The detection of a renal mass is a relatively frequent occurrence in the daily practice of any Radiology Department. The diagnostic approaches depend on whether the lesion is cystic or solid. Cystic lesions can be managed using the Bosniak classification, while management of solid lesions depends on whether the lesion is well-defined or infiltrative. The approach to well-defined lesions focuses mainly on the differentiation between renal cancer and benign tumors such as angiomyolipoma (AML) and oncocytoma. Differential diagnosis of infiltrative lesions is wider, including primary and secondary malignancies and inflammatory disease, and knowledge of the patient history is essential. Radiologists may establish a possible differential diagnosis based on the imaging features of the renal masses and the clinical history. The aim of this review is to present the contribution of the different imaging techniques and image guided biopsies in the diagnostic management of cystic and solid renal lesions.

Objective: The purpose of this study is to validate a multivariable predictive model previously developed to differentiate between renal cell carcinoma (RCC) and oncocytoma using CT parameters. Methods and materials: We included 100 renal lesions with final diagnosis of RCC or oncocytoma studied before surgery with 4-phase multidetector CT (MDCT). We evaluated the characteristics of the tumors and the enhancement patterns at baseline, arterial, nephrographic and excretory MDCT phases. Results: Histopathologically 15 tumors were oncocytomas and 85 RCCs. RCCs were significantly larger (median 4.4 cm vs 2.8 cm, p = 0.006). There were significant differences in nodule attenuation in the excretory phase compared to baseline (median: 31 vs 42, p = 0.015), with RCCs having lower values. Heterogeneous enhancement patterns were also more frequent in RCCs (85.9% vs 60%, p = 0.027). Multivariable analysis showed that the independent predictors of malignancy were the enhancement pattern, with oncocytomas being more homogeneous in the nephrographic phase [Odds Ratio (OR) 0.16 (95% CI 0.03 to 0.75, p = 0.02)], nodule enhancement in the excretory phase compared to baseline, with RCCs showing lower enhancement [OR 0.96 (95% CI 0.93 to 0.99, p = 0.005)], and a size > 4 cm, with RCCs being larger [OR 5.89 (95% CI 1.10 to 31.58), p = 0.038]. Conclusion: The multivariable predictive model previously developed which combines different MDCT parameters, including lesion size > 4 cm, lesion enhancement in the excretory phase compared to baseline and enhancement heterogeneity, can be successfully applied to distinguish RCC from oncocytoma. Advances in knowledge: This study confirms that multiparametric assessment using MDCT (including parameters such as size, homogeneity and enhancement differences between the excretory and the baseline phases) can help distinguish between RCCs and oncocytomas. While it is true that this multiparametric predictive model may not always correctly classify renal tumors such as RCC or oncocytoma, it can be used to determine which patients would benefit from pre-surgical biopsy to confirm that the tumor is in fact an oncocytoma, and thereby avoid unnecessary surgical treatments.

Background/Objectives: Infiltrative renal masses, characterized by ill-defined margins and parenchymal invasion without forming a discrete mass, present a diagnostic challenge, particularly in patients without a prior history of malignancy. Differentiating among the most common malignant etiologies—renal cell carcinoma (RCC), urothelial carcinoma (UC), and lymphoma—is essential for guiding appropriate treatment. This study aimed to evaluate whether specific computed tomography (CT) features can assist in the differential diagnosis of these lesions. Methods: A retrospective review was conducted on 68 patients with infiltrative renal masses presented at a tertiary hospital’s oncologic urology committee between 2018 and 2022. Patients with prior malignancy or signs of infection were excluded. All cases underwent contrast-enhanced CT within three months of diagnosis and had histopathological confirmation. Imaging features such as necrosis, collecting system involvement, lymphadenopathy, and others were assessed and statistically analyzed. Results: RCC was the most frequent diagnosis (68%), followed by UC (18%) and lymphoma (7.4%). Significant differences were observed in imaging features: necrosis was more common in RCC (87%) than in UC (25%) and lymphoma (20%), p < 0.001; collecting system involvement was universal in UC (100%) and less common in RCC (65%) and lymphoma (40%), p = 0.009; and lymphadenopathy was more frequent in lymphoma (80%) than in UC (67%) and RCC (35%), p = 0.038. Tumor size also varied significantly, with lymphomas presenting the largest median size (11 cm), followed by RCCs (8.2 cm) and UCs (5 cm), p < 0.001. Conclusions: CT imaging features, particularly necrosis, collecting system involvement, and lymphadenopathy, can aid in distinguishing among RCC, UC, and lymphoma in patients with infiltrative renal masses and no prior cancer history. These findings may support more accurate diagnoses and inform tailored therapeutic strategies.

Objectives: The aim of the study was to assess the utility of contrast-enhanced ultrasound (CEUS), using both qualitative and quantitative perfusion analysis, in differentiating subtypes of renal cell carcinoma (RCC). Methods: This prospective, single-center study includes 91 patients with histologically confirmed RCC. We performed a CEUS within one week prior to nephrectomy. Qualitative parameters (enhancement pattern, heterogeneity, pseudocapsule) and quantitative perfusion metrics were assessed. Logistic regression models were developed to evaluate the diagnostic performance of CEUS in differentiating high-grade (clear cell RCC) from low-grade RCC (papillary and chromophobe). Results: Qualitative CEUS findings showed that hyperenhancement and isoenhancement were significantly associated with high-grade RCC (OR = 38.3 and OR = 7.8, respectively; p < 0.001 and p = 0.014). Hypoenhancement was predominant in low-grade RCC (80.0%). Quantitative parameters, including peak enhancement and wash-in/wash-out area under the curve, significantly differed between tumor grades (p < 0.001). A model using qualitative parameters alone achieved an AUC of 0.847 and 81.9% accuracy. Adding quantitative metrics marginally improved performance (AUC 0.912, accuracy 86.2%), though not significantly. Conclusions: CEUS provides valuable diagnostic information in differentiating RCC subtypes, with qualitative parameters alone demonstrating strong predictive power. While quantitative analysis slightly enhances diagnostic accuracy, its added value may be limited by technical challenges.

Renal cell carcinoma encompasses a heterogeneous group of kidney tumors with wide variations in biological behavior, histologic subtype, and clinical aggressiveness. Accurate preoperative characterization is essential for management, yet remains challenging because benign, indolent, and aggressive lesions often show overlapping imaging features. CT is the most widely used modality for renal mass evaluation, offering broad availability, high spatial resolution, and multiphasic acquisition. This comprehensive narrative review summarizes current evidence on CT-based characterization of renal cell carcinoma, radiologic–pathologic correlation, imaging markers of tumor aggressiveness, renal mass biopsy, and radiomics. Radiomics and other quantitative imaging approaches may complement conventional imaging by capturing tumor heterogeneity and biologically relevant features; however, most studies remain retrospective, single-center, and methodologically heterogeneous. Multicenter validation, standardized acquisition and segmentation, transparent reporting, and demonstration of added clinical value are required before these methods can be implemented in routine care.

Renal cell carcinoma encompasses a heterogeneous group of kidney tumors with wide variations in biological behavior, histologic subtype, and clinical aggressiveness. Accurate preoperative characterization is essential for management; however, it remains challenging due to overlapping imaging features and tumor complexity. CT is the most widely used imaging technique for renal mass evaluation, providing broad availability, high spatial resolution, and multiphasic acquisition capabilities. However, its ability to distinguish histologic subtypes and predict tumor aggressiveness remains limited. This review provides an updated overview of renal cell carcinoma epidemiology and evidence supporting CT as an essential imaging modality. It outlines key radiologic features of main histologic subtypes, highlights markers of aggressive behavior, and discusses the relationship between CT findings and the International Society of Urological Pathology (ISUP) grading system. We explore radiomics, summarizing its methodological foundations and applications in characterizing solid renal masses, emphasizing the need for multicenter studies and standardized radiomic workflows to develop accurate, reproducible tools for improving diagnostic accuracy and risk stratification for renal cell carcinoma.