OBJECTIVE: The purpose of this study was to determine whether renal tumor enhancement or heterogeneity on triphasic helical CT scans is predictive of the papillary cell subtype or nuclear grade of renal cell carcinoma. MATERIALS AND METHODS: We reviewed the CT scans of 90 consecutive patients with renal masses who had undergone triphasic renal helical CT before a complete or partial nephrectomy (12 with papillary renal cell carcinomas, 66 with nonpapillary renal cell carcinomas, and 12 with benign lesions). Three radiologists who were unaware of the patients' diagnoses retrospectively and independently measured the attenuation of each patient's tumor, abdominal aorta, and normal renal parenchyma on the scans obtained during all three phases. Ratios of tumor-to-aorta enhancement and tumor-to-normal renal parenchyma enhancement were calculated for both of the phases performed after contrast material had been administered. Tumor heterogeneity was calculated as the difference between the highest and lowest attenuation values divided by the value of the enhancement of the aorta. Values were correlated with cell type and nuclear grade found at surgical pathology. RESULTS: Low tumor-to-aorta enhancement and low tumor-to-normal renal parenchyma enhancement ratios on the vascular phase scans significantly correlated (p < 0.001) with papillary renal cell type carcinoma. Homogeneity and tumor-to-parenchyma enhancement ratios on the parenchymal phase scans also significantly correlated (p < 0.001) with papillary renal cell type carcinoma. Heterogeneity and tumor enhancement ratios did not correlate with the nuclear grade of the carcinoma. CONCLUSION: Papillary renal cell carcinomas are typically hypovascular and homogeneous. A high tumor-to-parenchyma enhancement ratio (> or = 25%) essentially excludes the possibility of a tumor being papillary renal cell carcinoma. A low tumor-to-aorta enhancement ratio or tumor-to-normal renal parenchyma enhancement ratio is more likely to indicate papillary renal cell carcinoma.
OBJECTIVE: The purpose of this study was to determine whether renal tumor enhancement or heterogeneity on triphasic helical CT scans is predictive of the papillary cell subtype or nuclear grade of renal cell carcinoma. MATERIALS AND METHODS: We reviewed the CT scans of 90 consecutive patients with renal masses who had undergone triphasic renal helical CT before a complete or partial nephrectomy (12 with papillary renal cell carcinomas, 66 with nonpapillary renal cell carcinomas, and 12 with benign lesions). Three radiologists who were unaware of the patients' diagnoses retrospectively and independently measured the attenuation of each patient's tumor, abdominal aorta, and normal renal parenchyma on the scans obtained during all three phases. Ratios of tumor-to-aorta enhancement and tumor-to-normal renal parenchyma enhancement were calculated for both of the phases performed after contrast material had been administered. Tumor heterogeneity was calculated as the difference between the highest and lowest attenuation values divided by the value of the enhancement of the aorta. Values were correlated with cell type and nuclear grade found at surgical pathology. RESULTS: Low tumor-to-aorta enhancement and low tumor-to-normal renal parenchyma enhancement ratios on the vascular phase scans significantly correlated (p < 0.001) with papillary renal cell type carcinoma. Homogeneity and tumor-to-parenchyma enhancement ratios on the parenchymal phase scans also significantly correlated (p < 0.001) with papillary renal cell type carcinoma. Heterogeneity and tumor enhancement ratios did not correlate with the nuclear grade of the carcinoma. CONCLUSION:Papillary renal cell carcinomas are typically hypovascular and homogeneous. A high tumor-to-parenchyma enhancement ratio (> or = 25%) essentially excludes the possibility of a tumor being papillary renal cell carcinoma. A low tumor-to-aorta enhancement ratio or tumor-to-normal renal parenchyma enhancement ratio is more likely to indicate papillary renal cell carcinoma.
Authors: Ivan Pedrosa; Mary T Chou; Long Ngo; Ronaldo H Baroni; Elizabeth M Genega; Laura Galaburda; William C DeWolf; Neil M Rofsky Journal: Eur Radiol Date: 2007-09-26 Impact factor: 5.315
Authors: Massimo Galia; Domenico Albano; Alberto Bruno; Antonino Agrusa; Giorgio Romano; Giuseppe Di Buono; Francesco Agnello; Giuseppe Salvaggio; Ludovico La Grutta; Massimo Midiri; Roberto Lagalla Journal: Br J Radiol Date: 2017-07-13 Impact factor: 3.039