Is fat quantification based on proton density fat fraction useful for differentiating renal tumor types?

Purpose : This study retrospectively assessed the diagnostic accuracy of fat quantification based on PDFF for differentiating renal tumors. Methods : In this retrospective study, 98 histologically confirmed clear cell renal cell carcinomas (RCCs), 35 papillary RCCs, 14 oncocytomas, 16 chromophobe RCCs, 10 lymphomas, 19 uroepithelial tumors, 10 lipid-poor angiomyolipomas (AMLs), and 25 lipid-rich AMLs were identified in 226 patients (127 males and 99 females) over 5 years. All patients underwent multiparametric kidney MRI. Demographic data were recorded, and PDFF values were independently reviewed by two radiologists blinded to pathologic results. MRI examinations were performed using a 1.5 T system. MRI-PDFF measurements were obtained from the solid parts of all renal tumors. Fat quantification was performed using a standard region of interest for each tumor, compared to histopathological diagnoses. Sensitivity and specificity analyses were performed to calculate the diagnostic accuracy for each histopathological tumor type. P -values < 0.05 were considered statistically significant. Results : In all, 102 patients underwent partial nephrectomy, 70 patients underwent radical nephrectomy, and the remaining 54 had biopsies. Patient age (mean: 58.11 years; range: 18–87 years) and tumor size (mean: 29.5 mm; range: 14–147 mm) did not significantly differ across groups. All measurements exhibited good interobserver agreement. Clear cell RCCs presented a significantly higher fat ratio than other RCC types, uroepithelial tumors, lymphomas, and lipid-poor AMLs. Lipid-rich AMLs demonstrated a very high fat ratio. Conclusion : MRI-PDFF facilitated accurate differentiation of clear cell RCCs from other renal tumors with high sensitivity and specificity.