Abdominal Radiology

, Volume 42, Issue 5, pp 1464–1471 | Cite as

Correlation between CT perfusion parameters and Fuhrman grade in pTlb renal cell carcinoma

  • Chao Chen
  • Qinqin Kang
  • Qiang Wei
  • Bing Xu
  • Hui Ye
  • Tiegong Wang
  • Yayun Lu
  • Jianping LuEmail author



To evaluate the correlation of CT perfusion parameters with the Fuhrman grade in pT1b (4–7 cm) renal cell carcinoma (RCC).


CT perfusion imaging and Fuhrman pathological grading of pT1b RCC were performed in 48 patients (10 grade 1, 27 grade 2, 9 grade 3, and 2 grade 4). Equivalent blood volume (BV Equiv), permeability surface area product (PS), and blood flow (BF) of tumors were measured. Grade 1 and 2 were defined as low-grade group (n = 37), meanwhile high-grade group (n = 11) included grade 3 and 4. Comparisons of CT perfusion parameters and tumor size of the two different groups were performed. Correlations between CT perfusion parameters, Fuhrman grade (grade 1, 2, 3, and 4), and tumor size were assessed.


PS was significantly lower in high grade than in low-grade pT1b RCC (P = 0.004). However, no significant differences were found in BV Equiv and BF between the two groups (P > 0.05 for both). The optimal threshold value, sensitivity, specificity, and the area under the ROC curve for distinguishing the two groups using PS were 68.8 mL/100 g/min, 0.7, 0.8, and 0.8, respectively. Negative significant correlation was observed between PS and Fuhrman grade (r = −0.338, P = 0.019).


The PS of pT1b RCC had negative significant correlation with Fuhrman grade. CT perfusion appeared to be a non-invasive means to predict high Fuhrman grade of pT1b RCC preoperatively and guide the optimal treatment for the patient.


Computed tomography Perfusion imaging Renal cell carcinoma Fuhrman grade 



The authors thank Chaan S Ng, M.D., of Department of Diagnostic Radiology, University of Texas M.D. Anderson Cancer Center for good advice on writing in this study.

Compliance with ethical standards


No funding was received for this study.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required.

Informed consent

Statement of informed consent was not applicable since the manuscript does not contain any patient data.


  1. 1.
    Ferlay J, Shin HR, Bray F, et al. (2010) Estimates of worldwide burden of cancer in 2008: gLOBOCAN 2008. Int J Cancer 127(12):2893–2917. doi: 10.1002/ijc.25516 CrossRefPubMedGoogle Scholar
  2. 2.
    Chow WH, Dong LM, Devesa SS (2010) Epidemiology and risk factors for kidney cancer. Nat Rev Urol 7(5):245–257. doi: 10.1038/nrurol.2010.46 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Ridge CA, Pua BB, Madoff DC (2014) Epidemiology and staging of renal cell carcinoma. Semin Intervent Radiol 31(1):3–8. doi: 10.1055/s-0033-1363837 CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Leibovich BC, Lohse CM, Crispen PL, et al. (2010) Histological subtype is an independent predictor of outcome for patients with renal cell carcinoma. J Urol 183(4):1309–1315. doi: 10.1016/j.juro.2009.12.035 CrossRefPubMedGoogle Scholar
  5. 5.
    Edge SB, American Joint Committee on Cancer (2010) AJCC cancer staging manual. New York: Springer, p 648Google Scholar
  6. 6.
    Fuhrman SA, Lasky LC, Limas C (1982) Prognostic significance of morphologic parameters in renal cell carcinoma. Am J Surg Pathol 6(7):655–663CrossRefGoogle Scholar
  7. 7.
    Zisman A, Pantuck AJ, Dorey F, et al. (2001) Improved prognostication of renal cell carcinoma using an integrated staging system. J Clin Oncol 19(6):1649–1657CrossRefGoogle Scholar
  8. 8.
    Touijer K, Jacqmin D, Kavoussi LR, et al. (2010) The expanding role of partial nephrectomy: a critical analysis of indications, results, and complications. Eur Urol 57(2):214–222. doi: 10.1016/j.eururo.2009.10.019 CrossRefPubMedGoogle Scholar
  9. 9.
    Weight CJ, Larson BT, Gao T, et al. (2010) Elective partial nephrectomy in patients with clinical T1b renal tumors is associated with improved overall survival. Urology 76(3):631–637. doi: 10.1016/j.urology.2009.11.087 CrossRefPubMedGoogle Scholar
  10. 10.
    Zhang ZL, Chen W, Li YH, et al. (2011) Stage T1N0M0 renal cell carcinoma: the prognosis in Asian patients. Chin J Cancer 30(11):772–778. doi: 10.5732/cjc.011.10085 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Lau WK, Cheville JC, Blute ML, et al. (2002) Prognostic features of pathologic stage T1 renal cell carcinoma after radical nephrectomy. Urology 59(4):532–537CrossRefGoogle Scholar
  12. 12.
    Leibovich BC, Blute M, Cheville JC, et al. (2004) Nephron sparing surgery for appropriately selected renal cell carcinoma between 4 and 7 cm results in outcome similar to radical nephrectomy. J Urol 171(3):1066–1070. doi: 10.1097/01.ju.0000113274.40885.db CrossRefPubMedGoogle Scholar
  13. 13.
    Ishigami K, Leite LV, Pakalniskis MG, et al. (2014) Tumor grade of clear cell renal cell carcinoma assessed by contrast-enhanced computed tomography. Springerplus 3:694. doi: 10.1186/2193-1801-3-694 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Rosenkrantz AB, Niver BE, Fitzgerald EF, et al. (2010) Utility of the apparent diffusion coefficient for distinguishing clear cell renal cell carcinoma of low and high nuclear grade. AJR Am J Roentgenol 195(5):W344–W351. doi: 10.2214/AJR.10.4688 CrossRefPubMedGoogle Scholar
  15. 15.
    Goyal A, Sharma R, Bhalla AS, et al. (2012) Diffusion-weighted MRI in renal cell carcinoma: a surrogate marker for predicting nuclear grade and histological subtype. Acta Radiol 53(3):349–358. doi: 10.1258/ar.2011.110415 CrossRefPubMedGoogle Scholar
  16. 16.
    Maruyama M, Yoshizako T, Uchida K, et al. (2015) Comparison of utility of tumor size and apparent diffusion coefficient for differentiation of low- and high-grade clear-cell renal cell carcinoma. Acta Radiologica 56(2):250–256. doi: 10.1177/0284185114523268 CrossRefPubMedGoogle Scholar
  17. 17.
    Zhang YD, Wu CJ, Wang Q, et al. (2015) Comparison of utility of histogram apparent diffusion coefficient and R2* for differentiation of low-grade from high-grade clear cell renal cell carcinoma. AJR Am J Roentgenol 205(2):W193–W201. doi: 10.2214/AJR.14.13802 CrossRefPubMedGoogle Scholar
  18. 18.
    Vargas HA, Delaney HG, Delappe EM, et al. (2013) Multiphasic contrast-enhanced MRI: single-slice versus volumetric quantification of tumor enhancement for the assessment of renal clear-cell carcinoma fuhrman grade. J Magn Reson Imaging 37(5):1160–1167. doi: 10.1002/jmri.23899 CrossRefPubMedGoogle Scholar
  19. 19.
    Delahunt B, Sika-Paotonu D, Bethwaite PB, et al. (2007) Fuhrman grading is not appropriate for chromophobe renal cell carcinoma. Am J Surg Pathol 31(6):957–960. doi: 10.1097/01.pas.0000249446.28713.53 CrossRefPubMedGoogle Scholar
  20. 20.
    Delahunt B, Cheville JC, Martignoni G, et al. (2013) The International Society of Urological Pathology (ISUP) grading system for renal cell carcinoma and other prognostic parameters. Am J Surg Pathol 37(10):1490–1504. doi: 10.1097/PAS.0b013e318299f0fb CrossRefPubMedGoogle Scholar
  21. 21.
    Moch H, Cubilla AL, Humphrey PA, et al. (2016) The 2016 WHO classification of tumours of the urinary system and male genital organs-part A: renal, penile, and testicular tumours. Eur Urol 70(1):93–105. doi: 10.1016/j.eururo.2016.02.029 CrossRefPubMedGoogle Scholar
  22. 22.
    Chen C, Liu Q, Hao Q, et al. (2014) Study of 320-slice dynamic volume CT perfusion in different pathologic types of kidney tumor: preliminary results. PLoS ONE 9(1):e85522. doi: 10.1371/journal.pone.0085522 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Miles KA (1991) Measurement of tissue perfusion by dynamic computed tomography. Br J Radiol 64(761):409–412CrossRefGoogle Scholar
  24. 24.
    Patlak CS, Blasberg RG, Fenstermacher JD (1983) Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 3(1):1–7. doi: 10.1038/jcbfm.1983.1 CrossRefPubMedGoogle Scholar
  25. 25.
    Noda Y, Kanematsu M, Goshima S, et al. (2015) 18-F fluorodeoxyglucose uptake in positron emission tomography as a pathological grade predictor for renal clear cell carcinomas. Eur Radiol 25(10):3009–3016. doi: 10.1007/s00330-015-3687-2 CrossRefPubMedGoogle Scholar
  26. 26.
    Polat EC, Otunctemur A, Ozbek E, et al. (2014) Standardized uptake values highly correlate with tumor size and Fuhrman grade in patients with clear cell renal cell carcinoma. Asian Pac J Cancer Prev 15(18):7821–7824CrossRefGoogle Scholar
  27. 27.
    Villalobos-Gollas M, Aguilar-Davidov B, Culebro-Garcia C, et al. (2012) Pathological implications of areas of lower enhancement on contrast-enhanced computed tomography in renal-cell carcinoma: additional information for selecting candidates for surveillance protocols. Int Urol Nephrol 44(5):1369–1374. doi: 10.1007/s11255-012-0199-8 CrossRefPubMedGoogle Scholar
  28. 28.
    Zhu YH, Wang X, Zhang J, et al. (2014) Low enhancement on multiphase contrast-enhanced CT images: an independent predictor of the presence of high tumor grade of clear cell renal cell carcinoma. AJR Am J Roentgenol 203(3):W295–W300. doi: 10.2214/AJR.13.12297 CrossRefPubMedGoogle Scholar
  29. 29.
    Huhdanpaa H, Hwang D, Cen S, et al. (2015) CT prediction of the Fuhrman grade of clear cell renal cell carcinoma (RCC): towards the development of computer-assisted diagnostic method. Abdom Imaging 40(8):3168–3174. doi: 10.1007/s00261-015-0531-8 CrossRefPubMedGoogle Scholar
  30. 30.
    Imao T, Egawa M, Takashima H, et al. (2004) Inverse correlation of microvessel density with metastasis and prognosis in renal cell carcinoma. Int J Urol 11(11):948–953. doi: 10.1111/j.1442-2042.2004.00931.x CrossRefPubMedGoogle Scholar
  31. 31.
    Reiner CS, Roessle M, Thiesler T, et al. (2013) Computed tomography perfusion imaging of renal cell carcinoma: systematic comparison with histopathological angiogenic and prognostic markers. Invest Radiol 48(4):183–191. doi: 10.1097/RLI.0b013e31827c63a3 CrossRefPubMedGoogle Scholar
  32. 32.
    Delahunt B, Bethwaite PB, Thornton A (1997) Prognostic significance of microscopic vascularity for clear cell renal cell carcinoma. Br J Urol 80(3):401–404CrossRefGoogle Scholar
  33. 33.
    Chen Y, Zhang J, Dai J, et al. (2010) Angiogenesis of renal cell carcinoma: perfusion CT findings. Abdom Imaging 35(5):622–628. doi: 10.1007/s00261-009-9565-0 CrossRefPubMedGoogle Scholar
  34. 34.
    Miles KA, Lee TY, Goh V, et al. (2012) Current status and guidelines for the assessment of tumour vascular support with dynamic contrast-enhanced computed tomography. Eur Radiol 22(7):1430–1441. doi: 10.1007/s00330-012-2379-4 CrossRefPubMedGoogle Scholar
  35. 35.
    Miles KA (2003) Perfusion CT for the assessment of tumour vascularity: which protocol? Br J Radiol 76(1):S36–S42CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Chao Chen
    • 1
  • Qinqin Kang
    • 1
  • Qiang Wei
    • 2
  • Bing Xu
    • 1
  • Hui Ye
    • 3
  • Tiegong Wang
    • 1
  • Yayun Lu
    • 1
  • Jianping Lu
    • 1
    Email author
  1. 1.Department of Radiology, Changhai Hospital of ShanghaiThe Second Military Medical UniversityShanghaiChina
  2. 2.Department of Orthopaedics, Changhai Hospital of ShanghaiThe Second Military Medical UniversityShanghaiChina
  3. 3.Hunan Tumor Hospital, PET-CT CenterChangshaChina

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