European Radiology

, Volume 30, Issue 1, pp 1–10 | Cite as

Papillary vs clear cell renal cell carcinoma. Differentiation and grading by iodine concentration using DECT—correlation with microvascular density

  • Julian MarconEmail author
  • Anno Graser
  • David Horst
  • Jozefina Casuscelli
  • Annabel Spek
  • Christian G. Stief
  • Maximilian F. Reiser
  • Johannes Rübenthaler
  • Alexander Buchner
  • Michael Staehler



Various imaging methods have been evaluated regarding non-invasive differentiation of renal cell carcinoma (RCC) subtypes. Dual-energy computed tomography (DECT) allows iodine concentration (IC) analysis as a correlate of tissue perfusion. Microvascular density (MVD) in histopathology specimens is evaluated to determine intratumoral vascularization. The objective of this study was to assess the potential of IC and MVD regarding the differentiation between papillary and clear cell RCC and between well- and dedifferentiated tumors. Further, we aimed to investigate a possible correlation between these parameters.


DECT imaging series of 53 patients with clear cell RCC (ccRCC) and 15 with papillary RCC (pRCC) were analyzed regarding IC. Histology samples were stained using CD31/CD34 monoclonal antibodies; MVD was evaluated digitally. Statistical analysis included performance of Mann-Whitney U test, ROC analysis, and Spearman rank correlation.


Analysis of IC demonstrated significant differences between ccRCC and pRCC (p < 0.001). A cutoff value of ≤ 3.1 mg/ml at IC analysis allowed identification of pRCC with an accuracy of 86.8%. Within the ccRCC subgroup, G1/G2 tumors could significantly be differentiated from G3/G4 carcinomas (p = 0.045). A significant positive correlation between IC and MVD could be determined for the entire RCC cohort and the ccRCC subgroup. Limitations include the small percentage of pRCCs.


IC analysis is a useful method to differentiate pRCC from ccRCC. The significant positive correlation between IC and MVD indicates valid representation of tumor perfusion by DECT.

Key Points

• Analysis of iodine concentration using DECT imaging could reliably distinguish papillary from clear cell subtypes of renal cell cancer (RCC).

• A cutoff value of 3.1 mg/ml allowed a distinction between papillary and clear cell RCCs with an accuracy of 86.8%.

• The positive correlation with microvascular density in tumor specimens indicates correct display of perfusion by iodine concentration analysis.


Carcinoma, renal cell Kidney neoplasms Neovascularization, pathologic Cell differentiation Tomography, X-ray computed 



Area under the curve


Clear cell renal cell carcinoma


Cluster of differentiation


Chromophobe renal cell carcinoma


Computed tomography


Dual-energy computed tomography


Field of view


Hematoxylin and eosin


Hounsfield unit


Kilovoltage peak


Magnetic resonance imaging


Mammalian target of rapamycin


Microvascular density


Papillary renal cell carcinoma


Renal cell carcinoma


Receiver operating characteristic


Vascular endothelial growth factor


Virtual non-contrast


Virtual non-enhanced



The authors state that this work has not received any funding.

Compliance with ethical standards


The scientific guarantor of this publication is Michael Staehler.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.


• Retrospective

• Experimental

• Performed at one institution

Supplementary material

330_2019_6298_MOESM1_ESM.docx (15 mb)
ESM 1 (DOCX 15.0 mb)

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Julian Marcon
    • 1
    Email author
  • Anno Graser
    • 2
  • David Horst
    • 3
  • Jozefina Casuscelli
    • 1
  • Annabel Spek
    • 1
  • Christian G. Stief
    • 1
  • Maximilian F. Reiser
    • 2
  • Johannes Rübenthaler
    • 2
  • Alexander Buchner
    • 1
  • Michael Staehler
    • 1
  1. 1.Department of UrologyLudwig-Maximilians-Universität MünchenMunichGermany
  2. 2.Department of RadiologyLudwig-Maximilians-Universität MünchenMunichGermany
  3. 3.Institute of PathologyLudwig-Maximilians-Universität MünchenMunichGermany

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