Evaluation of diagnostic accuracy and a practical algorithmic approach for the diagnosis of renal masses by FNA.

BACKGROUND: The classification of renal neoplasms is essential for oncologic risk stratification and clinical management, and an accurate pretreatment pathologic diagnosis can provide useful guidance for active surveillance, minimally invasive ablative therapy, or surgical resection and can reduce the incidence of overtreatment. Previous studies evaluating the diagnostic accuracy of fine-needle aspiration (FNA) and core-needle biopsy (CNB) for renal masses are limited and show variable results.

METHODS: Two hundred forty-seven renal FNA cases with or without concurrent CNB performed and/or reviewed at the Stanford University School of Medicine over the course of 20 years were identified. Cytohistopathologic correlation was performed for 77 cases with subsequent resection specimens. All available case materials were reviewed, and select cases were worked up further and reclassified as necessary.

RESULTS: Cytohistopathologic correlation showed 96% diagnostic specificity and 83% sensitivity for renal FNA with or without concurrent CNB. Discordant cases were mostly attributed to sampling errors or suboptimal specimens (79%) and also included 2 non-renal cell carcinoma entities (1 case of angiomyolipoma and 1 case of a benign peripheral nerve sheath tumor) and 1 case involving misclassification of the renal cell carcinoma subtype.

CONCLUSIONS: There is considerable value in FNA/CNB for the initial diagnosis of renal masses because of the high diagnostic specificity and sensitivity. Sensitivity is predominantly dependent on sufficient sampling, and additional potential diagnostic pitfalls include nonepithelial and rare entities. Judicious use of ancillary techniques is encouraged, especially when one is presented with a limited specimen, and this article presents a practical algorithmic approach to the diagnosis of renal masses using salient morphologic features and results from ancillary studies. Fine-needle aspiration is an accurate method for the diagnosis of renal masses. A practical diagnostic algorithm, based on salient morphologic and ancillary findings, is presented.