Our objective was to develop algorithms to predict adverse pathology (AP) and recurrence-free survival (RFS) for patients with renal tumours primarily based on multifaceted analysis of preoperative CT imaging.
Seven hundred forty-eight patients with non-metastatic renal tumours managed with definitive surgery at Cleveland Clinic (2011-2014) were retrospectively evaluated (median follow-up 9.1 years). All patients underwent contrast-enhanced CT and parenchymal volume analysis using semi-automated software. A variety of conventional radiological features were evaluated in addition to parenchymal volume replacement (PVR) due to invasive tumour growth, using the contralateral kidney as a control. Adverse pathology (AP) was defined as stage ≥pT3a, grade 3/4 or sarcomatoid/rhabdoid features. Multivariable logistic regression and Cox proportional hazards regression analyses were used to develop predictive models.
Overall, 339/748 patients (45%) had AP, which significantly associated with reduced RFS. On univariable analysis, tumour-size, degree of vascularity, heterogeneity, irregular contour, sinus margin irregularity, necrosis, non-cystic tumour and increased PVR significantly associated with AP. On multivariable logistic regression, male sex, R.E.N.A.L. Nearness, heterogeneity, necrosis, sinus margin irregularity and PVR ≥ 25% independently associated with AP. Multivariable analysis indicated that tumour size, heterogeneity, necrosis, PVR ≥ 25% and tumour-related symptoms significantly associated with reduced RFS. Models for AP and RFS at 3, 5 and 10 years showed area under the curve (AUC) values of 0.81 and 0.84-0.86, respectively.
These findings confirm that radiological features and PVR are associated with AP and reduced RFS after definitive renal cancer surgery. Our predictive models are entirely based on preoperative parameters and may improve patient counselling and occasionally preclude the need for renal mass biopsy.
BJUI compass. 2026 Feb 27*** epublish ***
Akira Kazama, Carlos Munoz-Lopez, Worapat Attawettayanon, Eran Maina, Nityam Rathi, Kieran Lewis, Anne Wong, Angelica Bartholomew, Rebecca A Campbell, Jihad Kaouk, Samuel Haywood, Nima Almassi, Christopher J Weight, Nick Heller, Shetal Shah, Erick M Remer, Ryan Ward, Amy S Nowacki, Steven C Campbell
Glickman Urological and Kidney Institute Cleveland Clinic Cleveland Ohio USA., Imaging Institute Cleveland Clinic Cleveland Ohio USA., Department of Quantitative Health Sciences Cleveland Clinic Cleveland Ohio USA.