Predictive ability of renal cortex enhancement in dynamic computed tomography for residual renal function after nephroureterectomy: Comparison with Tc-diethylenetriaminopentacetic acid renography and validation study.

OBJECTIVE

To estimate postoperative residual renal function after radical nephroureterectomy for upper tract urothelial carcinoma using the preoperative dynamic computed tomography renal cortex enhancement ratio in comparison with the split kidney glomerular filtration rate measured by Tc-diethylenetriaminopentacetic acid renography.

METHODS

A total of 47 patients who received radical nephroureterectomy and underwent both preoperative dynamic computed tomography and renography were the model-development cohort; and 109 patients who underwent dynamic computed tomography alone were the validation cohort. Postoperative renal function of the unremoved kidney was estimated using the following formulas: preoperative estimated glomerular filtration rate × the percentage of total renal cortex radiodensity for the intact kidney in Hounsfield units obtained from corticomedullary phase images in the computed tomography-based model, or the percentage of the total glomerular filtration rate measured by renography in the nuclear model. The correlation between observed and estimated postoperative renal function was determined. The computed tomography-based prediction model derived from linear regression analysis was validated externally.

RESULTS

The correlation of computed tomography-based split renal function with the observed postoperative estimated glomerular filtration rate (r = 0.80) was equivalent to that of nuclear split renal function (r = 0.78). In the validation cohort, the computed tomography-based prediction model showed an equivalently strong correlation (r = 0.78).

CONCLUSIONS

The present study showed that the percentage of total renal cortex radiodensity for the intact kidney is a useful tool for predicting unremoved kidney function in upper tract urothelial carcinoma patients, thereby allowing appropriate patient selection for perioperative cisplatin-based combination chemotherapy.