Jeff L. Zhang PhD, Presenter: Nothing to Disclose

Henry Rusinek PhD, Abstract Co-Author: Nothing to Disclose

Louisa Bokacheva, Abstract Co-Author: Nothing to Disclose

Qun C. Chen PhD, Abstract Co-Author: Nothing to Disclose

Chekema Prince, Abstract Co-Author: Nothing to Disclose

Niels Oesingmann PhD, Abstract Co-Author: Nothing to Disclose

Ting Song, Abstract Co-Author: Nothing to Disclose

Vivian Shu-Ching Lee MD, PhD, Abstract Co-Author: Speakers Bureau, Schering AG (MEDRAD, Inc)

et al, Abstract Co-Author: Nothing to Disclose

et al, Abstract Co-Author: Nothing to Disclose

We propose a novel approach to analyzing MR renography (MRR) data to derive glomerular filtration rate (GFR) and renal plasma flow (RPF) using impulse retention functions (IRF) with net delay times applied to a three-compartmental model of the kidney, and compare this approach with reference scintigraphic data.

The model fits convolution of measured input from the aorta and IRFs for renal cortex and medulla which are derived from compartmental IRFs. We performed sensitivity analysis and Monte Carlo simulation to evaluate the identificability and reliability of the fitted parameters. Our method was tested in 10 patients (5 female and 5 male patients, mean age 69.8 yrs ± 16.9) using low-dose Gd-DTPA-enhanced MRR, and model-derived GFR and RPF were compared with scintigraphic reference values using linear regression.

Renal enhancement curves were fitted by the model with relative root mean square error 11.6% ±4.9. GFR estimates correlated well with reference values, which ranged from 3.5 – 89.4 ml/min (correlation coefficient r = 0.82) determined by Tc99m-DTPA renal scintigraphy, while for RPF, r = 0.80 (range 0.0 – 308.9 ml/min). Parameter-sensitivity analysis and Monte Carlo simulation indicated that parameters GFR, RPF, and the vascular and tubular mean transit times (MTT), can be reliably identified (coefficient of variance < 4.0% with 5% data noise).

The proposed model achieves consistent fitting of measured MRR renal enhancement curves and can be used to derive GFR, RPF and vascular/tubular MTTs accurately.

The model-derived parameters such as GFR and RPF are diagnostically useful for renal dysfunction and some renovascular diseases.

Zhang, J, Rusinek, H, Bokacheva, L, Chen, Q, Prince, C, Oesingmann, N, Song, T, Lee, V, et al, , et al, , Assessment of Renal Function with MR Renography: Impulse Retention Approach to a Multi-Compartmental Model.  Radiological Society of North America 2007 Scientific Assembly and Annual Meeting, November 25 - November 30, 2007 ,Chicago IL. http://archive.rsna.org/2007/5013671.html