Validation of 3D volumetric-based renal function prediction calculator for nephron sparing surgery

Abstract

Objective To evaluate a recently published volume-based renal function prediction calculator intended to be used in small renal mass surgical counseling. Methods Retrospective data collection included 3-dimensional calculation of renal mass and parenchyma of patients who have undergone extirpative therapy. The predicted glomerular filtration rate (GFR) was calculated using the online calculator. The predicted GFR was compared with the actual 6-month GFR. The Pearson correlation coefficient, paired T-test and root mean square error (RMSE) are utilized for statistical analysis. Results After institutional review board approval, 3 institutions provided data for analysis. After patients with renal mass size >300 cc, renal size >400 cc, or preoperative CKD ≥ stage 3 had been excluded, we retrospectively analyzed data from 136 patients. The median mass volume was 22.2 cc (IQR 7-49). In multiple linear regression analysis, the most significant variables predicting postoperative GFR were partial vs. radical nephrectomy and preoperative GFR with an overall R2 of 0.68 (F = 26.13, P < .001). The predicted GFR was 75.4 mL/min/1.73 m2 compared to an actual GFR of 70.7 mL/min/1.73 m2 (P < .001, paired T test). The predicted GFR was highly correlated with the actual post-operative GFR at 6 months (Pearson correlation, r=0.65, P < .001). RMSE of the validation cohort was 16.87. Conclusions The Predictive Tool to Determine Renal Function Benefit of Nephron Sparing Surgery Compared to Radical Nephrectomy online calculator effectively predicts GFR and could potentially be used to help urologists and patients discuss renal function prior to extirpative renal surgery.

The Current Evidence for Factors that Influence Treatment Decision Making in Localized Kidney Cancer: A Mixed Methods Systematic Review

“…Prognostic factors including anatomical, histological, clinical and molecular factors were found to be facilitators to decision making in kidney cancer in this review. 12–32 This is similar to the findings reported in Campi et al’s SR: they identified most decisions are based on tumor related factors and renal mass growth was the most influential trigger. 54 This was consistent with our findings, where prognostic factors were identified as facilitators to clinical decision making.…”

“…Eleven papers described predictive tools to support decision making. 12,13,15,17,20,22,27,33,35,44,48 The RENAL (radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrectomy score was used to help overcome selection bias, 31 assist surgeons in preoperative decision making 48 and correlate with tumor histology and grade. 35,44 Similarly, the PADUA score was reported to support the process of decision making by identifying the tumor complexity.…”

“…50% of included papers highlighted prognostic factors such as anatomical, histological, clinical and molecular factors. These papers highlighted tumor size at diagnosis as a facilitator to treatment decision making, 12–32 with larger tumors being more likely to be of malignant potential. 12,14…”

A systematic review of the clinical value and applications of three-dimensional virtual reconstructions in renal tumors

“…Postoperative renal function and chronic kidney disease remain a concern in the surgical management of renal masses, as they has been related to an increased risk of hospitalization, cardiovascular morbidity and death [33,58]. Few papers [31][32][33]60] have focused directly on the relationship between postoperative renal function and resected cortex margin volume, calculated by a 3D reconstruction technique based on the resected specimen, to determine the predictors of renal function after robot-assisted partial nephrectomy. Meyer et al [32] found that using accurate 3D volumetric analysis, ischemia time, tumor size and endophytic/exophytic properties of a localized renal mass were the most important determiners of renal parenchymal volume loss.…”

Will three‐dimensional models change the way nephrometric scoring is carried out?

“…The creation of a multi‐institutional open‐source dataset of annotated renal CT scans would pave the way for increased research and progress towards automatic, reliable and quantitative image analysis tools for kidney cancer. In particular, research on 3D nephrometric scoring , image‐based volumetry (segmentation) and tracking of tumours to assess the response of therapy , and CT volumetry to predict 6‐month postoperative estimated GFR could be developed into fully automatic and robust software that finds its way into clinical practice.…”