Renal function measurements from MR renography and a simplified multicompartmental model

Am J Physiol Renal Physiol. 2007 May;292(5):F1548-59. doi: 10.1152/ajprenal.00347.2006. Epub 2007 Jan 9.

Abstract

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 1-4 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 (4.0-71.4 ml/min) agreed well with reference measurements from (99m)Tc-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 = 5.8-17.9 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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Computer Simulation
  • Gadolinium
  • Glomerular Filtration Rate*
  • Humans
  • Image Enhancement
  • Kidney / physiology*
  • Magnetic Resonance Imaging*
  • Models, Biological*
  • Monte Carlo Method
  • Radioisotope Renography*
  • Sensitivity and Specificity

Substances

  • Gadolinium