American Journal of Physiology-Renal Physiology · 2007 · 141 citations · 32 references
MedicineNuclear MedicineRadiologyDiagnostic ImagingDiagnostic RadiologyRenal Nuclear MedicineGlomerular FiltrationRenal AssessmentRenal Function TestsRenal ImagingRenal Nuclear ImagingRenal ScintigraphyContrast-enhanced Renal ImagingGlomerular Filtration AssessmentGlomerular Filtration Rate AssessmentGlomerular Filtration Rate MeasurementSingle-kidney Function AssessmentSingle-kidney RenographySingle-nephron Glomerular Filtration RateThree-compartment Models
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.
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A Simplex Method for Function Minimization
J. A. Nelder, R. Mead · The Computer Journal · 1965 · 28.9K citations
Generalized autocalibrating partially parallel acquisitions (GRAPPA)
Mark A. Griswold, Peter M. Jakob, Robin M. Heidemann et al. · Magnetic Resonance in Medicine · 2002 · 5.3K citations · Full text