Literature DB >> 28726505

Renal Angiomyolipoma: Radiologic Classification and Imaging Features According to the Amount of Fat.

Byung Kwan Park1.   

Abstract

OBJECTIVE: The purposes of this article are to introduce the radiologic classifications of renal angiomyolipoma (AML) and the clinical implications, to show the imaging features of each type of AML, and to describe which types of AML should be biopsied.
CONCLUSION: Renal AML can be classified according to amount of fat as fat rich, fat poor, or fat invisible. To detect fat, one needs to thoroughly evaluate the entire AML by controlling the size and shape of the ROI. Fat-invisible AML should be biopsied, and fat-poor AML requires further investigation to determine whether biopsy is necessary to differentiate it from renal cell carcinoma. If differentiation between AML and renal cell carcinoma is not clear with CT and MRI, percutaneous biopsy may be performed.

Entities:  

Keywords:  CT; MRI; angiomyolipoma; kidney; sonography

Mesh:

Year:  2017        PMID: 28726505     DOI: 10.2214/AJR.17.17973

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  18 in total

1.  Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

Authors:  Hersh Sagreiya; Alireza Akhbardeh; Dandan Li; Rosa Sigrist; Benjamin I Chung; Geoffrey A Sonn; Lu Tian; Daniel L Rubin; Jürgen K Willmann
Journal:  Ultrasound Med Biol       Date:  2019-05-25       Impact factor: 2.998

2.  A CT-based radiomics nomogram for differentiation of renal angiomyolipoma without visible fat from homogeneous clear cell renal cell carcinoma.

Authors:  Pei Nie; Guangjie Yang; Zhenguang Wang; Lei Yan; Wenjie Miao; Dapeng Hao; Jie Wu; Yujun Zhao; Aidi Gong; Jingjing Cui; Yan Jia; Haitao Niu
Journal:  Eur Radiol       Date:  2019-09-10       Impact factor: 5.315

3.  MR texture analysis in differentiating renal cell carcinoma from lipid-poor angiomyolipoma and oncocytoma.

Authors:  Abdul Razik; Ankur Goyal; Raju Sharma; Devasenathipathy Kandasamy; Amlesh Seth; Prasenjit Das; Balaji Ganeshan
Journal:  Br J Radiol       Date:  2020-08-26       Impact factor: 3.039

Review 4.  Adrenal pheochromocytoma: is it all or the tip of the iceberg?

Authors:  Ke Wang; Guanglei Tang; Yang Peng; Chang Li; Wenhao Fu; Ruixi Li; Jian Guan
Journal:  Jpn J Radiol       Date:  2021-09-21       Impact factor: 2.374

5.  Fat-only Dixon: how to use it in body MRI.

Authors:  Reza Salari; David H Ballard; Mark J Hoegger; Daniel Young; Anup S Shetty
Journal:  Abdom Radiol (NY)       Date:  2022-05-18

6.  Non-Wilms' renal tumors in children: experience with 139 cases treated at a single center.

Authors:  Yi Wei Fang; Hong Cheng Song; Ning Sun; Wei Ping Zhang
Journal:  BMC Urol       Date:  2022-06-22       Impact factor: 2.090

Review 7.  [CEUS-diagnosis of solid renal tumors].

Authors:  K Stock; H Kübler; T Maurer; J Slotta-Huspenina; K Holzapfel
Journal:  Radiologe       Date:  2018-06       Impact factor: 0.635

Review 8.  Diagnostic Imaging for Solid Renal Tumors: A Pictorial Review.

Authors:  Tim J van Oostenbrugge; Jurgen J Fütterer; Peter F A Mulders
Journal:  Kidney Cancer       Date:  2018-08-01

9.  A large bi-lobed classic renal angiomyolipoma with vena caval extension.

Authors:  Nassib F Abou Heidar; Jad A Degheili; Raja B Khauli; George Abi Saad
Journal:  Radiol Case Rep       Date:  2020-02-05

10.  Renal Angiomyolipoma: The Good, the Bad, and the Ugly.

Authors:  Nicolas Vos; Raymond Oyen
Journal:  J Belg Soc Radiol       Date:  2018-04-20       Impact factor: 1.894

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