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BMC Cancer

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Open Access 01-12-2024 | Kidney Cancer | Research

CT features based preoperative predictors of aggressive pathology for clinical T1 solid renal cell carcinoma and the development of nomogram model

Authors: Keruo Wang, Liang Dong, Songyang Li, Yaru Liu, Yuanjie Niu, Gang Li

Published in: BMC Cancer | Issue 1/2024

Abstract

Background

We aimed to identify preoperative predictors of aggressive pathology for cT1 solid renal cell carcinoma (RCC) by combining clinical features with qualitative and quantitative CT parameters, and developed a nomogram model.

Methods

We conducted a retrospective study of 776 cT1 solid RCC patients treated with partial nephrectomy (PN) or radical nephrectomy (RN) between 2018 and 2022. All patients underwent four-phase contrast-enhanced CT scans and the CT parameters were obtained by two experienced radiologists using region of interest (ROI). Aggressive pathology was defined as patients with nuclear grade III-IV; upstage to pT3a; type II papillary renal cell carcinoma (pRCC), collecting duct or renal medullary carcinoma, unclassified RCC or sarcomatoid/rhabdoid features. Univariate and multivariate logistic analyses were used to determine significant predictors and develop the nomogram model. To evaluate the accuracy and clinical utility of the nomogram model, we used the receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis (DCA), risk stratification, and subgroup analysis.

Results

Of the 776 cT1 solid RCC patients, 250 (32.2%) had aggressive pathological features. The interclass correlation coefficient (ICC) of CT parameters accessed by two reviewers ranged from 0.758 to 0.982. Logistic regression analyses showed that neutrophil-to-lymphocyte ratio (NLR), distance to the collecting system, CT necrosis, tumor margin irregularity, peritumoral neovascularity, and RER-NP were independent predictive factors associated with aggressive pathology. We built the nomogram model using these significant variables, which had an area under the curve (AUC) of 0.854 in the ROC curve.

Conclusions

Our research demonstrated that preoperative four-phase contrast-enhanced CT was critical for predicting aggressive pathology in cT1 solid RCC, and the constructed nomogram was useful in guiding patient treatment and postoperative follow-up.

Scosyrev E, Messing EM, Sylvester R, Campbell S, Van Poppel H. Renal function after nephron-sparing surgery versus radical nephrectomy: results from EORTC randomized trial 30904. Eur Urol. 2014;65(2):372–7. https://doi.org/10.1016/j.eururo.2013.06.044.CrossRefPubMed

Finelli A, Ismaila N, Bro B, Durack J, Eggener S, Evans A, et al. Management of small renal masses: American society of clinical oncology clinical practice guideline. J Clin Oncol. 2017;35(6):668–80. https://doi.org/10.1200/JCO.2016.69.9645.CrossRefPubMed

Lee H, Lee M, Lee SE, Byun SS, Kim HH, Kwak C, et al. Outcomes of pathologic stage T3a renal cell carcinoma up-staged from small renal tumor: emphasis on partial nephrectomy. BMC Cancer. 2018;18(1):427. https://doi.org/10.1186/s12885-018-4338-1.CrossRefPubMedPubMedCentral

Adibi M, Thomas AZ, Borregales LD, Merrill MM, Slack RS, Chen HC, et al. Percentage of sarcomatoid component as a prognostic indicator for survival in renal cell carcinoma with sarcomatoid dedifferentiation. Urol Oncol. 2015;33(10):427e17-42723. https://doi.org/10.1016/j.urolonc.2015.04.011.CrossRef

Chan VW, Keeley FX Jr, Lagerveld B, Breen DJ, King A, Nielsen TK, et al. The changing trends of image-guided biopsy of small renal masses before intervention-an analysis of European multinational prospective EuRECA registry. Eur Radiol. 2022;32(7):4667–78. https://doi.org/10.1007/s00330-022-08556-2.CrossRefPubMedPubMedCentral

Lane BR, Abouassaly R, Gao T, Weight CJ, Hernandez AV, Larson BT, et al. Active treatment of localized renal tumors may not impact overall survival in patients aged 75 years or older. Cancer. 2010;116(13):3119–26. https://doi.org/10.1002/cncr.25184.CrossRefPubMed

Xing M, Kokabi N, Zhang D, Ludwig JM, Kim HS. Comparative effectiveness of thermal ablation, surgical resection, and active surveillance for T1a renal cell carcinoma: a surveillance, epidemiology, and end results (SEER)-medicare-linked population study. Radiology. 2018;288(1):81–90. https://doi.org/10.1148/radiol.2018171407.CrossRefPubMed

Bhindi B, Thompson RH, Lohse CM, Mason RJ, Frank I, Costello BA, et al. The probability of aggressive versus indolent histology based on renal tumor size: implications for surveillance and treatment. Eur Urol. 2018;74(4):489–97. https://doi.org/10.1016/j.eururo.2018.06.003.CrossRefPubMed

Ficarra V, Brunelli M, Cheng L, Kirkali Z, Lopez-Beltran A, Martignoni G, et al. Prognostic and therapeutic impact of the histopathologic definition of parenchymal epithelial renal tumors. Eur Urol. 2010;58(5):655–68. https://doi.org/10.1016/j.eururo.2010.08.001.CrossRefPubMed

10.

Wang H, Wang K, Liu C, Wang G, Liu Y, Li G, et al. Risk factors and oncologic outcomes for clinical T1 renal cell carcinoma upstaging to pathological T3a and the construction of predictive model: a retrospective study. Urol J. 2023;20(3):148–56. https://doi.org/10.22037/uj.v19i.7294.CrossRefPubMed

11.

Kutikov A, Smaldone MC, Egleston BL, Manley BJ, Canter DJ, Simhan J, et al. Anatomic features of enhancing renal masses predict malignant and high-grade pathology: a preoperative nomogram using the RENAL nephrometry score. Eur Urol. 2011;60(2):241–8. https://doi.org/10.1016/j.eururo.2011.03.029.CrossRefPubMedPubMedCentral

12.

Marconi L, Dabestani S, Lam TB, Hofmann F, Stewart F, Norrie J, et al. Systematic review and meta-analysis of diagnostic accuracy of percutaneous renal tumour biopsy. Eur Urol. 2016;69(4):660–73. https://doi.org/10.1016/j.eururo.2015.07.072.CrossRefPubMed

13.

Macklin PS, Sullivan ME, Tapping CR, Cranston DW, Webster GM, Roberts ISD, et al. Tumour seeding in the tract of percutaneous renal tumour biopsy: a report on seven cases from a UK tertiary referral centre. Eur Urol. 2019;75(5):861–7. https://doi.org/10.1016/j.eururo.2018.12.011.CrossRefPubMed

14.

Elstob A, Gonsalves M, Patel U. Diagnostic modalities. Int J Surg. 2016;36(Pt C):504–12. https://doi.org/10.1016/j.ijsu.2016.06.005.CrossRefPubMed

15.

Tosoian JJ, Feldman AS, Abbott MR, Mehra R, Tiemeny P, Wolf JS Jr, et al. Biopsy cell cycle proliferation score predicts adverse surgical pathology in localized renal cell carcinoma. Eur Urol. 2020;78(5):657–60. https://doi.org/10.1016/j.eururo.2020.08.032.CrossRefPubMed

16.

Tanaka H, Ding X, Ye Y, Wang Y, Campbell RA, DeWitt-Foy ME, et al. Infiltrative renal masses: clinical significance and fidelity of documentation. Eur Urol Oncol. 2021;4(2):264–73. https://doi.org/10.1016/j.euo.2019.07.015.CrossRefPubMed

17.

Oberle AD, Brown JA. Small renal mass with sarcomatoid features. Curr Urol. 2021;15(4):244. https://doi.org/10.1159/000499259.CrossRef

18.

Ficarra V, Caloggero S, Rossanese M, Giannarini G, Crestani A, Ascenti G, et al. Computed tomography features predicting aggressiveness of malignant parenchymal renal tumors suitable for partial nephrectomy. Minerva Urol Nephrol. 2021;73(1):17–31. https://doi.org/10.23736/S2724-6051.20.04073-4.CrossRefPubMed

19.

Li C, Cen D, Liu Z, Liang C. Presence of intratumoral calcifications and vasculature is associated with poor overall survival in clear cell renal cell carcinoma. J Comput Assist Tomogr. 2018;42(3):418–22. https://doi.org/10.1097/RCT.0000000000000704.CrossRefPubMed

20.

Yanagi M, Kiriyama T, Akatsuka J, Endo Y, Takeda H, Katsu A, et al. Differential diagnosis and prognosis of small renal masses: association with collateral vessels detected using contrast-enhanced computed tomography. BMC Cancer. 2022;22(1):856. https://doi.org/10.1186/s12885-022-09971-w.CrossRefPubMedPubMedCentral

21.

Dagher J, Delahunt B, Rioux-Leclercq N, Egevad L, Srigley JR, Coughlin G, et al. Clear cell renal cell carcinoma: validation of World Health Organization/International Society of Urological Pathology grading. Histopathology. 2017;71(6):918–25. https://doi.org/10.1111/his.13311.CrossRefPubMed

22.

Leibovich BC, Lohse CM, Crispen PL, Boorjian SA, Thompson RH, Blute ML, et al. Histological subtype is an independent predictor of outcome for patients with renal cell carcinoma. J Urol. 2010;183(4):1309–15.CrossRefPubMed

23.

Liu H, Tang K, Chen Z, Li Z, Meng X, Xia D. Comparison and development of preoperative systemic inflammation markers-based models for the prediction of unfavorable pathology in newly diagnosed clinical T1 renal cell carcinoma. Pathol Res Pract. 2021;225: 153563. https://doi.org/10.1016/j.prp.2021.153563.CrossRefPubMed

24.

Ball MW, Gorin MA, Bhayani SB, Rogers CG, Stifelman MD, Kaouk JH, et al. Preoperative predictors of malignancy and unfavorable pathology for clinical T1a tumors treated with partial nephrectomy: a multi-institutional analysis. Urol Oncol. 2015;33(3):112e9-1114. https://doi.org/10.1016/j.urolonc.2014.11.003.CrossRef

25.

Verhoest G, Veillard D, Guillé F, De La Taille A, Salomon L, Abbou CC, et al. Relationship between age at diagnosis and clinicopathologic features of renal cell carcinoma. Eur Urol. 2007;51(5):1298–304. https://doi.org/10.1016/j.eururo.2006.11.056. (discussion 1304–1305).CrossRefPubMed

26.

Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A, et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst. 2014;106(6): dju124. https://doi.org/10.1093/jnci/dju124.CrossRefPubMed

27.

Allenet C, Klein C, Rouget B, Margue G, Capon G, Alezra E, et al. Can pre-operative neutrophil-to-lymphocyte ratio (NLR) help predict non-metastatic renal carcinoma recurrence after nephrectomy? (UroCCR-61 study). Cancers (Basel). 2022;14(22):5692. https://doi.org/10.3390/cancers14225692.CrossRefPubMed

28.

Davenport MS, Hu EM, Zhang A, Shinagare AB, Smith AD, Pedrosa I, et al. Standardized report template for indeterminate renal masses at CT and MRI: a collaborative product of the SAR disease-focused panel on renal cell carcinoma. Abdom Radiol (NY). 2019;44(4):1423–9. https://doi.org/10.1007/s00261-018-1851-2.CrossRefPubMed

29.

Bolster F, Durcan L, Barrett C, Lawler LP, Cronin CG. Renal cell carcinoma: accuracy of multidetector computed tomography in the assessment of renal sinus fat invasion. J Comput Assist Tomogr. 2016;40(6):851–5. https://doi.org/10.1097/RCT.0000000000000448.CrossRefPubMed

30.

Karlo CA, Kou L, Di Paolo PL, Kattan MW, Motzer RJ, Russo P, et al. Renal cell carcinoma: a nomogram for the CT imaging-inclusive prediction of indolent, non-clear cell renal cortical tumours. Eur J Cancer. 2016;59:57–64. https://doi.org/10.1016/j.ejca.2016.02.012.CrossRefPubMedPubMedCentral

31.

Correa AF, Toussi A, Amin M, Hrebinko RL, Gayed BA, Parwani AV, et al. Small renal masses in close proximity to the collecting system and renal sinus are enriched for malignancy and high Fuhrman grade and should be considered for early intervention. Clin Genitourin Cancer. 2018;16(4):e729-733. https://doi.org/10.1016/j.clgc.2018.01.017.CrossRefPubMed

32.

Yan Y, Liu L, Zhou J, Li L, Li Y, Chen M, et al. Clinicopathologic characteristics and prognostic factors of sarcomatoid renal cell carcinoma. J Cancer Res Clin Oncol. 2015;141(2):345–52. https://doi.org/10.1007/s00432-014-1740-1.CrossRefPubMed

33.

Bradley AJ, MacDonald L, Whiteside S, Johnson RJ, Ramani VA. Accuracy of preoperative CT T staging of renal cell carcinoma: which features predict advanced stage. Clin Radiol. 2015;70(8):822–9. https://doi.org/10.1016/j.crad.2015.03.013.CrossRefPubMed

34.

Oh S, Sung DJ, Yang KS, Sim KC, Han NY, Park BJ, et al. Correlation of CT imaging features and tumor size with Fuhrman grade of clear cell renal cell carcinoma. Acta Radiol. 2017;58(3):376–84. https://doi.org/10.1177/0284185116649795.CrossRefPubMed

35.

Suo X, Chen J, Zhao Y, Tang Q, Yang X, Yuan Y, et al. Clinicopathological and radiological significance of the collateral vessels of renal cell carcinoma on preoperative computed tomography. Sci Rep. 2021;11(1):5187. https://doi.org/10.1038/s41598-021-84631-w.CrossRefPubMedPubMedCentral

36.

Yoshino S, Kato M, Okada K. Clinical significance of angiogenesis, proliferation and apoptosis in renal cell carcinoma. Anticancer Res. 2000;20(1C):591–4.PubMed

37.

Zhu YH, Wang X, Zhang J, Chen YH, Kong W, Huang YR. 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. 2014;203(3):W295-300. https://doi.org/10.2214/AJR.13.12297.CrossRefPubMed

38.

Guo K, Ren S, Cao Y, Zhang H, Zhang Y, Gu X, et al. Differentiation between renal oncocytomas and chromophobe renal cell carcinomas using dynamic contrast-enhanced computed tomography. Abdom Radiol (NY). 2021;46(7):3309–16. https://doi.org/10.1007/s00261-021-03018-7.CrossRefPubMed

39.

Coy H, Young JR, Pantuck AJ, Douek ML, Sisk A, Magyar C, et al. Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma. Abdom Radiol (NY). 2020;45(10):3184–92. https://doi.org/10.1007/s00261-019-02271-1.CrossRefPubMed

40.

Qu JY, Jiang H, Wang XF, Song XH, Hao CJ. Use of specific contrast-enhanced CT regions of interest to differentiate renal oncocytomas from small clear cell and chromophobe renal cell carcinomas. Diagn Interv Radiol. 2022;28(6):555–62. https://doi.org/10.5152/dir.2022.2111504.CrossRefPubMedPubMedCentral

Title: CT features based preoperative predictors of aggressive pathology for clinical T1 solid renal cell carcinoma and the development of nomogram model
Authors: Keruo Wang
Liang Dong
Songyang Li
Yaru Liu
Yuanjie Niu
Gang Li
Publication date: 01-12-2024
Publisher: BioMed Central
Keywords: Kidney Cancer
Kidney Cancer
Kidney Cancer
Computed Tomography
Computed Tomography
Pathology
Renal Cancer
Nephrectomy
Nephrectomy
Nephrectomy
Published in: BMC Cancer / Issue 1/2024
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-024-11870-1

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