These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

163 related articles for article (PubMed ID: 32415344)

  • 1. Differential diagnosis of hypervascular ultra-small renal cell carcinoma and renal angiomyolipoma with minimal fat in early stage by using thin-section multidetector computed tomography.
    Wang X; Song G; Sun J; Shao G
    Abdom Radiol (NY); 2020 Nov; 45(11):3849-3859. PubMed ID: 32415344
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Differentiation of Minimal Fat Angiomyolipoma from Clear Cell Renal Cell Carcinoma.
    Li H; Li A; Zhu H; Hu Y; Li J; Xia L; Hu D; Kamel IR; Li Z
    Acad Radiol; 2019 May; 26(5):632-639. PubMed ID: 30087067
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models: Quantitative biomarkers for differentiating renal clear cell carcinoma and minimal fat angiomyolipoma.
    Li H; Liang L; Li A; Hu Y; Hu D; Li Z; Kamel IR
    J Magn Reson Imaging; 2017 Jul; 46(1):240-247. PubMed ID: 27859853
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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; 21(1):47. PubMed ID: 34225784
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Angiomyolipoma with minimal fat and non-clear cell renal cell carcinoma: differentiation on MDCT using classification and regression tree analysis-based algorithm.
    Woo S; Cho JY; Kim SH; Kim SY
    Acta Radiol; 2014 Dec; 55(10):1258-69. PubMed ID: 24259298
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Early dark cortical band sign on CT for differentiating clear cell renal cell carcinoma from fat poor angiomyolipoma and detecting peritumoral pseudocapsule.
    Ogawa Y; Morita S; Takagi T; Yoshida K; Tanabe K; Nagashima Y; Nishina Y; Sakai S
    Eur Radiol; 2021 Aug; 31(8):5990-5997. PubMed ID: 33559699
    [TBL] [Abstract][Full Text] [Related]  

  • 9. MDCT-based scoring system for differentiating angiomyolipoma with minimal fat from renal cell carcinoma.
    Kim MH; Lee J; Cho G; Cho KS; Kim J; Kim JK
    Acta Radiol; 2013 Dec; 54(10):1201-9. PubMed ID: 23864062
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Can whole-tumor radiomics-based CT analysis better differentiate fat-poor angiomyolipoma from clear cell renal cell caricinoma: compared with conventional CT analysis?
    Ma Y; Cao F; Xu X; Ma W
    Abdom Radiol (NY); 2020 Aug; 45(8):2500-2507. PubMed ID: 31980867
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The value of quantitative CT texture analysis in differentiation of angiomyolipoma without visible fat from clear cell renal cell carcinoma on four-phase contrast-enhanced CT images.
    You MW; Kim N; Choi HJ
    Clin Radiol; 2019 Jul; 74(7):547-554. PubMed ID: 31010583
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 13. [Role of multiphasic multidetector CT imaging in differential diagnosis of small renal cell carcinoma].
    Zhang Y; Gao W; Zhao B; Zhang X
    Zhonghua Zhong Liu Za Zhi; 2015 Nov; 37(11):850-4. PubMed ID: 26887517
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification.
    Lee HS; Hong H; Jung DC; Park S; Kim J
    Med Phys; 2017 Jul; 44(7):3604-3614. PubMed ID: 28376281
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Histogram analysis of small solid renal masses: differentiating minimal fat angiomyolipoma from renal cell carcinoma.
    Chaudhry HS; Davenport MS; Nieman CM; Ho LM; Neville AM
    AJR Am J Roentgenol; 2012 Feb; 198(2):377-83. PubMed ID: 22268181
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Sonographic Features of Small (< 4 cm) Renal Tumors With Low Signal Intensity on T2-Weighted MR Images: Differentiating Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma.
    Park KJ; Kim MH; Kim JK; Cho KS
    AJR Am J Roentgenol; 2018 Sep; 211(3):605-613. PubMed ID: 30040467
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Stepwise algorithm using computed tomography and magnetic resonance imaging for diagnosis of fat-poor angiomyolipoma in small renal masses: Development and external validation.
    Tanaka H; Fujii Y; Tanaka H; Ishioka J; Matsuoka Y; Saito K; Uehara S; Numao N; Yuasa T; Yamamoto S; Masuda H; Yonese J; Kihara K
    Int J Urol; 2017 Jul; 24(7):511-517. PubMed ID: 28600877
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Does Computer-Aided Diagnosis Permit Differentiation of Angiomyolipoma Without Visible Fat From Renal Cell Carcinoma on MDCT?
    Lee Y; Kim JK; Shim W; Sung YS; Cho KS; Shin JH; Kim MH
    AJR Am J Roentgenol; 2015 Sep; 205(3):W305-12. PubMed ID: 26295666
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Morphologic analysis with computed tomography may help differentiate fat-poor angiomyolipoma from renal cell carcinoma: a retrospective study with 602 patients.
    Kim YH; Han K; Oh YT; Jung DC; Cho NH; Park SY
    Abdom Radiol (NY); 2018 Mar; 43(3):647-654. PubMed ID: 28677004
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.