Fat status detection and histotypes differentiation in solid renal masses using Dixon technique

Jun Sun, Zhaoyu Xing, Jie Chen, Tingting Zha, Yunjie Cao, Dachuan Zhang, Dexing Zeng, Wei Xing

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Purpose: To detect fat status and differentiate histotypes of renal masses by using Dixon technique. Materials and methods: This study included 134 solid renal masses. Signal intensity index (SII) and fat fraction (FF) in different histotypes were compared. Results: Only angiomyolipoma (AML), clear cell renal cell carcinoma (RCC), and papillary RCC were confirmed to contain fat. The FF of 16.8% can effectively differentiate AML from clear cell RCC, so did the SII of 9.2% can differentiate clear cell RCC from non-clear cell RCC and rare benign histotypes. Conclusion: Dixon technique successfully evaluated the fat status and histotypes of renal masses.

Original languageEnglish (US)
Pages (from-to)12-22
Number of pages11
JournalClinical Imaging
Volume51
DOIs
StatePublished - Sep 2018

Keywords

  • Dixon technique
  • Fat status
  • Histotype
  • Solid renal masses

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Fingerprint

Dive into the research topics of 'Fat status detection and histotypes differentiation in solid renal masses using Dixon technique'. Together they form a unique fingerprint.

Cite this