BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Li Y, Yan C, Weng S, Shi Z, Sun H, Chen J, Xu X, Ye R, Hong J. Texture analysis of multi-phase MRI images to detect expression of Ki67 in hepatocellular carcinoma. Clin Radiol 2019;74:813.e19-27. [PMID: 31362887 DOI: 10.1016/j.crad.2019.06.024] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 3.3] [Reference Citation Analysis]
Number Citing Articles
1 Weng S, Xu X, Li Y, Yan C, Chen J, Ye R, Zhu Y, Wen L, Hong J. Quantitative analysis of multiphase magnetic resonance images may assist prediction of histopathological grade of small hepatocellular carcinoma. Ann Transl Med 2020;8:1023. [PMID: 32953823 DOI: 10.21037/atm-20-2874] [Reference Citation Analysis]
2 Fan Y, Yu Y, Wang X, Hu M, Hu C. Radiomic analysis of Gd-EOB-DTPA-enhanced MRI predicts Ki-67 expression in hepatocellular carcinoma. BMC Med Imaging 2021;21:100. [PMID: 34130644 DOI: 10.1186/s12880-021-00633-0] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
3 Zhao YF, Xiong X, Chen K, Tang W, Yang X, Shi ZR. Evaluation of the Therapeutic Effect of Adjuvant Transcatheter Arterial Chemoembolization Based on Ki67 After Hepatocellular Carcinoma Surgery. Front Oncol 2021;11:605234. [PMID: 33718156 DOI: 10.3389/fonc.2021.605234] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Hu MJ, Yu YX, Fan YF, Hu CH. CT-based radiomics model to distinguish necrotic hepatocellular carcinoma from pyogenic liver abscess. Clin Radiol 2021;76:161.e11-7. [PMID: 33267948 DOI: 10.1016/j.crad.2020.11.002] [Reference Citation Analysis]
5 Harding-Theobald E, Louissaint J, Maraj B, Cuaresma E, Townsend W, Mendiratta-Lala M, Singal AG, Su GL, Lok AS, Parikh ND. Systematic review: radiomics for the diagnosis and prognosis of hepatocellular carcinoma. Aliment Pharmacol Ther 2021;54:890-901. [PMID: 34390014 DOI: 10.1111/apt.16563] [Reference Citation Analysis]
6 Cannella R, Sartoris R, Grégory J, Garzelli L, Vilgrain V, Ronot M, Dioguardi Burgio M. Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice. Br J Radiol 2021;94:20210220. [PMID: 33989042 DOI: 10.1259/bjr.20210220] [Reference Citation Analysis]
7 Shi G, Han X, Wang Q, Ding Y, Liu H, Zhang Y, Dai Y. Evaluation of Multiple Prognostic Factors of Hepatocellular Carcinoma with Intra-Voxel Incoherent Motions Imaging by Extracting the Histogram Metrics. Cancer Manag Res 2020;12:6019-31. [PMID: 32765101 DOI: 10.2147/CMAR.S262973] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
8 Ye Z, Cao L, Wei Y, Chen J, Zhang Z, Yao S, Duan T, Song B. Preoperative prediction of hepatocellular carcinoma with highly aggressive characteristics using quantitative parameters derived from hepatobiliary phase MR images. Ann Transl Med 2020;8:85. [PMID: 32175378 DOI: 10.21037/atm.2020.01.04] [Reference Citation Analysis]
9 Geng Z, Zhang Y, Wang S, Li H, Zhang C, Yin S, Xie C, Dai Y. Radiomics Analysis of Susceptibility Weighted Imaging for Hepatocellular Carcinoma: Exploring the Correlation between Histopathology and Radiomics Features. Magn Reson Med Sci 2021;20:253-63. [PMID: 32788505 DOI: 10.2463/mrms.mp.2020-0060] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
10 Gong XQ, Tao YY, Wu YK, Liu N, Yu X, Wang R, Zheng J, Liu N, Huang XH, Li JD, Yang G, Wei XQ, Yang L, Zhang XM. Progress of MRI Radiomics in Hepatocellular Carcinoma. Front Oncol 2021;11:698373. [PMID: 34616673 DOI: 10.3389/fonc.2021.698373] [Reference Citation Analysis]
11 Feng M, Zhang M, Liu Y, Jiang N, Meng Q, Wang J, Yao Z, Gan W, Dai H. Texture analysis of MR images to identify the differentiated degree in hepatocellular carcinoma: a retrospective study. BMC Cancer 2020;20:611. [PMID: 32605628 DOI: 10.1186/s12885-020-07094-8] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]