocellular carcinoma with macrovascular invasion: multimodality imaging features for the diagnosis. Diagn Interv Radiol 2020;26:531-40. [PMID: 32990243 DOI: 10.5152/dir.2020.19569] [Cited by in Crossref: 4] [Article Influence: 2.0] [Reference Citation Analysis]
9 Li Y, Xu X, Weng S, Yan C, Chen J, Ye R. CT Image-Based Texture Analysis to Predict Microvascular Invasion in Primary Hepatocellular Carcinoma. J Digit Imaging 2020;33:1365-75. [PMID: 32968880 DOI: 10.1007/s10278-020-00386-2] [Reference Citation Analysis]
10 Shukla A, Giri S. Portal Vein Thrombosis in Cirrhosis. Journal of Clinical and Experimental Hepatology 2021. [DOI: 10.1016/j.jceh.2021.11.003] [Reference Citation Analysis]
11 David A, Frampas E, Douane F, Perret C, Leaute F, Cantarovich D, Karam G, Branchereau J. Management of vascular and nonvascular complications following pancreas transplantation with interventional radiology. Diagn Interv Imaging 2020;101:629-38. [PMID: 32089482 DOI: 10.1016/j.diii.2020.02.002] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
12 Corrias G, Micheletti G, Barberini L, Suri JS, Saba L. Texture analysis imaging "what a clinical radiologist needs to know". Eur J Radiol 2022;146:110055. [PMID: 34902669 DOI: 10.1016/j.ejrad.2021.110055] [Reference Citation Analysis]
13 Ren S, Li Q, Liu S, Qi Q, Duan S, Mao B, Li X, Wu Y, Zhang L. Clinical Value of Machine Learning-Based Ultrasomics in Preoperative Differentiation Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: A Multicenter Study. Front Oncol 2021;11:749137. [PMID: 34804935 DOI: 10.3389/fonc.2021.749137] [Reference Citation Analysis]
14 Hu W, Yang H, Xu H, Mao Y. Radiomics based on artificial intelligence in liver diseases: where we are? Gastroenterol Rep (Oxf) 2020;8:90-7. [PMID: 32280468 DOI: 10.1093/gastro/goaa011] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 4.0] [Reference Citation Analysis]
15 Cerrito L, Annicchiarico BE, Iezzi R, Gasbarrini A, Pompili M, Ponziani FR. Treatment of hepatocellular carcinoma in patients with portal vein tumor thrombosis: Beyond the known frontiers. World J Gastroenterol 2019; 25(31): 4360-4382 [PMID: 31496618 DOI: 10.3748/wjg.v25.i31.4360] [Cited by in CrossRef: 29] [Cited by in F6Publishing: 20] [Article Influence: 9.7] [Reference Citation Analysis]
16 Khan AR, Wei X, Xu X. Portal Vein Tumor Thrombosis and Hepatocellular Carcinoma - The Changing Tides. J Hepatocell Carcinoma 2021;8:1089-115. [PMID: 34522691 DOI: 10.2147/JHC.S318070] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
17 Li J, Lu J, Liang P, Li A, Hu Y, Shen Y, Hu D, Li Z. Differentiation of atypical pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas: Using whole-tumor CT texture analysis as quantitative biomarkers. Cancer Med 2018;7:4924-31. [PMID: 30151864 DOI: 10.1002/cam4.1746] [Cited by in Crossref: 24] [Cited by in F6Publishing: 24] [Article Influence: 6.0] [Reference Citation Analysis]
18 Vasilakis GM, Lakhani DA, Adelanwa A, Hogg JP, Kim C. Atypical imaging presentation of a massive intracavitary cardiac thrombus: A case report and brief review of the literature. Radiol Case Rep 2021;16:2847-52. [PMID: 34401011 DOI: 10.1016/j.radcr.2021.06.089] [Reference Citation Analysis]