Imaging of Renal Cancer

Satheesh Krishna, Ashley Leckie, Ania Kielar, Robert Hartman, Ashish Khandelwal

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Renal masses are common incidental findings on cross-sectional imaging. Accurate characterization of renal masses is essential to guide management. Renal mass CT protocol comprises of a good quality noncontrast, corticomedullary and nephrographic phases, with each phase providing complementary information for diagnosis. Attenuation measurements in different phases are central to the ‘golden-rules’ in renal mass imaging in the characterization of renal masses. Newer modalities like dual energy CT scan obviate need for repeat imaging by generation of iodine-overlay image and also help in eliminating artifactual pseudoenhancement which can be problematic, especially in small endophytic cysts. Contrast- enhanced ultrasound (CEUS) is extremely sensitive in identification of enhancing components in indeterminate masses, especially in the setting of renal failure as the microbubbles are not excreted via the renal route. The Bosniak classification for renal cystic masses has been revised in 2019 to standardize terminology and further improve upon the original version. The current version includes CT and MRI, although CEUS is yet to be included. Image- guided biopsy of renal mass helps confirm the diagnosis and also gives information regarding the subtype and grading and is useful in avoiding overtreatment of benign entities, and in active surveillance. Multiparametric MRI can potentially help avoid needle biopsy in a subset of patients by accurate characterization through a previously validated algorithm.

Original languageEnglish (US)
Pages (from-to)152-169
Number of pages18
JournalSeminars in Ultrasound, CT and MRI
Volume41
Issue number2
DOIs
StatePublished - Apr 2020

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Fingerprint

Dive into the research topics of 'Imaging of Renal Cancer'. Together they form a unique fingerprint.

Cite this