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1Department of Radiology, New York University School of Medicine, Departments of 3Biomedical Engineering and 4Chemical Engineering, Columbia University, New York, New York; and 2Siemens Medical Solutions, Malvern, Pennsylvania
Submitted 31 August 2006 ; accepted in final form 1 January 2007
The purpose of this study was to determine the accuracy and sources of error in estimating single-kidney glomerular filtration rate (GFR) derived from low-dose gadolinium-enhanced T1-weighted MR renography. To analyze imaging data, MR signal intensity curves were converted to concentration vs. time curves, and a three-compartment, six-parameter model of the vascular-nephron system was used to analyze measured aortic, cortical, and medullary enhancement curves. Reliability of the parameter estimates was evaluated by sensitivity analysis and by Monte Carlo analyses of model solutions to which random noise had been added. The dominant sensitivity of the medullary enhancement curve to GFR 14 min after tracer injection was supported by a low coefficient of variation in model-fit GFR values (4%) when measured data were subjected to 5% noise. These analyses also showed the minimal effects of bolus dispersion in the aorta on parameter reliability. Single-kidney GFR from MR renography analyzed by the three-compartment model (4.071.4 ml/min) agreed well with reference measurements from 99mTc-DTPA clearance and scintigraphy (r = 0.84, P < 0.001). Bland-Altman analysis showed an average difference of 11.9 ml/min (95% confidence interval = 5.817.9 ml/min) between model and reference values. We conclude that a nephron-based multicompartmental model can be used to derive clinically useful estimates of single-kidney GFR from low-dose MR renography.
multicompartmental modeling; magnetic resonance imaging; tracer kinetics; glomerular filtration rate; radionuclide scintigraphy; gadolinium chelates
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