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For: 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]
Number Citing Articles
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12 Preuss K, Thach N, Liang X, Baine M, Chen J, Zhang C, Du H, Yu H, Lin C, Hollingsworth MA, Zheng D. Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning Applications. Cancers (Basel) 2022;14:1654. [PMID: 35406426 DOI: 10.3390/cancers14071654] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Chen G, Jiang J, Wang X, Yang M, Xie Y, Guo H, Tang H, Zhou L, Hu D, Kamel IR, Chen Z, Li Z. Evaluation of hepatic steatosis before liver transplantation in ex vivo by volumetric quantitative PDFF-MRI. Magn Reson Med 2021;85:2805-14. [PMID: 33197060 DOI: 10.1002/mrm.28592] [Reference Citation Analysis]
14 Chu LC, Park S, Kawamoto S, Yuille AL, Hruban RH, Fishman EK. Pancreatic Cancer Imaging: A New Look at an Old Problem. Curr Probl Diagn Radiol 2021;50:540-50. [PMID: 32988674 DOI: 10.1067/j.cpradiol.2020.08.002] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
15 Liang P, Li S, Xu C, Li J, Tan F, Hu D, Kamel I, Li Z. Assessment of renal function using magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses. Ann Transl Med 2021;9:1614. [PMID: 34926658 DOI: 10.21037/atm-21-2299] [Reference Citation Analysis]
16 Chu LC, Park S, Kawamoto S, Fouladi DF, Shayesteh S, Zinreich ES, Graves JS, Horton KM, Hruban RH, Yuille AL, Kinzler KW, Vogelstein B, Fishman EK. Utility of CT Radiomics Features in Differentiation of Pancreatic Ductal Adenocarcinoma From Normal Pancreatic Tissue. AJR Am J Roentgenol. 2019;213:349-357. [PMID: 31012758 DOI: 10.2214/ajr.18.20901] [Cited by in Crossref: 42] [Cited by in F6Publishing: 24] [Article Influence: 14.0] [Reference Citation Analysis]
17 Virarkar M, Wong VK, Morani AC, Tamm EP, Bhosale P. Update on quantitative radiomics of pancreatic tumors. Abdom Radiol (NY) 2021. [PMID: 34292365 DOI: 10.1007/s00261-021-03216-3] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
18 Liang P, Xu C, Tan F, Li S, Chen M, Hu D, Kamel I, Duan Y, Li Z. Prediction of the World Health Organization Grade of rectal neuroendocrine tumors based on CT histogram analysis. Cancer Med 2021;10:595-604. [PMID: 33263225 DOI: 10.1002/cam4.3628] [Reference Citation Analysis]
19 Bartoli M, Barat M, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Chassagnon G, Soyer P. CT and MRI of pancreatic tumors: an update in the era of radiomics. Jpn J Radiol 2020;38:1111-24. [PMID: 33085029 DOI: 10.1007/s11604-020-01057-6] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 5.5] [Reference Citation Analysis]
20 Hayashi H, Uemura N, Matsumura K, Zhao L, Sato H, Shiraishi Y, Yamashita YI, Baba H. Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma. World J Gastroenterol 2021; 27(43): 7480-7496 [PMID: 34887644 DOI: 10.3748/wjg.v27.i43.7480] [Reference Citation Analysis]
21 Zhang T, Zhang Y, Liu X, Xu H, Chen C, Zhou X, Liu Y, Ma X. Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient's Pathological Grades. Front Oncol 2020;10:521831. [PMID: 33643890 DOI: 10.3389/fonc.2020.521831] [Reference Citation Analysis]
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23 Doan NV, Duc NM, Ngan VK, Anh NV, Khuyen HK, Nhan NT, Giang BV, Thong PM. Hypovascular pancreatic neuroendocrine tumor with hepatic metastases: A case report and literature review. Radiol Case Rep 2021;16:1424-7. [PMID: 33912257 DOI: 10.1016/j.radcr.2021.03.024] [Reference Citation Analysis]
24 Thomasian NM, Kamel IR, Bai HX. Machine intelligence in non-invasive endocrine cancer diagnostics. Nat Rev Endocrinol 2021. [PMID: 34754064 DOI: 10.1038/s41574-021-00543-9] [Reference Citation Analysis]
25 Yu H, Huang Z, Li M, Wei Y, Zhang L, Yang C, Zhang Y, Song B. Differential Diagnosis of Nonhypervascular Pancreatic Neuroendocrine Neoplasms From Pancreatic Ductal Adenocarcinomas, Based on Computed Tomography Radiological Features and Texture Analysis. Acad Radiol 2020;27:332-41. [PMID: 31495760 DOI: 10.1016/j.acra.2019.06.012] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]
26 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]
27 Han X, Yang J, Luo J, Chen P, Zhang Z, Alu A, Xiao Y, Ma X. Application of CT-Based Radiomics in Discriminating Pancreatic Cystadenomas From Pancreatic Neuroendocrine Tumors Using Machine Learning Methods. Front Oncol 2021;11:606677. [PMID: 34367940 DOI: 10.3389/fonc.2021.606677] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
28 Liu K, Wu T, Chen P, Tsai YM, Roth H, Wu M, Liao W, Wang W. Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation. The Lancet Digital Health 2020;2:e303-13. [DOI: 10.1016/s2589-7500(20)30078-9] [Cited by in Crossref: 23] [Cited by in F6Publishing: 10] [Article Influence: 11.5] [Reference Citation Analysis]
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30 Ding L, Wu S, Shen Y, Hu X, Hu D, Kamel I, Li Z. Primary Gastro-Intestinal Lymphoma and Gastro-Intestinal Adenocarcinoma: An Initial Study of CT Texture Analysis as Quantitative Biomarkers for Differentiation. Life (Basel) 2021;11:264. [PMID: 33806817 DOI: 10.3390/life11030264] [Reference Citation Analysis]
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32 Reinert CP, Baumgartner K, Hepp T, Bitzer M, Horger M. Complementary role of computed tomography texture analysis for differentiation of pancreatic ductal adenocarcinoma from pancreatic neuroendocrine tumors in the portal-venous enhancement phase. Abdom Radiol (NY) 2020;45:750-8. [PMID: 31953587 DOI: 10.1007/s00261-020-02406-9] [Cited by in Crossref: 13] [Cited by in F6Publishing: 7] [Article Influence: 6.5] [Reference Citation Analysis]