220 related articles for article (PubMed ID: 28677004)
1. 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]
2. 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]
3. Angiomyolipoma with minimal fat: differentiation of morphological and enhancement features from renal cell carcinoma at CT imaging.
Sung CK; Kim SH; Woo S; Moon MH; Kim SY; Kim SH; Cho JY
Acta Radiol; 2016 Sep; 57(9):1114-22. PubMed ID: 26663389
[TBL] [Abstract][Full Text] [Related]
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
[TBL] [Abstract][Full Text] [Related]
5. 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
[TBL] [Abstract][Full Text] [Related]
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
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Differentiation between papillary renal cell carcinoma and fat-poor angiomyolipoma: a preliminary study assessing detection of intratumoral hemorrhage with chemical shift MRI and T2*-weighted gradient echo.
Woo S; Kim SY; Cho JY; Kim SH
Acta Radiol; 2018 May; 59(5):627-634. PubMed ID: 29069911
[TBL] [Abstract][Full Text] [Related]
9. Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma.
Yang G; Gong A; Nie P; Yan L; Miao W; Zhao Y; Wu J; Cui J; Jia Y; Wang Z
Mol Imaging; 2019; 18():1536012119883161. PubMed ID: 31625454
[TBL] [Abstract][Full Text] [Related]
10. CT differentiation of fat-poor angiomyolipomas from papillary renal cell carcinomas: development of a predictive model.
Salvador R; Sebastià M; Cárdenas G; Páez-Carpio A; Paño B; Solé M; Nicolau C
Abdom Radiol (NY); 2021 Jul; 46(7):3280-3287. PubMed ID: 33674961
[TBL] [Abstract][Full Text] [Related]
11. The value of CT features and demographic data in the differential diagnosis of type 2 papillary renal cell carcinoma from fat-poor angiomyolipoma and oncocytoma.
Zhou C; Ban X; Luo L; Shi C
Abdom Radiol (NY); 2022 Nov; 47(11):3838-3846. PubMed ID: 36085376
[TBL] [Abstract][Full Text] [Related]
12. 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
[No Abstract] [Full Text] [Related]
13. Diagnostic performance of the "drooping" sign in CT diagnosis of exophytic renal angiomyolipoma.
Shen L; Nawaz R; Tse JR; Negrete LM; Lubner MG; Toia GV; Liang T; Wentland AL; Kamaya A
Abdom Radiol (NY); 2023 Jun; 48(6):2091-2101. PubMed ID: 36947205
[TBL] [Abstract][Full Text] [Related]
14. Quantitative Analysis of Multiphase Contrast-Enhanced CT Images: A Pilot Study of Preoperative Prediction of Fat-Poor Angiomyolipoma and Renal Cell Carcinoma.
Tang Z; Yu D; Ni T; Zhao T; Jin Y; Dong E
AJR Am J Roentgenol; 2020 Feb; 214(2):370-382. PubMed ID: 31799870
[No Abstract] [Full Text] [Related]
15. 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]
16. Differentiation of clear from non-clear cell renal cell carcinoma using CT washout formula.
Kopp RP; Aganovic L; Palazzi KL; Cassidy FH; Sakamoto K; Derweesh IH
Can J Urol; 2013 Jun; 20(3):6790-7. PubMed ID: 23783049
[TBL] [Abstract][Full Text] [Related]
17. Utility of radiomics features of diffusion-weighted magnetic resonance imaging for differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma: model development and external validation.
Matsumoto S; Arita Y; Yoshida S; Fukushima H; Kimura K; Yamada I; Tanaka H; Yagi F; Yokoyama M; Matsuoka Y; Oya M; Tateishi U; Jinzaki M; Fujii Y
Abdom Radiol (NY); 2022 Jun; 47(6):2178-2186. PubMed ID: 35426498
[TBL] [Abstract][Full Text] [Related]
18. Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.
Feng Z; Rong P; Cao P; Zhou Q; Zhu W; Yan Z; Liu Q; Wang W
Eur Radiol; 2018 Apr; 28(4):1625-1633. PubMed ID: 29134348
[TBL] [Abstract][Full Text] [Related]
19. Angiomyolipomas that do not contain fat attenuation at unenhanced CT.
Jinzaki M; Silverman SG; Tanimoto A; Shinmoto H; Kuribayashi S
Radiology; 2005 Jan; 234(1):311; author reply 311-2. PubMed ID: 15618388
[No Abstract] [Full Text] [Related]
20. Differential diagnosis and prognosis of small renal masses: association with collateral vessels detected using contrast-enhanced computed tomography.
Yanagi M; Kiriyama T; Akatsuka J; Endo Y; Takeda H; Katsu A; Honda Y; Suzuki K; Nishikawa Y; Ikuma S; Mikami H; Toyama Y; Kimura G; Kondo Y
BMC Cancer; 2022 Aug; 22(1):856. PubMed ID: 35932010
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
