Skip to main content

Advertisement

SpringerLink
Log in

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

  • Urogenital
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

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.

Methods

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.

Results

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.

Conclusions

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

AUC:

Area under the curve

ccRCC:

Clear cell renal cell carcinoma

CD:

Cluster of differentiation

chRCC:

Chromophobe renal cell carcinoma

CT:

Computed tomography

DECT:

Dual-energy computed tomography

FOV:

Field of view

H&E:

Hematoxylin and eosin

HU:

Hounsfield unit

kVp:

Kilovoltage peak

MRI:

Magnetic resonance imaging

mTOR:

Mammalian target of rapamycin

MVD:

Microvascular density

pRCC:

Papillary renal cell carcinoma

RCC:

Renal cell carcinoma

ROC:

Receiver operating characteristic

VEGF:

Vascular endothelial growth factor

VNC:

Virtual non-contrast

VNE:

Virtual non-enhanced

Reference list

  1. Ljungberg B, Campbell SC, Choi HY et al (2011) The epidemiology of renal cell carcinoma. Eur Urol 60(4):615–621

    Article  Google Scholar 

  2. Muglia VF, Prando A (2015) Renal cell carcinoma: histological classification and correlation with imaging findings. Radiol Bras 48(3):166–174

    Article  Google Scholar 

  3. Capitanio U, Cloutier V, Zini L et al (2009) A critical assessment of the prognostic value of clear cell, papillary and chromophobe histological subtypes in renal cell carcinoma: a population-based study. BJU Int 103(11):1496–1500

    Article  Google Scholar 

  4. Ljungberg B, Bensalah K, Canfield S et al (2015) EAU guidelines on renal cell carcinoma: 2014 update. Eur Urol 67(5):913–924

    Article  Google Scholar 

  5. Novara G, Martignoni G, Artibani W, Ficarra V (2007) Grading systems in renal cell carcinoma. J Urol 177(2):430–436

    Article  Google Scholar 

  6. Nico B, Benagiano V, Mangieri D, Maruotti N, Vacca A, Ribatti D (2008) Evaluation of microvascular density in tumors: pro and contra. Histol Histopathol 23(5):601–607

  7. Meert AP, Paesmans M, Martin B et al (2002) The role of microvessel density on the survival of patients with lung cancer: a systematic review of the literature with meta-analysis. Br J Cancer 87(7):694–701

    Article  Google Scholar 

  8. Vikram R, Ng CS, Tamboli P et al (2009) Papillary renal cell carcinoma: radiologic-pathologic correlation and spectrum of disease. Radiographics. 29(3):741–754 discussion 755–747

    Article  Google Scholar 

  9. Young JR, Margolis D, Sauk S, Pantuck AJ, Sayre J, Raman SS (2013) Clear cell renal cell carcinoma: discrimination from other renal cell carcinoma subtypes and oncocytoma at multiphasic multidetector CT. Radiology. 267(2):444–453

  10. Hotker AM, Mazaheri Y, Wibmer A et al (2017) Differentiation of clear cell renal cell carcinoma from other renal cortical tumors by use of a quantitative multiparametric MRI approach. AJR Am J Roentgenol 208(3):W85–W91

    Article  Google Scholar 

  11. Graser A, Johnson TR, Chandarana H, Macari M (2009) Dual energy CT: preliminary observations and potential clinical applications in the abdomen. Eur Radiol 19(1):13–23

    Article  Google Scholar 

  12. Graser A, Becker CR, Staehler M et al (2010) Single-phase dual-energy CT allows for characterization of renal masses as benign or malignant. Invest Radiol 45(7):399–405

    Article  Google Scholar 

  13. Weidner N, Semple JP, Welch WR, Folkman J (1991) Tumor angiogenesis and metastasis--correlation in invasive breast carcinoma. N Engl J Med 324(1):1–8

    Article  CAS  Google Scholar 

  14. Weidner N (1995) Intratumor microvessel density as a prognostic factor in cancer. Am J Pathol 147(1):9–19

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Kroeger N, Choueiri TK, Lee JL et al (2014) Survival outcome and treatment response of patients with late relapse from renal cell carcinoma in the era of targeted therapy. Eur Urol 65(6):1086–1092

    Article  Google Scholar 

  16. Ascenti G, Mileto A, Krauss B et al (2013) Distinguishing enhancing from nonenhancing renal masses with dual-source dual-energy CT: iodine quantification versus standard enhancement measurements. Eur Radiol 23(8):2288–2295

    Article  Google Scholar 

  17. Lubner MG, Stabo N, Abel EJ, Del Rio AM, Pickhardt PJ (2016) CT textural analysis of large primary renal cell carcinomas: pretreatment tumor heterogeneity correlates with histologic findings and clinical outcomes. AJR Am J Roentgenol 207(1):96–105

    Article  Google Scholar 

  18. Mileto A, Marin D, Alfaro-Cordoba M et al (2014) Iodine quantification to distinguish clear cell from papillary renal cell carcinoma at dual-energy multidetector CT: a multireader diagnostic performance study. Radiology. 273(3):813–820

    Article  Google Scholar 

  19. Hsieh JJ, Purdue MP, Signoretti S et al (2017) Renal cell carcinoma. Nat Rev Dis Primers 3:17009

    Article  Google Scholar 

  20. Apfaltrer P, Meyer M, Meier C et al (2012) Contrast-enhanced dual-energy CT of gastrointestinal stromal tumors: is iodine-related attenuation a potential indicator of tumor response? Invest Radiol 47(1):65–70

    Article  CAS  Google Scholar 

  21. Hellbach K, Sterzik A, Sommer W et al (2016) Dual energy CT allows for improved characterization of response to antiangiogenic treatment in patients with metastatic renal cell cancer. Eur Radiol 27:2532–2537

  22. Cheng SH, Liu JM, Liu QY et al (2014) Prognostic role of microvessel density in patients with renal cell carcinoma: a meta-analysis. Int J Clin Exp Pathol 7(9):5855–5863

    PubMed  PubMed Central  Google Scholar 

  23. Zocchi MR, Poggi A (2004) PECAM-1, apoptosis and CD34+ precursors. Leuk Lymphoma 45(11):2205–2213

    Article  CAS  Google Scholar 

  24. Jinzaki M, Tanimoto A, Mukai M et al (2000) Double-phase helical CT of small renal parenchymal neoplasms: correlation with pathologic findings and tumor angiogenesis. J Comput Assist Tomogr 24(6):835–842

    Article  CAS  Google Scholar 

  25. Jiang Y, Li J, Wang J et al (2016) Assessment of vascularity in hepatic alveolar echinococcosis: comparison of quantified dual-energy CT with histopathologic parameters. PLoS One 11(2):e0149440

    Article  Google Scholar 

  26. Young JR, Coy H, Douek M et al (2017) Type 1 papillary renal cell carcinoma: differentiation from type 2 papillary RCC on multiphasic MDCT. Abdom Radiol (NY) 42(7):1911–1918

    Article  Google Scholar 

  27. Graser A, Johnson TR, Hecht EM et al (2009) Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images? Radiology. 252(2):433–440

    Article  Google Scholar 

Download references

Funding

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

Author information

Authors and Affiliations

  1. Department of Urology, Ludwig-Maximilians-Universität München, Munich, Germany

    Julian Marcon, Jozefina Casuscelli, Annabel Spek, Christian G. Stief, Alexander Buchner & Michael Staehler

  2. Department of Radiology, Ludwig-Maximilians-Universität München, Munich, Germany

    Anno Graser, Maximilian F. Reiser & Johannes Rübenthaler

  3. Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany

    David Horst

Authors
  1. Julian Marcon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anno Graser
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David Horst
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jozefina Casuscelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Annabel Spek
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Christian G. Stief
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Maximilian F. Reiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Johannes Rübenthaler
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Alexander Buchner
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Michael Staehler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julian Marcon.

Ethics declarations

Guarantor

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.

Methodology

• Retrospective

• Experimental

• Performed at one institution

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 15.0 mb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Marcon, J., Graser, A., Horst, D. et al. Papillary vs clear cell renal cell carcinoma. Differentiation and grading by iodine concentration using DECT—correlation with microvascular density. Eur Radiol 30, 1–10 (2020). https://doi.org/10.1007/s00330-019-06298-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-019-06298-2

Keywords

Search

Navigation