Skip to main content
Log in

Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma

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

Abstract

Purpose

The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to differentiate between juxtatumoral perinephric fat (JPF) surrounding low-grade (ISUP 1–2) versus high-grade (ISUP 3–4) clear cell renal cell carcinoma (ccRCC).

Methods

In this IRB-approved study, we retrospectively queried the surgical database between June 2009 and April 2016 and identified 83 patients with pathologically confirmed ccRCC (low grade: n = 54, mean age = 61.5 years, 18F/35M; high grade n = 30, mean age = 61.7 years, 8F/22M) who also had pre-operative multiphase CT acquisitions. CT images were transferred to a 3D workstation, and nephrographic phase JPF regions were manually segmented. Using an in-house developed Matlab program, a CTTA panel comprising of texture metrics extracted using six different methods, histogram, 2D- and 3D-Gray-level co-occurrence matrix (GLCM) and Gray-level difference matrix (GLDM), and 2D-Fast Fourier Transform (FFT) analyses, was applied to the segmented images to assess JPF textural heterogeneity in low- versus high-grade ccRCC. Univariate analysis and receiver-operator characteristics (ROC) analysis were used to assess interclass differences in texture metrics and their prediction accuracy, respectively.

Results

All methods except GLCM consistently revealed increased heterogeneity in the JPF surrounding high- versus low-grade ccRCC. FFT showed increased complexity index (p < 0.01). Histogram analysis showed increased kurtosis and positive skewness in (p < 0.03), and GLDM analysis showed decreased measure of correlation coefficient (MCC) (p < 0.04). Several of the GLCM metrics showed statistically significant (p < 0.04) textural differences between the two groups, but with no consistent trend. ROC analysis showed that MCC in GLCM analysis had an area under the curve of 0.75.

Conclusions

Our study suggests that CTTA of ccRCC shows statistically significant textural differences in JPF surrounding high- versus low-grade ccRCC.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Siegel R, DeSantis C, Virgo K, Stein K, Mariotto A, Smith T, et al. Cancer treatment and survivorship statistics, 2012. CA Cancer J Clin. 2012;62(4):220–41.

    Article  PubMed  Google Scholar 

  2. Xing T, He H. Epigenomics of clear cell renal cell carcinoma: mechanisms and potential use in molecular pathology. Chin J Cancer Res. 2016;28(1):80–91.

    PubMed Central  CAS  PubMed  Google Scholar 

  3. Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501(7467):338–45.

    Article  CAS  PubMed  Google Scholar 

  4. Shuch B, Amin A, Armstrong AJ, Eble JN, Ficarra V, Lopez-Beltran A, et al. Understanding pathologic variants of renal cell carcinoma: distilling therapeutic opportunities from biologic complexity. Eur Urol. 2015;67(1):85–97.

    Article  PubMed  Google Scholar 

  5. Casbas-Hernandez P, Sun X, Roman-Perez E, D'Arcy M, Sandhu R, Hishida A, et al. Tumor intrinsic subtype is reflected in cancer-adjacent tissue. Cancer Epidemiol Biomarkers Prev. 2015;24(2):406–14.

    Article  CAS  PubMed  Google Scholar 

  6. Panis C, Victorino VJ, Herrera AC, Cecchini AL, Simao AN, Tomita LY, et al. Can Breast Tumors Affect the Oxidative Status of the Surrounding Environment? A Comparative Analysis among Cancerous Breast, Mammary Adjacent Tissue, and Plasma. Oxid Med Cell Longev. 2015;2015:6429812.

    CAS  PubMed  Google Scholar 

  7. Macleod LC, Hsi RS, Gore JL, Wright JL, Harper JD. Perinephric fat thickness is an independent predictor of operative complexity during robot-assisted partial nephrectomy. J Endourol. 2014;28(5):587–91.

    Article  PubMed  Google Scholar 

  8. Anderson KM, Lindler TU, Lamberton GR, Baron PW, Ojogho OK, Baldwin DD. Laparoscopic donor nephrectomy: effect of perirenal fat upon donor operative time. J Endourol. 2008;22(10):2269–74.

    Article  PubMed  Google Scholar 

  9. Kocher NJ, Kunchala S, Reynolds C, Lehman E, Nie S, Raman JD. Adherent perinephric fat at minimally invasive partial nephrectomy is associated with adverse peri-operative outcomes and malignant renal histology. BJU Int. 2016;117(4):636–41.

    Article  PubMed  Google Scholar 

  10. Varghese BA HD, Cen SY, Desai BB, Yap, FY, Gill I, Desai M, et al. . Fast fourier transform based analysis of renal masses on contrast-enhanced computed tomography images for grading of tumor. International Society for Optics and Photonics2017. p. 101600J-J-8.

  11. Yu H, Scalera J, Khalid M, Touret AS, Bloch N, Li B, et al. Texture analysis as a radiomic marker for differentiating renal tumors. Abdom Radiol (NY). 2017.

  12. Just N. Improving tumour heterogeneity MRI assessment with histograms. Br J Cancer. 2014;111(12):2205–13.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Yoo C, Song C, Hong JH, Kim CS, Ahn H. Prognostic significance of perinephric fat infiltration and tumor size in renal cell carcinoma. J Urol. 2008;180(2):486–91; discussion 91.

  14. Skogen K, Ganeshan B, Good C, Critchley G, Miles K. Measurements of heterogeneity in gliomas on computed tomography relationship to tumour grade. J Neurooncol. 2013;111(2):213–9.

    Article  PubMed  Google Scholar 

  15. Yang L, Dong D, Fang M, Zhu Y, Zang Y, Liu Z, et al. Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer? Eur Radiol. 2018;28(5):2058–67.

    Article  PubMed  Google Scholar 

  16. Chen C, Kang Q, Xu B, Guo H, Wei Q, Wang T, et al. Differentiation of low- and high-grade clear cell renal cell carcinoma: Tumor size versus CT perfusion parameters. Clin Imaging. 2017;46:14–9.

    Article  PubMed  Google Scholar 

  17. Qian BZ, Pollard JW. Macrophage diversity enhances tumor progression and metastasis. Cell. 2010;141(1):39–51.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  18. Mackin D, Fave X, Zhang L, Fried D, Yang J, Taylor B, et al. Measuring Computed Tomography Scanner Variability of Radiomics Features. Invest Radiol. 2015;50(11):757–65.

    Article  PubMed Central  PubMed  Google Scholar 

  19. Duda RO, Hart PE, Stork DG. Pattern Classification (2nd Edition): Wiley-Interscience; 2000.

  20. Haury AC, Gestraud P, Vert JP. The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures. PLoS One. 2011;6(12):e28210.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors acknowledge FUJIFILM Medical Systems USA, Inc. for the use of their Synapse® 3D software for completing this work.

Funding

The project did not receive any funding.

Author information

Authors and Affiliations

Authors

Contributions

TG is the first author and drafted the manuscript. She manually segmented the JPF in Synapse 3D. BV performed data processing and reviewed manuscript. DH aided in CT analysis. SC performed the statistical analysis. MA performed pathological correlation. MA provided urological clinical significance. VD supervised the study, as well as reviewed and edited manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Vinay A. Duddalwar.

Ethics declarations

Conflict of interest

Dr. Vinay Duddalwar serves as a consultant to Intuitive Surgical and as an advisor to DeepTek. Dr. Monish Aron serves as a consultant to Intuitive Surgical. The other authors have no conflict of interest with respect to the work presented in this manuscript.

Research involving human participants and/or animals

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

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gill, T.S., Varghese, B.A., Hwang, D.H. et al. Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma. Abdom Radiol 44, 1470–1480 (2019). https://doi.org/10.1007/s00261-018-1848-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-018-1848-x

Keywords

Navigation