The gold standard to assess renal function is glomerular filtration rate (GFR). GFR is often estimated from serum creatinine (SCr), serum cystatin C (SCys) and creatinine clearance (CCr), or is predicted using formulas based on SCr or SCys. Ultrasound scanning evaluates morphology and dimensions of kidneys.Aim of this study was to evaluate the relationship among renal dimensions and renal function, and, in particular, the possibility to predict GFR from echographic renal dimensions, in potential kidney donors (POTDON) before donation.

Patients and Methods

Patients. POTDON: 98 (66 females), aged 25-74, m 53.2 years; SCr 0.4-1.3, m 0.81 mg/dL. Methods. GFR was measured as99mTc-DTPA clearance. GFR was also estimated from SCr according to Cockcroft&Gault (CG-CCr) and MDRD formula, and from SCys. Kidney dimensions were measured during bidimensional echography, and total and parenchymal kidney volumes were estimated with ellipsoid formula. GFR was predicted also from kidney dimensions and total and parenchymal volumes with a formula recently developed in our laboratory.


In POTDON SCr was not correlated with GFR; a slight, but significant, correlation with GFR was found for SCys and for CysGFR (p<0.05); a higher correlation was with MDRD formula (p<0.005), with CG Ccr (p<0.0001). The accuracy of CG-CCr and MDRD-GFR were better than Cys-GFR. However, their mean prediction errors versus GFR were relevant. Renal dimensions, particularly renal volume and renal parenchymal volume showed a good correlation with GFR, higher than all serum concentrations and prediction equations.  These estimates of GFR, obtained from renal dimensions,  were more closely correlated with measured GFR than CG-CCr, MDRD-GFR, and Cys-GFR. GFR estimated from renal volumes had also a better agreement and a lower prediction error versus true GFR than the other prediction formulas.


In conclusion, renal echography provides also functional information, and in potential living kidney donors, it is possible to estimate GFR from renal volumes more accurately and with a lower prediction error than using formulas based on SCr and SCys or CCr.