Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma



Clear cell renal cell carcinoma (ccRCC) comprises nearly 90% of all diagnosed RCC subtypes and has the worst prognosis and highest metastatic potential. The strongest prognostic factors for patients with ccRCC include histological subtype and Fuhrman grade, which are incorporated into prognostic models. Since ccRCC is a highly vascularized tumor, there may be differences in enhancement patterns on multidetector CT (MDCT) due to the hemodynamics and microvessel density (MVD) of the lesions. This may provide a noninvasive method to characterize incidentally detected low- and high-grade ccRCCs on MDCT. The purpose of our study was to determine the correlation between MDCT enhancement parameters, ccRCC MVD, and Fuhrman grade to determine its utility and value in assessing tumor vascularity and grade in vivo.


In this retrospective, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low-grade (LG), and 43 high-grade (HG) ccRCCs underwent preoperative four-phase MDCT. A 3D volume of interest (VOI) was obtained for every tumor and absolute enhancement and the wash-in/wash-out of enhancement for each phase was assessed. Immunohistochemistry on resected specimens was used to quantify MVD. Linear regression and Pearson correlation were used to investigate the strength of the association between 3D VOI enhancement and MVD. Stepwise logistic regression analysis determined independent predictors of HG ccRCC. Cut-off values and odds Ratio (OR) with 95% CIs were reported. The clinical, radiomic, and pathologic features with the highest performance in the stepwise logistic regression analysis were evaluated using receiver operator characteristics (ROC) and area under the curve (AUC).


Absolute enhancement in the nephrographic phase < 52.1 Hounsfield Units (HU) (HR 0.979, 95% CI 0.964–0.994, p value = 0.006), lesion size > 4.3 cm (HR 1.450, 95% CI 1.211–1.738, p value < 0.001), and an intratumoral MVD < 15% (HR 0.932, 95% CI 0.867–1.002, p value = 0.058) were independent predictors of HG ccRCC with an AUC of 0.818 (95% CI 0.725–0.911). HG ccRCCs had a significant association between 3D VOI enhancement and MVD in each post-contrast phase (r2 = 0.238 to 0.455, p < 0.05).


Absolute enhancement of the entire lesion obtained from a 3D VOI in the nephrographic phase on preoperative MDCT can provide quantitative data that are a significant, independent predictor of a high-grade clear cell RCC and can be used to assess tumor vascularity and grade in vivo.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6


  1. 1.

    Capitanio U, Bensalah K, Bex A, et al. Epidemiology of Renal Cell Carcinoma. European Urology 2019; 75(1): 74-84.

    Article  Google Scholar 

  2. 2.

    SEER. Cancer Stat Facts: Kidney and Renal Pelvis Cancer. Available from:

  3. 3.

    Sun M, Shariat SF, Cheng C, et al. Prognostic factors and predictive models in renal cell carcinoma: a contemporary review. European Urology 2011; 60(4): 644-661.

    Article  Google Scholar 

  4. 4.

    Fuhrman SA, Lasky LC, Limas C. Prognostic significance of morphologic parameters in renal cell carcinoma. Am J Surg Pathol. 1982 Oct; 6(7):655-63.

    Article  CAS  Google Scholar 

  5. 5.

    Patard JJ, Kim HL, Lam JS, et al. Use of the University of California Los Angeles integrated staging system to predict survival in renal cell carcinoma: an international multicenter study. J Clin Oncol 2004; 22(16): 3316-22.

    Article  Google Scholar 

  6. 6.

    Silverman SG, Israel GM, Trinh QD. Incompletely characterized incidental renal masses: emerging data support conservative management. Radiology 2015 Apr; 275(1):28-42.

    Article  Google Scholar 

  7. 7.

    Coy H, Young JR, Douek M, et al. Association of qualitative and quantitative imaging features on multiphasic multidetector CT with tumor grade in clear cell renal cell carcinoma. Abdominal Radiology ​2019;44(1):180–189.​

    Article  Google Scholar 

  8. 8.

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

    Article  Google Scholar 

  9. 9.

    Vargas H, Delany H, Delappe E, et al. Multiphasic Contrast-Enhanced MRI: Single-Slice Versus Volumetric Quantification of Tumor Enhancement for Assessment of Renal Clear-Cell Carcinoma Fuhrman Grade. Journal of Magnetic Resonance Imaging 2013; 37: 1160-1167.

    Article  Google Scholar 

  10. 10.

    Young JR, Coy H, Kim HJ, et al. Utility of multiphasic multidetector computed tomography in discriminating between clear cell renal cell carcinomas with high and low carbonic anhydrase-IX expression. Abdominal Radiology 2018; 43(10): 2734-2742.

    Article  Google Scholar 

  11. 11.

    Gerlinger, Rowan, Horswell S, et al. Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing. New England Journal of Medicine 2012; 366(10) 883-92.

  12. 12.

    Jamshidi N, Jonasch E, Zapala M, et al. The Radiogenomic Risk Score: Construction of a Prognostic Quantitative, Noninvasive Image-based Molecular Assay for Renal Cell Carcinoma. Radiology 2015; 277:114-123.

    Article  Google Scholar 

  13. 13.

    Lubner M, Stabo N, Abel EJ, Munoz del Rio A, Pickhardt P. CT Textural Analysis of Large Primary Renal Cell Carcinomas: Pretreatment Tumor Heterogeneity Correlates With Histologic Findings and Clinical Outcomes. AJR 2016; 207: 96-105.

  14. 14.

    Yin Q, Hung SC, Wang L, et al. Associations between Tumor Vascularity, Vascular Endothelial Growth Factor Expression and PET/MRI Radiomic Signatures in Primary Clear Cell Renal Cell Carcinoma: Proof of Concept Study. Sci Rep 2017; 7: 43356.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Coy H, Young JR, Douek M, et al. Quantitative computer-aided diagnostic algorithm for automated detection of peak lesion attenuation in differentiating clear cell from papillary and chromophobe renal cell carcinoma, oncocytoma, and fat-poor amgiomyolipoma on multiphasic multidetector computed tomography. Abdom Radiol 2017; 42(7): 1919-1928.

    Article  Google Scholar 

  16. 16.

    Zhu YH, Wang X, Zhang J, et al. Low enhancement on multiphase contrast-enhanced CT images: an independent predictor of the presence of high grade tumor of clear cell renal cell carcinoma. Am J Roentgenol 2014; 203: W295-W300.

    Article  Google Scholar 

  17. 17.

    Huhdanpaa H, Hwang D, Cen S, et al. CT prediction of the Fuhrman grade of clear cell renal cell carcinoma (RCC): towards the development of computer-assisted diagnostic method. Abdom Imaging 2015; 40(8): 3168-74.

    Article  Google Scholar 

  18. 18.

    Kopp RP, Aganovic L, Palazzi KL, Cassidy FH, Sakamoto K, Derweesh IH. Differentiation of clear from non-clear cell renal cell carcinoma using CT washout formula. Can J Urol 2013 Jun; 20 (3): 6790-7.

    PubMed  Google Scholar 

  19. 19.

    Wang JH, Min PQ, Wang PJ, et al. Dynamic CT Evaluation of Tumor Vascularity in Renal Cell Carcinoma. AJR 2006; 186:1423-1430.

    Article  Google Scholar 

  20. 20.

    Reiner C, Roessle M, Thiesler T, et al. Computed Tomography Perfusion Imaging of Renal Cell Carcinoma. Invest Radiol 2013; 48: 183-191.

    Article  Google Scholar 

  21. 21.

    Jinzaki M, Tanimoto A, Mukai M et al. Double-Phase Helical CT of Small Renal Parenchymal Neoplasms: Correlation with Pathologic Findings and Tumor Angiogenesis. Journal of Computer Assisted Tomography 2000; 24(6): 835-842.

    Article  CAS  Google Scholar 

  22. 22.

    Villalobos-Gollas M, Aguilar-Davidov B, Culebro-Garcia C, et al. Pathological implications of areas of lower enhancement on contrast-enhanced computed tomography in renal cell carcinoma: additional information for selecting candidates for surveillance protocols. In Urol Nephrol 2012; 44: 1369-1374.

    Article  Google Scholar 

  23. 23.

    Yuan Q, Kapur P, Zhang Y. Intratumor Heterogeneity of Perfusion and Diffusion in Clear-Cell Renal Cell Carcinoma: Correlation With Tumor Cellularity. Clinical Genitourinary Cancer 2016; 14(6) e585-94.

    Article  Google Scholar 

  24. 24.

    Shinagare A, Krajewski K, Braschi-Amirfarzan M, Ramaiya N. Advanced Renal Cell Carcinoma: Role of the Radiologist in the Era of Precision Medicine. Radiology 2017; 284(2): 333-351.

    Article  Google Scholar 

  25. 25.

    Hlatky L, Hahnfeldt P, Folkman J. Clinical Application of Antiangiogenic Therapy: Microvessel Density, What it Does and Doesn’t Tell Us. Journal of the National Cancer Institute 2002; 94 (12): 883-893.

    Article  Google Scholar 

  26. 26.

    Jilaveanu L, Puligandla M, Weiss S, et al. Tumor Microvessel Density as a Prognostic Marker in High-Risk Renal Cell Carcinoma Patients Treated on ECOG-ACRIN E2805. Clinical Cancer Research 2018; 24(1): 217-223.

    Article  CAS  Google Scholar 

  27. 27.

    Frank I, Blute ML, Cheville JC, Lohse CM, Weaver AL, Zincke H. An outcome prediction model for patients with clear cell renal cell carcinoma treated with radical nephrectomy based on tumor stage, size, grade and necrosis: the SSIGN score. J Urol. 2002 Dec; 168(6):2395-400.

    Article  Google Scholar 

  28. 28.

    Leibovich BC, Blute ML, Cheville JC, Lohse CM, Frank I, Kwon ED, Weaver AL, Parker AS, Zincke H. Prediction of progression after radical nephrectomy for patients with clear cell renal cell carcinoma: a stratification tool for prospective clinical trials. Cancer. 2003 Apr 1; 97(7):1663-71.

    Article  Google Scholar 

  29. 29.

    Sahni VA, Silverman SG. Imaging management of incidentally detected small renal masses. Semin Intervent Radiol. 2014 Mar; 31(1):9-19.

    Article  Google Scholar 

  30. 30.

    Sun M, Lughezani G, Jeldres C et al. A proposal for reclassification of the Fuhrman grading system in patients with clear cell renal cell carcinoma. Eur Urol 2009; 56: 775-781.

    Article  Google Scholar 

  31. 31.

    Ouyang A, Wei Z, Su X, et al. Relative Computed Tomography (CT) Enhancement Value for the Assessment of Microvascular Architecture in Renal Cell Carcinoma. Med Sci Monit 2017; 23: 3706-3714.

    Article  Google Scholar 

  32. 32.

    Jeswani T, Padhani. Imaging tumor angiogenesis. Cancer Imaging 2005; 5(1): 31-138.

    Google Scholar 

  33. 33.

    Garcia-Figueiras R, Padhani AR, Beer AJ, et al. Imaging of Tumor Angiogenesis for Radiologists-Part 1: Biological and Technical Basis. Curr Probl Diagn Radiol 2015; 44(5): 407-24.

    Article  Google Scholar 

  34. 34.

    Ganeshan B, Miles K. Quantifying tumour heterogeneity with CT. Cancer Imaging 2013; 13(1): 140-149.

    Article  Google Scholar 

  35. 35.

    Qian C, Huang D, Wondergem B, Teh B. Complexity of Tumor Vasculature in Clear Cell Renal Cell Carcinoma 2009; 115(10 Suppl): 2282-9.

    CAS  Google Scholar 

  36. 36.

    Cuenod C, Balvay D. Perfusion and vascular permeability: Basic concepts and measurement in DCE-CT and DCE-MRI. Diagnostic and Interventional Imaging 2013; 94: 1187-1204.

    Article  CAS  Google Scholar 

Download references


Funding was provided by Society of Abdominal Radiology Howard S. Stern Research [Grant No. 20163335].

Author information



Corresponding author

Correspondence to Heidi Coy.

Ethics declarations

Conflict of interest

All authors have no conflict of interest.

Informed consent

All data were acquired with IRB approval, followed HIPAA guidelines, and with a waiver of informed consent.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Coy, H., Young, J.R., Pantuck, A.J. et al. Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma. Abdom Radiol 45, 3184–3192 (2020).

Download citation


  • Clear cell RCC
  • Microvessel density
  • Tumor grade
  • Multiphasic CT
  • Angiogenesis
  • Radiomics