Utilization of Re-VASC, the Novel Retroperitoneal Neovascularity Scoring System, for Characterization of T1a Small Renal Masses.

Purpose: Early characterization of small (T1a, <4 cm) renal masses is imperative for patient care and treatment planning. Renal biopsy is a sensitive and specific procedure that can accurately differentiate small renal masses as malignant or benign. However, it is an invasive procedure with a nonnegligible complication rate and is not performed routinely at most institutions. In this study, we sought to apply the Retroperitoneal Vascularity Assessment and Scoring in Carcinoma (Re-VASC) scoring system to T1a renal masses and analyzed whether it could differentiate these masses as benign or malignant. Methods: We obtained Institutional Review Board approval to retrospectively examine the records of all patients who presented to our single, urban academic referral center for surgical treatment of renal cell carcinoma (RCC). For the malignant group, patients with a diagnosis of T1a RCC from pathologic evaluation were included. Additionally, patients with a histopathological diagnosis of a T1a nonmalignant renal mass (fat poor-angiomyolipoma or oncocytoma) were included in our benign group. Results: This study includes 57 benign and 69 malignant T1a renal tumors. Average size for benign and malignant masses were 2.47 and 2.63, respectively (p = 0.267). Analysis demonstrated no significant difference between both groups in terms of sex, laterality, or size. The average Re-VASC score of benign and malignant masses was 0.175 and malignant masses was 0.784, respectively (p < 0.001). Additionally, the Re-VASC score was independently associated with malignancy with an odds ratio of 2.223 (p = 0.0109). Conclusion: The Re-VASC scoring system exhibits significantly greater values for malignant T1a renal masses when compared to benign masses. As a result, it shows promise as an adjunctive tool to renal biopsy for clinical decision-making. Further assessment of Re-VASC's true efficacy as a diagnostic marker will include prospective evaluation of a larger multicenter population.

Novel Retroperitoneal Neovascularity Scoring System in Renal Cell Carcinoma Tumor Staging.

Purpose: Renal cell carcinoma (RCC) is the most common type of kidney cancer worldwide. Although radiologists assess enhancement patterns of renal tumors to predict tumor pathology report, to our knowledge, no formal scoring system has been created and validated to assess the level of neovascularity in RCC, despite its critical role in cancer metastases. In this study, we characterized and analyzed the level of angiogenesis in tumor-burdened kidneys and their benign counterparts. We then created and validated a scoring scale for neovascularity that can help predict tumor staging for RCC. Methods: After Institutional Review Board approval, the charts of patients who had undergone operation for RCC between January 13, 2014 and February 4, 2020 were retrospectively reviewed for inclusion in this study. Inclusion criteria were a diagnosis of RCC, simple/radical nephrectomy, preoperative contrast-enhanced CT scans, and complete pathology reports. Neovascularity was scored on a scale of 0-4 where 0 = no neovascularity detected, 1 = a single vessel <3 mm wide, 2 = a single vessel ≥3 mm wide, 3 = multiple vessels <3 mm wide, and 4 = multiple vessels ≥3 mm wide. Results: A total of 227 patients were included in this study. Most of the tumor pathology reports were clear cell carcinoma, regardless of tumor staging. The average neovascularity score was 1.07 for pT1x tumors, 2.83 for pT2x tumors, and 3.04 for pT3x tumors. There was a significant difference in neovascularity score between pT1x and pT2x tumors (p = 0.0046), pT1x and pT3x tumors (p < 0.0001), and benign kidneys and kidneys with RCC (p < 0.0001). Conclusion: Our novel vascular scoring system for RCC demonstrates significant correlation with RCC pathological tumor staging. This scoring system may be utilized as part of a comprehensive radiological assessment of renal tumors, potentially improving tumor characterization and clinical decision making.