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266 related items for PubMed ID: 31070481

  • 1. Use of Iodine Concentration in the Lipid-Poor Portion of the Renal Mass for Differentiation of Angiomyolipoma from Renal Cell Carcinoma.
    Sun J, Zhang XY, Li XT, Li YL, Wang ZL.
    Cancer Biother Radiopharm; 2019 May; 34(4):224-230. PubMed ID: 31070481
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  • 2. Quantitative computer-aided diagnostic algorithm for automated detection of peak lesion attenuation in differentiating clear cell from papillary and chromophobe renal cell carcinoma, oncocytoma, and fat-poor angiomyolipoma on multiphasic multidetector computed tomography.
    Coy H, Young JR, Douek ML, Brown MS, Sayre J, Raman SS.
    Abdom Radiol (NY); 2017 Jul; 42(7):1919-1928. PubMed ID: 28280876
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  • 3. Angiomyolipoma with minimal fat: differentiation from renal cell carcinoma at biphasic helical CT.
    Kim JK, Park SY, Shon JH, Cho KS.
    Radiology; 2004 Mar; 230(3):677-84. PubMed ID: 14990834
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  • 4. Differentiation of Clear Cell Renal Cell Carcinoma From Other Subtypes and Fat-Poor Angiomyolipoma by Use of Quantitative Enhancement Measurement During Three-Phase MDCT.
    Kim SH, Kim CS, Kim MJ, Cho JY, Cho SH.
    AJR Am J Roentgenol; 2016 Jan; 206(1):W21-8. PubMed ID: 26700359
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  • 5. Subjective and objective heterogeneity scores for differentiating small renal masses using contrast-enhanced CT.
    Leng S, Takahashi N, Gomez Cardona D, Kitajima K, McCollough B, Li Z, Kawashima A, Leibovich BC, McCollough CH.
    Abdom Radiol (NY); 2017 May; 42(5):1485-1492. PubMed ID: 28025654
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  • 6. Fat poor angiomyolipoma differentiation from renal cell carcinoma at 320-slice dynamic volume CT perfusion.
    Chen C, Kang Q, Xu B, Shi Z, Guo H, Wei Q, Lu Y, Wu X.
    Abdom Radiol (NY); 2018 May; 43(5):1223-1230. PubMed ID: 28828638
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  • 7. Are there useful CT features to differentiate renal cell carcinoma from lipid-poor renal angiomyolipoma?
    Yang CW, Shen SH, Chang YH, Chung HJ, Wang JH, Lin AT, Chen KK.
    AJR Am J Roentgenol; 2013 Nov; 201(5):1017-28. PubMed ID: 24147472
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  • 10. Angiomyolipoma with minimal fat: differentiation from clear cell renal cell carcinoma and papillary renal cell carcinoma by texture analysis on CT images.
    Yan L, Liu Z, Wang G, Huang Y, Liu Y, Yu Y, Liang C.
    Acad Radiol; 2015 Sep; 22(9):1115-21. PubMed ID: 26031228
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  • 13. Diagnosis of renal angiomyolipoma with hounsfield unit thresholds: effect of size of region of interest and nephrographic phase imaging.
    Davenport MS, Neville AM, Ellis JH, Cohan RH, Chaudhry HS, Leder RA.
    Radiology; 2011 Jul; 260(1):158-65. PubMed ID: 21555349
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  • 14. Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.
    Yang R, Wu J, Sun L, Lai S, Xu Y, Liu X, Ma Y, Zhen X.
    Eur Radiol; 2020 Feb; 30(2):1254-1263. PubMed ID: 31468159
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  • 15. Alkaline phosphatase combines with CT factors for differentiating small (≤ 4 cm) fat-poor angiomyolipoma from renal cell carcinoma: a multiple quantitative tool.
    Peng T, Fan J, Xie B, Wang Q, Chen Y, Li Y, Wu K, Feng C, Li T, Chen H, Pu X, Liu J.
    World J Urol; 2023 May; 41(5):1345-1351. PubMed ID: 37093317
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  • 16. Differentiation of renal angiomyolipoma without visible fat from small clear cell renal cell carcinoma by using specific region of interest on contrast-enhanced CT: a new combination of quantitative tools.
    Wang X, Song G, Jiang H.
    Cancer Imaging; 2021 Jul 05; 21(1):47. PubMed ID: 34225784
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