For: | Li XL, Shi LX, Du QC, Wang W, Shao LW, Wang YW. Magnetic resonance imaging features of minimal-fat angiomyolipoma and causes of preoperative misdiagnosis. World J Clin Cases 2020; 8(12): 2502-2509 [PMID: 32607327 DOI: 10.12998/wjcc.v8.i12.2502] |
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URL: | https://www.wjgnet.com/2307-8960/full/v8/i12/2502.htm |
Number | Citing Articles |
1 |
Ruiting Wang, Lianting Zhong, Pingyi Zhu, Xianpan Pan, Lei Chen, Jianjun Zhou, Yuqin Ding. MRI-based radiomics machine learning model to differentiate non-clear cell renal cell carcinoma from benign renal tumors. European Journal of Radiology Open 2024; 13: 100608 doi: 10.1016/j.ejro.2024.100608
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2 |
Özlem Akıncı, Furkan Türkoğlu, Mustafa Orhan Nalbant, Ercan İnci. Differentiating Renal Cell Carcinoma and Minimal Fat Angiomyolipoma with Volumetric MRI Histogram Analysis. Bakirkoy Tip Dergisi / Medical Journal of Bakirkoy 2023; 19(3): 256 doi: 10.4274/BMJ.galenos.2023.2023.3-19
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3 |
Lian Jian, Yan Liu, Yu Xie, Shusuan Jiang, Mingji Ye, Huashan Lin. MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.876664
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4 |
Yun Xu, Qingxuan Wan, Xihui Ren, Yutao Jiang, Fang Wang, Jing Yao, Peng Wu, Aijun Shen, Peijun Wang. Amide proton transfer-weighted MRI for renal tumors: Comparison with diffusion-weighted imaging. Magnetic Resonance Imaging 2024; 106: 104 doi: 10.1016/j.mri.2023.12.002
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