Appropriately selected cases of renal angiomyolipoma can be managed by active surveillance. For those patients requiring treatment nephron sparing approaches, including partial nephrectomy and selective arterial embolization, are preferred options. For those with tuberous sclerosis complex mTOR inhibitors may represent a viable approach to control tumor burden while conserving renal parenchyma.

Compared with precontrast MR imaging, postcontrast MR imaging with Gd-EOB-DTPA demonstrated improved sensitivity for lesion detection in the majority of blinded readers, with no substantial adverse events.

No abstract

Characterization of renal tumors is critical to determine the best therapeutic approach and improve overall patient survival. Because of increased use of high-resolution cross-sectional imaging in clinical practice, renal masses are being discovered with increased frequency. As a result, accurate imaging characterization of these lesions is more important than ever. However, because of the wide array of imaging features encountered as well as overlapping characteristics, identifying reliable imaging criteria for differentiating malignant from benign renal masses remains a challenge. Multiparametric magnetic resonance (MR) imaging based on various anatomic and functional parameters has an important role and adds diagnostic value in detection and characterization of renal masses. MR imaging may allow distinction of benign solid renal masses from several renal cell carcinoma (RCC) subtypes, potentially suggest the histologic grade of a neoplasm, and play an important role in ensuring appropriate patient management to avoid unnecessary surgery or other interventions. It is also a useful noninvasive imaging tool for patients who undergo active surveillance of renal masses and for follow-up after treatment of a renal mass. The purpose of this article is to review the characteristic MR imaging features of RCC and common benign renal masses and propose a diagnostic imaging approach to evaluation of solid renal masses using multiparametric MR imaging. RSNA, 2017.