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Article

The superiority of contact surface area as a predictor of renal cortical volume change after partial nephrectomy compared to RENAL, PADUA and C-index: an approach using computed tomography-based renal volumetry

ORCID Icon, , , &
Pages 129-133 | Received 13 Dec 2018, Accepted 29 Apr 2019, Published online: 24 May 2019
 

Abstract

Objective: To evaluate the renal cortical volume (RCV) change after nephron sparing surgery and the predictive value of the nephrometry score in RCV preservation after partial nephrectomy.

Materials and methods: Overall, 162 patients with renal tumors that were treated with open partial nephrectomy were retrospectively analyzed. The contact surface area (CSA), RENAL, PADUA and C-index scores were obtained from a preoperative CT scan. The RCV of the tumor-bearing kidney was measured preoperatively and postoperatively using dedicated software. The correlation between the four nephrometry scores and perioperative parameters were evaluated and the scores were compared in terms of their ability to predict a reduction in the RCV.

Results: All scores showed a significant association with reduction in RCV (all p < 0.001), percent reduction in RCV (all p < 0.001) and estimated blood loss (all p < 0.05). Only the CSA and PADUA scores showed a significant association with percent reduction in eGFR (p = 0.038 and p = 0.026, respectively). On multivariate analysis, the CSA, PADUA and C-index scores independently affected the percent reduction in RCV (p = 0.003, p = 0.025 and p = 0.013, respectively). On ROC curve analysis, CSA was a better independent predictor of a greater than 10% and 20% reduction in the RCV (AUC 0.87 and 0.72, respectively).

Conclusion: CT-based RCV measurement successfully differentiated the RCV change after partial nephrectomy. Compared to the other three nephrometry scores, CSA was a superior predictor of RCV change in the operated kidney.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the 2018 Inje University research grant.

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