Author:
Rathi Nityam,Attawettayanon Worapat,Yasuda Yosuke,Lewis Kieran,Roversi Gustavo,Shah Snehi,Wood Andrew,Munoz-Lopez Carlos,Palacios Diego A.,Li Jianbo,Abdallah Nour,Schober Jared P.,Strother Marshall,Kutikov Alexander,Uzzo Robert,Weight Christopher J.,Eltemamy Mohamed,Krishnamurthi Venkatesh,Abouassaly Robert,Campbell Steven C.
Abstract
AbstractAccurate prediction of new baseline GFR (NBGFR) after radical nephrectomy (RN) can inform clinical management and patient counseling whenever RN is a strong consideration. Preoperative global GFR, split renal function (SRF), and renal functional compensation (RFC) are fundamentally important for the accurate prediction of NBGFR post-RN. While SRF has traditionally been obtained from nuclear renal scans (NRS), differential parenchymal volume analysis (PVA) via software analysis may be more accurate. A simplified approach to estimate parenchymal volumes and SRF based on length/width/height measurements (LWH) has also been proposed. We compare the accuracies of these three methods for determining SRF, and, by extension, predicting NBGFR after RN. All 235 renal cancer patients managed with RN (2006–2021) with available preoperative CT/MRI and NRS, and relevant functional data were analyzed. PVA was performed on CT/MRI using semi-automated software, and LWH measurements were obtained from CT/MRI images. RFC was presumed to be 25%, and thus: Predicted NBGFR = 1.25 × Global GFRPre-RN × SRFContralateral. Predictive accuracies were assessed by mean squared error (MSE) and correlation coefficients (r). The r values for the LWH/NRS/software-derived PVA approaches were 0.72/0.71/0.86, respectively (p < 0.05). The PVA-based approach also had the most favorable MSE, which were 120/126/65, respectively (p < 0.05). Our data show that software-derived PVA provides more accurate and precise SRF estimations and predictions of NBGFR post-RN than NRS/LWH methods. Furthermore, the LWH approach is equivalent to NRS, precluding the need for NRS in most patients.
Publisher
Springer Science and Business Media LLC
Cited by
3 articles.
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