Precise measurement of renal filtration and vascular parameters using a two-compartment model for dynamic contrast-enhanced MRI of the kidney gives realistic normal values

OBJECTIVE To model the uptake phase of T(1)-weighted DCE-MRI data in normal kidneys and to demonstrate that the fitted physiological parameters correlate with published normal values. METHODS The model incorporates delay and broadening of the arterial vascular peak as it appears in the capillary bed, two distinct compartments for renal intravascular and extravascular Gd tracer, and uses a small-vessel haematocrit value of 24%. Four physiological parameters can be estimated: regional filtration K ( trans ) (ml min(-1) [ml tissue](-1)), perfusion F (ml min(-1) [100 ml tissue](-1)), blood volume v ( b ) (%) and mean residence time MRT (s). From these are found the filtration fraction (FF; %) and total GFR (ml min(-1)). Fifteen healthy volunteers were imaged twice using oblique coronal slices every 2.5 s to determine the reproducibility. RESULTS Using parenchymal ROIs, group mean values for renal biomarkers all agreed with published values: K ( trans ): 0.25; F: 219; v ( b ): 34; MRT: 5.5; FF: 15; GFR: 115. Nominally cortical ROIs consistently underestimated total filtration (by ~50%). Reproducibility was 7-18%. Sensitivity analysis showed that these fitted parameters are most vulnerable to errors in the fixed parameters kidney T(1), flip angle, haematocrit and relaxivity. CONCLUSIONS These renal biomarkers can potentially measure renal physiology in diagnosis and treatment. KEY POINTS • Dynamic contrast-enhanced magnetic resonance imaging can measure renal function. • Filtration and perfusion values in healthy volunteers agree with published normal values. • Precision measured in healthy volunteers is between 7 and 15%.