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Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

  • Kidneys, Ureters, Bladder, Retroperitoneum
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Objective

To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC.

Materials and methods

With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen’s kappa.

Results

Tumor size was 24 ± 7 (13–39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5–100.0]) with low sensitivity (36.8% [21.8–54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94–1.0) with sensitivity/specificity 87.5%/100%.

Conclusion

The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.

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References

  1. Gupta K, Miller JD, Li JZ, Russell MW, Charbonneau C. Epidemiologic and socioeconomic burden of metastatic renal cell carcinoma (mRCC): a literature review. Cancer Treat Rev 2008;34(3):193-205.

    Article  PubMed  Google Scholar 

  2. Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA: a cancer journal for clinicians 2010;60(5):277-300.

  3. Almassi N, Gill BC, Rini B, Fareed K. Management of the small renal mass. Transl Androl Urol 2017;6(5):923-930.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Volpe A, Cadeddu JA, Cestari A, et al. Contemporary Management of Small Renal Masses. European urology 2011;60(3):501-515.

    Article  PubMed  Google Scholar 

  5. Pierorazio PM, Hyams ES, Mullins JK, Allaf ME. Active surveillance for small renal masses. Reviews in urology 2012;14(1-2):13-19.

    PubMed  PubMed Central  Google Scholar 

  6. Lee H, Lee JK, Kim K, et al. Risk of metastasis for T1a renal cell carcinoma. World journal of urology 2016;34(4):553-559.

    Article  CAS  PubMed  Google Scholar 

  7. Cheville JC, Lohse CM, Zincke H, Weaver AL, Blute ML. Comparisons of outcome and prognostic features among histologic subtypes of renal cell carcinoma. The American journal of surgical pathology 2003;27(5):612-624.

    Article  PubMed  Google Scholar 

  8. Lim RS, McInnes MDF, Siddaiah M, Flood TA, Lavallee LT, Schieda N. Are growth patterns on MRI in small (< 4 cm) solid renal masses useful for predicting benign histology? European radiology 2018;28(8):3115-3124.

    Article  PubMed  Google Scholar 

  9. Ljungberg B, Bensalah K, Canfield S, et al. EAU guidelines on renal cell carcinoma: 2014 update. European urology 2015;67(5):913-924.

    Article  PubMed  Google Scholar 

  10. Wang R, Wolf JS, Wood DP, Higgins EJ, Hafez KS. Accuracy of Percutaneous Core Biopsy in Management of Small Renal Masses. Urology 2009;73(3):586-590.

    Article  PubMed  Google Scholar 

  11. Canvasser NE, Kay FU, Xi Y, et al. Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging to Identify Clear Cell Renal Cell Carcinoma in cT1a Renal Masses. J Urol 2017;198(4):780-786.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Dagher J, Delahunt B, Rioux-Leclercq N, et al. Clear cell renal cell carcinoma: validation of World Health Organization/International Society of Urological Pathology grading. Histopathology 2017;71(6):918-925.

    Article  PubMed  Google Scholar 

  13. Delahunt B, Cheville JC, Martignoni G, et al. The International Society of Urological Pathology (ISUP) grading system for renal cell carcinoma and other prognostic parameters. The American journal of surgical pathology 2013;37(10):1490-1504.

    Article  PubMed  Google Scholar 

  14. Marconi L, Dabestani S, Lam TB, et al. Systematic Review and Meta-analysis of Diagnostic Accuracy of Percutaneous Renal Tumour Biopsy. Eur Urol 2016;69(4):660-673.

    Article  PubMed  Google Scholar 

  15. Rosenkrantz AB, Niver BE, Fitzgerald EF, Babb JS, Chandarana H, Melamed J. Utility of the apparent diffusion coefficient for distinguishing clear cell renal cell carcinoma of low and high nuclear grade. AJR Am J Roentgenol 2010;195(5):W344-351.

    Article  PubMed  Google Scholar 

  16. Sun MR, Ngo L, Genega EM, et al. Renal cell carcinoma: dynamic contrast-enhanced MR imaging for differentiation of tumor subtypes--correlation with pathologic findings. Radiology 2009;250(3):793-802.

    Article  PubMed  Google Scholar 

  17. Vargas HA, Delaney HG, Delappe EM, et al. Multiphasic contrast-enhanced MRI: Single-slice versus volumetric quantification of tumor enhancement for the assessment of renal clear-cell carcinoma fuhrman grade. Journal of Magnetic Resonance Imaging 2012;37(5):1160-1167.

    Article  PubMed  Google Scholar 

  18. 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. Abdominal imaging 2015;40(8):3168-3174.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ding J, Xing Z, Jiang Z, et al. CT-based radiomic model predicts high grade of clear cell renal cell carcinoma. European journal of radiology 2018;103:51-56.

    Article  PubMed  Google Scholar 

  20. Lubner MG, Stabo N, Abel EJ, Del Rio AM, Pickhardt PJ. CT Textural Analysis of Large Primary Renal Cell Carcinomas: Pretreatment Tumor Heterogeneity Correlates With Histologic Findings and Clinical Outcomes. AJR Am J Roentgenol 2016;207(1):96-105.

    Article  PubMed  Google Scholar 

  21. Amin MB, Greene FL, Edge SB, et al. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging. CA: a cancer journal for clinicians 2017;67(2):93-99.

  22. Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Annals of surgical oncology 2010;17(6):1471-1474.

  23. Takayama T, Sugiyama T, Kai F, et al. Characteristics of aggressive variants in T1a renal cell carcinoma. Journal of cancer research and clinical oncology 2011;137(11):1653-1659.

    Article  PubMed  Google Scholar 

  24. Schlomer B, Figenshau RS, Yan Y, Venkatesh R, Bhayani SB. Pathological features of renal neoplasms classified by size and symptomatology. The Journal of urology 2006;176(4 Pt 1):1317-1320; discussion 1320.

  25. Bagrodia A, Darwish OM, Rapoport Y, Margulis V. Risk prediction in the management of small renal masses. Current opinion in urology 2012;22(5):347-352.

    Article  PubMed  Google Scholar 

  26. Tomaszewski JJ, Uzzo RG, Smaldone MC. Heterogeneity and renal mass biopsy: a review of its role and reliability. Cancer biology & medicine 2014;11(3):162-172.

    Google Scholar 

  27. Samaratunga H, Gianduzzo T, Delahunt B. The ISUP system of staging, grading and classification of renal cell neoplasia. Journal of kidney cancer and VHL 2014;1(3):26-39.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Schieda N, Thornhill RE, Al-Subhi M, et al. Diagnosis of Sarcomatoid Renal Cell Carcinoma With CT: Evaluation by Qualitative Imaging Features and Texture Analysis. AJR Am J Roentgenol 2015;204(5):1013-1023.

    Article  PubMed  Google Scholar 

  29. Zhang Y, Udayakumar D, Cai L, et al. Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI. JCI Insight 2017;2(15).

  30. Ramamurthy NK, Moosavi B, McInnes MD, Flood TA, Schieda N. Multiparametric MRI of solid renal masses: pearls and pitfalls. Clin Radiol 2014.

  31. Sasiwimonphan K, Takahashi N, Leibovich BC, Carter RE, Atwell TD, Kawashima A. Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology 2012;263(1):160-168.

    Article  PubMed  Google Scholar 

  32. Hindman N, Ngo L, Genega EM, et al. Angiomyolipoma with minimal fat: can it be differentiated from clear cell renal cell carcinoma by using standard MR techniques? Radiology 2012;265(2):468-477.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Karlo CA, Donati OF, Burger IA, et al. MR imaging of renal cortical tumours: qualitative and quantitative chemical shift imaging parameters. Eur Radiol 2013;23(6):1738-1744.

    Article  PubMed  Google Scholar 

  34. Cornelis F, Tricaud E, Lasserre AS, et al. Routinely performed multiparametric magnetic resonance imaging helps to differentiate common subtypes of renal tumours. Eur Radiol 2014;24(5):1068-1080.

    Article  CAS  PubMed  Google Scholar 

  35. Schieda N, Dilauro M, Moosavi B, et al. MRI evaluation of small (<4cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis. Eur Radiol 2015.

  36. Kay FU, Canvasser NE, Xi Y, et al. Diagnostic Performance and Interreader Agreement of a Standardized MR Imaging Approach in the Prediction of Small Renal Mass Histology. Radiology 2018;287(2):543-553.

    Article  PubMed  Google Scholar 

  37. Outwater EK, Bhatia M, Siegelman ES, Burke MA, Mitchell DG. Lipid in renal clear cell carcinoma: detection on opposed-phase gradient-echo MR images. Radiology 1997;205(1):103-107.

    Article  CAS  PubMed  Google Scholar 

  38. Lopez JI, Angulo JC. Pathological Bases and Clinical Impact of Intratumor Heterogeneity in Clear Cell Renal Cell Carcinoma. Curr Urol Rep 2018;19(1):3.

    Article  PubMed  Google Scholar 

  39. Krishnan B, Truong LD. Renal epithelial neoplasms: the diagnostic implications of electron microscopic study in 55 cases. Human pathology 2002;33(1):68-79.

    Article  PubMed  Google Scholar 

  40. Sayeed S, Lindsey KG, Baras AS, et al. Cytopathologic features of clear cell papillary renal cell carcinoma: A recently described variant to be considered in the differential diagnosis of clear cell renal epithelial neoplasms. Cancer cytopathology 2016;124(8):565-572.

    Article  PubMed  Google Scholar 

  41. Pedrosa I, Chou MT, Ngo L, et al. MR classification of renal masses with pathologic correlation. European radiology 2008;18(2):365-375.

    Article  PubMed  Google Scholar 

  42. Parada Villavicencio C, Mc Carthy RJ, Miller FH. Can diffusion-weighted magnetic resonance imaging of clear cell renal carcinoma predict low from high nuclear grade tumors. Abdominal radiology (New York) 2017;42(4):1241-1249.

    Article  Google Scholar 

  43. Woo S, Suh CH, Kim SY, Cho JY, Kim SH. Diagnostic Performance of DWI for Differentiating High- From Low-Grade Clear Cell Renal Cell Carcinoma: A Systematic Review and Meta-Analysis. AJR Am J Roentgenol 2017;209(6):W374-W381.

    Article  PubMed  Google Scholar 

  44. Mytsyk Y, Dutka I, Borys Y, et al. Renal cell carcinoma: applicability of the apparent coefficient of the diffusion-weighted estimated by MRI for improving their differential diagnosis, histologic subtyping, and differentiation grade. International urology and nephrology 2017;49(2):215-224.

    Article  CAS  PubMed  Google Scholar 

  45. Tabibi A, Parvin M, Abdi H, Bashtar R, Zamani N, Abadpour B. Correlation between size of renal cell carcinoma and its grade, stage, and histological subtype. Urology journal 2007;4(1):10-13.

    PubMed  Google Scholar 

  46. Thompson RH, Kurta JM, Kaag M, et al. Tumor size is associated with malignant potential in renal cell carcinoma cases. The Journal of urology 2009;181(5):2033-2036.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Campbell S, Uzzo RG, Allaf ME, et al. Renal Mass and Localized Renal Cancer: AUA Guideline. The Journal of urology 2017;198(3):520-529.

    Article  PubMed  Google Scholar 

  48. Ream JM, Gaing B, Mussi TC, Rosenkrantz AB. Characterization of adrenal lesions at chemical-shift MRI: a direct intraindividual comparison of in- and opposed-phase imaging at 1.5 T and 3 T. AJR Am J Roentgenol 2015;204(3):536-541.

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Authors and Affiliations

  1. Department of Medical Imaging, The Ottawa Hospital, Ottawa, ON, Canada

    Kevin Moran, Daniel Walker, Matthew D. F. McInnes & Nicola Schieda

  2. Department of Anatomical Pathology, The Ottawa Hospital, Ottawa, ON, Canada

    Jorge Abreu-Gomez & Trevor A. Flood

  3. Joint Department of Medical Imaging, University Health Network, The University of Toronto, Toronto, ON, Canada

    Satheesh Krishna

  4. Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada

    Nicola Schieda

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  1. Kevin Moran
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Moran, K., Abreu-Gomez, J., Krishna, S. et al. Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?. Abdom Radiol 44, 2841–2851 (2019). https://doi.org/10.1007/s00261-019-02018-y

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  • DOI: https://doi.org/10.1007/s00261-019-02018-y

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