Skip to main content
Log in

Tumor contour irregularity on preoperative imaging: a practical and useful prognostic parameter for papillary renal cell carcinoma

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

Abstract

Objectives

To illustrate tumor contour irregularity on preoperative imaging with a practical method and further determine its value in predicting disease-free survival (DFS) in patients with pRCC (papillary renal cell carcinoma).

Methods

We performed a retrospective single-institution review of 267 Chinese pRCC patients between March 2009 and May 2019. Contour irregularity on cross-section was classified into smooth but distorted margin, unsmooth and sharply nodular margin, and blurred margin. Then, the ratio of the cross-section numbers of irregularity and the total tumor was defined as the contour irregular degree (CID). Cox regression and Kaplan-Meier analysis were performed to analyze the impact of CID on DFS. Then, the prognostic performance of CID was compared with pRCC risk stratification published by Leibovich et al.

Results

The median follow-up was 45 months (IQR: 23–69), in which 27 (10%) patients had metastasis or recurrence. Observed DFS rates were 95%, 90%, and 88% at 1, 3, and 5 years. The CID was an independent prognostic factor of DFS (HR = 1.048, 95% CI = 1.029–1.068, p < 0.001). The Kaplan-Meier plot showed that high-risk patients (CID ≥ 50%) tended to have a significantly shorter DFS (p < 0.001). The CID and Leibovich’s pRCC model for DFS prediction had a C-index of 0.934 (95% CI = 0.907–0.961) and 0.833 (95% CI = 0.739–0.927) respectively.

Conclusions

With our standard and practical method, the CID can be a reliable imaging marker for DFS prediction in patients with pRCC.

Key Points

• The updated contour irregularity was an independent parameter for predicting disease-free survival in patients with pRCC.

• High-risk pRCC patients (contour irregular degree ≥ 50%) tended to have a shorter disease-free survival.

• Tumor contour irregularity in pRCC risk stratification outperformed Leibovich’s model from our cohort.

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

Abbreviations

CI:

Confidence interval

CID:

Contour irregular degree

DFS:

Disease-free survival

HR:

Hazard ratio

IQR:

Interquartile range

OR:

Odds ratio

PRCC:

Papillary renal cell carcinoma

References

  1. Linehan WM, Spellman PT, Ricketts CJ et al (2016) Comprehensive molecular characterization of papillary renal-cell carcinoma. N Engl J Med 374:135–145

    Article  Google Scholar 

  2. Motzer RJ, Hutson TE, Cella D et al (2013) Pazopanib versus sunitinib in metastatic renal-cell carcinoma. N Engl J Med 369:722–731

    Article  CAS  Google Scholar 

  3. Choueiri TK, Motzer RJ (2017) Systemic therapy for metastatic renal-cell carcinoma. N Engl J Med 376:354–366

    Article  CAS  Google Scholar 

  4. Shuch B, Hahn AW, Agarwal N (2017) Current treatment landscape of advanced papillary renal cancer. J Clin Oncol 35:2981–2983

    Article  CAS  Google Scholar 

  5. Albiges L, Flippot R, Rioux-Leclercq N, Choueiri TK (2018) Non-clear cell renal cell carcinomas: from shadow to light. J Clin Oncol:O2018792531. https://doi.org/10.1200/JCO.2018.79.2531

  6. Kay FU, Canvasser NE, Xi Y et al (2018) Diagnostic performance and interreader agreement of a standardized MR imaging approach in the prediction of small renal mass histology. Radiology 287:543–553

    Article  Google Scholar 

  7. Leslie S, Gill IS, de Castro AA et al (2014) Renal tumor contact surface area: a novel parameter for predicting complexity and outcomes of partial nephrectomy. Eur Urol 66:884–893

    Article  Google Scholar 

  8. Gill IS, Aron M, Gervais DA, Jewett MA, Di J (2010) Clinical practice. Small renal mass. N Engl J Med 2:154–155

    Google Scholar 

  9. Karlo CA, Di Paolo PL, Chaim J et al (2014) Radiogenomics of clear cell renal cell carcinoma: associations between CT imaging features and mutations. Radiology 270:464–471

    Article  Google Scholar 

  10. Jamshidi N, Jonasch E, Zapala M et al (2015) The radiogenomic risk score: construction of a prognostic quantitative, noninvasive image-based molecular assay for renal cell carcinoma. Radiology 277:114–123

    Article  Google Scholar 

  11. Hotker AM, Karlo CA, Zheng J et al (2016) Clear cell renal cell carcinoma: associations between CT features and patient survival. AJR Am J Roentgenol 206:1023–1030

    Article  Google Scholar 

  12. Yamada T, Endo M, Tsuboi M et al (2008) Differentiation of pathologic subtypes of papillary renal cell carcinoma on CT. AJR Am J Roentgenol 191:1559–1563

    Article  Google Scholar 

  13. Rosenkrantz AB, Sekhar A, Genega EM et al (2013) Prognostic implications of the magnetic resonance imaging appearance in papillary renal cell carcinoma. Eur Radiol 23:579–587

    Article  Google Scholar 

  14. Davarpanah AH, Spektor M, Mathur M, Israel GM (2016) Homogeneous T1 hyperintense renal lesions with smooth borders: is contrast-enhanced MR imaging needed? Radiology 280:128–136

    Article  Google Scholar 

  15. Yap FY, Hwang DH, Cen SY et al (2018) Quantitative contour analysis as an image-based discriminator between benign and malignant renal tumors. Urology 114:121–127

    Article  Google Scholar 

  16. Parker WP, Cheville JC, Frank I et al (2017) Application of the Stage, Size, Grade, and Necrosis (SSIGN) score for clear cell renal cell carcinoma in contemporary patients. Eur Urol 71:665–673

    Article  Google Scholar 

  17. Pal SK, Ali SM, Yakirevich E et al (2018) Characterization of clinical cases of advanced papillary renal cell carcinoma via comprehensive genomic profiling. Eur Urol 73:71–78

    Article  CAS  Google Scholar 

  18. Edge SB, Compton CC (2010) The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol 17:1471–1474

    Article  Google Scholar 

  19. 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 37:1490–1504

    Article  Google Scholar 

  20. Moch H, Cubilla AL, Humphrey PA, Reuter VE, Ulbright TM (2016) The 2016 WHO classification of tumours of the urinary system and male genital organs-part a: renal, penile, and testicular tumours. Eur Urol 70:93–105

    Article  Google Scholar 

  21. Marszalek M, Carini M, Chlosta P et al (2012) Positive surgical margins after nephron-sparing surgery. Eur Urol 61:757–763

    Article  Google Scholar 

  22. Leibovich BC, Lohse CM, Cheville JC et al (2018) Predicting oncologic outcomes in renal cell carcinoma after surgery. Eur Urol 73:772–780

    Article  Google Scholar 

  23. Margulis V, Tamboli P, Matin SF, Swanson DA, Wood CG (2008) Analysis of clinicopathologic predictors of oncologic outcome provides insight into the natural history of surgically managed papillary renal cell carcinoma. Cancer 112:1480–1488

    Article  Google Scholar 

  24. Brú A, Albertos S, Luis Subiza J, García-Asenjo JL, Brú I (2003) The universal dynamics of tumor growth. Biophys J 85:2948–2961

    Article  Google Scholar 

  25. Deisboeck TS, Guiot C, Delsanto PP, Pugno N (2006) Does cancer growth depend on surface extension? Med Hypotheses 67:1338–1341

    Article  CAS  Google Scholar 

  26. Perez-Beteta J, Molina-Garcia D, Ortiz-Alhambra JA et al (2018) Tumor surface regularity at MR imaging predicts survival and response to surgery in patients with glioblastoma. Radiology 288:218–225

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank Yeqing Xu for his valuable collaboration with the pictures.

Funding

This study has received funding by Scientific Research Cultivation and Medical Innovation Project of Fujian Province (No. 2019CXB33), Fujian Province Department of Science and Technology (No. 2019D025), Medical and Health Key Project of Xiamen (No.3502Z20199716), and Shanghai Municipal Health Commission (No.2019SY073).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Hang Wang or Jianjun Zhou.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Jianjun Zhou.

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 not required for this study because this study is a retrospective study and patients have full autonomy in decision-making.

Ethical approval

Institutional Review Board approval was not required because this study is a retrospective study and patients have full autonomy in decision-making.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dai, C., Huang, J., Li, Y. et al. Tumor contour irregularity on preoperative imaging: a practical and useful prognostic parameter for papillary renal cell carcinoma. Eur Radiol 31, 3745–3753 (2021). https://doi.org/10.1007/s00330-020-07456-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-020-07456-7

Keywords

Navigation